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Planning and Conducting Research in Medicine

Planning and Conducting Research in Medicine. Outline. Introduction Planning Research Collecting Research Data Analyzing Research Data Conclusion. Medical Research. Observe Phenomenon. Propose Hypothesis. Plan Research. Collect and Analyze Data. Interpret Results. Example.

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Planning and Conducting Research in Medicine

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  1. Planning and Conducting Research in Medicine

  2. Outline • Introduction • Planning Research • Collecting Research Data • Analyzing Research Data • Conclusion

  3. Medical Research Observe Phenomenon Propose Hypothesis Plan Research Collect and Analyze Data Interpret Results

  4. Example • Some of my friends are eating vitamin E to prevent colon cancer. • Hypothesis: Vitamin E can prevent colon cancer • Questions • How many people are eating vitamin E? How many people are having colon cancer? • What is the association between eating vitamin E and having colon cancer? • Can vitamin E prevent colon cancer?

  5. Purpose of Research • Description • Estimation • Making comparisons • Assessing association

  6. Planning Research • Literature Review • DEFINITION • Consult Experts • Study Design • Sampling Arrangement • Data Collection Arrangement • Statistical Analysis Plan • Practical Considerations

  7. Planning Research • Literature Review • DEFINITION • Consult Experts • Study Design • Sampling Arrangement • Data Collection Arrangement • Statistical Analysis Plan • Practical Considerations

  8. Literature Review • What has been done and how • Population • Study design • Statistical methods • What has not been done • Limitation of the studies • Issues missed in the previous studies • Learn more about background info • Find more relevant studies

  9. Planning Research • Literature Review • DEFINITION • Consult Experts • Study Design • Sampling Arrangement • Data Collection Arrangement • Statistical Analysis Plan • Practical Considerations

  10. DEFINITION • The key to a successful study • “A Problem well defined is a problem half solved” • Refine the hypothesis • Be specific • Define variables • Outcome variables (primary and secondary) • Explanatory variables • Biological meaningful and clinically useful

  11. DEFINITION (continued) • Clearly described in the protocol and report • Examples • Classification of BMI (body mass index) • Estrogen-Receptor Status

  12. Planning Research • Literature Review • DEFINITION • Consult Experts • Study Design • Sampling Arrangement • Data Collection Arrangement • Statistical Analysis Plan • Practical Considerations

  13. Consult Experts • When? • BEFORE design your study • Who? • Colleagues with experiences in study design and statistical analyses • Epidemiologist • Biostatistician

  14. Planning Research • Literature Review • DEFINITION • Consult Experts • Study Design • Sampling Arrangement • Data Collection Arrangement • Statistical Analysis Plan • Practical Considerations

  15. Design of Analytical Studies • Observational studies • Cross-sectional / prevalence • Case-control / retrospective • Cohort / prospective • Experimental studies • Controlled clinical trials

  16. Cross-Sectional Study TIME No Disease Diseased Exposed Exposed Not Exposed Not Exposed

  17. Cross-Sectional Study (continued) • Data collected at a single point in time • A “snapshot” • Describe prevalence • Prevalence vs. Incidence • Assess associations

  18. Cross-Sectional Study (continued) • Strength • Quick • Cheap • Weakness • Can not establish cause-effect

  19. Case-Control Study TIME Not Exposed Not Exposed Exposed Exposed Exposed No Disease Diseased cases controls

  20. Case-Control Study (continued) • Starts with people who have disease • Matches them with people who do not have disease (control) • Looks history for exposures • Assesses associations

  21. Case-Control Study (continued) • Strength • Fast • Cheap • Useful to generate hypothesis • Good for rare diseases • Can examine several exposures • Estimates odds ratio

  22. Case-Control Study (continued) • Weakness • Can only study one outcome • Can not measure • Prevalence • Incidence • Relative risk • High susceptibility to bias

  23. Cohort Study TIME Not Exposed Exposed disease free Disease Free Develop Disease Disease Free Develop Disease

  24. Cohort Study • Starts with disease-free subjects • Classifies subjects as exposed or not exposed • Records outcomes • Assesses associations

