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Principles of Scientific Writing for an International Audience


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  • 1. Successful  Scien+fic  Wri+ng   Eugene  Elbert,  MS  (Johns  Hopkins     University,  U.S.)   Special  thanks  to  :  Paul  Siegel  MD,  MPH   9-­‐10  August  2012  
  • 2. Biological  Threat  Reduc+on  Program     of  the   Defense  Threat  Reduc+on  Agency   (DTRA)     2  
  • 3. Biological  Threat  Reduc+on  Program    •  Consolidate  especially  dangerous  pathogens   (EDPs)  into  one  or  two  safe,  secure  central   reference  laboratories  or  repositories  •  Build  and  sustain  long-­‐term  partnerships  through   interna+onal  scien+fic  engagement  and   coopera+on  •  Improve  capacity  to  detect,  diagnose  and  report   outbreaks  and  poten+al  pandemics  by  providing   training  to  personnel  of  the  appropriate  facili+es   3  
  • 4. Biological  Threat  Reduc+on  Program  (BTRP)   •  EDPs  for  human  and  animal  health  include:   o  Avian  and  pandemic  influenza  (influenza  viruses)   o  Crimean-­‐Congo  Hemorrhagic  Fever  (CCHF  virus)   o  Anthrax  (Bacillus  anthracis)   o  Brucella  (Brucella  species)   o  Tularemia  (Francisella  tularensis)   o  Botulism  (Clostridium  botulinum)   o  Tick  Borne  Encephali+s  (TBE  virus)   o  Plague  (Yersinia  pes6s)   o  Foot  and  Mouth  Disease  (FMD)   o  Glanders   o  Newcastle  Disease  Virus   o  Rinderpest   o  Pox  viruses  (goat  and  sheep  pox)   o  Swine  fevers  (African  and  Classical  Swine  Fever)   •  Although   the   BTRP-­‐provided   training   focus   on   these   pathogens,   the  knowledge  and  skills  learned  and  prac+ced  are  applicable  to  a   broad   range   of   other   infec+ous   diseases   and   public   and   animal   health  concerns       4  
  • 5. 5  
  • 6. BTRP-­‐Provided  Training  Courses  include:     •  Disease  recogni+on;     •  Laboratory  equipment  use  and  maintenance;     •  Biosafety  and  security;     •  Laboratory  safety;     •  Laboratory  quality  systems;     •  Respiratory  protec+on  program;     •  Purchasing  and  inventory  control;     •  Introduc+on  to  microbiology;     •  Introduc+on  to  molecular  biology;     •  Introduc+on  to  immunology/serology;     •  Diagnos+c  assays  for  specific  EDPs;     •  Laboratory  management;     •  Sample  collec+on  and  processing;     •  Basics  of  epidemiology;  and  others   6  
  • 7. Conceptual  design  of  approved  TIPME   Training  Facility   7  
  • 8. BTRP  Summary  •  Enhancement  of  exis+ng  surveillance  capacity   through  expansion  of  generic  skills  •  Development  of  capacity  for  rapid  detec+on  (PCR   and  ELISA),  which  contributes  to  public  health  •  Improved  biosafety  and  biosecurity  for   laboratory  personnel  •  BTRP-­‐provided  training  complements  the   Ministry  training  requirements  for  specialists   8    
  • 9. Successful  Scien+fic  Wri+ng   9  
  • 10. Introduc+on  Objec+ves  of  the  workshop:    •  To    introduce  basic  concepts  of  scien+fic  approach  •  To  detail  the  structure  and  format  of  scien+fic  papers.  •  To  compare  examples  of  different  research  designs.  •  To  examine  components  of  a  scien+fic  paper.  •  To  cri+cally  examine  published  examples  of  scien+fic   wri+ng.  •  To  apply  new  wri+ng  skills  to  draging  an  abstract.  •  To  learn  about  the  submission  process  for  publica+ons,   funding  proposals,  and  presenta+ons   10  
  • 11. Why  do  we  publish?  •  Presen+ng  research  •  Reaching  global  scien+fic  community  •  Advancing  science  •  Educa+on  •  Funding  and  credibility     11  
  • 12. 12  
  • 13. Repor+ng  Scien+fic  Research  •  Hypothesis  or  research  ques+on  •  Planned  research  •  Ethics     –  Plagiarism   –  Misuse  of  data  and  informa+on   –  Conflict  of  interest   –  Integrity   –  Human  subject  research       13  
  • 14. Process  of  scien6fic  wri6ng   Submiing   Hypothesis   Wri+ng     Study  plan   ar+cle  Having     Experiment  journal,  audience    in  mind   Results   Data  processing   genera+on   14  
  • 15. General  Guidelines  for  Scien+fic   Papers:  Style  and  Content  EASE  guidelines  •  Complete,  concise  and  clear  •  For  effec+veness  of  interna+onal   coopera+on  all  publica+ons  should  be:  •  COMPLETE,  CONCISE  AND   CLEAR!  •  IMPORTANT     15  
  • 16. General  Guidelines  for  Scien+fic   Papers:  Style  and  Content  •  Do  not  include  irrelevant  informa+on  •  Informa+on  should  not  be  repeated  •  Include  only  necessary  tables  and  figures  •  Cap+ons  –  informa+ve  but  concise  •  Delete  redundancies  •  Define  abbrevia+on  at  first  use  •  Do  not  over-­‐generalize  •  Numbers  for  all  numerals   16  
  • 17. Content  •  Study  should  be  planned  in  advance  •  The  journal  and  the  audience  should  be   chosen  •  Informa+on  should  be  organized  •  All  the  components  of  scien+fic  ar+cle   should  be  present  and  sa+sfy  the   guidelines  for  a  chosen  journal   17  
  • 18. Repor+ng  Guidelines:  Content  •  Dis+nguish  your  original  ideas  •  Paraphrase  text  from  other  sources  •  Proper  terms  (plant  community  vs.  phytocoenosis)  •  Define  every  uncommon  term    •  Avoid  ambiguity  •  Be  clear  what  you  regard  as  100%  when  repor+ng  %  •  SI  units  (interna+onal  system  of  units;  metric)  •  Decimal  point    •  Remember  that  the  text  will  be  read  by  foreigners   18  
  • 19. Repor+ng  Guidelines:  Content  •  Make  posi+ve,  objec+ve  asser+ons,  directly  supported  by  the   results,    with  necessary  qualifica+ons  and  caveats  •  Don’t  oversell:    “This  result  clearly  proves  that  the  neural   network  approach  is  superior  and  will  revolu+onize  research   methods”.  •  Don’t  base  substan+al  claims  on  unpublished  data  or  on   “experience”  without  objec+ve  suppor+ng  evidence.        •  If  you  rely  on  a  reference  to  draw  a  conclusion,  be  sure  the   reference  supports  the  idea,  and  say  where  the  support  may   be  found  in  the  reference.   19  
  • 20. A  Dic+onary  of  Useful  Research  Phrases    •  "It  has  long  been  known..."     •  I  didnt  look  up  the  original  •  "It  is  believed  that..."   references  •  "It  is  generally  believed   •  I  think   that..."   •  My  friends  think  so,  too  •  "A  sta+s+cally  oriented     projec+on..."   •  Wild  guess  •  “Typical  results  are  shown”   •  Best  results  are  shown  •  “Obviously,  we  will  need   •  I  don’t  understand  anything   addi+onal  studies”    •  “Authors  thanks  Joe  in   •  Joe  did  the  work  and   conduc+ng  experiment  and   George  explained  it  to  me   George  for  helpful     comments”   20  
  • 21. Example  “In   order   to   provide   analy+c   control   during   forensic-­‐chemical   inves+ga+on,   it   is   customary   to   use   highly  sensi+ve  and  specific  analysis  methods.  Very  popular  in   the   prac+ce   of   chemic-­‐toxic   studies   is   the   TLC  method   in   view   of   its   accessibility,   ease   of   conduc+ng  and  expressiveness.  Due  to  the  possibility  of  changing  not   only   sorbents   but   also   solvents,   it   is   possible   to  quickly  solve  the  problems  of  separa+on”   21  
  • 22. Repor+ng  Guidelines:  Text  Structure  •  Simple  sentences,  should  not  be  very  long  •  Avoid  passive  voice  •  Text  should  be  cohesive,  logically  organized  •  Each  paragraph  should  start  with  a  topic  sentence  •  Use  text  tables  •  Make  figures  and  tables  understandable  by  themselves  •  Explain  your  figures  and  charts,  and  jus+fy  their   inclusion.    Do  not  just  show  them  with  no  stated   reason.   22  
  • 23. Text  tables  Original  sentence:  •  Iron  concentra+on  means  (±standard  devia+on)  were  as   follows:  11.2±0.3  mg/dm3  in  sample  A,  12.3±0.2  mg/ dm3  in  sample  B,  and  11.4±0.9  mg/dm3  in  sample  C.  Modified:   •  Iron  concentra+on  means  (±standard  devia+on,  in   mg/dm3)  were  as  follows:   •  sample  B    12.3±0.2   •  sample  C    11.4±0.9   •  sample  A    11.2±0.3   23  
  • 24. Replace  phrases  with  a  single  word  •  Considering  this  fact  •  In  the  rela+on  to    •  Exceeding  number  •  In  the  previous  case  •  In  the  absence  •  In  large  number  of  cases   24  
  • 25. Passive  Voice  “Have  you  ever  been  told  to  use  passive  voice”          or  “Did  anyone  tell  you  to  use  passive  voice”  Examples:  •  “James  Watson  was  awarded  the  Nobel  Prize  for   discovering  the  molecular  structure  of  DNA.“  vs.  •  "The  Nobel  CommiSee  awarded  James  Watson   the  Nobel  Prize  for  discovering  the  molecular   structure  of  DNA."   25  
  • 26. Passive  voice  Nobody  takes  responsibility  in  passive  voice:    “Mistakes  were  made  during  the  experiment”  vs.  We  made  mistakes  during  the  experiment    “It  is  shown  in  the  table”  vs.  The  table  shows       26  
  • 27. Example  Common  dysfunc+on  of  the  immune  system  was  shown  in  the  trials  on  humans  and  animals  __________________________________  Trials  on  humans  and  animals  show  a  common  dysfunc+on  of  the  immune  system   27  
  • 28. Correct  Use  of  Passive  Voice  •  When  the  ac+on  is  more  important  than  the   agent  of  it  (as  in  Materials  and  Methods)    •  In  order  to  emphasize  somebody  other  than   the  ac+ng    agent    •  When  the  agent  is  unknown   28  
  • 29. Repor+ng  Guidelines:  Language  •  Use  commonly  known  words,  but  not   idioma+c  expressions  •  Define  abbrevia+ons  (avoid  them  in  abstract)  •  Spelling    •  Past  tense  in  body,  present  in  general   statements  •  Refer  to  the  author  as  “we”  or  “I”  not  “the   author”   29  
  • 30. Repor+ng  Guidelines:  Language  Transforma2on  of  verbs  into  nouns    Obtained  es+mates  –  es+mated  Gained  improvement-­‐  improved  Showed  growth  –  grew  Made  a  decision  –  decided       30  
  • 31. Common  Fallacies  in  Wri+ng    •  Non  Causa  Pro  Causa  Fallacies  —  No  Cause   for  Cause  •  Asempts  to  establish  a  causal  rela+onship   –  Cum  Hoc,  Ergo  Propter  Hoc     –  Post  Hoc,  Ergo  Propter  Hoc     –  The  Regression  Fallacy     –  Texas  Sharpshooter  Fallacy   31  
  • 32. Fallacies  in  Wri+ng    Cum  Hoc,  Ergo  Propter  Hoc  —  With  This,  Therefore  •  African  American  popula+on  is  more  likely  to  experience  metabolic   consequences  of  Chronic  Kidney  Disease  (CKD)  before  reaching  the   eGFR  <60  ml/min  threshold  …  that  these  observa+ons  support  a   need  to  adapt  clinical  prac+ce  guidelines  shiging  screening  for  CKD   to  a  higher  eGFR  threshold  specifically  for  African  Americans  (1)    •  The  assump6on  that  the  measured  clinical  parameters  in  this   representa6ve  popula6on  are  physiologically  linked  to  CKD  in   African  Americans  is  simplis6c  and  ignores  the  effects  of  a   combina6on  of  gene6c  and  physiologic  adapta6ons  superimposed   on  a  background  of  social  and  environmental  factors  that  account   for  minority  health  dispari6es  (2)    •  Lesson:  Adjustment  for  possible  confounders  and  other  sources  of   bias     32  
  • 33. Fallacies  in  Wri+ng    Post  Hoc,  Ergo  Propter  Hoc  —  AAer  This,    Therefore    Because  of  This    •  “Since  that  event  followed  this  one,  this  event  must   have  caused  that  one.”  It  also  is  referred  to  as  “false   cause”  or  “coincidental  correla+on.”  •  7  women  in  California  developed  ovarian  cysts  taking   the  new  mul+phasic  oral  contracep+ve  pills  which  led   to  case  series  report  and  media  prin+ng  the  story  [1].    •  No  associa6on  was  shown  in  follow-­‐up  studies  [2]    •  Lesson:  Checking  for  possible  confounders,  conduc+ng   valida+on  studies  before  jumping  to  conclusions,   repor+ng  on  it  in  wri+ng   33  
  • 34. Fallacies  in  Wri+ng    Texas  Sharpshooter  Fallacy       Outbreak  foci?      •  In  medical  research,  this  fallacy  occurs  when  inves6gators  select   certain  data  to  demonstrate  a  cause-­‐effect  rela6onships.   34  
  • 35. Fallacies  in  Wri+ng    The  Art  of  Argumenta   –  Argumentum  ad  Ignoratum  (Appeal  to  Ignorance):   Absence  of  evidence  is  not  evidence  of  absence   Width  of  Confidence  Interval(±w)   Sample  Size(n)     0.01   9612   0.02   2403   0.03   1068   0.05   384   0.10   96   0.15   43   Sample  sizes  required  to  es2mate  a  true  prevalence  of  0.50  with  95%  confidence   intervals  of  different  widths  (±w)    Lesson:  Making  sure  that  the  sample  size  is  large  enough.  Recognizing  beneficence  and  non-­‐maleficence   35  
