ArticleStatistics in medicine2019
Quantifying the association between progression-free survival and overall survival in oncology trials using Kendall's τ.
Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Evaluation of Progression-Free Survival as a Surrogate Endpoint for Overall Survival in Localized Pancreatic Cancer: Trans-Atlantic Pancreatic Surgery Consortium Study.Annals of surgical oncology · 2026Article
- Disease Complexity and Nodule-Specific Responses to Atezolizumab plus Bevacizumab in Advanced Hepatocellular Carcinoma.Liver cancer · 2026Article
- Methods of multi-indication meta-analysis for health technology assessment: A simulation study.Research synthesis methods · 2026Article
- Evaluation of pathological complete response as a surrogate endpoint for overall survival in resectable oesophageal cancer: integrated analysis of individual patient data from phase III trials.The British journal of surgery · 2025Article
- Article
- Recurrence-free survival as a surrogate endpoint for overall survival after neoadjuvant chemotherapy and surgery for oesophageal squamous cell carcinoma.The British journal of surgery · 2024Article
- Prediction of Rapid Early Progression and Survival Risk with Pre-Radiation MRI in WHO Grade 4 Glioma Patients.Cancers · 2023Article
- Adjuvant Therapy for Renal Cell Carcinoma: Hype or Hope?International journal of molecular sciences · 2023Review
- Review
- Counterfactual mediation analysis in the multistate model framework for surrogate and clinical time-to-event outcomes in randomized controlled trials.Pharmaceutical statistics · 2022Article
- Quantifying the association between progression-free survival and overall survival in oncology trials using Kendall's τ.Statistics in medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper considers methods for estimating the association between progression-free and overall survival in oncology trials. Copula-based, nonparametric, and illness-death model-based methods are reviewed. In addition, the approach based on an underlying illness-death model is generalized to allow general parametric models. The performance of these methods, in terms of bias and efficiency, is investigated through simulation and also illustrated using data from a clinical trial of treatments for colon cancer. The simulations suggest that the illness-death model-based method provides good estimates of Kendall's τ across several scenarios. In some situations, copula-based methods perform well but their performance is sensitive to the choice of copula. The Clayton copula is most appropriate in scenarios, which might realistically reflect an oncology trial, but the use of copula models in practice is questionable.
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.