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Study design


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Study design

  1. 1. Study Design Observational study design Dr. Hawazen Zarif
  2. 2. Observational study A study in which no intervention is made. Such studies provide estimates and examine associations of events in their natural settings
  3. 3. Retrospective vs. Prospective • Retrospective = measurement obtained after outcome occurred • Prospective = measurement obtained before outcome occurred
  4. 4. What is an observational study? There are three main types of observational studies: – Cohort (prospective and retrospective), – Case control – Cross-sectional
  5. 5. Which Design to choose? • Depending on the study question Object Common Design Prevalence Cross Sectional Incidence Cohort Cause (in order of reliability) Cohort, case-control, cross sectional Prognosis Cohort Treatment effect Controlled Trial
  6. 6. Study Design • Research Question – P patient – I intervention – C comparison group – O outcome – T time • Literature Search
  7. 7. The Evidence Hierarchy Meta- Analysis Systematic Review Randomized Controlled Studies Cohort Studies Case Control Studies Case Series/Reports
  8. 8. When should observational studies be performed? – Clinical trials difficult in certain areas, e.g Surgery or Anesthesiology – Exploratory (generate hypothesis) – Exposure cannot be manipulated by the investigator – Interventions for very rare diseases or rare adverse effect – Studies about accuracy of diagnostic tests
  9. 9. Cross-Section Cohort Case-Control Present: Disease and exposure Present: Exposure Future: Disease Present: Disease Past: Exposure Observational Studies
  10. 10. Cross Sectional Studies Sample ControlsCases Exposed Unexposed
  11. 11. Cross-sectional studies Not ExpExp Disease No Disease a d E b nE c N nD D Odds Ratio (OR) = a/b C/D
  12. 12. Measures Disease Frequency Cross-Sectional Study • Prevalence: The number of cases in a population at a given point in time. • Notice any proportion can be estimated in the 2X2 table Not ExpExp Disease No Disease a d E b nE c N nD D
  13. 13. Cross Sectional Study • Cross sectional studies are also used to infer causation. • At one point in time the subjects are assessed to determine whether they were exposed to the relevant agent and whether they have the outcome of interest. Some of the subjects will not have been exposed nor have the outcome of interest
  14. 14. Advantages • Subjects are neither deliberately exposed, treated, or not treated and hence there are seldom ethical difficulties. • Only one group is used, data are collected only once and multiple outcomes can be studied • There is no loss to follow up
  15. 15. Advantages • Quick and cheap- less resources are required to run the study • Cross sectional studies are the best way to determine prevalence and are useful at identifying associations that can then be more rigorously studied using a cohort study or randomized controlled study
  16. 16. Disadvantages • The most important problem with this type of study is differentiating cause and effect from simple association. For example, a study finding an association between low CD4 counts and HIV infection does not demonstrate whether HIV infection lowers CD4 levels or low CD4 levels predispose to HIV infection. • Only a snap shot (At a specific time)
  17. 17. Disadvantages • Often there are a number of plausible explanations. For example, if a study shows a negative relation between height and age it could be concluded that people lose height as they get older, younger generations are getting taller, or that tall people have a reduced life expectancy when compared with short people. • Cross sectional studies do not provide an explanation for their findings
  18. 18. Disadvantages • Rare conditions cannot efficiently be studied using cross sectional studies because even in large samples there may be no one with the disease. In this situation it is better to study a cross sectional sample of patients who already have the disease (a case series).
  19. 19. Population Risk factor Disease present Risk factor No disease present No risk factor Disease Present No risk factor No disease Selected sample Cross sectional study Summary
  20. 20. Key Points Cross Sectional Studies - The best way to determine prevalence. - Are relatively quick & cheap - Can study multiple outcomes. - Do not themselves differentiate between cause and effect or the sequence of events. - Not for studying rare conditions - The principal summary statistic is the odds ratio Cross sectional study Summary
  21. 21. Cohort studies A group of individuals who share a common characteristic and who are then followed up at specified intervals to determine outcomes.
