Matthew Burnell1, Aleksandra Gentry-Maharaj1, Steven J Skates2, Andy Ryan1, Chloe Karpinskyj1, Jatinderpal Kalsi3, Sophia Apostolidou1, Naveena Singh4, Anne Dawnay5, Robert Woolas6, Lesley Fallowfield7, Stuart Campbell8, Alistair McGuire9, Ian J Jacobs3,10, Mahesh Parmar1, Usha Menon11. 1. MRC CTU at UCL, Institute of Clinical Trials and Methodology, University College London, 90 High Holborn, 2nd Floor, London, WC1V 6LJ, UK. 2. MGH Biostatistics, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA. 3. Department of Women's Cancer, Institute for Women's Health, University College London, 84-86 Chenies Mews, London, WC1E 6HU, UK. 4. Department of Pathology, Barts Health National Health Service Trust, The Royal Hospital, Whitechapel Rd, London, E1 1BB, UK. 5. Department of Clinical Biochemistry, Barts Health National Health Service Trust, Barts Health, 4th floor, Pathology and Pharmacy, 80 Newark St, London, E1 2ES, UK. 6. Department of Gynaecological Oncology, Queen Alexandra Hospital, Cosham, Portsmouth, Hampshire, PO6 3LY, UK. 7. Sussex Health Outcomes Research and Education in Cancer, Brighton and Sussex Medical School, University of Sussex, Science Park Road, Falmer, Brighton, BN1 9RX, UK. 8. Create Health, 150 Cheapside, London, EC2V 6ET, UK. 9. Department of Social Policy, London School of Economics, Houghton Street, London, WC2A 2AE, UK. 10. University of New South Wales, Sydney, NSW, 2052, Australia. 11. MRC CTU at UCL, Institute of Clinical Trials and Methodology, University College London, 90 High Holborn, 2nd Floor, London, WC1V 6LJ, UK. u.menon@ucl.ac.uk.
Abstract
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. TRIAL REGISTRATION: ISRCTN22488978 . Registered on 6 April 2000.
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. TRIAL REGISTRATION: ISRCTN22488978 . Registered on 6 April 2000.
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