ReviewBMC medical research methodology2012
A framework for organizing and selecting quantitative approaches for benefit-harm assessment.
Review in BMC medical research methodology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05237635 (Defining Decision Thresholds for Judgments on Health Benefits and Harms Using the GRADE Evidence to Decision), which is not on this map. Cited by 27 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Defining Decision Thresholds for Judgments on Health Benefits and Harms Using the GRADE Evidence to Decision (EtD) Frameworks: Protocol for a Randomized Methodological Study (GRADE-THRESHOLD)
Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The GRADE Working Group clarifies the construct of certainty of evidence.Journal of clinical epidemiology · 2017Guideline
- Personalized respiratory medicine: exploring the horizon, addressing the issues. Summary of a BRN-AJRCCM workshop held in Barcelona on June 12, 2014.American journal of respiratory and critical care medicine · 2015Pooled it
- Outcome Preferences in Patients With Noninfectious Uveitis: Results of a Best-Worst Scaling Study.Investigative ophthalmology & visual science · 2015Trial
- Enhancing clinical interpretation of patient-reported outcomes: A cross-platform toolkit for clinically important difference estimation using R Shiny and statistical analysis system.General psychiatry · 2026Article
- Dose-response, net clinical benefit and optimal dose ranges of stimulants in children and adolescents with ADHD: a network meta-analysis.European child & adolescent psychiatry · 2026Article
- Optimal risk thresholds for prescribing statins as primary prevention of cardiovascular disease in Iranian general population: a benefit-harm modelling study.BMC cardiovascular disorders · 2024Article
- A proposal for using benefit-risk methods to improve the prominence of adverse event results when reporting trials.Trials · 2024Article
- Methodological guidelines and publications of benefit-risk assessment for health technology assessment: a scoping review.BMJ open · 2024Article
- Methodological guidelines and publications of benefit-risk assessment for health technology assessment: a scoping review protocol.BMJ open · 2023Article
- Large-scale prevention trials could provide stronger evidence for decision-makers: Opportunities to design and report with a focus on the benefit-harm balance.Clinical trials (London, England) · 2022Article
- Article
- To Expand the Evidence Base About Harms from Tests and Treatments.Journal of general internal medicine · 2021Article
- Use of Patient Preferences in Health Technology Assessment: Perspectives of Canadian, Belgian and German HTA Representatives.The patient · 2021Article
- Iranian general populations' and health care providers' preferences for benefits and harms of statin therapy for primary prevention of cardiovascular disease.BMC medical informatics and decision making · 2020Article
- Extensions of the probabilistic ranking metrics of competing treatments in network meta-analysis to reflect clinically important relative differences on many outcomes.Biometrical journal. Biometrische Zeitschrift · 2020Article
- Article
- Factors and Situations Affecting the Value of Patient Preference Studies: Semi-Structured Interviews in Europe and the US.Frontiers in pharmacology · 2019Article
- E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance.Frontiers in pharmacology · 2019Article
- Should statin guidelines consider patient preferences? Eliciting preferences of benefit and harm outcomes of statins for primary prevention of cardiovascular disease in the sub-Saharan African and European contexts.BMC cardiovascular disorders · 2018Article
- Benefit, risk and cost of new oral anticoagulants and warfarin in atrial fibrillation; A multicriteria decision analysis.PloS one · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundSeveral quantitative approaches for benefit-harm assessment of health care interventions exist but it is unclear how the approaches differ. Our aim was to review existing quantitative approaches for benefit-harm assessment and to develop an organizing framework that clarifies differences and aids selection of quantitative approaches for a particular benefit-harm assessment.
methodsWe performed a review of the literature to identify quantitative approaches for benefit-harm assessment. Our team, consisting of clinicians, epidemiologists, and statisticians, discussed the approaches and identified their key characteristics. We developed a framework that helps investigators select quantitative approaches for benefit-harm assessment that are appropriate for a particular decisionmaking context.
resultsOur framework for selecting quantitative approaches requires a concise definition of the treatment comparison and population of interest, identification of key benefit and harm outcomes, and determination of the need for a measure that puts all outcomes on a single scale (which we call a benefit and harm comparison metric). We identified 16 quantitative approaches for benefit-harm assessment. These approaches can be categorized into those that consider single or multiple key benefit and harm outcomes, and those that use a benefit-harm comparison metric or not. Most approaches use aggregate data and can be used in the context of single studies or systematic reviews. Although the majority of approaches provides a benefit and harm comparison metric, only four approaches provide measures of uncertainty around the benefit and harm comparison metric (such as a 95 percent confidence interval). None of the approaches considers the actual joint distribution of benefit and harm outcomes, but one approach considers competing risks when calculating profile-specific event rates. Nine approaches explicitly allow incorporating patient preferences.
conclusionThe choice of quantitative approaches depends on the specific question and goal of the benefit-harm assessment as well as on the nature and availability of data. In some situations, investigators may identify only one appropriate approach. In situations where the question and available data justify more than one approach, investigators may want to use multiple approaches and compare the consistency of results. When more evidence on relative advantages of approaches accumulates from such comparisons, it will be possible to make more specific recommendations on the choice of approaches.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.