  22. 22. • Cohort studies look forwards in time by following up each subject • Subjects are selected before the outcome of interest is observed • They establish the sequence of events • Numerous outcomes can be studied • They are the best way to establish the incidence of a disease • They are a good way to determine causes of diseases • The principal summary statistic of cohort studies is the relative risk ratio Cohort Study -Summary
  23. 23. Disease-Free Cohort Exposed Unexposed Cases Controls Cases Controls Present Future
  24. 24. Cohort Study = sampled = observed Not ExpExp Disease No Disease a d E b nE c N nD D Note that E and nE are fix by design. Relative risk (RR)= a/(a+b) C/(C+D)
  25. 25. A prospective cohort study • A group of people is chosen who do not have the outcome of interest (e.g MI) • The investigator then measures a variety of variables that might be relevant to the development of the condition. • Over a period of time the people in the sample are observed to see whether they develop the outcome of interest (that is, myocardial infarction). • One group has been exposed to or treated with the agent of interest and the other has not, thereby acting as an external control.
  26. 26. Cohort Study - Prospective = sampled = observed EXPOSED UNEXPOSED Present Future D nD D nD
  27. 27. A retrospective cohort study • If the data are readily available then a retrospective design is the quickest method. • These use data already collected for other purposes. • The methodology is the same as prospective cohort
  28. 28. Cohort Study – Retrospective (Historical) = sampled = observed EXPOSED UNEXPOSED Past of Past Past D nD D nD
  29. 29. Advantages • A randomised controlled trial may be unethical; for e.g cigarette smoke or asbestos. Thus research on risk factors relies heavily on cohort studies • The study can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is cause and which is effect. • Allow to calculate the incidence of disease • A single study can examine various outcome variables e.g smokers can simultaneously look at deaths from lung, cardiovascular, and cerebrovascular disease • Calculation of the effect of each variable on the probability of developing the outcome of interest (relative risk).
  30. 30. Disadvantges • Expensive and time consuming • Inappropriate for rare diseases – disease with a long latency • Loss of follow up: incidence = cases/per period of time), it can be seen that the loss of a few cases will seriously affect the numerator • Presence of confounders
  31. 31. Confounding Variable • A confounding variable is independently associated with both the variable of interest and the outcome of interest. For example, lung cancer (outcome) is less common in people with asthma (variable). However, it is unlikely that asthma in itself confers any protection against lung cancer. • The only way to eliminate all possibility of a confounding variable is via a prospective randomized controlled study. In this type of study each type of exposure is assigned by chance and so confounding variables should be present in equal numbers in both groups.
  32. 32. Retrospective Vs. Prospective Cohort studies • Retrospective studies are much cheaper as the data have already been collected. • Unlikely that all the relevant information will have been rigorously collected.
  33. 33. Population Selected Sample Variable Present Conditions Developed Conditions do not develop (internal controls) Variable Absent External Controls Conditions Developed Condition does not develop Cohort Study -Summary
  34. 34. Key Points Cohort Studies - Cohort studies describe incidence or natural history. - They analyze predictors (risk factors) thereby enabling calculation of relative risk. - Cohort studies measure events in temporal sequence thereby distinguishing causes from effects. - Retrospective cohorts where available are cheaper and quicker. - Confounding variable are the major problem in analyzing cohort studies. - Subject selection and loss to follow up is major potential cause of bias. Cohort Study -Summary
  35. 35. Case Control Exposed Unexposed Exposed Unexposed Present Past Population
  36. 36. Case-control studies • Retrospective • A population with a particular outcome is compared with a matched population without the outcome. Researchers can then look at variables “retrospectively” in each group to see if there are any factors that are associated with having or not having the outcome • Where the outcome is rare, case-control studies may be the only feasible approach. As some of the subjects have been deliberately chosen because they have the disease • Only one outcome is studied • Case-control studies can however be used to calculate odds ratios
  37. 37. Case-control Study = sampled = observed Not ExpExp Disease No Disease a d E b nE c N nD D One may estimate: OR Odds (Exp|D) Odds (nE|D) = ad bc = Odds (Exp|D) = P (Exp|D) 1−P (nE|D) Odds (D|Exp) Odds (D|nExp) =
  38. 38. Advantages • When conditions are rare • When there is a long latent period between an exposure and the disease, • The only feasible option e.g of new variant CJD and possible aetiologies • Requires few study subjects • Less funds – Quick results
  39. 39. Disadvantages • Can not generate incidence data • Difficult if records are inadequate • Selection bias • Recall bias
  40. 40. Disadvantages Sampling bias: • The patients with the disease may be a biased sample • Observation and recall bias : As the study assesses predictor variables retrospectively there is great potential for a biased assessment of their presence and significance by the patient or the investigator, or both.
