ReviewPloS one2016
Review of the Reporting of Survival Analyses within Randomised Controlled Trials and the Implications for Meta-Analysis.
Review in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- A systematic review of the quality of conduct and reporting of survival analyses of tuberculosis outcomes in Africa.BMC medical research methodology · 2021Pooled it
- Subsequent Injury Risk After Return-to-Play From Lower-Extremity Muscle Injuries in Professional Male Football (Soccer).Orthopaedic journal of sports medicine · 2026Article
- NMAsurv: An R Shiny application for network meta-analysis based on survival data.Research synthesis methods · 2025Review
- Meta-Analysis Using Time-to-Event Data: A Tutorial.Cochrane evidence synthesis and methods · 2025Article
- One-step parametric network meta-analysis models using the exact likelihood that allow for time-varying treatment effects.Research synthesis methods · 2025Article
- The Time Course of Injury Risk After Return-to-Play in Professional Football (Soccer).Sports medicine (Auckland, N.Z.) · 2025Article
- Exploring the characteristics, methods and reporting of systematic reviews with meta-analyses of time-to-event outcomes: a meta-epidemiological study.BMC medical research methodology · 2024Article
- Infant Circumcision for Sexually Transmitted Infection Risk Reduction Globally.Global health, science and practice · 2022Article
- Lutetium in prostate cancer: Reconstruction of patient-level data from published trials and generation of a multi-trial Kaplan-Meier curve.World journal of methodology · 2022Article
- Article
- Mistakes to Avoid for Accurate and Transparent Reporting of Survival Analysis in Imaging Research.Korean journal of radiology · 2021Article
- Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study.BMC medical research methodology · 2021Article
- Testing the proportional hazards assumption in cox regression and dealing with possible non-proportionality in total joint arthroplasty research: methodological perspectives and review.BMC musculoskeletal disorders · 2021Article
- Value of surgical resection compared to transarterial chemoembolization in the treatment of hepatocellular carcinoma with portal vein tumor thrombus: A meta-analysis of hazard ratios from five observational studies.Annals of hepato-biliary-pancreatic surgery · 2020Article
- Are non-constant rates and non-proportional treatment effects accounted for in the design and analysis of randomised controlled trials? A review of current practice.BMC medical research methodology · 2019Review
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
backgroundMeta-analysis is a growing approach to evidence synthesis and network meta-analysis in particular represents an important and developing method within Health Technology Assessment (HTA). Meta-analysis of survival data is usually performed using the individual summary statistic-the hazard ratio (HR) from each randomised controlled trial (RCT).
objectivesThe objectives of this study are to: (i) review the methods and reporting of survival analyses in oncology RCTs; and (ii) assess the suitability and relevance of survival data reported in RCTs for inclusion into meta-analysis.
methodsFive oncology journals were searched to identify Phase III RCTs published between April and July 2015. Eligible studies included those that analysed a survival outcome.
resultsThirty-two RCTs reporting survival outcomes in cancer populations were identified. None of the publications reported details relating to a strategy for statistical model building, the goodness of fit of the final model, or final model validation for the analysis of survival outcomes. The majority of studies (88%) reported the use of Cox proportional hazards (PH) regression to analyse survival endpoints. However, most publications failed to report the validation of the statistical models in terms of the PH assumption.
conclusionsThis review highlights deficiencies in terms of reporting the methods and validity of survival analyses within oncology RCTs. We support previous recommendations to encourage authors to improve the reporting of survival analyses in journal publications. We also recommend that the final choice of a statistical model for survival should be informed by goodness of model fit to a given dataset, and that model assumptions are validated. The failure of trial investigators and statisticians to investigate the PH for RCT survival data is likely to result in clinical decisions based on inappropriate methods. The development of alternative approaches for the meta-analysis of survival outcomes when the PH assumption is implausible is required if valid clinical decisions are to be made.
Indexed as
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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.