  • 36. Fallacies  in  Wri+ng    Argumentum  ad  Verecundiam  (Appeal  to  Authority):  Users  of  this  fallacy  ogen  call  upon  the  published  works  of  others  to  bolster  their  arguments,  without  ques+oning  the  accuracy,  reliability,  or  validity  of  those  sources  •  Quote  from  an  editor  as  a  condi+on  for  publica+on  highlights   the  problem:  “you  cite  Leukemia  [once  in  42  references].   Consequently,  we  kindly  ask  you  to  add  references  of  ar6cles   published  in  Leukemia  to  your  present  ar6cle”  (1)  •  Editors  incen+ve  to  inflate  impact  factors  through  self-­‐ cita+on  •  Survey  found  that  having  a  tenure  posi6on  also  increased   coercion  •  Lesson:    Being  true  to  your  work   36  
  • 37. Fallacies  in  Wri+ng    Argumentum  ad  An;quitatem  (Appeal  to    Tradi2on  or  History)    “(Talking  about  acupuncture)  I  think  it  is  insul+ng  to  say  that  Chinese  people  would  carry  on  with  some  sort  of  mys+cal  belief  when  it  didn’t  work”   “Well,  you  know  –  acupuncture  is  one  of  those  amazing   things.  I  mean  it  has  been  around    for  several  thousand   years  .  .  .  there  is  a  huge  amount  of  validity  to  what  it   represents,     and  there  has  to  be  –  or  it  wouldn’t  have  survived  such  a  long   +me  “     Lesson:    Not  making  unsupported  claims   37  
  • 38. Fallacies  in  wri+ng    •  Argumentum  ad  Populum  (Appeal  to  the  People  or  Popularity)    •  4  from  5  den+sts  recommend  sugar-­‐ free  “Trident”“  chewing-­‐gum!  •  The  adver+sement  “forgot”  to  men+on  “If  pa+ents  INSIST  to   use  chewing-­‐gum”.  They  also  hid  each  5th  den+st   recommended  to  avoid  the  use  of  chewing-­‐gum.  •  «Thus  based  on  the  assessment  of  leading  Russian  clinics   “Sangviri+n”  is  one  of  the  effec+ve  modern  an+microbial  drug   of  local  and  common-­‐  resorp+ve  ac+on  for  preven+on  and   treatment  of  different  infec+ous  diseases  [14–17].»  7/28/2012  
  • 39. Fallacies  in  Wri+ng  Myths  of  Beneficence    An  analysis  of  60  adver+sements  that  had  appeared  in  the  Bri+sh  Medical  Journal  between  1999  and  2001  demonstrated  that  drug  adver+sing  uses  strong  imagery  to  fabricate  mythical  associa+ons  between  medical  condi+ons  and  branded  drugs,  and  that  drug  adver+sing  manipulates  readers’  percep+ons  by  subtle  appeal  to  ancient  and  modern  mythological  founda+ons  of  humanism  and  Western  psychology.     39  
  • 40. Fallacies  in  Wri+ng  False  Dichotomy    This  is  also  called  a  false  dilemma,  an  either-­‐or  fallacy,  fallacy  of  false  choice,  or  black-­‐and-­‐white  thinking.    Most  wide-­‐spread  false  dichotomy  in  scien+fic  repor+ng:      Sta+s+cal  significance  P  =  0.049  vs.  P  =  0.051     40  
  • 41. Fallacies  in  Wri+ng  Essen2alism    Some  argument  in  print  or  spoken  word,  some  “essen+al  feature”  is  proposed  as  a  defining  characteris+c  of  an  otherwise  complex  issue  or  larger  problem    Each  scien+fic  specialty  looks  at  disease  differently.  For  example,  cancer  from  the  perspec+ve  of  a  general  surgeon,  a  pathologist  or  an  acupuncturist  are  completely  different.      Lesson:  To  be  aware  of  specialized  terminology  and  body  of  knowledge  when  repor+ng   41  
  • 42. Fallacies  in  Wri+ng  Редукционизм  Efforts  to  simplify  the  problem  to  the  simple  rela+ons    (O’Connor  et  al.  2011):  “Reduc+onist  methods  of  disease  control  involve  the  removal  of  infec+on  or  the  infec+ous  agent,  implemen+ng  barriers  to  direct  and  indirect  transmission  or  by  increasing  inherent  or  acquired  immunity  to  the  infec+ous  agent.  However,  for  those  diseases  which  evade  such  methods  of  conven+onal  control,  a  more  comprehensive  understanding  of  the  complex  interac+ons  amongst  biological  (agent  and  host(s)),  environmental,  economic  and  social  factors  which  can  affect  the  emergence  and  spread  of  an  infec+ous  disease  is  required.”   42  
  • 43. Things  to  avoid:  •  Plagiarism    •  Fishing  expedi+ons  –  research  must  be  hypothesis  driven  •  Do  not  plan  your  study  in  order  to  use  your  results  to  pool   evidence  against  the  same  problem  (e.g.  meta-­‐analyses.    •  Do  not  fail  to  take  into  account  heterogeneity,  uncertainty   and  dependence  •  Do  not  fail  to  have  a  robust  exploratory  data  analysis  (EDA)   before  proceeding  into  any  confirmatory  tes+ng  (John   Tukey  teachings)  •  Do  not  discount  the  importance  of  internal  and  external   validity  when  interpre+ng  results  •  Do  not  underes+mate  the  sta+s+cs.    The  absence  of   evidence  is  not  the  evidence  of  absence  –  your  study  may   not  have  enough  power  to  detect  anything  unless  you  have   large  numbers   43  
  • 44. Things  that  annoy  reviewers  –  Poor  English  –  Repe++on  –  Lack  of  structure  in  the  text  –  Sentences  that  are  too  convoluted  and  long    –  Lack  of  asen+on  to  detail  (a  premature  drag  with   typographical  errors,  etc.)  –  Not  well  thought  out  statements  (make  each  word   count)  –  Obscure  methods  or  not  well  described  –  Oversta+ng  the  results  –  Too  long  of  a  paper   44  
  • 45. Repor+ng  Guidelines:  Structure  •  IMRaD  standard  (Introduc+on,  Methods,  Results,  and   Discussion)  •  Design  Specific  –  EQUATOR  network  •  Journal  -­‐specific  •  General:   –  Title  Page   –  Conflict  of  Interest  No+fica+on  Page   –  Abstract   –  Introduc+on   –  Methods   –  Results     –  Discussion   –  References   45  
  • 46. Standardizing  Health  Repor+ng  EQUATOR  (Enhancing  Quality  and  Transparency  of  Health   Research)  network:  “Too  oaen,  good  research  evidence  is  undermined  by  poor   quality  repor6ng”  •  Raising  awareness  of  the  crucial  importance  of  good   repor+ng  of  research    •  Becoming  the  recognized  global  center  providing  resources,   educa+on  and  training  rela+ng  to  the  repor+ng  of  health   research  and  use  of  repor+ng  guidelines  •  Assis+ng  in  the  development,  dissemina+on  and   implementa+on  of  repor+ng  guidelines  •  Monitoring  the  status  of  the  quality  of  repor+ng  across   health  research  literature  •  Conduc+ng  research  rela+ng  to  the  quality  of  repor+ng     46    
  • 47. Guidelines  for  Repor+ng  Common   Study  Types  •  CONSORT  –  Consolidate  Standards  of   Repor+ng  Trials  •  STROBE  –  Strengthening  the  Repor+ng  of   Observa+onal  studies  •  STARD  –  Standards  for  repor+ng  of  Diagnos+c   Accuracy  •  QUOROM  –  Quality  of  Repor+ng  of  Meta-­‐ analyses  (under  CONSORT)   47  
  • 48. Example  –  STROBE  checklist     Item No RecommendationTitle and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract (b) Provide in the abstract an informative and balanced summary of what was done and what was foundIntroductionBackground/rationale 2 Explain the scientific background and rationale for the investigation being reportedObjectives 3 State specific objectives, including any prespecified hypothesesMethodsStudy design 4 Present key elements of study design early in the paperSetting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collectionParticipants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for the choice of cases and controls Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants (b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed Case-control study—For matched studies, give matching criteria and the number of controls per case 48  
  • 49. Study  Designs  in  Public  Health  Experimental  (Interven2onal)  Studies   Observa2onal  Studies  Randomized  Trials   Case  reports  Community  Trials   Case  Series   Descrip+ve  Therapeu+c/Preven+ve  Trials   Cross-­‐sec+onal  Studies   Surveillance     Cohort  Studies     Analy+c   Case-­‐Control   49  
  • 50. Observa+onal  Descrip+ve  Studies  •  Case  Reports  –  detailed  presenta+ons  of  a   single  case  or  a  handful  of  cases.     “Normal  Plasma  Cholesterol  in  an  88-­‐Year-­‐Old  Man  Who  Eats  25  Eggs  a   Day  —  Mechanisms  of  Adapta+on”  [Kern  J,  NEJM  1991;  324:896–899]  •  Case  Series  –survey  of  a  group  of  individuals   with  a  par+cular  disease  performed  at  a  single   point  of  +me.   “Pneumocy+s  pneumonia:  Los  Angeles”  [MMWR  Morbidity  and   Mortality  Weekly  Report  1981;30:250-­‐252]       50  
  • 51. Cross-­‐Sec+onal  Studies  •  Describes  health  of  popula+ons  (both  exposed   and  non-­‐exposed)  •  Iden+fies  prevalent  cases  •  Finds  associa+on,  not  causa+on    •  Best-­‐suited  for  lisle  disability,  pre-­‐symptoma+c   studies  •  Surveys  •  Good  for  planning  health  care   –  Na+onal  Health  Surveys  are  a  good  example   51  
  • 52. Surveillance  •  An  ongoing,  systema6c  collec6on,  analysis  and  interpreta6on  of   health-­‐related  data  essen6al  to  the  planning,  implementa6on,  and   evalua6on  of  public  health  prac6ce  •  Detec+on  and  no+fica+on  of  health  events  •  Collec+on  and  consolida+on  of  data  •  Inves+ga+on  of  cases  and  outbreaks  •  Rou+ne  Repor+ng    •  Feedback   U.S.  CDC:  Ears,  EWIDS,  NTSIP,  ESP,  NEDSS,  FluNet,  BRFSS,  FoodNet,  etc.   Australia:    NNDSS   U.S.:  ProMED,  HealthMap   Canada:  FluWatch,  GPHIN   France:  GPs  Sen+nelles  Network   Asia:  APEC  EINet   WHO:  GOARN   Europe:  MedlSys   52  
  • 53. Case-­‐Control  Studies  •  Comparison  of  cases  versus  non-­‐cases   (controls)  •  Retrospec+ve  for  exposure  •  Matching  all  popula+on  characteris+cs  of   cases  to  those  of  controls  (including  biases)  •  Mostly  for  prevalent  cases  (but  could  be  for   incident  cases,  too)   53  
  • 54. Cohort  Studies  •  To  support  the  rela+on  between  the  cause   and  disease  •  Presence  or  absence  of  risk  factor  is   determined  before  outcome  occurs  •  Longitudinal/prospec+ve/incidence  studies  •  Cohorts  are  free  of  disease  at  baseline  •  Cohorts  should  be  comparable  •  Diagnos+cs  and  eligibility  should  be  defined   54  
  • 55. Cohort  vs.  Case-­‐Control   COHORT  STUDY  DATA  COLLECTION   Sick   Exposed   Sample  of   Not  Sick   disease-­‐free   individuals   Sick   Not   Exposed   Not  Sick   Exposed   Develop   Illness  Not  Exposed   Popula+on   Exposed   Don’t   Develop  Not  Exposed   Illness   Case-­‐Control  Data  Collec+on   55  
  • 56. Experimental:  Control  Study    Controlled:   –  Inves+gator  decides  on  interven+on    Randomized:   –  Gold  Standard  in  Epidemiological  research   –  Controls  for  confounding   –  Prevents  selec+on  Bias  Therapeu+c  vs.  Preven+ve:              Pa+ents  with  Disease  vs.  Popula+on  at  Risk     56    
  • 57. Experimental:  Controlled  Studies    DATA  COLLECTION   Exposure   COHORT  (Observa+onal)   occurs   naturally   Sick   Exposed   Sample  of   Not  Sick  disease-­‐free   individuals   Sick   Not   Exposed   Not  Sick   Inves+gator   CONTROLLED  (Interven+onal)   Determines   Exposure   57  
  • 58. Randomized  Clinical  Trial  •   Sample  size  should  be  sufficient  •   Possibility  to  follow  up  during  the  trial  •   Par+cipants  should  be  informed  of  risks/  benefits/  blinding/  placebo  •   Inclusion  Criteria   Reference  Popula+on     Reference  Popula+on     Experimental   Experimental   Popula+on   Popula+on       Study   Popula+on   Internal  Validity   External  Validity   58  
  • 59. Randomized  Clinical  Trial  •  Design   –  Simple   –  Cross-­‐over,  factorial    •  Sampling  •  Eligibility  criteria  •  Blinding:  single  vs.  double  •  Alloca+on:  Randomiza+on  •  Follow-­‐up  •  Analysis  •  Therapeu+c  vs.  Non-­‐therapeu+c   59  
  • 60. Randomized  Trial:  CONSORT  Flow   Eligible     Non-­‐eligible   Declined   Alloca+on  using   randomiza+on   scheme   Follow-­‐up   Included  in   analysis   60  
  • 61. Protocol of clinical study (typical errors)•  During  development  of  CS  protocol:   –  Fail  to  jus+fy  the  study  of  given  drug  by  the  given  indica+ons;   –  Absence  of  pre-­‐clinical  and  clinical  (if  applicable)  trials;   –  The  objec+ves  of  study  are  not  listed  (primary  and  secondary   objec+ves),  hypothesis  of  study;   –  Mixed  concep+on  of  primary  objec+ve  of  study  and  criteria  of   efficacy;   –  Sta+s+cs!  Instead  of  sample  size  jus+fica+on  and  sta+s+cal  power:   “the  assessment  will  be  performed  with  PC,  Excel,  Student’s   methods,  etc.”;   –  Vague  procedures  and  methods,  allowing  ambiguous  interpreta+on;   –  No  dates,  no  versions  
