Evidence map›Paper›PMID 41085859›Full record

ArticlePharmacoEconomics2026

Cure Models: What is Meant by a Survival 'Plateau', and Do Experts Agree on What Constitutes One?

Dan Jackson, Michael Sweeting, Robert Hettle, Binbing Yu, Neil Hawkins, Keith Abrams, Rose Baker

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Article in PharmacoEconomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Dan JacksonStatistical Innovation Group, AstraZeneca, Cambridge, UK. daniel.jackson1@astrazeneca.com.ORCID http://orcid.org/0000-0002-4963-8123
Michael SweetingStatistical Innovation Group, AstraZeneca, Cambridge, UK.
Robert HettleHealth Technology Assessment and Modelling Science, AstraZeneca, Cambridge, UK.
Binbing YuStatistical Innovation Group, AstraZeneca, Cambridge, UK.
Neil HawkinsHealth Economics and Health Technology Assessment, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Keith AbramsDepartment of Statistics and Warwick Medical School, University of Warwick, Coventry, UK.
Rose BakerSalford Business School, University of Salford, Salford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCure models are becoming more popular for modelling survival data where long-term survival, or 'cure', is considered plausible. One criterion for considering fitting cure models is evidence for a plateau in the Kaplan-Meier survival curve. However, what constitutes a mathematical definition of a plateau in survival probability is unclear, and visual inspections of survival curves are subjective.

objectiveWe investigate these issues and clarify what is meant by a plateau in this context.

methodsWe begin by describing an activity where five experts were presented with 10 survival curves from oncology trials. They were asked to rank these curves in order of their potential suitability for mixture cure modelling. We explore mathematically what features of data are required to produce a positive estimated cure fraction under an exponential mixture cure model. We show how these results can be generalised to a Weibull mixture cure model. A case study was performed using one of the survival curves.

resultsWe found weak correlations between the experts' rankings. Mathematical investigations revealed the features of data required for mixture cure models to be potentially useful, such as a decreasing event rate, but this is highly model dependent. The case study illustrated similar statistical issues.

conclusionsWe conclude that a precise definition of the extent to which a Kaplan-Meier survival curve demonstrates a plateau is likely to prove elusive. External evidence or subject matter expert knowledge about the plausibility of cure must therefore play a key role.

Indexed as

Models, StatisticalModels, TheoreticalNeoplasmsHumansKaplan-Meier EstimateSurvival Analysis

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