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Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials.

ABSTRACT: BACKGROUND:Evidence based medicine aims to integrate scientific evidence, clinical experience, and patient values and preferences. Individual health care professionals need to appraise the evidence from randomized trials and observational studies when guidelines are not yet available. To date, tools for assessment of bias and terminologies for bias are specific for each study design. Moreover, most tools appeal only to methodological knowledge to detect bias, not to subject matter knowledge, i.e. in-depth medical knowledge about a topic. We propose a unified framework that enables the coherent assessment of bias across designs. METHODS:Epidemiologists traditionally distinguish between three types of bias in observational studies: confounding, information bias, and selection bias. These biases result from a common cause, systematic error in the measurement or common effect of the intervention and outcome respectively. We applied this conceptual framework to randomized trials and show how it can be used to identify bias. The three sources of bias were illustrated with graphs that visually represent researchers' assumptions about the relationships between the investigated variables (causal diagrams). RESULTS:Critical appraisal of evidence started with the definition of the research question in terms of the population of interest, the compared interventions and the main outcome. Next, we used causal diagrams to illustrate how each source of bias can lead to over- or underestimated treatment effects. Then, we discussed how randomization, blinded outcome measurement and intention-to-treat analysis minimize bias in trials. Finally, we identified study aspects that can only be appraised with subject matter knowledge, irrespective of study design. CONCLUSIONS:The unified framework encompassed the three main sources of bias for the effect of an assigned intervention on an outcome. It facilitated the integration of methodological and subject matter knowledge in the assessment of bias. We hope that graphical diagrams will help clarify debate among professionals by reducing misunderstandings based on different terminology for bias.

SUBMITTER: Luijendijk HJ

PROVIDER: S-EPMC7510067 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials.

Luijendijk Hendrika J HJ Page Matthew J MJ Burger Huibert H Koolman Xander X

BMC medical research methodology 20200923 1

<h4>Background</h4>Evidence based medicine aims to integrate scientific evidence, clinical experience, and patient values and preferences. Individual health care professionals need to appraise the evidence from randomized trials and observational studies when guidelines are not yet available. To date, tools for assessment of bias and terminologies for bias are specific for each study design. Moreover, most tools appeal only to methodological knowledge to detect bias, not to subject matter knowle ...[more]

PMID: 32967622

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Project description:BackgroundProton-pump inhibitors (PPIs) are widely prescribed as acid-suppression therapy. Some observational studies suggest that long-term use of PPIs is potentially associated with certain adverse kidney outcomes. We conducted a systematic literature review to assess potential bias in non-randomized studies reporting on putative associations between PPIs and adverse kidney outcomes (acute kidney injury, acute interstitial nephritis, chronic interstitial nephritis, acute tubular necrosis, chronic kidney disease, and end-stage renal disease).MethodsWe searched the medical literature within 10 years of 17 December 2020. Pre-specified criteria guided identification of relevant English language articles for assessment. Risk of bias on an outcome-specific basis was evaluated using the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tool by two independent reviewers.ResultsOf 620 initially identified records, 26 studies met a priori eligibility criteria and underwent risk of bias assessment. Nineteen studies were judged as having a moderate risk of bias for reported adverse kidney outcomes, while six studies were judged as having a serious risk of bias (mainly due to inadequate control of confounders and selection bias). We were unable to determine the overall risk of bias in two studies (one of which was assessed as having a moderate risk of bias for a different adverse kidney outcome) due to insufficient information presented. Effect estimates for PPIs in relation to adverse kidney outcomes varied widely (0.24-7.34) but associations mostly showed increased risk.ConclusionUsing ROBINS-I, we found that non-randomized observational studies suggesting kidney harm by PPIs have moderate to serious risk of bias, making it challenging to establish causality. Additional high-quality, real-world evidence among generalizable populations are needed to better understand the relation between PPI treatment and acute and chronic kidney outcomes, accounting for the effects of varying durations of PPI treatment, self-treatment with over-the-counter PPIs, and potential critical confounders.

Project description:ImportanceObservational (nonexperimental) studies that aim to emulate a randomized trial (ie, the target trial) are increasingly informing medical and policy decision-making, but it is unclear how these studies are reported in the literature. Consistent reporting is essential for quality appraisal, evidence synthesis, and translation of evidence to policy and practice.ObjectiveTo assess the reporting of observational studies that explicitly aimed to emulate a target trial.Evidence reviewWe searched Medline, Embase, PsycINFO, and Web of Science for observational studies published between March 2012 and October 2022 that explicitly aimed to emulate a target trial of a health or medical intervention. Two reviewers double-screened and -extracted data on study characteristics, key predefined components of the target trial protocol and its emulation (eligibility criteria, treatment strategies, treatment assignment, outcome[s], follow-up, causal contrast[s], and analysis plan), and other items related to the target trial emulation.FindingsA total of 200 studies that explicitly aimed to emulate a target trial were included. These studies included 26 subfields of medicine, and 168 (84%) were published from January 2020 to October 2022. The aim to emulate a target trial was explicit in 70 study titles (35%). Forty-three studies (22%) reported use of a published reporting guideline (eg, Strengthening the Reporting of Observational Studies in Epidemiology). Eighty-five studies (43%) did not describe all key items of how the target trial was emulated and 113 (57%) did not describe the protocol of the target trial and its emulation.Conclusion and relevanceIn this systematic review of 200 studies that explicitly aimed to emulate a target trial, reporting of how the target trial was emulated was inconsistent. A reporting guideline for studies explicitly aiming to emulate a target trial may improve the reporting of the target trial protocols and other aspects of these emulation attempts.

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Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials.

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Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials.

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