  • 62. Protocol of clinical study (typical errors)•  While  repor+ng  of  CS:     –  Vague  descrip+on  of  study  popula+on,  that  unable  the  formula+on  of   conclusion  about  homoscendacity;     –  No  sta+s+cal  assessment  inclusion/exclusion  criteria  of  lost  follow-­‐up   pa+ents;     –  No  side  therapy  details  and  its  effect  in  sta+s+cal  analysis;     –  No  severity  and  resolving  of  side  effects  (e.g.  2  pa+ents  presented  the   head  ache  –  no  terms,  methods  od  treatment,  outcome,  etc.);     –  No  pa+ents’  compliance  data;     –  Separate  reports  from  each  center  instead  of  all-­‐centers  consolidated   report  …  
  • 63. General  Guidelines  For  Selec+on  of  Study  Type   Study  objec2ve   Study  type   Study  of  rare  diseases   Case  control  studies   Study  of  rare  exposure,  such  as  exposure  to   Cohort  studies  in  a  popula+on  group  in   industrial  chemicals   which  there  has  been  exposure  (e.g.   industrial  workers)   Study  of  mul+ple  exposures,  such  as  the   Case  control  studies   combined  effect  of  oral  contracep+ves  and   smoking  on  myocardial  infarc+on   Study  of  mul+ple  end  points,  such  as   Cohort  studies   mortality  from  different  causes   Es+mate  of  the  incidence  rate  in  exposed   Exclusively  cohort  studies   popula+ons   Study  of  covariables  which  change  over   Preferably  cohort  studies   +me   Study  of  the  effect  of  interven+ons   Interven+on  studies   63  
  • 64. Costs  of  different  types  of  bias  for  different  study  designs   Ecological   Cross-­‐ Case-­‐ Cohort   study   sec2onal   control   study(and   study   study   RCT)   Selec+on   N/A   2   3   1   bias   Recall  bias   N/A   3   3   1   Loss  to   N/A   N/A   1   3   follow-­‐up   Confounding   3   2   2   1   Time   1   2   2   3   Required   Costs   1   2   2   3   1-­‐slight;  2-­‐moderate;  3-­‐high;  N/A=  not  applicable   64  
  • 65. Introduc+on  sec+on   Purpose:  to  convince  the  reader  that  your  study  will   yield  knowledge  or  know-­‐how  that  is  new  and  useful  •  Iden+fy  a  gap  in  knowledge  or  know-­‐how  (study   problem)   o  Provide  key  background  (scope/nature/magnitude  of  the  gap)   o  Be  clear  that  filling  this  gap  will  be  useful.   o  Describe  the  relevant  limita+ons  of  previous  studies  •  Present  your  approach  to  filling  the  gap  (study   purpose)   o  Be  clear  that  your  approach  is  new   o  Emphasize  that  your  approach  addresses  the  limita+ons  of   previous  studies  in  a  logical  and  compelling  way   Oaen  requires  just  three  paragraphs   65  
  • 66. Introduc+on  Checklist  Background Statement: Scope nature magnitude of the gap Be clear that filling the gap is usefulProblem Statement Describe relevant limitationsStudy Statement Be clear that your approach is new Emphasize that your approach addresses limitationsSummary Statement Summarizes the study 66  
  • 67. Introduc+on  sec+on    •  No  major  difference  in  introduc+on  sec+on   between  study  types  •  Some+mes  summary  statement  is  omised,  or   becomes  part  of  the  study  statement  •  STROBE:   Introduc+on Background/ra+onale 2 Explain  the  scien+fic  background  and  ra+onale  for   the  inves+ga+on  being  reported Objec+ves 3 State  specific  objec+ves,  including  any  pre-­‐specified   hypotheses 67  
  • 68. Introduc+on  sec+on  The  next  four  slides  detail  the  introduc+on  checklist  process  for  four  separate  studies:    •  Background  statement  •  Problem  statement  •  Study  statement   –  General  descrip+on  of  the  surveillance  system  •  Summary  statement   68  
  • 69. Background   The  treatment  of  human  immunodeficiency  virus  (HIV)  infec+on  has  undergone   Statement:   considerable  change.  Protease  inhibitors  and  non–nucleoside-­‐analogue     reverse-­‐transcriptase  inhibitors,  when  used  as  part  of  combina+on  drug   regimens,  can  profoundly  suppress  viral  replica+on,  with  consequent  reple+on   of  CD4+  cell  counts.   Mul+ple  clinical  trials  have  shown  the  virologic  and  immunologic  efficacy  of  the   newer,  highly  ac+ve  an+retroviral-­‐drug  combina+ons  by  measuring  the  plasma   load  of  HIV  RNA  and  CD4+  cell  counts.  In  addi+on,  prophylac+c  medica+ons  are   now  being  used  rou+nely  to  prevent  disseminated  Mycobacterium  avium   complex  infec+on Problem   Several  reports  have  described  reduc+ons  in  mortality  and  in  the  rate  of   Statement   hospitaliza+on  of  HIV  infected  pa+ents;  however,  such  reduc+ons  have  not       been  clearly  related  to  specific  therapeu+c  regimens.     Study  Statement   We  analyzed  data  collected  over  42  months  in  the  HIV  Outpa+ent  Study.  During   this  period,  rates  of  chemoprophylaxis  against  opportunis+c  infec+on  remained   rela+vely  constant  even  while  paserns  of  an+retroviral  therapy  were  changing Summary   This  report  outlines  the  changes  in  death  rates  and  the  incidence  of   Statement   opportunis+c  infec+ons  in  a  large  group  of  HIV-­‐infected  outpa+ents,  many  of   whom  had  previously  received  extensive  treatment. 69  
  • 70. Background   Among  the  few  diseases  claimed  to  occur  more  ogen  in  non-­‐smokers  than   Statement:   smokers  1  2  that  of  greatest  poten+al  importance  is  Alzheimers  disease,  which     accounts  for  most  of  the  demen+as  of  later  life  in  Britain Problem   The  published  epidemiological  evidence,  although  sugges+ve  of  an  inverse   Statement   rela+on  with  smoking,  is  not  conclusive  either  about  Alzheimers  disease  or       demen+a  in  general.  Much  of  the  evidence  derives  from  small  retrospec+ve     studies  of  uncertain  reliability,  many  of  which  excluded  vascular  demen+a.   Prospec+ve  studies,  in  which  smoking  habits  are  recorded  before  the  onset  of   demen+a,  should  be  more  informa+ve  about  the  overall  effects  of  smoking,   par+cularly  if  they  concern  large  numbers  and  prolonged  follow  up.  Only  a  few   such  studies  have,  however,  been  properly  reported  (none  of  which  had   prolonged  follow  up) Study   We  sought  evidence  from  the  cohort  of  Bri+sh  doctors  who  have  been   Statement   followed  since  1951,  with  their  smoking  habits  reviewed  every  six  to  12  years.3   4  Many  have  died  from  or  with  some  type  of  demen+a  over  the  past  two   decades. Summary   Statement   70  
  • 71. Background   Alcohol  was  first  implicated  as  a  possible  risk  factor  for  stroke  in  1725(1)   Statement:   Several  epidemiological  studies  now  suggest  a  U-­‐shaped  associa+on  between     alcohol  intake  and  stroke(2). Problem   Previous    studies  have  been  cri+cized  for  not  differen+a+ng  between   Statement   nondrinkers  who  were  lifelong  abstainers  and  those  who  had  given  up       drinking(3-­‐7)     By  asking  specifically  about  previous  regular  drinking  habits  we  have  been  able   to    dis+nguish  between  the  two  groups.  The  level  of  alcohol  consump+on  at   which  this  possible  protec+ve  effect  is  lost  and  alcohol  becomes  a  risk  factor   for  stroke  are  unknown. Study   We  report  the  findings  of  a  case-­‐control  study  that  examines  the  contribu+on   Statement   of  alcohol  to  the  risk  of  stroke  in  moderate  and  heavy  drinkers  (both  currently   and  previously),  lifelong  abstainers  (those  who  have  never  drunk  alcohol),  and   current  abstainers  (those  who  had  formerly  been  regular  drinkers  but  who   currently  do  not  drink  alcohol),  using  validated  measures  of  alcohol   consump+on. Summary   Statement   71  
  • 72. Background   Between  May  2009  and  May  2010,  Greece  experienced  two  waves   Statement:   of  influenza  A(H1N1)2009  transmission   Problem   Given  the  poten+al  for  worsening  in  the  clinical  severity  of  influenza   Statement   during  the  post-­‐pandemic  influenza  season,  as  was  the  case  for       previous  influenza  pandemics  [7-­‐9],  it  was  cri+cal  to  con+nue     surveillance  with  a  focus  on  severe  cases  and  their  clinical   characteris+c Descrip2on  of   In  Greece,  influenza  is  annually  monitored  through  the  rou+ne   the   sen+nel  surveillance  system,  which  became  opera+onal  in  1999.  The   Surveillance   sen+nel  surveillance  system,  which  covers  approximately  three   System   percent  of  the  total  Greek  popula+on  in  the  2010/11  influenza   season,  provides  data  representa+ve  of  the  na+onal  popula+on Summary   This  report  summarises  data  from  influenza  surveillance  in  Greece   Statement   during  the  post-­‐pandemic  2010/11  influenza  season.   72  
  • 73. Materials  and  Methods   Purpose:  to  describe  how  you  collected,  organized   and  analyzed  data  (relevant  to  the  study  purpose)  •  Clearly  present/define  all  analysis  variables  •  Organize  into  logical  subsec+ons  that  illustrate  the  steps   you  took  to  collect,  organize,  and  analyze  the  data:   o  Study  popula+on   o  Defini+on  of  variables   o  Laboratory  methods/  epidemiological  inves+ga+on   o  Interven+on  •  Describe  what  you  did,  not  what  you  found  (Results)  •  Respect  chronology  •  Describe  the  original  methods  in  detail;  otherwise  give   references   Length  varies  depending  on  originality  of  methods   73  
  • 74. Materials  and  Methods  –  part1  MethodsStudy  design Present  key  elements  of  study  design  early  in  the  paperSeing Describe  the  seing,  loca+ons,  and  relevant  dates,  including  periods  of   recruitment,  exposure,  follow-­‐up,  and  data  collec+onPar+cipants  and   (a)  Cohort  study—Give  the  eligibility  criteria,  and  the  sources  and  Seing methods  of  selec+on  of  par+cipants.  Describe  methods  of  follow-­‐up   Case-­‐control  study—Give  the  eligibility  criteria,  and  the  sources  and   methods  of  case  ascertainment  and  control  selec+on.  Give  the  ra+onale   for  the  choice  of  cases  and  controls   Cross-­‐sec6onal  study—Give  the  eligibility  criteria,  and  the  sources  and   methods  of  selec+on  of  par+cipants (b)  Cohort  study—For  matched  studies,  give  matching  criteria  and   number  of  exposed  and  unexposed   Case-­‐control  study—For  matched  studies,  give  matching  criteria  and  the   number  of  controls  per  case 74  
  • 75. Materials  and  Methods  –  part2   Clearly  define  all  outcomes,  exposures,  predictors,  poten+al  Variables confounders,  and  effect  modifiers.  Give  diagnos+c  criteria,  if   applicableData  sources/    For  each  variable  of  interest,  give  sources  of  data  and  details  of   methods  of  assessment  (measurement).  Describe  comparability  measurement of  assessment  methods  if  there  is  more  than  one  group Describe  any  efforts  to  address  poten+al  sources  of  biasBias Explain  how  the  study  size  was  arrived  atStudy  size (a)  Describe  all  sta+s+cal  methods,  including  those  used  to  Sta+s+cal   control  for  confoundingmethods (b)  Describe  any  methods  used  to  examine  subgroups  and   interac+ons (c)  Explain  how  missing  data  were  addressed (d)  Cohort  study—If  applicable,  explain  how  loss  to  follow-­‐up  was   addressed   Case-­‐control  study—If  applicable,  explain  how  matching  of  cases   and  controls  was  addressed   Cross-­‐sec6onal  study—If  applicable,  describe  analy+cal  methods   taking  account  of  sampling  strategy (e)  Describe  any  sensi+vity  analyses 75  
  • 76. Study  Design  •  Observa+onal  or  Experimental  •  Retrospec+ve  or  Prospec+ve   76  
  • 77. Seing  and  Par+cipants  •  Describe  the  study  popula+on  and  seing:  •  Descrip+on  should  involve  relevant   demographic,  environmental,  diagnos+c,   comorbid  factors  •  Defini+on  of  cohort/case  •  Exclusion/inclusion  criteria  •  How  was  consent  obtained?  •  Matching  (in  case-­‐control  study)   77  
  • 78. Examples  of  seing  and  par+cipants  -­‐-­‐   cohort  Smoking  and  demen6a  in  male  Bri6sh  doctors:  prospec6ve  study    The  cohort  originally  comprised  34,439  male  doctors  on  the   Bri+sh   medical   register,   resident   in   the   United  Kingdom,   who   had   responded   to   a   ques+onnaire   about  their   smoking   habits   in   1951.   Changes   in   such   habits  were  sought  in  1957,  1966,  1972,  1978,  1990,  and  1998,  and   other   personal   informa+on   was   sought   in   1978,  1990,  and  1998.  In  1971,  follow  up  was  discon+nued  for  2459   subjects   (10.1%   of   the   survivors)   who   were   living  abroad   and   218   (0.9%)   for   other   reasons.   Almost   all   of  the   remaining   survivors   have   con+nued   to   provide  informa+on  about  their  smoking  habits*.   78  
