Clinical Research Methodology


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Clinical Research Methodology

  1. 1. Clinical Research Methodology
  2. 2. Aims and Objectives <ul><li>Be able to understand different types of clinical research/epidemiology methodology </li></ul><ul><li>Understand the advantages and disadvantages of different clinical research/epidemiology methods </li></ul><ul><li>Use the appropriate clinical research/epidemiology method to investigate research questions </li></ul>
  3. 3. Clinical Research/Epidemiology <ul><li>Normality/abnormal </li></ul><ul><li>Diagnosis </li></ul><ul><li>Frequency </li></ul><ul><li>Risk </li></ul><ul><li>Prognosis </li></ul><ul><li>Treatment </li></ul>
  4. 4. Steps in Clinical Research <ul><li>Observation </li></ul><ul><li>Association </li></ul><ul><li>Causation </li></ul><ul><li>Intervention </li></ul><ul><li>Evaluation </li></ul>
  5. 5. Cross-sectional study <ul><li>Descriptive study or survey </li></ul><ul><li>measure exposure and outcome in one moment in time </li></ul><ul><li>exposure and outcome are measured simultaneously </li></ul>
  6. 6. Cross-sectional study <ul><li>Advantages </li></ul><ul><li>quick and simple </li></ul><ul><li>can study many associations </li></ul><ul><li>can estimate prevalence </li></ul><ul><li>low participation/high response </li></ul><ul><li>possible to show validity and reproducibility </li></ul><ul><li>healthcare planning </li></ul><ul><li>Disadvantages </li></ul><ul><li>problems with casualty </li></ul><ul><li>survivor bias </li></ul><ul><li>recall bias </li></ul><ul><li>inefficient for rare diseases </li></ul><ul><li>not suitable for disease of short duration </li></ul><ul><li>prevalence affected by low response and migration in and out of population </li></ul>
  7. 7. Steps in Clinical Research <ul><li>Observation </li></ul><ul><li>Association </li></ul><ul><li>Causation </li></ul><ul><li>Intervention </li></ul><ul><li>Evaluation </li></ul>
  8. 8. Association and Causation <ul><li>Association  Causation </li></ul><ul><ul><li>eg earlobe crease and ischemic heart disease </li></ul></ul><ul><li>Case control study </li></ul><ul><li>Cohort study </li></ul>
  9. 9. Explanations for a Positive Association <ul><li>Bias </li></ul><ul><li>Confounding </li></ul><ul><li>Chance </li></ul><ul><li>Reverse Causation </li></ul><ul><li>Causation </li></ul>
  10. 10. Bias <ul><li>A systemic error introduced into the study by an investigator </li></ul><ul><ul><li>Result from design </li></ul></ul><ul><ul><li>Just plain wrong </li></ul></ul><ul><li>Two main types of bias </li></ul><ul><ul><li>Selection bias </li></ul></ul><ul><ul><li>Information bias </li></ul></ul>
  11. 11. Selection Bias <ul><li>Occurs when selection of cases or control is related to exposure </li></ul><ul><ul><li>Selection of patients from hospitals, specialised centres </li></ul></ul><ul><ul><li>Selection of “healthy” controls from hospitals </li></ul></ul><ul><ul><li>Response rate bias </li></ul></ul><ul><ul><li>Self selection bias </li></ul></ul><ul><ul><li>Survival bias </li></ul></ul>
  12. 12. Selection Bias - example <ul><li>Large scale study showed that “married” better survival than “widowed” </li></ul><ul><li>But … if widowed who remarried are reclassified as “married” and if illnesses reduce the chance of remarried, effect may be due to selection bias </li></ul><ul><li>Control from hospitals are more likely to have higher risk of smoking and high alcohol intake </li></ul>
  13. 13. Information Bias <ul><li>Misclassification </li></ul><ul><li>Observer Bias </li></ul><ul><li>Recall Bias </li></ul>
  14. 14. Information Bias – Observer Bias <ul><li>Observer know the underlying hypothesis and ask more probing question to those exposed than controls </li></ul><ul><li>Remedies </li></ul><ul><ul><li>Blind the observer </li></ul></ul><ul><ul><li>Use highly structured interview </li></ul></ul>
  15. 15. Information Bias - Recall Bias <ul><li>Disease status affect patients’ response </li></ul><ul><ul><li>Patient with musculoskeletal diseases are more likely to remember minor trauma </li></ul></ul><ul><li>Particular problem with case control studies </li></ul><ul><li>Remedies </li></ul><ul><ul><li>Find reliable records </li></ul></ul><ul><ul><li>Use control with other illnesses </li></ul></ul>
