When To Select Observational Studies as Evidence for Comparative Effectiveness Reviews Prepared for: The Agency for Healthcare Research and Quality (AHRQ) Training Modules for Systematic Reviews Methods Guide

Systematic Review Process Overview

 To understand why reviewers should consider including observational studies in comparative effectiveness reviews (CERs)  To understand when to include observational studies in CERs  To review important considerations for deciding whether to include observational studies to assess benefits and harms Learning Objectives

 Comparative effectiveness reviews should always consider including observational studies.  Reviewers should explicitly state the rationale for including or excluding observational studies. Current Perspective

 Systematic reviews that compare the relative benefits and harms among a range of available treatments or interventions for a given condition. Comparative Effectiveness Reviews

 May be unnecessary, inappropriate, inadequate, or impractical  May be too short in duration  May report intermediate outcomes rather than main health outcomes of interest  Often not available for vulnerable populations  Generally report efficacy rather than effectiveness Danger of Overreliance on Randomized Controlled Trials

 In these studies, investigators do not assign the exposure or intervention. These studies include:  All nonexperimental studies  Cohort, case-control, cross-sectional studies  We present considerations for including observational studies to assess benefits and harms separately. Observational Studies

 Reviewers should answer two questions:  Are there gaps in trial evidence for the review questions under consideration?  Will observational studies provide valid and useful information to fill these gaps and, thereby, answer the review questions? Using Observational Studies To Assess Benefits (I)

OS = observational study; PICOTS = population, intervention, comparator, outcome, timing, and setting. Using Observational Studies To Assess Benefits (II) Consider OSs Always consider: Controlled trials Will OSs provide valid and useful information? Assess whether OSs address the review question Are there gaps in trial evidence? Systematic review question ( including PICOTS) Yes Refocus the review question on gaps Assess the suitability of OSs: Natural history of the disease or exposure Potential biases Confine review to controlled trials No

 Trial data may be insufficient for a number of reasons:  Population: may not be available for subpopulations or vulnerable populations  Intervention: may not be able to assign high-risk interventions randomly  Comparator: may be insufficient evidence for comparators of interest  Outcome: may report intermediate outcomes rather than main health outcomes of interest  Timing: duration of follow-up for outcomes assessment may be too short  Setting: may not represent typical practice Gaps in Trial Evidence: PICOTS

 Risk of bias (internal validity)  The degree to which the findings may be attributed to factors other than the intervention under review  Consistency  Extent to which effect size and direction vary within and across studies  Inconsistency may be due to heterogeneity across PICOTS  Directness  Degree to which outcomes that are important to users of the comparative effective review (patients, clinicians, or policymakers) are encompassed by trial data  Health outcomes are generally most important Are Trial Data Sufficient? (I)

 Precision  Includes sample size, number of studies, and heterogeneity of effect sizes  Reporting bias  Extent to which trial authors appear to have reported all outcomes examined  Applicability  Extent to which the trial data are likely to be applicable to populations, interventions, and settings of interest to the user  The review questions should reflect the study characteristics (PICOTS) of interest Are Trial Data Sufficient? (II)

 Gaps in trial evidence can be identified at a number of points in the comparative effectiveness review:  In scoping of the review  In consulting with the Technical Expert Panel  In reviewing titles and abstracts  In reviewing trial data in detail When To Identify Gaps in Trial Evidence

Prepare Topic Refine topic Refine topic Develop analytic framework Develop analytic framework Search for and Select Studies for Inclusion Identify study eligibility criteria Identify study eligibility criteria Search for relevant studies Search for relevant studies Select evidence for inclusion Select evidence for inclusion Extract Data from Studies Analyze and Synthesize Studies Assess the quality of individual studies Assess the quality of individual studies Assess applicability Assess applicability Present findings Present findings Synthesize quantitative data Synthesize quantitative data Grade strength of evidence Grade strength of evidence Report Systematic Review Iterative Process for Identifying Gaps in Evidence

 Reviewers may perform initial searches broadly to identify both observational studies and trials.  Or, they may perform searches sequentially and search for observational studies after reviewing trials in detail to identify gaps in evidence. Gaps in Trial Evidence

Using Observational Studies To Assess Benefits Systematic review question ( including PICOTS) OS = observational study; PICOTS = population, intervention, comparator, outcome, timing, and setting. OS = observational study; PICOTS = population, intervention, comparator, outcome, timing, and setting Consider OSs Always consider: Controlled trials Will OSs provide valid and useful information? Assess whether OSs address the review question Are there gaps in trial evidence? Yes Refocus the review question on gaps Assess the suitability of OSs: Natural history of the disease or exposure Potential biases Confine review to controlled trials No

 Refocus the study question on gaps in trial evidence.  Respecify the PICOTS for gaps in trial evidence.  Assess whether available observational studies (OSs) may address the review questions.  Assess the suitability of OSs to answer the review questions. Will Observational Studies Provide Valid and Useful Information?