  • 79. Examples  of  seing  and  par+cipants  –     case  control   Alcohol  and  stroke.  A  case-­‐control  study  of  drinking  habits  past   and  present     Cases  Three  hundred  sixty-­‐four  consecu+ve  pa+ents  hospitalized  for   acute   stroke   in   Newcastle   upon   Tyne   between   August  1989   and   July   1990   formed   the   study   popula+on.   No  pa+ent   refused   to   take   part   in   the   study.   Pa+ents   were  iden+fied  by  daily  contact  with  the  resident  medical  officer  and  completeness  of  case  ascertainment  was  checked  with  data   from   the   medical   records   department   at   each   of   the  three   par+cipa+ng   hospitals   (Freeman   Hospital,   Royal  Victoria   Infirmary,   and   Newcastle   General   Hospital)  Pa6ents   with   primary   subarachnoid   hemorrhage   were  excluded.     79  
  • 80. Examples  of  seing  and  par+cipants  –     case  control  (con+nued)     Controls  Three  hundred  sixty-­‐four  community  control  subjects  were  matched  for  age,  sex,  and  family  doctor.  Control  subjects  were  the  next  unrelated  matching  individual  to  the  case  in  the  family  doctor  register.  Control  subjects  with  a  previous  history  of  stroke  were  excluded.   80  
  • 81. Examples  of  seing  and  par+cipants  –     cross  sec+onal   Breast  feeding  and  obesity:  cross  sec6onal  study  The   1997   obligatory   health   examina+on   before   school  entry   evaluated   134,577   children   in   Bavaria,   southern  Germany.   At   the   examina+on,   the   parents   of   13,345  children   seen   in   two   rural   regions   were   asked   to  complete   a   ques+onnaire   about   risk   factors   for   atopic  diseases.   Data   collected   by   this   ques+onnaire   were  linked   with   the   data   from   the   school   health  examina+on.   Our   analysis   was   confined   to   children  aged  5  and  6  who  had  German  na+onality.   81  
  • 82. Examples  of  seing  and  par+cipants  –     cross  sec+onal   Supplementary  feeding  with  either  ready-­‐to-­‐use  for6fied  spread  or  corn-­‐soy  blend  in   wasted  adults  star6ng  an6retroviral  therapy  in  Malawi:  randomised,  inves6gator   blinded,  controlled  trial    The   study   took   place   at   the   an+retroviral   therapy   clinic   of   Queen  Elizabeth  Central  Hospital  in  Blantyre,  Malawi,  from  January  2006  to   April   2007.   Blantyre   is   the   major   commercial   city   of   Malawi,  with  a  popula+on  of  1,000,000  and  an  es+mated  HIV  prevalence  of   27%   in   adults   in   2004.Eligible   par+cipants   were   all   adults   aged  18   or   over   with   HIV   who   met   the   eligibility   criteria   for  an+retroviral   therapy   according   to   the   Malawian   na+onal   HIV  treatment   guidelines   (WHO   clinical   stage   III   or   IV   or   any   WHO  stage   with   a   CD4   count   <250/mm3)   and   who   were   star+ng  treatment   with   a   BMI   <18.5.   Exclusion   criteria   were   pregnancy  and   lacta6on   or   par6cipa6on   in   another   supplementary   feeding  program   82  
  • 83. Seing  and  par+cipants-­‐Surveillance    ONGOING  OUTBREAK  OF  WEST  NILE  VIRUS  INFECTION  IN  HUMANS,  GREECE,  JULY   TO  AUGUST  2011  Case-­‐Defini2on  •   A  confirmed  case  is  defined  as  a  person  mee+ng  any  of  the   following  clinical  criteria:  encephali+s,  meningi+s,  fever   without  specific  diagnosis  and  at  least  one  of  the  four   laboratory  criteria:  (i)  isola+on  of  WNV  from  blood  or   cerebrospinal  fluid  (CSF),  (ii)  detec+on  of  WNV  nucleic  acid  in   blood  or  CSF,  (iii)  WNV-­‐specific  an+body  response  (IgM)  in   CSF,  and  (iv)  WNV  IgM  high  +tre,  and  detec+on  of  WNV  IgG,   and  confirma+on  by  neutralisa+on.   83  
  • 84. Study  Variables  •  Specify  unit  of  measurement  (if  applicable)  •  Quan+fy  exposure  •  Variable  transforma+ons  •  Criteria  for  defini+ons  •  Units  of  +me  and  special  categories   84  
  • 85. Study  Variables  (examples)  The   childrens   height   and   weight   were   measured   as  part  of  the  rou+ne  examina+on.  Body  mass  index  was  calculated   as   weight   (kg)/(height   (m)2).   The   age  specific  and  sex  specific  distribu+on  of  the  body  mass  index   among   all   children   with   German   na+onality   in  Bavaria,  which  had  been  inves+gated  during  the  1997  school  health  examina+on,  was  used  as  the  reference  for   being   overweight   (defined   as   body   mass   index  above  the  90th  cen6le)  or  obese  (defined  as  body  mass  index   above   the   97th   cen6le)   because   these   cen+les  were  higher  than  other  European  reference  values.     85  
  • 86. Study  Variables  (examples)    Hypertension   was   iden6fied   by   medical   history   or  posi6ve  screening  results  (systolic  pressure  ≥140  mm  Hg).  Pre-­‐hypertension  (asystolic  pressure  of  120–139  mm   Hg)   and   pre-­‐diabetes   (a   fas6ng   blood   glucose  concentra6on   of   6.1–6.9   mmol/L)   were   defined   on  the   basis   of   screened   laboratory   results.   Individuals  were   regarded   as   regular   alcohol   drinkers   if   they  consumed   two   or   more   alcoholic   drinks   a   day   on  three  or  more  days  a  week,  and  occasional  drinkers  if  they  consumed  less  than  regular  drinkers.   86  
  • 87. Study  Variables  (con+nued)  Data   from   clinic   visits   were   used   to   calculate   the   number   of   days   of  observa6on   per   quarter   for   each   pa+ent   in   each   of   four   categories   of  prescribed  an+retroviral  therapy.  These  categories,  in  increasing  order  of  intensity,  were  no  an+retroviral  therapy,  monotherapy,  combina+on  therapy   without   a   protease   inhibitor,   and   combina+on   therapy   that  included  a  protease  inhibitor.      The   data   collected   for   each   case,   using   a   standardised   form,   were:  demographic   characteris+cs   (age,   sex),   dates   of   admission   to   the  hospital   and   the   ICU,   the   +me   course   of   illness   including   the   date   of  symptom   onset,   underlying   condi+ons,   complica+ons,   use   of  mechanical   ven+la+on   support   (dates   of   intuba+on   and   extuba+on),  and  an+viral  treatment   87  
  • 88. Data  Sources/Management  •  How  the  data  were  collected  •  If  it  was  part  of  the  registry,  describe:   –  Original  purpose  of  the  database   –  How  large  the  database  is,  +meliness   –  Valida+on,  quality  checks   –  Error  rate  •  Database  sogware/hardware  •  For  surveillance  paper  –  a  diagram  of  the   surveillance  system  is  preferred     88  
  • 89. Data  Sources/Management  Pa+ents   (with   a   close   rela+ve   or   significant   other  when   possible)   were   interviewed   and   examined   by  H.R.   (79%)   or   P.D.A.   within   48   hours   of  hospitaliza+on.   Control   subjects   were   interviewed   in  their   homes   by   H.R.   (also   with   a   rela+ve   or   significant  other   when   possible).   Inter-­‐observer   valida+on  studies   between   the   two   interviewers   were   carried  out.   The   propor+on   of   agreement   between   two  observers,  K,  was  0.68.     89  
  • 90. Data  Sources/Management  Drinking   frequency   was   recorded   as   a   categorical  variable,   whereas   past   and   present   amounts   of  alcohol   consump+on,   dura+on   of   abs+nence,   and  heavy   drinking   were   recorded   as   con+nuous  variables.   Data   were   transferred   to   Northumbrian  Universitys   Mul6ple   Access   Computer   (NUMAC).  Following   verifica6on   procedures   to   ensure   accurate  transcrip6on,  data  were  analyzed  using  spss-­‐x  (SPSS-­‐X  Batch  System,  SPSS  Inc.,  Chicago,  Illinois).   90  
  • 91. Data  Sources/Management  •  Informa6on  in  five  general  categories  has  been  abstracted   from  the  chart  for  each  outpa6ent  visit  and  entered   electronically  by  trained  data  abstracters;  the  data  are   compiled  centrally,  reviewed,  and  corrected  before  being   included  in  the  data  base.  Because  the  study  physicians  are   the  source  of  primary  care  for  these  pa+ents,  all  symptoms,   diagnoses,  and  treatments  since  the  previous  visit,  are  noted   at  each  clinic  visit.  The  categories  of  informa+on  are  as   follows:  demographic  characteris+cs;  symptoms;  diagnosed   diseases;  medica+ons  prescribed;  and  laboratory  values.     91  
  • 92. Data  Sources/Management   92  
  • 93. Study  Size  •  Specify  the  null  hypothesis  and  whether  it  is   one  or  two-­‐sided  •  Specify  the  minimum  difference  in  response   variable  that  is  considered  to  be  clinically   important  •  Specify  power  and  alpha  level  for  calcula+ng   sample  size   93  
  • 94. Examples  To   detect   a   reduc+on   in   PHS   (postopera+ve  hospital   stay)   of   3   days   (SD   5   days),   which   is   in  agreement   with   the   study   of   Lobo   et   al.   with   a  two-­‐sided   5%   significance   level   and   a   power   of  80%,   a   sample   size   of   50   pa+ents   per   group   was  necessary,   given   an   an+cipated   dropout   rate   of  10%.   To   recruit   this   number   of   pa+ents,   a   12-­‐month  inclusion  period  was  an+cipated   94  
  • 95. Examples  Based   on   an   expected   incidence   of   the   primary  composite  endpoint  of  11%  at  2.25  years  in  the  placebo   group,   we   calculated   that   we   would  need  950  primary  endpoint  events  and  a  sample  size   of   9650   pa+ents   to   give   90%   power   to  detect   a   significant   difference   between  ivabradine   and   placebo,   corresponding   to   a   19%  reduc;on  of  rela;ve  risk  (with  a  two-­‐sided  type  1  error  of  5%)   95  
  • 96. Randomiza+on  –     Randomized  controlled  trials  (RCT)  Par+cipants   should   be   assigned   to  comparison   groups   in   the   trial   on   the  basis   of   a   chance   (random)   process  characterized  by  unpredictability                 96  
  • 97.   Randomized  controlled  trials  (RCT)  -­‐-­‐   examples  •  Independent  pharmacists  dispensed  either   ac+ve  or  placebo  inhalers  according  to  a   computer  generated  randomiza+on  list    •  For  alloca+on  of  the  par+cipants,  a   computer-­‐generated  list  of  random  numbers   was  used                 97  
  • 98. Randomiza+on  (con+nued)  •  Randomiza+on  sequence  was  created  using   Stata  9.0  (StataCorp,  College  Sta+on,  TX)   sta+s+cal  sogware  and  was  stra+fied  by   center  with  a  1:1  alloca+on  using  random   block  sizes  of  2,  4,  and  6    •  Par+cipants  were  randomly  assigned  following   simple  randomiza+on  procedures   (computerized  random  numbers)  to  1  of  2   treatment  groups   98  
  • 99. Randomiza+on  -­‐-­‐  Concealment  A   generated   alloca+on   schedule   should   be  implemented  by  using  alloca+on  concealment,  a   c r i + c a l   m e c h a n i s m   t h a t   p r e v e n t s  foreknowledge   of   treatment   assignment   and  thus  shields  those  who  enroll  par+cipants  from  being   influenced   by   this   knowledge.   The  decision   to   accept   or   reject   a   par+cipant  should  be  made,  and  informed  consent  should  be  obtained  from  the  par+cipant,  in  ignorance  of  the  next  assignment  in  the  sequence   99  
  • 100. Randomiza+on  (concealment)  The  doxycycline  and  placebo  were  in  capsule  form  and  iden+cal  in  appearance.  They  were  prepackaged   in   bosles   and   consecu+vely  numbered  for  each  woman  according  to  the  randomiza+on   schedule.   Each   woman   was  assigned   an   order   number   and   received   the  capsules   in   the   corresponding   pre-­‐packed  bosle   100  
  • 101. Blinding  (RCTs)  The   term   “blinding”   or   “masking”   refers   to  withholding   informa+on   about   the   assigned  interven+ons  from  people  involved  in  the  trial  who  may   poten+ally   be   influenced   by   this   knowledge.  Blinding   is   an   important   safeguard   against   bias,  par+cularly  when  assessing  subjec+ve  outcomes.  EXAMPLE:  Whereas   pa+ents   and   physicians   allocated   to   the  interven+on   group   were   aware   of   the   allocated  arm,   outcome   assessors   and   data   analysts   were  kept  blinded  to  the  alloca+on.   101  