  16. 16. Confounding <ul><li>Confounders confuse an association </li></ul>A C B
  17. 17. Features of Confounding <ul><li>Causal relationship between confounder and outcome </li></ul><ul><li>Confounder associated with outcome </li></ul><ul><li>Not simple on chain of causation </li></ul><ul><li>Eg depression smoking MI </li></ul>
  18. 18. Remedies to Confounding <ul><li>Design </li></ul><ul><ul><li>Match (match case and control for gender and age) </li></ul></ul><ul><ul><li>Restriction (limit study to certain groups) </li></ul></ul><ul><ul><li>Randomisation (limit to treatment) </li></ul></ul><ul><li>Analysis </li></ul><ul><ul><li>Stratification </li></ul></ul><ul><ul><li>Standardisation </li></ul></ul><ul><ul><li>Statistical modeling </li></ul></ul>
  19. 19. Case Control Study <ul><li>Retrospective study of previous exposure </li></ul><ul><li>Identify “Cases” and “Controls” </li></ul><ul><li>Assess and compare the “exposure to risk” in “Cases” and “Controls” </li></ul><ul><li>eg smoking and lung cancer, HRT and ischemic heart disease </li></ul>
  20. 20. Case Control Study <ul><li>Advantages </li></ul><ul><li>efficient for rare diseases </li></ul><ul><li>relatively cheap and quick </li></ul><ul><li>useful for long latency periods </li></ul><ul><li>useful for acute exposure </li></ul><ul><li>Disadvantages </li></ul><ul><li>prone to bias </li></ul><ul><li>difficulties in selecting controls </li></ul><ul><li>inefficient for rare exposures </li></ul><ul><li>cannot calculate incidence rate </li></ul><ul><li>temporal relationship may not be clear </li></ul>
  21. 21. Cohort Study <ul><li>Measures exposure then seek information on subsequent disease experience </li></ul><ul><li>PROSECTIVE </li></ul><ul><li>Avoid bias provide large number are not lost to follow up </li></ul><ul><li>BUT don’t remove confounding </li></ul>
  22. 22. Steps in Clinical Research <ul><li>Observation </li></ul><ul><li>Association </li></ul><ul><li>Causation </li></ul><ul><li>Intervention </li></ul><ul><li>Evaluation </li></ul>
  23. 23. Intervention and Evaluation <ul><li>Randomised controlled trial (RCTs) </li></ul><ul><li>Not all risk can be tested in RCTs </li></ul><ul><ul><li>sex </li></ul></ul><ul><ul><li>smoking </li></ul></ul><ul><ul><li>income </li></ul></ul><ul><li>Clinical Effectiveness </li></ul><ul><ul><li>Efficacy in trials vs efficacy in real world </li></ul></ul><ul><li>Costs, feasibility, acceptibility </li></ul>
  24. 24. Steps in Designing Clinical Trial <ul><li>Rationale </li></ul><ul><li>Hypothesis </li></ul><ul><li>Type of trial </li></ul><ul><li>Population studied </li></ul><ul><li>Outcome Measures </li></ul><ul><li>Number of cases </li></ul><ul><li>Analysis of results </li></ul>
  25. 25. Rationale for Trial <ul><li>New drug </li></ul><ul><ul><li>does it work </li></ul></ul><ul><li>Established drug </li></ul><ul><ul><li>are there new indications </li></ul></ul><ul><li>Conventional therapy </li></ul><ul><ul><li>improving efficacy </li></ul></ul><ul><li>Delivering care </li></ul><ul><ul><li>benefits of non-drug therapy </li></ul></ul>
  26. 26. Rationale for Trial <ul><li>The clinical problem </li></ul><ul><li>The burden of disease </li></ul><ul><li>Conventional therapy </li></ul><ul><ul><li>Benefits </li></ul></ul><ul><ul><li>Limitations </li></ul></ul>
  27. 27. Rationale for trial <ul><li>Strong </li></ul><ul><li>Common disease </li></ul><ul><li>High health costs </li></ul><ul><li>High social costs </li></ul><ul><li>Poor current therapy </li></ul><ul><li>Significant clinical benefit likely </li></ul><ul><li>Weak </li></ul><ul><li>Rare disease </li></ul><ul><li>Limited morbidity </li></ul><ul><li>Reasonable current therapy </li></ul><ul><li>Limited benefit likely </li></ul>
  28. 28. Examples in Rheumatoid Arthritis <ul><li>Does new analgesic reduce pain? </li></ul><ul><li>Does new slow-acting drug reduce inflammation? </li></ul><ul><li>Can combination therapy decrease joint damage in early disease? </li></ul>
  29. 29. Hypothesis <ul><li>Simple </li></ul><ul><li>Testable </li></ul><ul><li>Relevant </li></ul><ul><li>Concise </li></ul>
  30. 30. An Example In RA Does adding monthly IM depot steroids to conventional slow-acting drugs reduce the number of patients developing new erosions?
