Devlin, Sean M;
O'Quigley, John;
(2023)
Deconstructing the Kaplan-Meier curve: Quantification of treatment effect using the treatment effect process.
Contemporary Clinical Trials
, 125
, Article 107043. 10.1016/j.cct.2022.107043.
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Abstract
In studies of survival and its association with treatment and other prognostic variables, elapsed time alone will often show itself to be among the strongest, if not the strongest, of the predictor variables. Kaplan-Meier curves will show the overall survival of each group and the general differences between groups due to treatment. However, the time-dependent nature of treatment effects is not always immediately transparent from these curves. More sophisticated tools are needed to spotlight the treatment effects. An important tool in this context is the treatment effect process. This tool can be potent in revealing the complex myriad of ways in which treatment can affect survival time. We look at a recently published study in which the outcome was relapse-free survival, and we illustrate how the use of the treatment effect process can provide a much deeper understanding of the relationship between time and treatment in this trial.
| Type: | Article |
|---|---|
| Title: | Deconstructing the Kaplan-Meier curve: Quantification of treatment effect using the treatment effect process |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.cct.2022.107043 |
| Publisher version: | http://dx.doi.org/10.1016/j.cct.2022.107043 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Kaplan-Meier survival curves; Clinical trials; Biostatistics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10194441 |
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