  41. 41. Study Individuals Selected Cases Exposed Not Exposed Selected Controls Exposed Not Exposed
  42. 42. Key Points Case Control Studies - Case control studies are simple to organize - Retrospectively compare two groups - Aim to identify predictors of an outcome. - Permit assessment of the influence of predictors on outcome via calculation of an odds ratio - Useful for hypothesis generation - Can only look at one outcome - Bias is a major problem
  43. 43. Experimental Study Design Randomized Controlled Trials
  44. 44. • Why do a randomized clinical trial? • generally reserved for mature questions • considered as "gold standard" for demonstrating efficacy • incorporates design features to maximize outcome ascertainment and minimize bias • minimize risk of confounding • Why not do a randomized clinical trial? • major ethical or feasibility issues (e.g. vaccine, toxic agents) • cost and logistics concerns • unrealistic time horizon
  45. 45. Randomized Controlled Trials
  46. 46. Randomized Controlled Clinical Trials • Phases of a clinical trial • Equipoise • Randomization • Blinding • Intention to treat analysis
  47. 47. Definition A prospective planned experiment designed to assess the effect of a treatment by comparing the observed outcomes in a group exposed to an intervention with those in a comparable group receiving a control or placebo treatment. e.g. drug vs. placebo, drug vs. standard of care, medicine vs. surgery; low dose vs. high dose, etc. The observed differences are attributed to the intervention. The outcome must be clearly defined prior to commencing the study.
  48. 48. The Principle of Equipoise Equipoise indicates genuine, community-based uncertainty. A consensus regarding the uncertainty of the risk/benefit of an investigational agent. Needed to justify carrying out an RCT (i.e. randomizing treatment)
  49. 49. Choice of Participants INCLUSION CRITERIA  appropriate to the study question  reflect the potential benefit the intervention  generalizable  ease of recruitment EXCLUSION CRITERIA  safety concerns  intervention likely ineffective  conditions that could compete with the outcomes (e.g. early death)  contradictions to intervention of interest  adherence issues
  50. 50. Typically, and inert agent (i.e. placebo) is ideal but might not always possible (e.g. "sham" surgery, side effects). May want to consider and active therapy as a control (e.g. standard of care). Note: Placebo is not ethical in virtually all studies that involve diseases with a proven/established treatment. Remains ethical in trials where no proven treatment is established Choice of Control
  51. 51. • Easy to diagnose, collect or observe • Clinically relevant • Chosen before the start of data collection • Outcomes: – Primary – Secondary – Surrogate – Composite Choice of Outcomes
  52. 52. Experimental Design sample intervention control Yes No Yes NoInclusion Exclusion improved
  53. 53. Randomization The process of assigning participants to treatment and control – Assuming that each participant has an equal chance of being assigned to any group. – Assignment of participants to treatment by a random process such that neither the investigator nor the participant knows the treatment to be assigned at the start of the study. – Study participants are assigned to treatment groups by chance (not by choice). • Random number generator (table or computer) • Centralized and secure system
  54. 54. Why is it important? In a clinical trial, you need comparability among study groups and the best way to assure comparability is by randomization. Features: - Balances patient baseline characteristics to all arms of the study. - Equal distribution of all known and unknown confounding variables i.e. minimizes the possibility that the observed association between the exposure and the outcome is in reality caused by another factor. - Allows for an unbiased comparison between groups and forms the basis for the derivation of statistical tests
  55. 55. Refers to masking treatment assignment from patients, investigators and/ or end point assessors. • Single blind - participants are not aware of treatment assignment • Double blind - both participants and investigators unaware • Triple blind - various meanings – - persons who perform tests – - outcome adjudicators – - safety monitoring group I C Blinding (Masking)
  56. 56. If an outcome can conceivably be affected by patient or investigator expectations, then maintaining blinding is important. Maintains balanced groups during follow-up and minimizes biased outcome ascertainment (participant) and measurement (investigator). Can be assessed: - ask participants to guess treatment - ask study staff to guess treatment Why Blinding?
