ArticleJournal of the American Statistical Association2025
Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects.
Article in Journal of the American Statistical Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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
25 citing papers in PubMed.
- 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
- Low-Dose Aspirin for Individualized Cancer Prevention in Older Adults: A Secondary Analysis of the ASPREE Randomized Clinical Trial.JAMA oncology · 2025Trial
- A Risk Stratification Model for Predicting Benefits of Intensive Blood Pressure Treatment: Analysis of the Systolic Blood Pressure Intervention Trial.Journal of clinical hypertension (Greenwich, Conn.) · 2025Trial
- Heterogeneity in the Effect of Early Goal-Directed Therapy for Septic Shock: A Secondary Analysis of Two Multicenter International Trials.Critical care medicine · 2025Trial
- Machine Learning-Driven Analysis of Individualized Treatment Effects Comparing Buprenorphine and Naltrexone in Opioid Use Disorder Relapse Prevention.Journal of addiction medicineTrial
- Separating Ranking Signal, Incremental Feature Value, and Evaluation-Induced Optimism in Breast MRI Treatment-Effect Analysis: Foundation Model and Radiomic Representations.Journal of imaging informatics in medicine · 2026Article
- Machine learning methods for estimating personalized treatment effects-insights on validity from two large trials.American journal of epidemiology · 2026Article
- Hemodiafiltration beyond the CONVINCE trial.Clinical kidney journal · 2026Review
- Evaluating treatment benefit predictors using observational data: contending with identification and confounding bias.American journal of epidemiology · 2026Article
- Personalized Fluid Management in Patients With Sepsis and Acute Kidney Injury: A Causal Machine Learning Approach.Critical care explorations · 2025Article
- Understanding the causal effects and heterogeneity between metabolic syndrome and lung function: a nationwide prospective cohort study in China.Diabetology & metabolic syndrome · 2025Article
- Predictive Modeling of Heterogeneous Treatment Effects in RCTs: A Scoping Review.JAMA network open · 2025Article
- Estimating Treatment Effect Heterogeneity in Psychiatry: A Review and Tutorial With Causal Forests.International journal of methods in psychiatric research · 2025Review
- Measuring the Performance of Survival Models to Personalize Treatment Choices.Statistics in medicine · 2025Article
- Application of Causal Forest Model to Examine Treatment Effect Heterogeneity in Substance Use Disorder Psychosocial Treatments.International journal of methods in psychiatric research · 2025Article
- Multidisciplinary perspectives on cumulative impact assessment for vulnerable communities: expert elicitation using a Delphi method.Integrated environmental assessment and management · 2025Article
- Potential clinical impact of predictive modeling of heterogeneous treatment effects: scoping review of the impact of the PATH Statement.medRxiv : the preprint server for health sciences · 2025Article
- Two-step pragmatic subgroup discovery for heterogeneous treatment effects analyses: perspectives toward enhanced interpretability.European journal of epidemiology · 2025Article
- A prediction model for differential resilience to the effects of combat-related stressors in US army soldiers.International journal of methods in psychiatric research · 2024Article
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
There are a number of available methods for selecting whom to prioritize for treatment, including ones based on treatment effect estimation, risk scoring, and hand-crafted rules. We propose rank-weighted average treatment effect (RATE) metrics as a simple and general family of metrics for comparing and testing the quality of treatment prioritization rules. RATE metrics are agnostic as to how the prioritization rules were derived, and only assess how well they identify individuals that benefit the most from treatment. We define a family of RATE estimators and prove a central limit theorem that enables asymptotically exact inference in a wide variety of randomized and observational study settings. RATE metrics subsume a number of existing metrics, including the Qini coefficient, and our analysis directly yields inference methods for these metrics. We showcase RATE in the context of a number of applications, including optimal targeting of aspirin to stroke patients.
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.