  • 102. Laboratory  Methods(Surveillance)  Serum  and  CSF  specimens  were  tested  for  the  presence  of  WNV-­‐specific  IgM  and  IgG  an+bodies  using  commercial  ELISA  kits  (WNV  IgM  capture  DxSelect  and  WNV  IgG  DxSelect,  Focus  Diagnos+cs  Inc,  Cypress,  CA,  USA).  WNV  posi+ve  specimens  were  also  tested  for  the  presence  of  other  flaviviruses:  +ck-­‐borne  encephali+s  virus  (TBEV)  and  dengue  virus  (DENV).   102  
  • 103. Sta+s+cal  Methods  •  Describe  all  sta+s+cal  methods,  including  those   used  to  control  for  confounding  •  Describe  the  comparisons  to  be  made  and  the   sta+s+cal  procedures  to  be  used  for  making  them  •  State  whether  the  sta+s+cal  analysis  will  be  on   the  basis  of  inten+on-­‐to-­‐treat  •  Control  for  mul+ple  tes+ng  problem  •  Report  hypothesis  power  and  level  (if  it  is  not   reported  in  sampling  sec+on)  •  Report  all  required  p-­‐values  and  confidence   intervals   103  
  • 104. Assessment  of  risk  ra+on   Sick                                      Not  sick          Cases    Controls           No  history  of  disease            History  of  disease                                Exposed                Not  exposed   A   В   A   В           С   D   С   D   In  case  control  study  the  risk  ra+on  has  no  outcome,  odds  ra+on  used   instead  
  • 105. Repor+ng  sta+s+cal  methods  in    Cross-­‐Sec+onal  studies  •  Standard  descrip+ve  sta+s+cs:   -­‐Simple  prevalence  calcula+on  •  Prevalence  of  disease  or  prevalence  of   exposure  •  Regression  to  control  confounders   105  
  • 106. Cross-­‐sec+onal  study  example:   Sta+s+cal  Methods  Pa+ent   characteris+cs,   adjusted   for   stone   history  and  age,  were  compared  using  linear  regression  for  con+nuous   covariates   and   logis6c   regression   for  categorical   covariates.   Mul6ple   linear   regression  was  used  to  compare  mean  es+mated  GFR  between  stone   formers   and   non-­‐stone   formers.   Covariates  iden+fied   as   poten+al   confounders   in   the  rela+onship   between   es+mated   GFR   and   stone  history  were  adjusted  for.  Mul6plica6ve  interac6ons  between   stone   history   and   age,   gender,   race,  diabetes,  and  BMI  were  formally  tested.     106  
  • 107. Cross-­‐sec+onal  study  example:   Sta+s+cal  Methods  Mul6nomial   logis6c   regression   was   used   to   compare  the   rela+ve   risk   of   having   an   es+mated   GFR   in   a  lower   category   rela+ve   to   the   highest   category  between   persons   with   and   without   nephrolithiasis.  Model  based  es+mates  are  reported  as  rela6ve  risk  ra6os   comparing   stone   formers   with   non-­‐stone  formers.   Adjustment   covariates   included   in   the  mul+nomial   logis+c   regression   included   age,   gender,  race,   BMI,   systolic   blood   pressure,   HbA1c,   diabetes,  history   of   cardiovascular   disease,   smoking   status,  health   insurance   status,   and   use   of   prescrip+on  diure+cs.   107  
  • 108. Cross-­‐sec+onal  study  example   Sta+s+cal  Methods  •  The  prevalence  of  overweight  and  obese  children  were   calculated  according  to  the  dura+on  of  breast  feeding.   The  appropriate  χ2  tests  were  used  to  compare  several   items  in  breas†ed  and  non-­‐breas†ed  children  and  their   associa+on  with  the  child  being  overweight  or  obese.   Logis6c  regression  models  were  used  to  assess  the   impact  of  variables  that  were  significantly  associated   (P<0.05)  with  both  breast  feeding  and  being  overweight   or  obese  Confounding  was  assumed  to  have  occurred  if   the  odds  ra6o  changed  by  ≥10%.  Confounders  and   independent  risk  factors  were  included  in  the  final   logis6c  regression  model.  All  calcula+ons  were  carried   out  with  the  SAS  sogware  package,  version  6.12.   108  
  • 109. Sta+s+cal  Methods  (Case-­‐control)  •  Comparing  groups:   –  Nominal  (chi-­‐squared  or  McNemar’s  test)   –  Ordinal  (Wilcoxon,  signed-­‐rank,  Kruskal-­‐Wallis,   ANOVA)   –  Con+nuous  (t-­‐test,  ANOVA)  •  Odds  ra+os  –  strength  of  associa+on  between   exposure  and  disease  is  commonly  measure  by   an  OR  •  Logis+c  Regression:  to  make  inference  on   exposure-­‐disease  associa+on  while  adjus+ng  for   covariates   109  
  • 110. Repor+ng  Sta+s+cal  Methods  in  Case-­‐ Control  Study  The  Mann-­‐Whitney  U  test  was  used  for  between  group  analyses  of  nonparametric  data,  the  standard  χ2  test  when  appropriate  for  discrete  variables,  and  McNemars  χ2  test  to  compare  discordant  pairs.  The  odds  ra6o  (OR)  with  95%  confidence  intervals  (CIs)  was  used  as  an  es+mate  of  risk.  Log-­‐linear  analysis  was  used  to  calculate  the  adjusted  odds  ra+o  for  poten+al  confounding  variables.   110  
  • 111. Repor+ng  Sta+s+cal  Methods  in  Cohort   Studies  and  Clinical  Trials  •  Time-­‐to-­‐event  data:  Survival  func+ons   –  Describe  censored  data     –  Confirm  that  requirements  have  been  met  •  Kaplan-­‐Meier  analysis  •  Specify  methods  to  compare  two  or  more  survival   curves(log-­‐rank  or  Wilcoxon)  •  Hazard  ra+o  •  Cox  Propor+onal  Hazards  Model   –  Report  measure  of  risk  for  each  variable  •  Repeated  measures(for  mul+ple  +me  points)  •  ANCOVA  for  primary  and  secondary  end-­‐points  •  Number  of  end  points     111  
  • 112. Repor+ng  Sta+s+cal  Methods  in  Cohort   Studies  and  RCTs  As  pre-­‐specified,  efficacy  analyses  were  performed  with   the   use   of   a   modified   inten+on-­‐to-­‐treat  approach,  which  included  the  randomized  pa+ents  and   the   end-­‐point   events   that   occurred   ager  randomiza+on  and  no  later  than  the  comple+on  of  the  treatment  phase  of  the  study  (i.e.,  the  global-­‐treatment   end   date),   30   days   ager   early  permanent   discon+nua+on   of   the   study   drug,   or  30   days   ager   randomiza+on   for   pa+ents   who   did  not  receive  a  study  drug   112  
  • 113. Repor+ng  Sta+s+cal  Methods  in  Cohort   Studies  and  RCTs  (con+nued)  We  used  hazard  ra6os  and  two-­‐sided  95%  confidence  intervals  to   compare   the   study   groups.   Rates   of   the   end   points   were  expressed   as   Kaplan–Meier   es+mates   through   24   months.  Tes+ng  was  pre-­‐specified  to  occur  between  the  combined-­‐dose  group  for  rivaroxaban  and  placebo  at  an  alpha  level  of  0.05  on  the   basis   of   the   log-­‐rank   test,   stra+fied   according   to   the  inten+on  to  use  a  thienopyridine.  If  this  comparison  significantly  favored   rivaroxaban,   then   each   of   the   two   doses   of   rivaroxaban  was   simultaneously   compared   with   placebo   with   the   use   of   a  similar   stra+fied   log-­‐rank   test   at   an   alpha   level   of   0.05   on   the  basis   of   the   closed   tes+ng   procedure.   Results   were   examined  according   to   major   subgroups   for   general   consistency   of  treatment  effect,  and  interac+on  tes+ng  was  performed.   113  
  • 114. Repor+ng  Sta+s+cal  Methods  in   Randomized  Controlled  Experiments  The   primary   endpoint   was   change   in  bodyweight   during   the   20   weeks   of   the   study  in   the   inten+on-­‐to-­‐treat   popula+on   …  Secondary  efficacy  endpoints  included  change  in   waist   circumference,   systolic   and   diastolic  blood   pressure,   prevalence   of   metabolic  syndrome  …   114  
  • 115. Repor+ng  Sta+s+cal  Methods  in   Randomized  Controlled  Experiments  We   used   an   analysis   of   covariance   (ANCOVA)   for  the  primary  endpoint  and  for  secondary  endpoints  waist   circumference,   blood   pressure,   and   pa+ent-­‐reported   outcome   scores;   this   was   supplemented  by   a   repeated   measures   analysis.   The   ANCOVA  model   included   treatment,   country,   and   sex   as  fixed   effects,   and   bodyweight   at   randomiza+on   as  covariate.   We   aimed   to   assess   whether   data  provided  evidence  of  superiority  of  each  liraglu+de  dose   to   placebo   (primary   objec+ve)   and   to   orlistat  (secondary  objec+ve   115  
  • 116. Repor+ng  Sta+s+cal  Methods  in   Cohort  Studies  and  RCTs  We   calculated   hazard   ra6os   (HR)   to   compare   mortality  risks   between   individuals   in   different   exercise   groups  (grouped  by  volume  of  exercise)  and  those  in  the  inac+ve  group.   We   used   a   Cox   propor6onate   model   to   analyze  categorical  and  con+nuous  variables  …    The   life   table   method   was   used   to   es+mate   life  expectancy.  We  calculated  adjusted  odds  ra+os  and  95%   CIs   by   comparing   the   propor+on   of   individuals  mee+ng  ac+vity  recommenda+ons  with  the  propor+on  of  those  who  were  inac+ve  within  each  characteris+c  group   116  
  • 117. Sta+s+cal  Methods  -­‐  Surveillance  •  Exploratory  data  analysis:   –  Incidence  by  age,  sex,  geography   –  Trends  •  Severity  factors  •  Group  comparisons     –  Two  sample  tests,  etc.  •  Event  detec+on   –  Detec+on  methods(+me  series/spa+otemporal)   –  Timeliness   –  Sensi+vity/Specificity     117  
  • 118. Sta+s+cal  Methods  -­‐  Surveillance  •  For  early  detec+on  of  localized  clusters  of  dead    birds,  we   used  a  prospec+ve  surveillance  system    that  is  based  on   the  spa+al  scan  sta+s+c  (9).  This    scan  sta+s+c  uses  a   circular  window  to  represent  poten+al  geographic  clusters.  •  Temporal  trends  in  annual  no+fica+on  rates  of   salmonellosis,  infec+ous  diarrhoea  and  outbreaks  of  food-­‐ borne  diseases  were  assessed  using  the  Cuzick  test  [9].   Annual  rates  of  salmonellosis  and  infec+ous  diarrhoea   were  compared  between  the  sexes  using  the  Mann– Whitney  test  and  among  age  groups  using  the  Kruskal– Wallis  test.  Post  hoc  paired  comparisons  ager  the  Kruskal– Wallis  test  were  tested  using  the  Mann–Whitney  test  on   each  pair  of  age  group  and  p-­‐value  adjustment  according   to  Bonferroni’s  method  [10]   118  
  • 119. Results  Purpose:  to  describe  the  results  of  data  analysis  that  are  relevant  to  the  study  purpose  •  Start  with  the  tables  and  figures.    Write  the  text  later.   o  Use  tables  to  highlight  individual  values   o  Use  figures  to  highlight  trends  and  rela+onships  •  Text  supplements  and  reinforces  tables  and  figures   o  Summarize/emphasize  highlights   o  Fill  in  gaps  (ogen  minor)  •  Present  results  in  a  logical  sequence  •  Describe  what  you  found,  not  what  you  did  (Methods)  •  Consider  sub-­‐sec+ons  similar  to  the  ones  in  Methods  •  Look  to  published  ar+cles  for  poten+al  templates   119  
  • 120. Results  (con+nued)  Tables/Figures  •  Check  your  math;  provide  consistent  row  or  column   summa+on.  •  Keep  lines  to  a  minimum;  avoid  ver+cal  lines.  •  Use  footnotes  to  clarify  points  of  poten+al  ambiguity.  •  Check  headings,  labels  of  rows/columns/axes,  and  footnotes  Text  •  Highlight  key  rela+onships  between  dependent/independent   variables.  •  Present  a  logical  sequence:     o  in  parallel  with  methods  (consider  similar  subheadings)   o  background  data  →  descrip+ve  →  bivariate  →  mul+variate  •  Make  sure  all  numbers  in  text  are  consistent  with  tables/ figures.                 Oaen  requires  just  three  paragraphs  +  three  tables/figures   120  
  • 121. Tables  versus  Figures  Tables:  beser  to  use  when  knowledge  of  individual  values  or  sta+s+cs  are  more  important  than  trends  and  conceptual  understanding   1.  Title   2.  Column/row  headings   3.  Data  fields   4.  Footnotes   5.  Spanner   121  
  • 122. Five  elements  of  a  table   122  
  • 123. Table  Title:  Example  Example  1:      Sta+n  therapy  and  cancer  recurrence.  Example  2:      Effect  of  daily  oral  primvasta+n  or  dorvasta+n  on  the  4-­‐year  odds  ra+o  for  the  recurrence  of  prostate  and  breast  cancer.  Example  3:      The  effect  of  daily  oral  primvasta+n  or  dorvasta+n  on  the  4-­‐year  odds  ra+o  (OR)  for  the  recurrence  of  prostate  and  breast  cancer  shows  a  3-­‐fold  lower  (P  =  0.002)  OR  for  the  recurrence  of  breast  cancer  for  pa+ents  receiving  primvasta+n  (OR  =  2.3)  versus  dorvasta+n  (OR  =  6.8).   123  
