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Systematic Reviews EPI 214

Systematic Reviews EPI 214

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Systematic Reviews EPI 214

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  1. Systematic ReviewsEPI 214 • Course Goals • Learn the skills necessary to design and complete a systematic review (but know when to seek statistical help) • Be able to critique published systematic reviews • Have a fun and interesting class

  2. Course Overview

  3. Grading and Homework • Grading is not a priority, but a requirement • 60% homework • 40% final exam • Homework • BRING 2 HARD COPIES TO CLASS! (one to hand in, one to use for notes, if desired). • If you are going to miss class, let us know ahead of time and e-mail homework to our class TA (Ashok: • Final Exam: • Will be distributed in class on April 28th • Please complete and hand in by May 12th, 5pm, to Olivia Deleon in China Basin Suite 5706-02 (5th floor)  mailbox 0560 OR e-mail to our class TA)

  4. Sections • Steve Bent Rm 6702 • Wendy Katzman Rm 6704 • Dejana Braithwaite Rm 5759

  5. TICR Professional Conduct StatementClarifications for this class • I will maintain the highest standards of academic honesty • I will neither give nor receive aid in examinations or assignments unless such cooperation is expressly permitted by the instructor • I will conduct research in an unbiased manner, report results truthfully, and credit ideas developed and work done by others • I will not use answer keys from prior years • I will write answers in my own words, and, when collaboration is permitted, acknowledge collaborators when answers are jointly formulated

  6. EPI-214: Lecture 1 Designing a Systematic Review (Meta-analysis) Dejana Braithwaite Assistant Professor UCSF Department of Epidemiology and Biostatistics

  7. 8 steps of a systematic review Bent et al. 2004 1 Formulate research question Lecture 1 2 Develop review protocol 3 Initiate search strategy 4 Apply inclusion /exclusion criteria 5 Quality appraisal 6 Data abstraction 7 Analysis Lectures 1, 2 & 3 8 Interpret findings

  8. What’s a Systematic Review? “A review of the evidence on a clearly formulated question that uses systematic and explicit methods to identify, select and critically appraise relevant primary research, and to extract and analyze data from the studies that are included in the review.” Cochrane Collaboration

  9. …and meta-analysis? Statistical combination of ≥ 2 studies to produce single estimate of effect of exposure

  10. Rapid growth Pubmed search up to 3/29/2010: Systematic review >1.5 million hits Meta-analysis >40,000 hits • up to 1/1/1990: • Systematic review 300,994 hits • Meta-analysis 845

  11. The Cochrane CollaborationInternational systematic review initiative • Archie Cochrane’s vision led to the opening of the first Cochrane centre (in Oxford, UK) in 1992 and the founding of the Cochrane Collaboration in 1993 Source:

  12. Meta-analysis in the NYT accessed 3/30/10 Sattar N, et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet. 2010 Feb 27;375(9716):735-42. Epub 2010 Feb 16.

  13. Meta-analysis in the NYT February 2010

  14. Systematic Review in context

  15. Narrative review Key characteristics Uses informal, unsystematic and subjective methods Searching quality and synthesis not described • Disadvantages • may have preconceived biases and may overestimate value of some studies

  16. Systematic review Driven by evidence-based medicine movement Advantages: • Reduces bias • Replicable • Resolves controversy between conflicting findings • Provides reliable basis for decision making

  17. Use of meta-analysis as a prelude to clinical trials Define pre-trial expected effect sizes sample size estimation • Determine effect estimates in key subgroups (e.g. based on gender, race/ethnicity or age) • Identify sources of heterogeneity in prior studies • Addressing these sources in design phase of new trial

  18. Use of meta-analysis in study designs that are not clinical trials Observational studies • Studies evaluating diagnostic tests • “IPD” = individual patient data studies • Qualitative studies (meta-ethnography)

  19. Meta-analyses IPD* Systematic reviews *IPD= individual participant data

  20. Resources required for systematic reviewing Can be time consuming Team science (to reduce bias) Bibliographic software (e.g. Endnote) Statistical software (if appropriate)

