UKCTOCS update: applying insights of delayed effects in cancer screening trials to the long-term follow-up mortality analysis

This article consists of a citation of a published article describing research funded by the Health Technology Assessment programme under project number 16/46/01, and is provided as as part of the complete record of research outputs for this project. The original publication is available at: https://doi.org/10.1186/s13063-021-05125-8 Background During trials that span decades, new evidence including progress in statistical methodology, may require revision of original assumptions. An example is the continued use of a constant-effect approach to analyse the mortality reduction which is often delayed in cancer-screening trials. The latter led us to re-examine our approach for the upcoming primary mortality analysis (2020) of long-term follow-up of the United Kingdom Collaborative Trial of Ovarian Cancer Screening (LTFU UKCTOCS), having initially (2014) used the proportional hazards (PH) Cox model. Methods We wrote to 12 experts in statistics/epidemiology/screening trials, setting out current evidence, the importance of pre-specification, our previous mortality analysis (2014) and three possible choices for the follow-up analysis (2020) of the mortality outcome: (A) all data (2001–2020) using the Cox model (2014), (B) new data (2015–2020) only and (C) all data (2001–2020) using a test that allows for delayed effects. Results Of 11 respondents, eight supported changing the 2014 approach to allow for a potential delayed effect (option C), suggesting various tests while three favoured retaining the Cox model (option A). Consequently, we opted for the Versatile test introduced in 2016 which maintains good power for early, constant or delayed effects. We retained the Royston-Parmar model to estimate absolute differences in disease-specific mortality at 5, 10, 15 and 18 years. Conclusions The decision to alter the follow-up analysis for the primary outcome on the basis of new evidence and using new statistical methodology for long-term follow-up is novel and has implications beyond UKCTOCS. There is an urgent need for consensus building on how best to design, test, estimate and report mortality outcomes from long-term randomised cancer screening trials. Funding This publication was funded by the Health Technology Assessment programme as a part of award number 16/46/01. This article reports on one component of the research award Long term impact of screening on ovarian cancer mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). For more information about this research please view the award page [https://fundingawards.nihr.ac.uk/award/16/46/01] DOI https://doi.org/10.1186/s13063-021-05125-8

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Publication Details

Journal
Health Technology Assessment
Published
2025-03-01
DOI
https://doi.org/10.3310/kjha9892
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
Field-Weighted Citation Impact
0.00

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article

UKCTOCS update: applying insights of delayed effects in cancer screening trials to the long-term follow-up mortality analysis

Health Technology Assessment
Health Systems, Economic Evaluations, Quality of Life
article

UKCTOCS update: applying insights of delayed effects in cancer screening trials to the long-term follow-up mortality analysis

article en

Abstract

This article consists of a citation of a published article describing research funded by the Health Technology Assessment programme under project number 16/46/01, and is provided as as part of the complete record of research outputs for this project. The original publication is available at: https://doi.org/10.1186/s13063-021-05125-8 Background During trials that span decades, new evidence including progress in statistical methodology, may require revision of original assumptions. An example is the continued use of a constant-effect approach to analyse the mortality reduction which is often delayed in cancer-screening trials. The latter led us to re-examine our approach for the upcoming primary mortality analysis (2020) of long-term follow-up of the United Kingdom Collaborative Trial of Ovarian Cancer Screening (LTFU UKCTOCS), having initially (2014) used the proportional hazards (PH) Cox model. Methods We wrote to 12 experts in statistics/epidemiology/screening trials, setting out current evidence, the importance of pre-specification, our previous mortality analysis (2014) and three possible choices for the follow-up analysis (2020) of the mortality outcome: (A) all data (2001–2020) using the Cox model (2014), (B) new data (2015–2020) only and (C) all data (2001–2020) using a test that allows for delayed effects. Results Of 11 respondents, eight supported changing the 2014 approach to allow for a potential delayed effect (option C), suggesting various tests while three favoured retaining the Cox model (option A). Consequently, we opted for the Versatile test introduced in 2016 which maintains good power for early, constant or delayed effects. We retained the Royston-Parmar model to estimate absolute differences in disease-specific mortality at 5, 10, 15 and 18 years. Conclusions The decision to alter the follow-up analysis for the primary outcome on the basis of new evidence and using new statistical methodology for long-term follow-up is novel and has implications beyond UKCTOCS. There is an urgent need for consensus building on how best to design, test, estimate and report mortality outcomes from long-term randomised cancer screening trials. Funding This publication was funded by the Health Technology Assessment programme as a part of award number 16/46/01. This article reports on one component of the research award Long term impact of screening on ovarian cancer mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). For more information about this research please view the award page [https://fundingawards.nihr.ac.uk/award/16/46/01] DOI https://doi.org/10.1186/s13063-021-05125-8

Health Technology AssessmentVol. 29(10)
Brighton and Sussex Medical School (GB), Harvard University (US), University of Sussex (GB), Barts Health NHS Trust (GB), UNSW Sydney (AU), Massachusetts General Hospital (US), MRC Clinical Trials Unit at UCL (GB), CREATe Centre (GB), University College London (GB), London School of Economics and Political Science (GB)
Health Technology Assessment Programme
Openalex Percentile: Top 92%
Health Systems, Economic Evaluations, Quality of Life
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