  • 124. Tables  :  General  Recommenda+ons  •  Indicate  missing  data  by  using  a  dash,  NA,  or  …  •  Each  footnote  should  be  placed  on  a  separate  line  at   the  bosom  of  the  table  •  Lesers  (or  numbers,  or  symbols)  designa+ng   footnotes  should  be  ordered  alphabe+cally  (or   numerically)  •  The  symbol  designa+ng  a  footnote  that  applies  to   the  en+re  table  should  be  placed  ager  the  +tle   124  
  • 125. Table  Alignment  •  The  stubs  should  be  all  leg  jus+fied  •  In  the  columns/data  fields,  words  should  be  leg   jus+fied  and  whole  numbers  right-­‐jus+fied    •  Data  fields  containing  decimal  points,  plus/minus   symbols,  slashes,  hyphens,  or  parentheses  should   be  aligned  on  these  elements.  •  When  the  text  in  a  stub  wraps  to  a  second  line,   the  corresponding  data  field  should  align  with  the   top  line  of  the  stub.   125  
  • 126. Table  alignment  example  A.  Annual  per  capita  healthcare  expenditures.   Expenditure,  $  Israel   1971  Madagascar   36  Sweden   2828  Yemen   82  Zimbabwe   149  B.  Annual  per  capita  healthcare  expenditures.   Expenditure,  $   Israel   1971   Madagascar   36   Sweden   2828   Yemen   82   Zimbabwe   149  C.  Annual  per  capita  healthcare  expenditures.   Expenditure,  $  Sweden   2828  Israel   1971  Zimbabwe   149  Yemen   82  Madagascar   36   126  
  • 127. Tables,  column  formats  example  Table 3. Phenytoin concentrations measured by immunoassay for matricessupplemented with 10 mg/L phenytoin.# Mean (SD), mg/ Mean ± SD, mg/ Deviation from L L target, %Pig serum 11.4 (2.1) 11.4 ± 2.1 14Sheep serum 10.7 (1.4) 10.7 ± 1.4 7Artificial 10.3 (0.8) 10.3 ± 0.8 3serumSaline 10.1 (0.6) 10.1 ± 0.6 1Human serum 9.9 (0.6) 9.9 ± 0.6 −1Cow serum 9.6 (1.4) 9.6 ± 1.4 −4Horse serum 8.9 (0.7) 8.9 ± 0.7 −11 Two  different  styles    of  presen2ng  results     127  
  • 128. What  is  the  right  size?  •  60  characters  for  half-­‐page,  120  for  full  •  For  a  2-­‐column  journal,  110  characters  would  fit   onto  a  portrait-­‐formased  page.  •  Otherwise  journal  might  publish  landscape    •  Re-­‐orient  if  number  of  column  headings  :  row   headings  greater  2:1  •  If  only  one  p-­‐value  out  of  the  whole  column  is   significant  –  remove  and  place  a  not  in  a  footnote  •  Use  abbrevia+ons  when  journals  permit  it  •  Split  into  2   128  
  • 129. Example  :  Table  Too  Wide   Table 5. Age-related 5-year survival for forms of acute myelogenous leukemia.# Microkar Undiffer Myelobla Promyelo Myelomon Monocyti Megakary Erythrol yoblastiAge, entiated stic cytic ocytic c eukemia, c oblasticyears leukemia leukemia leukemia leukemia leukemia leukemia % leukemia , % , % , % , % , % , % , %<21 91 80 85 81 82 73 62 5221–40 89 83 79 77 68 61 57 4141–60 74 62 68 59 40 37 31 24>60 51 48 39 34 28 21 16 9 129  
  • 130. Table,  re-­‐oriented  Table  7.  Age-­‐related  5-­‐year  survival  for  forms  of  acute  myelogenous  leukemia  (AML)   Age AML type <21 Years 21–40 Years 41–60 Years >60 YearsUndifferentiated, % 91 89 74 51Myeloblastic, % 80 83 62 48Promyelocytic, % 85 79 68 39Myelomonocytic, % 51 48 39 34Monocytic, % 82 68 40 28Erythroleukemia, % 73 61 37 21Microkaryoblastic, % 62 57 31 16Megakaryoblastic, % 52 41 24 9 130  
  • 131. Formaing  tables,  con+nued  Table 6. Previous studies of leukocyte reduction during kelvac therapy in patients withchronic myelogenous leukemia.# Leukocyte count, %a No. of Study Day Day Day Day Day Day Day patients 0 7 14 21 28 56 84Wilkins and Potter, Refb11 M11;F11 100 97 — 84 — — 70Pillsbury et al., Ref 12 M10;F18 100 100 81 — 76 — 64Annesley et al., Ref 18 M27;F20 100 89 76 — 63 — 62Kronnenberg and M9;F7 100 103 95 — 88 69 —Stenmeyerson, Ref 20Flowers and Peterson, Ref M20;F23 100 101 96 93 89 86 9825Flloyd et al., Ref 26 M27;F23 100 95 — — 91 — 79Robinson et al., Ref 27 M19;F20 100 — 100 — 96 — 94Nowicki and Phillips, Ref M15;F16 100 — 92 — 82 74 —32 Are  these    columns  necessary?   131  
  • 132. Figures  •  Proper+es  of  a  good  graph:   –  Draws  asen+on  to  the  data  and  not  the  graph   –  The  symbols  and  connec+ng  lines  are  easy  to  read   –  Axis  number  and  labels  are  easy  to  read   –  The  lengths  of  the  two  axes  are  balance  (  1:1.3)   –  The  scales  used  on  each  axis  match  the  range   –  Tick  marks  are  used  appropriately   –  The  legend  is  clear  and  concise   –  Self-­‐sufficient     –  The  data  deserve  to  be  graphed   132  
  • 133. Common  Mistakes  Plasma  vs.  serum  sodium  for  paired  specimens  from  150  pa2ents.  (A),  x-­‐  and  y-­‐axis  scales  of  0–165  mmol/L;    (B),  x-­‐  and  y-­‐axis  scales  of  120–170  mmol/L;    (C),  Bland–Altman  plot.   133  
  • 134. Using  appropriate  axis  interval   134  
  • 135. Why  include  this  graph?   135  
  • 136. Results  vs.  Data   Figure  1  shows  the  survival  rates  following   diagnosis  and  ini+a+on  of  treatment  in  the  3   treatment  groups.  At  6  months  the  survival   rates  were  95%  for  the  A  group,  91%  for  the  B   group,  and  39%  for  the  radia+on-­‐treated   group.  At  12  months  the  rates  were  83%,  69%,   and  23%;,  at  18  months  74%,  17%,  and  15%;   and  at  24  months  were  70%,  11%,  and  9%.   Data  but  no  results   Results,  but  no  data  Figure  1  shows  the  survival  rates  following  diagnosis  and  ini+a+on  of  treatment  in  the  3  treatment  groups.  At  6  months  the  survival  rates  were  significantly  higher  in  the  A  and  B  treatment  groups  compared  with  the  radia+on-­‐treatment  group.  At  12,  18,  and  24  months  the  survival  rates  in  the  A  group  exceeded  those  of  both  the  B  and  radia+on-­‐treatment  groups.   136  
  • 137. Results  vs.  Data   Six   months   ager   diagnosis   and   ini+a+on   of  treatment,  the  survival  rates  for  the  A   and   B   groups   were   2.4   and   2.3   +mes   higher,   respec+vely,   than   the   radia+on   treatment   group   (both   P   <   0.001),   but   survival   rates   were   not   found   to   differ   between   the   A   and   B   groups   (P   =   0.56)   (Figure   1).   By   12   months,   however,   pa+ent   survival   in   the   A   group   was   1.2   +mes   higher   than   in   the   B   group   (P   =   0.031),   and   4.3   and   6.4   +mes   higher   at   18  and  24  months  (both  P  <0.001).   137  
  • 138. Results  and  only  the  Results  We   compared   the   death   rates   for   the   262   healthy   controls  with  those  of  the  203  conges6ve  heart  failure  pa6ents  over  a  2-­‐year   period.   Survival   curves   were   generated   with   the  Masterson   mortality   index   formula.   The   conges+ve   heart  failure  group  was  found  to  have  a  significantly  higher  short-­‐term  mortality  rate.  When   the   2-­‐year   survival   curves   for   healthy   controls   and  conges+ve   heart   failure   pa+ents   were   compared,   the  conges+ve   heart   failure   group   was   found   to   have   a  significantly  higher  short-­‐term  mortality  rate.   138  
  • 139. Using  modern  graphics  and  visualiza+on  
  • 140. Using  modern  graphics  and  visualiza+on   Penn-­‐state  university:  mul+-­‐purpose  map  with  +me  and  spa+al  flu  cases   distribu+on  support  
  • 141. Using  modern  graphics  and  visualiza+on   Red  –  anger,  blue  –  dissa+sfac+on,  yellow  –  joy,  emo+ons  in   blog  community  
  • 142. Использование  современных  графиков  и  методов  визуализации  Popula+on  distribu+on  by  countries  
  • 143. Results  -­‐  Key  Tables  •  Study  flow  •  Comparison  between  study  and  control  group  at  baseline  (so   groups  are  comparable)   –  Give  characteris+cs  of  study  par+cipants  (e.g.  demographic,   clinical,  social)  and  informa+on  on  exposures  and  poten+al   confounders   –   Cohort  study—Summarise  follow-­‐up  +me  (e.g.,  average  and   total  amount)  •  Primary  comparison  table   –  (cohort,  RCT)  Report  absolute  (and  rela+ve)  differences  for   primary  endpoints   –  (cohort,  RCT)  Report  95%  CI  for  primary  endpoints   –  (case-­‐control)Report  numbers  in  each  exposure  category,  or   summary  measures  of  exposure   –  (cross-­‐sec+onal)  Report  numbers  of  outcome  events  or   summary  measures   143  
  • 144. Results  -­‐  Key  Tables  (con+nued)  •  Main  Results:   –   Give  unadjusted  es+mates  and,  if   applicable,  confounder-­‐adjusted   es+mates  and  their  precision  (e.g.,  95%   confidence  interval).  Make  clear  which   confounders  were  adjusted  for  and  why   they  were  included   –   Report  category  boundaries  when   con+nuous  variables  were  categorized   –   If  relevant,  consider  transla+ng   es+mates  of  rela+ve  risk  into  absolute   risk  for  a  meaningful  +me  period   144  
  • 145. Results  Checklist  Par+cipants   Report  number  of  individuals  at  each   stage  of  the  study   • Consider  flow  diagram   • Give  reasons  for  non-­‐par+cipa+on  Baseline  Data   Baseline  demographic  and  clinical   characteris+cs  for  each  group  Variables/Outcomes   Report  numbers  of  outcome  events  or   summary  measures  over  +me  Main  results   Give  unadjusted  es+mates  and  if   applicable,  confounder-­‐adjusted   es+mates  and  their  precision.    Adverse  effects   Readers  need  informa+on  on  (for  Experimental  Designs)   poten+al  harm  as  well  as  benefit   145  
  • 146. Results  examples  T h e   n e x t   s e v e r a l   s l i d e s  demonstrate   different   ways   to  present  results   146  
  • 147. Results:  CONSORT  Flow   Eligible     Non-­‐eligible   Declined   Alloca+on  using   randomiza+on   scheme   Follow-­‐up   Included  in   analysis   147  
  • 148. Results  –  sample  study  flow   148  
  • 149. Results  –  baseline  comparison   149  
  • 150. Results:  Primary  outcome  (RCT)   150  
  • 151. Results  –  primary  outcomes  (RCT)   151  
  • 152. Results:  Primary  outcome  (RCT)   152  
  • 153. Results  –  primary  outcome  (cohort)   153  
  • 154. Primary  outcome  (alterna+ve  figure)   154  
  • 155. Primary  Efficacy  End  Point  (RCT)   155  
  • 156. Results  –  primary  outcome   (Cross-­‐sec+onal)     156  
  • 157. Regression  with  primary  outcomes   (Cross-­‐sec+onal  study)   157  
  • 158. Results  –  Regression  with  Odds-­‐Ra+os   158  
  • 159. Results-­‐Report  Adverse  Effects  “The   propor+on   of   pa+ents   experiencing   any   adverse   event  was   similar   between   the   rBPI21   [recombinant   bactericidal/permeability-­‐increasing   protein]   and   placebo   groups:   168  (88.4%)   of   190   and   180   (88.7%)   of   203,   respec+vely,   and   it  was   lower   in   pa+ents   treated   with   rBPI21   than   in   those  treated   with   placebo   for   11   of   12   body   systems   …   the  propor+on   of   pa+ents   experiencing   a   severe   adverse   event,  as   judged   by   the   inves+gators,   was   numerically   lower   in   the  rBPI21   group   than   the   placebo   group:   53   (27.9%)   of   190  versus   74   (36.5%)   of   203   pa+ents,   respec+vely.   There   were  only   three   serious   adverse   events   reported   as   drug-­‐related  and  they  all  occurred  in  the  placebo  group.”   159  
  • 160. Discussion   Purpose:  to  interpret  your  results  and  jus+fy  your   interpreta+on  •  Dis+ll  the  essence  of  your  study   o  Re-­‐state  key  results   o  State  main  conclusion   ü Be  clear  about  why  results  support  the  conclusion   ü Maintain  connec+on  with  the  purpose  of  the  study  •  Interpret  your  study  in  the  context  of  the  literature   o  Compare  with  results  of/methods  used  in  related  studies   o  Emphasize  strengths  of  your  study  and  what  is  new  •  State  limita+ons/caveats  (frankly,  without  apology)  •  Make  recommenda+ons   o  Changes  in  prac+ce/policy   o  Future  studies,  including  some  specifics  (e.g.  study  method)   Oaen  requires  just  four  or  five  paragraphs   160  
  • 161. Discussion  Checklist    Dis2ll  the  essence  of  study   a.  Restate  key  results   b.  State  main  conclusion  -­‐  Be  clear  about  why  results  support  the  conclusion.  -­‐  Maintain  connec2on  with  purpose  of  the  study.  Interpret  your  study  in  the  context  of  the  literature   a.  Compare  with  results  of/methods  used  in  related  studies   b.  Emphasize  strengths  of  your  study,  and  what  is  new  State  limita2ons/caveats  (use  examples)  Discuss  limita2ons  of  the  study,  taking  into  account  sources  of  poten2al  bias  or  imprecision.  Discuss  both  direc2on  and  magnitude  of  any  poten2al  bias  Make  recommenda2ons   a.  changes  in  prac2ce/policy   b.  future  studies,  including  some  specifics  (e.g.  study  method) 161  
