When to Select Observational Studies as Evidence for Comparative Effectiveness ReviewsPresentation Transcript
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 www.ahrq.gov
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
Comparative effectiveness reviews should always consider including observational studies.
Reviewers should explicitly state the rationale for including or excluding observational studies.
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.
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)
Using Observational Studies To Assess Benefits (II) 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? 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
Extent to which effect size and direction vary within and across studies
Inconsistency may be due to heterogeneity across PICOTS
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)
Includes sample size, number of studies, and heterogeneity of effect sizes
Extent to which trial authors appear to have reported all outcomes examined
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
Iterative Process for Identifying Gaps in Evidence
Develop analytic framework
Search for and Select Studies for Inclusion
Identify study eligibility criteria
Search for relevant studies
Select evidence for inclusion
Extract Data from Studies
Analyze and Synthesize Studies
Assess the quality of individual studies
Synthesize quantitative data
Grade strength of evidence
Report Systematic Review
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 OS = observational study; PICOTS = population, intervention, comparator, outcome, timing, and setting. Systematic review question ( including PICOTS) 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.
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.
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 www.ClinicalTrials.gov 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
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 Chou R, et al. J Clin Epidemiol 2010;63:502-12.
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
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.
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;63:502-12.
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.