  25. Cohort Study (continued) • Strength • Allows for accurate measurement of exposure variables • Estimates incidence • Estimates relative risk • Can measure multiple outcomes • Can adjust for confounding variables • Establishes time sequence for causality • Eliminates recall bias

  26. Cohort Study (continued) • Weakness • Time consuming • Expensive • Can not study rare outcomes • Confounding variables • Disease may have a long pre-clinical phase • Exposure may change over time • Attrition of study population

  27. Clinical Trial (therapeutic) TIME Studied population (with disease) Randomized Placebo Treatment No Disease No Disease Diseased Diseased

  28. Clinical Trial (preventive) TIME Studied population (without disease) Randomized Placebo Treatment No Disease No Disease Diseased Diseased

  29. Clinical Trial (continued) • Starts with subject with diseases (therapeutic) or without diseases (preventive) • Randomized • Blinding • Placebo controlled

  30. Clinical Trial (continued) • Strength • “Gold Standard” • Best design for controlling bias • Can measure multiple outcomes • Best measurement of causal relationship • Weakness • Expensive • Compliance • Ethical issues may be a problem

  31. Summary of Analytical Studies

  32. Meta-Analysis • Main Goal • Combine the results of previous studies to reach summary conclusions about a body of research • Steps • Identify studies with relevant data • Define inclusion and exclusion criteria • Abstract data • Analyze abstracted data statistically

  33. Planning Research • Literature Review • DEFINITION • Consult Experts • Study Design • Sampling Arrangement • Data Collection Arrangement • Statistical Analysis Plan • Practical Considerations

  34. Sampling Arrangement • Population • Methods of Sampling (observational) • Sample Assignment (experimental) • Sample Size • Bias

  35. Sampling Arrangement • Population • Inclusion and exclusion criteria • Methods of Sampling (observational) • Sample Assignment (experimental) • Sample Size • Bias

  36. Sampling Arrangement • Population • Methods of Sampling (observational) • Sample Assignment (experimental) • Sample Size • Bias

  37. Methods of Sampling • Probability Sampling • Simple random sampling • Systematic sampling • Stratified sampling • Cluster sampling • Area sampling

  38. Methods of Sampling (continued) • Non-Probability Sampling • Subjective (Judgment) sampling • Convenient (Chunk) sampling • Quota Sampling

  39. Sampling Arrangement • Population • Methods of Sampling (observational) • Sample Assignment (experimental) • Sample Size • Bias

  40. Sample Assignment • Randomization • Fixed Allocation Randomization • Adaptive Randomization Procedures

  41. Sampling Arrangement • Population • Methods of Sampling (observational) • Sample Assignment (experimental) • Sample Size • Bias

  42. Sample Size • Does size matter? • Why do we care? • Ethical Consideration • Time • $$$ • How to calculate? • Software (http://www.stat.ubc.ca/~rollin/stats/ssize/) • Expert

  43. Sample Size Calculation • Clinically significant effect • Ho and HA • Type I Error • Type II Error (or Power) • Variance in the outcome measure

  44. Sampling Arrangement • Population • Methods of Sampling (observational) • Sample Assignment (experimental) • Sample Size • Bias

  45. Bias • A process at any stage of inference tending to produce results that depart systematically from the true values • Selection bias • Measurement bias • Confounding bias

  46. Confounding • Confounding is an apparent association between disease and exposure caused by a third factor not taken into consideration

  47. Confounding (continued) • Example • A study found an association between cigar smoking and baldness. • What is a possible confounder?

  48. If we detected an association, is there an indirect effect of another (unrecognized) factor? Ispitivani čimbenik (proučavamo učinak kave) Zbunjujući čimbenik (pušenje “uz kavu” zapravo izaziva bolest)

  49. How to Control Confounding • Study Design • Restrict study eligibility • Match on confounding factor • Analysis • Stratify on the confounding factor • Adjust for the confounding factor • Multivariate analysis

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