 After the gaps in evidence have been identified that observational studies (OSs) could potentially fill, reviewers should:  Consider the clinical context and natural history of the condition under investigation  Assess how potential biases may influence the results of OSs Assessing the Suitability of Observational Studies To Answer the Review Questions

 Fluctuating or intermittent conditions are more difficult to assess with observational studies (OSs), especially if there is no well-formed comparison group.  For most chronic conditions, the natural history is for symptoms to wax and wane over time; regression to the mean is an important consideration.  OSs may be more useful for conditions with steady progression or decline. Clinical Context

 Selection bias  Performance bias  Detection bias  Attrition bias Potential Biases That May Limit the Suitability of Including Observational Studies

 Is a type of selection bias  Occurs when different diagnoses, severity of illness, or comorbid conditions are important reasons for physicians to assign different treatments  Is a common problem in pharmacoepidemiological studies comparing benefits  Is often difficult to adjust for, making studies with a high degree of this potential bias usually unsuitable for inclusion in a comparative effectiveness review Confounding by Indication

 Observational studies (OSs) without a comparison group are rarely helpful in assessing benefits because of a high risk of bias.  In general, OSs must have a well-formed comparison group to be useful.  Establishing treatment benefits from OSs is uncommon; generally, it is necessary that efficacy be established first in randomized controlled trials. Using Observational Studies To Assess Benefits

 Assessing harms can be difficult.  Trials often focus on benefits, with little effort to balance assessment of benefits with assessment of harms.  Observational studies are almost always necessary to assess harms adequately.  There are trade-offs between increasing comprehensiveness by reviewing all possible observational studies that present harms and the decreased quality that may occur from increased risk of bias. Harms Assessments

 Randomized controlled trials (RCTs) are the gold standard for evaluating efficacy.  Relying solely on RCTs to evaluate harms in comparative effectiveness reviews is problematic.  Most RCTs lack prespecified hypotheses for harms because they are designed to evaluate benefits.  Assessment of harms is often a secondary consideration.  The quality and quantity of harms reporting is frequently inadequate.  Few studies have sufficient sample sizes or duration to adequately assess uncommon or long-term harms. Using Randomized Controlled Trials To Assess Harms (I)

 Most randomized controlled trials (RCTs) are efficacy trials.  They assess benefits and harms in ideal, homogenous populations and settings.  Patients who are more susceptible to harms are often underrepresented.  Few RCTs directly compare alternative treatment strategies.  The potential for publication bias and selective outcome reporting bias should be considered.  RCTs may not be available. Using Randomized Controlled Trials To Assess Harms (II)

 Nevertheless, head-to-head randomized controlled trials (RCTs) provide the most direct evidence on comparative harms.  Placebo-controlled RCTs can provide important information.  Comparative effectiveness reviews (CERs) should include both head-to-head and placebo- controlled RCTs for assessment of harms.  In lieu of RCTs, CERs may incorporate findings of well-conducted systematic reviews if they evaluated the specific harms of interest. Using Randomized Controlled Trials To Assess Harms (III)

 Consider including the results of unpublished completed or terminated randomized controlled trials and unpublished results from published trials.  The United States Food and Drug Administration Web site and are important sources.  Reviewers must consider whether or not the risk of bias can be fully assessed.  When significant numbers of published trials fail to report important harms, reviewers should report this gap in the evidence and consider efforts to obtain unpublished data. Using Data From Unpublished Trials To Assess Harms

 Observational studies (OSs) are almost always necessary to assess harms adequately.  The exception is when there are sufficient data from randomized controlled trials to estimate harms reliably.  OSs may provide the best or only data for assessing harms in minority or vulnerable populations who are underrepresented in trials.  The types of OSs included in a comparative effectiveness research will vary.  Different types of OSs might be included or rendered irrelevant by data available from stronger study designs. Using Observational Studies To Assess Harms

Chou R, et al. J Clin Epidemiol 2010;63:  Determining whether or not a hypothesis is being tested or generated is an important consideration in deciding which observational studies to include in harms assessments.  Case reports and case series are hypothesis generating.  Cohort and case-control studies are well suited for testing hypotheses that one intervention is associated with a greater risk for an adverse event than another and for quantifying the risk. Hypothesis Testing Versus Hypothesis Generating

 Cohort and case-control studies  Routinely search for and include cohort and case-controlled studies, except when randomized controlled trial data are sufficient and valid  OSs based on patient registries  OSs based on analyses of large databases  Case reports, case series, and postmarketing surveillance studies  Include studies of new medications for which sufficient harms data are not available  Other OSs Types of Observational Studies That Can Be Used To Assess Harms

 Often there are many more observational studies (OSs) than trials; evaluating a large number of OSs can be impractical when conducting a comparative effectiveness review (CER).  Criteria commonly used to screen OSs for inclusion in CERs:  Minimum duration of followup  Minimum sample size  Defined threshold for risk of bias  Study design restrictions (cohort and case-control)  Specific population of interest Screening Observational Studies for Inclusion in Harms Assessments

 Evidence from trials is often insufficient to answer all the key questions to be addressed in comparative effectiveness reviews (CERs).  The default strategy for CERs should be to consider including observational studies (OSs).  CERs should explicitly state the rationale for including or excluding OSs.  To assess benefits, reviewers should consider two questions:  Are there gaps in trial evidence for the review questions under consideration?  Will observational studies provide valid and useful information to address key questions?  To assess harms, reviewers should routinely search for and include comparative cohort studies and case-control studies. Key Messages

 Norris S, Atkins D, Bruening W, et al. Comparative effectiveness reviews and observational studies In: Agency for Healthcare Research and Quality. Methods Guide for Comparative Effectiveness Reviews. Rockville, MD. In press.  Chou R, Aronson N, Atkins D, et al. AHRQ series paper 4: assessing harms when comparing medical interventions: AHRQ and the Effective Health Care Program. J Clin Epidemiol 2010;63: References

 This presentation was prepared by Dan Jonas, M.D., M.P.H., and Karen Crotty, Ph.D., M.P.H., members of the Research Triangle Institute– University of North Carolina Evidence-based Practice Center.  The module is based on Norris S, Atkins D, Bruening W, et al. Comparative effectiveness reviews and observational studies In: Agency for Healthcare Research and Quality. Methods Guide for Comparative Effectiveness Reviews. Rockville, MD. In press. Authors