When To Select Observational Studies as Evidence for

Comparative Effectiveness ReviewsPrepared 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

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 onRandomized 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 StudiesTo Assess Benefits (I)

OS = observational study; PICOTS = population, intervention, comparator, outcome, timing, and setting.

Using Observational StudiesTo 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 exposurePotential 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 Prepare TopicTopic

• Refine topicRefine topic

•Develop Develop analytic analytic frameworkframework

Search for and Search for and Select Studies for Select Studies for

InclusionInclusion

•Identify study Identify study eligibility criteriaeligibility criteria

•Search for relevant Search for relevant studiesstudies

•Select evidence for Select evidence for inclusioninclusion

Extract Extract Data from Data from

StudiesStudies

Analyze and Analyze and Synthesize StudiesSynthesize Studies

•Assess the quality Assess the quality of individual of individual studiesstudies

•Assess Assess applicabilityapplicability

•Present findingsPresent findings

•Synthesize Synthesize quantitative dataquantitative data

•Grade strength of Grade strength of evidenceevidence

Report Report Systematic Systematic

ReviewReview

Iterative Process forIdentifying 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, andsetting

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 exposurePotential 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 StudiesProvide 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 ObservationalStudies 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 theSuitability 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 ControlledTrials 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 ControlledTrials 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 ControlledTrials 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 UnpublishedUsing Data From UnpublishedTrials To Assess HarmsTrials 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;63:502-12.

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 studiesRoutinely search for and include cohort and case-

controlled studies, except when randomized controlled trial data are sufficient and valid

OSs based on patient registriesOSs based on analyses of large databasesCase 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 StudiesTypes of Observational StudiesThat Can Be Used To Assess HarmsThat 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 Studiesfor 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;63:502-12.

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