  57. 57. Key Features: In the attempt to reduce bias and to improve the quality of evidence: - Prospective - Comparison (control) - Pre specified outcomes and analysis - Randomization - Blinding Notes: - treatment is assigned by randomization into an experimental and control (comparison) group. - course is tracked prospectively and differences in outcomes are compared. - differences are attributed to the intervention. OutcomeInterventionPopulation timesample treatment group control group randomization Basic ("parallel") Design blinding
  58. 58. Crossover Design sample time treatment control randomization treatment control washout period OutcomeIntervention OutcomeIntervention Population Advantages - good for chronic or repeating conditions (e.g. epilepsy) - gain in power because each participant is their own control Disadvantage - washout and sequence effect considerations (e.g. long drug half life) - very susceptible to participant drop outs
  59. 59. Factorial Design sample treatment A + placebo B randomization OutcomeIntervention Population treatment A + treatment B placebo A + treatment B placebo A + placebo B A B C D 2 X 2 Design (simplest) treatment 1 treatment2 controlactive controlactive Advantages - can examine main effects and interaction effects Disadvantage - may be difficult to disentangle the interaction effect and interpret results
  60. 60. Analysis of RCTs • Intention to treat analysis: Once randomized always analyzed • Everyone on treatment (by assignment or choice) versus everyone not on treatment • Per protocol analysis: analyze only subjects that complied to the assigned treatment 61
  61. 61. # Subs. Length Purpose Success Phase I 20 – 100 Several months Mainly Safety 70% Phase II Up to several 100 Several months- 2 yrs. Short term safety; mainly effectiveness 33% Phase III 100s – several 1000 1-4 yrs. Safety, dosage & effectiveness 25-30% Summary of Phases
  62. 62. RCTs vs. Observational studies RCTs Observational Studies Selection bias If randomization is done properly, negligible Likely to occur Measurement bias If blinding is done properly in double blinded studies, less likely Possible especially with subjective outcomes Statistical Analysis Simpler – usually unadjusted simple analysis is sufficient (t-tests or ANOVAs) More complicated – adjusted analysis is necessary with logistic or linear regression or cox proportional hazard models (survival) Unmeasured confounders Usually balanced if sample size is appropriate Usually imbalanced External validity Usually limited as restrictions of patients who can participate in the trial The real-world scenario makes this design more externally valid Ethical issues Placebo use can be an ethical issue Minimal ethical issues usually Costs High Usually lower Power Might be under powered due high costs Usually high power (large cohorts) Follow-up Limited Usually long from Merit Cudkowicz, MD
  63. 63. Object Common Design Prevalence Cross Sectional Incidence Cohort Cause (in order of reliability) Cohort, case-control, cross sectional Prognosis Cohort Treatment effect Controlled Trial
  64. 64. Thank You 6th Clinical Methodology Research Course65 09/06/2014