ArticleLifetime data analysis2015
Does Cox analysis of a randomized survival study yield a causal treatment effect?
Article in Lifetime data analysis, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
96 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Individual participant data meta-analysis of intervention studies with time-to-event outcomes: A review of the methodology and an applied example.Research synthesis methods · 2020Pooled it
- Measuring and Analyzing Length of Stay in Critical Care Trials.Medical care · 2019Pooled it
- Bias of the additive hazard model in the presence of causal effect heterogeneity.Lifetime data analysis · 2024Trial
- Radiotherapy and paclitaxel plus pazopanib or placebo in anaplastic thyroid cancer (NRG/RTOG 0912): a randomised, double-blind, placebo-controlled, multicentre, phase 2 trial.The Lancet. Oncology · 2023Trial
- Estimating clinical trial hazard functions.Clinical trials (London, England) · 2026Article
- The Effect of Covariate Adjustment for Cox Regression in Cardiovascular Outcome Trials.Therapeutic innovation & regulatory science · 2026Article
- Impact of concomitant proton pump inhibitors in patients treated for advanced or metastatic NSCLC: a target trial emulation protocol.ESMO real world data and digital oncology · 2026Article
- Modeling treatment effects on absorbing outcomes in clinical trials: Leveraging longitudinal and ordinal data for efficiency gains.Statistical methods in medical research · 2026Article
- Statistical inference after variable selection in Cox models: a neutral simulation study.BMC medical research methodology · 2026Article
- Doubly Robust Estimators of the Restricted Mean Time in Favor Estimands in Individual- and Cluster-Randomized Trials.Statistics in medicine · 2026Article
- Polygenic risk score and 20-year prostate cancer-specific mortality and survival.Communications medicine · 2026Article
- A 'Target Trial Emulation' of Prehospital Sublingual Nitroglycerin Administration for Suspected Acute Coronary Syndrome.Prehospital emergency care · 2026Article
- Neural Network Assisted Estimation for the Structural Nested Accelerated Failure Time Models.Statistics in medicine · 2026Article
- Mediation analysis in longitudinal intervention studies with an ordinal treatment-dependent confounder.Statistical methods in medical research · 2026Article
- Subgroup analysis methods for time-to-event outcomes in heterogeneous randomized controlled trials.BMC medical research methodology · 2026Article
- Revisiting Hazard Ratios: Can We Define Causal Estimands for Time-Dependent Treatment Effects?Biometrical journal. Biometrische Zeitschrift · 2025Article
- Causal Inference for First Non-Fatal Events With the Competing Risk of Death: A Principal Stratification Approach.Statistics in medicine · 2025Article
- Time-resolved Mendelian randomization detects substantial variation in the detrimental effect of obesity throughout life.Science advances · 2025Article
- Pancancer outcome prediction via a unified weakly supervised deep learning model.Signal transduction and targeted therapy · 2025Article
- Early use of albumin may increase the risk of sepsis-associated acute kidney injury in sepsis patients: a target trial emulation.Military Medical Research · 2025Article
36 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Statistical methods for survival analysis play a central role in the assessment of treatment effects in randomized clinical trials in cardiovascular disease, cancer, and many other fields. The most common approach to analysis involves fitting a Cox regression model including a treatment indicator, and basing inference on the large sample properties of the regression coefficient estimator. Despite the fact that treatment assignment is randomized, the hazard ratio is not a quantity which admits a causal interpretation in the case of unmodelled heterogeneity. This problem arises because the risk sets beyond the first event time are comprised of the subset of individuals who have not previously failed. The balance in the distribution of potential confounders between treatment arms is lost by this implicit conditioning, whether or not censoring is present. Thus while the Cox model may be used as a basis for valid tests of the null hypotheses of no treatment effect if robust variance estimates are used, modeling frameworks more compatible with causal reasoning may be preferrable in general for estimation.
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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.