  31. 31. Type of Trial <ul><li>Parallel Group </li></ul><ul><li>Factorial </li></ul><ul><li>Cross-over </li></ul><ul><li>n- of- 1 </li></ul>
  32. 32. Parallel Groups Cases Randomised Treatment O Treatment A Cases Randomised Treatment O Treatment A Treatment B
  33. 33. Factorial design Cases Randomised O A B A+B
  34. 34. Cross-over Design Cases Randomised O A A O
  35. 35. Selecting Cases (a) <ul><li>Hospital / community </li></ul><ul><li>National/ international </li></ul><ul><li>Age, sex and general health </li></ul><ul><li>Activity, severity and duration </li></ul>
  36. 36. Select cases (b) <ul><li>Inclusion Criteria </li></ul><ul><li>Definite cases </li></ul><ul><li>Known activity </li></ul><ul><li>Known duration </li></ul><ul><li>Informed </li></ul><ul><li>Exclusion Criteria </li></ul><ul><li>Young </li></ul><ul><li>Elderly </li></ul><ul><li>Sick </li></ul><ul><li>Non-responders </li></ul>
  37. 37. Selecting cases (c) Hard Inclusion Criteria Soft Inclusion Criteria Less chance of response Good generalisability Rapid entry Good chance response Poor generalisability Long period of entry
  38. 38. Randomised Controlled Trials (RCT) <ul><li>Randomisation </li></ul><ul><li>Tossing a coin </li></ul><ul><li>Stratification </li></ul><ul><ul><li>sex </li></ul></ul><ul><ul><li>disease duration </li></ul></ul><ul><ul><li>geographic areas </li></ul></ul><ul><li>Blindness </li></ul><ul><li>To avoid placebo response </li></ul><ul><li>Levels of blindness </li></ul><ul><ul><li>Patient blind </li></ul></ul><ul><ul><li>Assessor blind </li></ul></ul><ul><ul><li>Triple blind </li></ul></ul><ul><li>Code breaking </li></ul>
  39. 39. Outcome measures <ul><li>Simple and reliable </li></ul><ul><li>Widely accept </li></ul><ul><li>Likely to change </li></ul><ul><li>Relevant for hypothesis </li></ul><ul><li>One primary outcome </li></ul><ul><li>A limited number of outcomes </li></ul>
  40. 40. Core Data In RA <ul><li>Demographic details </li></ul><ul><ul><li>Age, sex, disease duration </li></ul></ul><ul><ul><li>Social class and race </li></ul></ul><ul><li>EULAR core data set </li></ul><ul><ul><li>Joint Counts and Pain Scores </li></ul></ul><ul><ul><li>Acute Phase Measures (ESR) </li></ul></ul><ul><ul><li>Function (HAQ) and X-rays (Larsen score) </li></ul></ul><ul><li>Predictive factors </li></ul><ul><ul><li>Rheumatoid factor </li></ul></ul>
  41. 41. Physician And Patient Assessments
  42. 42. Clinical Outcomes <ul><li>Impairment </li></ul><ul><ul><li>Persisting synovitis </li></ul></ul><ul><li>Functional </li></ul><ul><ul><li>Limitations in daily living </li></ul></ul><ul><li>Radiological </li></ul><ul><ul><li>Anatomical joint damage </li></ul></ul><ul><li>Patient centred </li></ul><ul><ul><li>Changes in lifestyle </li></ul></ul>
  43. 43. Number of Cases: Sample Size <ul><li>Calculations are conventional based on showing a difference of 5% significant at 90% power </li></ul><ul><li>Continuous discrete variables can be used </li></ul><ul><li>Additional numbers should be included to allow for dropouts* </li></ul>
  44. 44. Controls and Blinding <ul><li>To avoid placebo response </li></ul><ul><li>Placebo or not </li></ul><ul><ul><li>placebo  no treatment </li></ul></ul><ul><li>Levels of blindness </li></ul><ul><ul><li>Patient blind </li></ul></ul><ul><ul><li>Assessor blind </li></ul></ul><ul><ul><li>Triple blind </li></ul></ul><ul><li>Code breaking </li></ul>
  45. 45. Significance and Power <ul><li>Convention needs a difference with less than 5% of being due to chance </li></ul><ul><li>Convention suggests we should be 90% certain that the failure to find no difference between treatments is just due to chance. </li></ul>
  46. 46. Analysis (a) <ul><li>Always planned in trial design </li></ul><ul><li>Usually after all patients completed study </li></ul><ul><li>Interim analysis are often misleading </li></ul><ul><li>Data dredging is unhelpful </li></ul>
  47. 47. Analysis (b) Potential cases Did not fulfil entry criteria Given information Did not consent Randomised Early withdrawal Adverse effect Lack of effect Inter-current illness Other Completed study
  48. 48. Analysis (c) <ul><li>Difference must be significant in primary outcome measure for positive trial </li></ul><ul><li>Changes in secondary out comes provides supportive information or places therapy in context. </li></ul>