  • 162. Discussion  (Examples)  During  periods  of  seasonal  influenza  ac+vity,  we  found  moderately  ac+ve  (1.5–2.9  METs/day)  and  ac+ve  (≥3.0  METs/day)  individuals  to  be  approximately  15%  less  likely  to  have  an  influenza-­‐coded  physician  office  or  emergency  department  visit  compared  to  inac+ve  individuals.  When  stra+fied  by  age,  we  observed  similar  findings  among  individuals  <65  years  but  not  ≥65  years       KEY  RESULTS    Among  individuals  <65  years,  moderately  ac+ve  and  ac+ve  individuals  were  not  more  likely  than  inac+ve  individuals  to  visit  physicians  for  non-­‐influenza-­‐related  condi+ons  such  as  derma++s  or  periodic  health  examina+ons  during  influenza  season…   MAIN  CONCLUSIONS   162  
  • 163. Discussion  (Examples)  Aging   is   linked   to   declines   in   the   ability   to   defend  against  pathogens  [40],  and  has  been  associated  with  increased   morbidity   and   mortality   from   infec+ous  diseases   in   the   elderly   [40]–[41].   Addi+onally,   age-­‐related   declines   in   immune   response   to   influenza  vaccines   are   well   documented   [42]–[44].   The  reduced   immune   func+on   of   the   elderly   may   prevent  them   from   receiving   any   immune   system   benefits  from   physical   ac+vity.   [Comparison   with   other  studies]   163  
  • 164. Discussion  (Examples)  To   our   knowledge,   this   is   the   first   epidemiologic   study   that   has  examined   the   rela6onship   between   physical   ac6vity   and  influenza-­‐related   morbidity   during   seasonal   influenza   epidemics.  Previous  studies  have  mostly  focused  on  upper  respiratory  tract  infec+ons   (URTIs)   with   an   emphasis   on   athletes   [4],   and   only   a  few   focused   on   the   general   popula+on   [12],   [19],   [45].   Our  finding  of  a  15%  reduc+on  in  influenza-­‐coded  outpa+ent  visits  is  similar   to   the   20%   reduc+on   in   URTIs   observed   in   popula+on-­‐based   studies,   although   those   studies   used   self-­‐reported  outcome  measures  [12],  [19],  [45].  Only  one  other  study  assessed  the   associa6on   between   physical   ac6vity   and   influenza,   and   the  outcome   was   influenza-­‐associated   mortality   [9].   Although   a  beneficial  effect  was  found,  our  study  suggests  a  protec6ve  effect  at  a  much  earlier  stage  than  mortality.   164  
  • 165. Discussion  (Examples)  -­‐  limita+ons  This  study  had  several  limita+ons.  First,  our  outcome  measure  was  influenza-­‐coded  outpa6ent  visits  rather  than  laboratory-­‐confirmed  influenza  infec6ons,  which  would  be  the  most  ideal  outcome  measure  A  second  limita+on  is  that  measurement  of  physical  ac6vity  and  certain  covariates  relied  on  self-­‐report,  and  verifica6on  of  subject  responses  was  not  possible    First,  we  are  limited  in  our  ability  to  adequately  es+mate  an  associa+on  between  stone  history  and  renal  func+on  in  young  adults  due  to  a  lack  of  data  on  stone  formers  less  than  age  30   165  
  • 166. Discussion  -­‐  Recommenda+ons  Future   research   should   ideally   use   laboratory-­‐confirmed   influenza   outcomes   to   confirm   the  associa+on   between   physical   ac+vity   and  influenza  infec+on.  Public  health  authori+es  and  clinicians  should  work  toward  a  common  goal  of  increasing   physical   ac+vity   and   the   public’s  awareness   of   its   benefits.   These   ac+ons   may  help   to   mi+gate   the   health   and   economic  burden  caused  by  influenza.     166  
  • 167. Discussion  -­‐  Recommenda+ons    Further   work   in   alternate   study   samples   is   needed  to   validate   this   finding   and   to   determine   the  mechanisms   for   the   associa+on   between   kidney  stones   and   decreased   GFR.   However,   this   is   the   first  study   to   show   such   a   connec+on   in   a   na+onally  representa+ve   sample   of   the   United   States  popula+on.   Given   our   observa+ons,   the   serious  nature   of   renal   disease   and   the   increasing   incidence  of   nephrolithiasis   in   the   United   States,   further  inves+ga+on  is  warranted.   167  
  • 168. Abstract  Purpose:  to  highlight  key  points  from  major  sec+ons  of  the  ar+cle   Component   Abstracted  from   Major  purpose  of  study        Introduc+on   Basic  procedures        Methods   Main  findings        Results   Principal  conclusions        Discussion   Emphasize  what  is  new  and  useful   168  
  • 169. Synopsis  –  Find  weaknesses   Reliability of information about risk factors of chronic diseases collected in Missouri through the Behavioral Risk Factors Surveillance System. Synopsis (initial version) The Behavioral Risk Factors Surveillance System is widely used by health care authorities of the States to measure the prevalence of risk factors of chronic diseases. Despite its extensive utilization, only a few studies that assess reliability and validity of collected data have been conducted. A double testing study was carried out in the State of Missouri to assess reliability of information collected through the System. Authors repeatedly interviewed 222 people by phone, who passed full interview in March-April 1993. The repeated interview was conducted after 6-30 days following the first one. Repeatability of results was high for demographic data (kappa 0.85-1.00). Reliability of information about chronic diseases and risk factors thereof was also high. Kappa values ranged from 0.82 for the question about hypertension up to 1.00 for the question about smoking at that moment. In respect of the cancer survey procedures the reliability was lower for the knowledge of prostate cancer detection tests (kappa 0.21), than the tests used to diagnose cancer in women (mammography and smears). The question about attitude to smoking showed lower reliability than the question about actions to combat smoking. In general our data demonstrate flexibility of the System and its applicability to collecting information.
  • 170. Synopsis  –  Published  version:  Find  weaknesses   The Behavioral Risk Factors Surveillance System is widely used by health care authorities of the States to measure the prevalence of risk factors of chronic diseases. We carried out a double testing study to assess reliability of information collected through the System in the State of Missouri. We repeatedly interviewed 222 people by phone, who passed full interview in March-April 1993. The repeated interview was conducted after 6-30 days following the first one. Repeatability of results was high for demographic data (kappa 0.85-1.00). Reliability of information about chronic diseases and risk factors thereof was also high. Kappa values ranged from 0.82 for the question about hypertension up to 1.00 for the question about smoking at that moment. In respect of the cancer survey procedures the reliability was lower for the knowledge of prostate cancer detection tests (kappa 0.21), than the tests used to diagnose cancer in women (mammography and smears). The question about attitude to smoking showed lower reliability than the question about actions to combat smoking.
  • 171. Structured  Synopsis  DECREASE OF MORTALITY OF RECTAL CANCER BY IMPLEMENTATION OF SCREENING FOR BLOOD IN FECES Introduction. Although tests to detect blood in feces are widely used to diagnose rectal cancer, there are no evidences that such use can result into decrease of mortality of this type of cancer. We conducted a randomized survey of the use of the method and showed its efficiency. Methods. 46,551 participants of the survey aged 50-80 were randomly selected either for the control group or for one of the test groups. The rectal cancer screening was carried out once a years in the first group, and once in two years in the second one. Those with positive test results passed through additional examination, including colonoscopy. Mortality statistics were collected for all participants over 13 years observation period. A group of experts determined causes of death, and an autopsist (pathologist) determined a stage of cancer for each case. Variations in mortality of rectal cancer were assessed by special statistical methods. Results. Total mortality of rectal cancer over the 13 year period was worth 5.88 per 1,000 (95% confidence interval 4.61-7.15) in the annually screened group, 8.44 (95% confidence interval 6.82-9.84) in the biannually screened group, and 8.83 (95% confidence interval 7.26-10.40) in the control group. This indicator in the first screened group (not the second one) was certainly lower as compared to the control group. This group showed detection of cancer at earlier stage, and the forecast of the survival rate in patients was better along with decrease of mortality. Conclusions. Annual tests to detect blood in feces decreased total mortality of rectal cancer by 33% within 13 years.
  • 172. Finalizing  the  paper  and  submission   •  Drag  a  +tle   •  Wri+ng  and  edi+ng  process   •  Picking  a  journal   •  Last  sec+ons  :     –  References   –  Special  men+on   •  Transla+on   172  
  • 173. Title  Purpose:  to  provide  a  brief,  informa+ve  summary  that  will  asract  your  target  audience   What  goes  into  the  +tle?  •  The  topic  (T)  –  study  subjects  and  seing   o  Who,  what,  when,  where  •  In  addi+on,  chose  one  or  two  among:   o  M  –  Methods   o  R  –  Results   o  C  –  Conclusions   o  N  –  name  of  study  or  data  set   Highlight  what  is  new  and  useful   173  
  • 174. Title  examples   Title              T              M              R              C              N  •  Longitudinal  evalua6on  of  prostrate-­‐ •  +                +   specific  an6gen  levels  in  men  with  and     without  prostrate  disease  o  An  injury  preven+on  program  in  an   o  +   African-­‐American  community    •  Smoking,  pregnancy,  and  source  of  pre-­‐ •  +                                                                      +   natal  care:  Results  from  the  Pregnancy   Risk  Assessment  Monitoring  System    o  Reduc+on  of  high-­‐risk  sexual  behavior   o  +                +              ?   among  heterosexuals  undergoing  HIV   an+body  tes+ng:  A  randomized  clinical   trial   174  
  • 175. Examples  of  +tles:  Your  opinion?  Title                                              T          M            R            C              N                                                                                                                           Massive  mailing  does  not  effect  the  use  of  vaccines  among     MedicAir  Medical  insurance  recipients     Nurses  stress  factors  in  neonatal  Intensive  Case  Units:   American  Study     Experience  and  sa+sfac+on  of  primary  care,  secondary   Analysis  with  mul+level  modeling       HIV  mortality  and  infec+vity  in  India:  assessment  of     na+onal-­‐representa+ve  census  1.1  mln  of  residents   175
  • 176. Racial  difference  of  Survival  with  Oral  cancer  in  Georgia    Time  of  experiment  implementa+on:  Racial  difference  of  Survival  with  Oral  cancer  in  Georgia:  1978-­‐2001    Which  race(s)  under  higher  risk?    Reduced  survival  among  Afro-­‐American  pa+ents  with  oral  cancer  in  Georgia:  1978-­‐2001    The  analysis  controlled  the  major  risk  factors:  Reduced  survival  among  Afro-­‐American  pa+ents  with  oral  cancer  in  Georgia  ager  Risk  Factors  Control:  1978-­‐2001    Data  source?  Reduced  survival  among  Afro-­‐American  pa+ents  with  oral  cancer  in  Georgia  ager  Risk  Factor  Control:  Georgia  Registra+on  Index  SEER,  1978-­‐2001    The  higher  risk  limited  by  several  subgroups  of  Afro-­‐American  pa+ents:  Reduced  survival  among  subgroups  of  Afro-­‐American  pa+ents  with  oral  cancer  in  Georgia  ager  Risk  Factor  Control:  Georgia  Registra+on  Index  SEER,  1978-­‐2001       176
  • 177. Title  requirements   Bri2sh  Medical  Journal  (BMJ):   The  +tle  must  include  study  design  if  presented  as  an  original  study     American  Journal  of  Preven2ve  Medicine   Title  must  be  brief  but  informa+ve,  underline  but  not  describe,  serve  as  a  shortcut   but  not  an  offer,  reflect  what  was  done,  do  not  use  verbs,  include  nouns  for  easier   search,  do  not  use  symbols  or  abbrevia+ons      ICMJE  (Interna2onal  Commidee  of  Medical  Journals  Editors)  :   Short  +tles  easier  to  read.  Too  short  +tles  may  lack  the  informa+on  about,  for   example,  the  study  design.  Authors  encouraged  to  include  all  possible   informa+on  into  the  +tle  which  will  make  the  search  more  sensible  and  relevant.  
