ArticleAnnals of internal medicine2020
The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement.
Article in Annals of internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 214 papers, 14 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
214 citing papers in PubMed, 14 syntheses or guidelines pooled it.
- Sex differences in trial representation and the cardiovascular effectiveness of newer glucose-lowering agents in patients with and without type 2 diabetes: A systematic review and meta-analysis of cardiovascular outcome trials.Diabetes, obesity & metabolism · 2026Pooled it
- Balanced crystalloid versus saline for resuscitation in pediatric septic shock: a systematic review and meta-analysis.BMC pediatrics · 2025Pooled it
- Blood Pressure Targets for Adults with Vasodilatory Shock - An Individual Patient Data Meta-Analysis.NEJM evidence · 2025Pooled it
- Mindfulness enhances cognitive functioning: a meta-analysis of 111 randomized controlled trials.Health psychology review · 2024Pooled it
- Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool.BMC neurology · 2024Pooled it
- Heterogeneity of treatment response to beta-blockers in the treatment of portal hypertension: A systematic review.Hepatology communications · 2024Pooled it
- Addressing Systematic Missing Data in the Context of Causally Interpretable Meta-analysis.Prevention science : the official journal of the Society for Prevention Research · 2023Pooled it
- Cardiovascular and Renal Benefits of Novel Diabetes Drugs by Baseline Cardiovascular Risk: A Systematic Review, Meta-analysis, and Meta-regression.Diabetes care · 2023Pooled it
- Estimating Patient-Specific Relative Benefit of Adding Biologics to Conventional Rheumatoid Arthritis Treatment: An Individual Participant Data Meta-Analysis.JAMA network open · 2023Pooled it
- Treatment effect modification due to comorbidity: Individual participant data meta-analyses of 120 randomised controlled trials.PLoS medicine · 2023Pooled it
- Assessment of Adherence to Reporting Guidelines by Commonly Used Clinical Prediction Models From a Single Vendor: A Systematic Review.JAMA network open · 2022Pooled it
- Mortality Rates Among Hospitalized Patients With COVID-19 Infection Treated With Tocilizumab and Corticosteroids: A Bayesian Reanalysis of a Previous Meta-analysis.JAMA network open · 2022Pooled it
- Association of Convalescent Plasma Treatment With Clinical Status in Patients Hospitalized With COVID-19: A Meta-analysis.JAMA network open · 2022Pooled it
- Hydroxychloroquine/chloroquine for the treatment of hospitalized patients with COVID-19: An individual participant data meta-analysis.PloS one · 2022Pooled it
- Causal Forests in Practice: Lessons on Detecting Heterogeneous Treatment Effects in a Randomized Controlled Trial of a Healthy Food Subsidy Program in Canada.The Journal of nutrition · 2026Trial
- Ketamine or Etomidate for Tracheal Intubation of Critically Ill Adults.The New England journal of medicine · 2026Trial
- Secondary analysis of a combined harm-reduction treatment and extended-release naltrexone randomized clinical trial for alcohol use disorder: Differences across race, ethnicity and sex assigned at birth.Addiction (Abingdon, England) · 2026Trial
- Impact of continuing renin-angiotensin-aldosterone system inhibitors before surgery on intraoperative hypotensive events: a secondary analysis of the STOP-or-NOT Trial.British journal of anaesthesia · 2026Trial
- Individualised treatment effects of enhanced early mobilisation in mechanically ventilated patients: a secondary analysis of the TEAM trial.Intensive care medicine · 2026Trial
- EEG-Derived Pain Threshold Index-Guided Remifentanil Titration During Laparoscopic Abdominal Surgery: A Randomized Trial.Journal of pain research · 2026Trial
154 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Commented on by
- Commented on by
Authors and funding
17 authors.
Funding
Abstract
Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.
Indexed as
Identifiers
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.