  21. Step 1 Formulate research question

  22. FINER criteria for research question Feasible Interesting Novel Ethical Relevant Hulley S, et al. 2001 Designing Clinical Research

  23. Anatomy of a research question – PICO(T) Patient Intervention (or “Exposure”) Comparison Outcome (Type of study)

  24. Patient: Disease or condition Stage, severity Demographic characteristics (age, gender, etc.) Intervention (or “Exposure”): Type of intervention or exposure Dose, duration, timing, route, etc. Comparison: Absence of risk or treatment Placebo or alternative therapy

  25. Outcome: • Risk or protective • Dichotomous or continuous • Type: mortality, morbidity, quality of life, etc. • Type of study: • RCTs • Cohort • Case-control • Cross-sectional • All

  26. Formulation of an etiology question Exposure Outcome Is smoking a risk factor for lung cancer? Patient Exposure Are people who smoke regularly at a greater risk of developing lung cancer as compared to those who do not smoke? + cohort & case-control studies Outcome Comparison

  27. Formulation of a diagnosis question Test (intervention) Outcome Is MRI a good test for breast cancer? Test (intervention) Outcome Is MRI a more sensitive and specific test in diagnosing breast cancer as compared to mammography? Comparison

  28. Step 2 Develop review protocol

  29. Protocol Background Objectives Pre-determined selection criteria Planned search strategy Planned data abstraction Proposed method of synthesis of findings Establishment of an advisory group

  30. Step 3 Initiate search strategy

  31. Where to locate studies Pubmed CINAHL Web of Science EMBASE PsychINFO

  32. Additional sources to identify studies for systematic reviews Reference lists of retrieved articles Manual searching of relevant publications Experts in the field Corresponding or first authors of published studies identified for the systematic review

  33. Issues to consider Publication bias Search bias

  34. Pubmed citation example Title: Interaction between 5-HTTLPR genotype, stressful life events and depression Search terms: Life stress Life event Depression Depress Serotonin transporter 5-HTTLPR Interaction Moderation Risch et al. JAMA 2010

  35. Step 4 Apply inclusion /exclusion criteria

  36. Inclusion/exclusion criteria P - Population I - Intervention C - Comparison (if necessary) O - Outcome T - Type of study (if necessary) Subject headings OR Textwords To find studies using all of the PICO elements: P and I and C and O (and T)

  37. Exclusion criteria Keep log of excluded studies Note reasons for exclusion Have eligibility checked by more than one reviewer Develop strategy to resolve disagreements

  38. Search strategy example Risch et al. JAMA 2010

  39. Step 5 Quality appraisal

  40. Principles of quality appraisal Quantitative studies Internal Validity allocation bias, confounding, attrition, statistical analysis, intervention integrity, withdrawals and dropouts External Validity (generalizability or applicability)

  41. Standard quality appraisal tools

  42. QUORUM for trials Moher et al. Improving the quality of reports of meta-analyses of randomized controlled trials: The QUORUM statement. Lancet 1999;354:1896-1900

  43. MOOSE for observational designs Stroup et al. Meta-analysis of observational studies in epidemiology. JAMA 2000;283:2008-12

  44. Qualitative research Checklists available to assess the quality of qualitative research. E.g. CASP appraisal tool for qualitative research (

  45. Recruit participants SELECTION BIAS ALLOCATION BIAS Allocate to intervention and control groups Intervention group Control group CONFOUNDING INTEGRITY OF INTERVENTION Implement intervention Implement intervention INTENTION-TO-TREAT Follow-up participants Follow-up participants WITHDRAWALS/ DROP OUTS Measure outcomes BLINDING OUTCOME ASSESSORS Measure outcomes DATA COLLECTION METHODS Analyze outcomes Analyze outcomes STATISTICAL ANALYSIS

  46. Step 6 Data abstraction

  47. Design and pilot data abstraction form • Consider >1 reviewer Data abstraction

  48. publication details study design population details (n, characteristics) intervention details setting outcomes and findings Data abstraction elements

  49. Summary of study characteristics - example Risch et al. JAMA 2009