  • 178. Wri+ng  the  ar+cle  and  submiing  it   to  a  journal   178  
  • 179. Wri+ng  and  submiing  the  ar+cle  •  Conduct  literature  review  •  Start  the  paper!  •  Conduct  study/analyze  data  •  Organize/summarize  results  succinctly  •  Get  early,  frequent  feedback  (in  pieces)  •  Formulate  your  key  message  •  Apply  the  “new/useful”  test  •  Choose  your  target  audience  •  Choose  your  target  journal  •  Read  journal  instruc+ons  to  authors   179  
  • 180. Wri+ng  and  submiing  the  ar+cle  •  Drag  (and  debug)  an  abstract  •  Write  the  first  drag  •  Master  the  literature  •  Relearn,  rethink,  and  rewrite  •  …and  rewrite,  rewrite,  rewrite  •  How  long?  •  Cri+cally  review  and  finalize  the  abstract  •  Asend  to  the  details  •  Submit  ar+cle  to  the  target  journal  •  Have  a  “Plan  B”   180  
  • 181. Conduct  literature  review  •  Google  scholar  •  PubMed  –  try  “Single  Cita+on  Matcher”  •  Web  of  Knowledge  •  NIH-­‐funded  research  (RePORTER)  •  Contact  leading  inves+gators  to  learn  about   in-­‐press  or  unpublished  work  •  Scopus  •  •   181  
  • 182. Start  the  paper!  •  Yes,  even  before  you  do  the  study  •  Drag  the  introduc+on  –  perhaps  borrow  from   a  study  protocol  or  grant  proposal  that  you   already  wrote  •  Drag  dummy  table  shells  and  figure  axes  for   Results  •  Decide  which  sta+s+cal  methods  you  may   need  –  may  dictate  study  design   182  
  • 183. Conduct  study/analyze  data   183  
  • 184. Organize/summarize  results  succinctly  •  Fill  in  dummy  tables  and  figures  with  real   data  •  Drag  addi+onal  tables  and  figures  if  needed  –   look  at  published  ar+cles  for  poten+al   templates  •  Summarize  each  table  or  figure  in  a  single   sentence   184  
  • 185. Get  early,  frequent  feedback  (in  pieces)  •  Ask  coauthors/colleagues  if  your  tables/figures   and  text  summaries  are  clear/concise/compelling  •  Give  presenta+ons  to  colleagues  and  at   conferences  •  The  more  hurdles  you  clear  before  you  submit   your  paper  to  a  journal,  the  fewer  you  will  be   asked  to  clear  during  the  review  process  •  Don’t  wait  for  a  complete  drag  to  begin  geing   feedback   185  
  • 186. Formulate  your  key  message  •  Keep  it  simple;  try  to  boil  down  to  a  single   sentence  •  Your  message  must  contain  something  new   and  useful  •  Make  sure  your  results  support  your  key   message  •  The  message  may  change  as  you  develop  the   paper   186  
  • 187. Apply  the  “new/useful”  test  •  Journal  editors  are  interested  in  new   informa+on  that  is  useful  to  their  target   audience  •  Does  your  study  meet  these  criteria?  •  If  not,  the  effort  of  wri+ng  a  manuscript  may   not  be  warranted  •  If  yes…   187  
  • 188. Choose  your  target  audience  What  audience  is  most  interested  in  your  message?   o  Clinicians?   o  Public  health  prac++oners?   o  Basic  scien+sts?   o  A  broad  audience?   188  
  • 189. Choose  your  target  journal  •  Journal  impact  factor  •  Select  based  on:   o  Match  with  target  audience   o  Strength  of  your  ar+cle  •  Consider  aiming  high  –  reviewer  comments   from  a  high-­‐level  journal  can  be  valuable  •  However,  aiming  high  with  data  that  are   geing  “stale”  is  risky     189  
  • 190. Read  journal  instruc+ons  to  authors  •  Find  your  target  journal  “instruc+ons  for   authors”  on  the  Internet  or  in  an  issue  of  the   journal  •  Is  your  key  message  relevant  to  the  target   journal’s  mission  statement?   190  
  • 191. Drag  (and  debug)  an  abstract  •  Check  for  internal  consistency   o  Logical  flow  from  Purpose  to  Methods  to  Results   to  Conclusion?   o  Conclusion  consistent  with  the  Purpose?  •  If  you  see  flaws  in  the  Abstract,  ask  yourself:   o  Do  I  need  to  do  addi+onal  analyses?   o  Addi+onal  literature  review?   o  Addi+onal  thinking?   191  
  • 192. Write  the  first  drag  •  Write  for  your  target  audience  (use   appropriate  terminology  or  jargon)  •  Consider  using  an  outline  •  Don’t  spend  too  much  +me  on  the   grammar,  syntax,  or  details  (only  you   need  to  understand  the  first  drag)   192  
  • 193. Master  the  literature  •  As  you  obtain  feedback,  colleagues  will   direct  you  to  new  references  •  Update  your  PubMed  Single  Cita+on   Matcher  search    •  Russian  Scien+fic  Cita+on  Index  •  (and/or  local  UZ  equivalent)   193  
  • 194. Relearn,  rethink,  and  rewrite  •  As  you  master  the  literature,  you  will  see   your  work  in  a  new  light  •  Transmit  this  new  thinking  to  your   manuscript   194  
  • 195. …  and  rewrite,  rewrite,  rewrite  •  Most  papers  require  at  least  five  drags,   maybe  ten  –  save  and  date  them  all  •  You  may  need  to  revise  your  key  message  •  Perhaps  consider  changing  target  audience,   target  journal  •  Perhaps  your  paper  is  now  beser  than  you   ever  imagined,  and  you  want  to  aim  for  a   higher-­‐circula+on/impact  journal   195  
  • 196. How  long?  •  How  long  should  your  manuscript  be?  •  Follow  guidance  in  target  journal’s   instruc+ons  for  authors  •  “Shorter  papers  get  luckier  faster”   196  
  • 197. Cri+cally  review  and  finalize  the  abstract   •  Check  again  for  internal  consistency  (as   described  previously)   •  Make  sure  the  abstract  is  fully  consistent   with  the  body  of  the  ar+cle   197  
  • 198. Asend  to  the  details  •  Carefully  review  and  comply  with  target   journal’s  instruc+ons  for  authors  •  Call/e-­‐mail  the  journal  if  you  s+ll  have   ques+ons   198  
  • 199. Submit  ar+cle  to  target  journal   199  
  • 200. Have  a  Plan  B  Decide  on  your  next  target  journal  in  case  you  receive  a  rejec+on   200  
  • 201. About  the  importance  of  opportunity   and  impact  •  As  to  how  being  opportunis+c   can  lead  to  high  acceptability  of   research  grants  and  scien+fic   outputs  (examples  of   bioterrorism  research  in  the  US   ager  2001,  or  the  large  number   of  papers  and  research  that   focus  on  Q  fever,  for  example,   ager  the  outbreak  in  the   Netherlands).  •  But  watch  out  because  the   search  for  high  impact   publica+ons  can  lead  to   “miscarriages”  (the  case  of   Wakefield)   201  
  • 202. Wri+ng  for  Grant  Proposals   Eugene  Elbert,  MS     Johns  Hopkins  University,  U.S.A.   August  2012    
  • 203. Phases  of  Grant  Wri+ng  1.  Planning2.  Preparing3.  Writing4.  Submitting 203  
  • 204. 1.  Planning  •  Research funder’s program areas and priorities. –  What other projects have been funded?•  Read the instructions!•  For a specific RFP (request for proposals), READ the RFP!•  Does your project match the funder’s needs?•  Do you have the capacity to do the proposed project?•  Be familiar with the submission process –  Is there an online submission process?
  • 205. 2.  Preparing  •  Develop  your  idea   –  Is  it  new?  Interes+ng?     –  What  are  the  specific  aims?   –  What  is  your  research  design?   –  What  will  the  outcomes  be?  •  What  will  it  take  to  make  it  successful?   –  Who  will  lead  the  project?     –  Who  else  will  be  involved?     •  Internal  staff  and  external  partners   –  How  long  will  it  take  to  accomplish?   –  How  much  money  will  it  take?  
  • 206. 2.  Preparing  (con+nued)  •  Get  organized   –  Read  the  RFP  again   –  Is  a  leser  of  intent  (LOI)  needed  before  the  full   proposal  can  be  submised?  •  Develop  a  +meline  for  wri+ng  the  grant   proposal   –  Be aware of deadlines. Start early!  •  Assign  roles  in  the  proposal  process   –  Will  different  people  write  different  parts?   206  
  • 207. 3.  Wri+ng  •  Follow  direc+ons   –  Are  you  including  everything  as  requested?   –  Pay  asen+on  to  format  and  page  limits.  •  Make  it  easy  for  the  reviewer  to  read   –  Be  clear  and  concise   –  Use  buzzwords  that  will  stand  out  and  show  your   work  is  aligned  with  the  funder’s  goals  and  mission.   –  Do  not  use  jargon   –  Spell  out  abbrevia+ons  and  acronyms   207  
  • 208. 3.  Wri+ng  (con+nued)  •  Title   –  Make  it  interes+ng  and  clear   –  Does  it  capture  what  you  will  do?   –  Look  at  +tles  of  other  projects  the  funder  has   funded  for  format  •  Know  the  review  process   –  How  will  the  proposal  be  scored?   –  Is  one  part  more  important  than  another?   208  
  • 209. What  the  customer  wants…  Innova+on     •  New  methods  for  old  problems  (examples)   •  Old  methods  (elsewhere)  for  old  problems   (examples)   •  Any  method  for  new  problems  (BE  THE  FIRST)   o First  papers,  no  maser  how  precarious   become  seminal  ones  (1)       (1) Ugbomoiko et al. 2008. Parasites of importance for human health in Nigerian dogs: high prevalence and limited knowledge of pet owners. BMC Vet Research. 209  
  • 210. Parts  of  a  Grant  Proposal  NOTE: These are are different for different funders –read the instructions!1.  Cover  leser  2.  Summary  or  abstract  3.  Problem  or  Needs  statement  4.  Project  descrip+on   •  Introduc+on   •  Objec+ves     •  Methods  5.  Evalua+on  6.  Key  personnel  7.  Budget   210  
  • 211. The  Sec+ons  1.  Cover  leder   –  One  page  leser  addressed  to  the  funding  source   and  signed  by  the  highest  official  2.  Summary  or  abstract  3.  Problem  or  Needs  Statement   –  State  the  problem  with  facts  and  evidence  that   support  the  need  for  your  project.   –  Be  sure  to  use  accurate  data.   211  
  • 212. The  Sec+ons  (con+nued)  4.  Project Description –  Introduc2on     •  Provide  history  of  organiza+on  and  experience  of  your   team   •  How  does  this  work  fit  into  what  has  been  done  previously   by  you  and  others?   –  Objec2ves     •  List  2-­‐4  Specific  Aims  of  the  project   •  Define  the  measurable  outcomes  of  your  program.   –  Methods     •  What  ac+vi+es  that  will  take  place  to  achieve  the   objec+ves?   •  What  is  the  research  design?   212  
  • 213. The  Sec+ons  (con+nued)  5.  Evalua2on   –  How  you  will  measure  the  success  of  your  project?   –  Plan  for  con+nua+on  beyond  the  grant  period  6.  Key  personnel   –  Describe  the  people  needed  to  do  project   –  What  are  the  qualifica+ons  of  the  project  director  and   others?   –  What  are  their  roles  on  the  project  (  Director,  Program   Manager,  Sta+s+cian,  etc.  7.  Budget   –  How  much  will  it  cost  to  conduct  the  project?   –  Be  aware  of  funding  limits-­‐  do  not  ask  for  more  than  they   are  giving  out   –  Provide  jus+fica+on  of  costs     213  
  • 214. 4.  Submiing  •  Review your work –  Have you followed instructions? –  Ask someone from outside of your team to review your proposal to get a new perspective•  Revise –  Correct any errors –  Make as clear and concise as possible•  Submit –  Follow directions 214  
  • 215. More  Informa+on  Grant  Wri+ng  Tips  Sheet  [hsp://]    Common  Grant  Applica+on  (Na+onal  Network  of  Grantmakers)  [hsp://]    EPA  Purdue  University  Grant-­‐Wri+ng  Tutorial  (Environmental  Protec+on  Agency)  [hsp://]    Sample  proposals:  [hsp://]    Grants  and  Grant  Proposal  Wri+ng  (St.  Louis  University)  [hsp://]    All  About  Grants  Tutorials  (Na+onal  Ins+tutes  of  Health)  [hsp://]     215