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Hamdy FC, Donovan JL, Lane JA, Mason M, Metcalfe C, Holding P, Wade J, Noble S, Garfield K, Young G, Davis M, Peters TJ, Turner EL, Martin RM, Oxley J, Robinson M, Staffurth J, Walsh E, Blazeby J, Bryant R, Bollina P, Catto J, Doble A, Doherty A, Gillatt D, Gnanapragasam V, Hughes O, Kockelbergh R, Kynaston H, Paul A, Paez E, Powell P, Prescott S, Rosario D, Rowe E, Neal D. Active monitoring, radical prostatectomy and radical radiotherapy in PSA-detected clinically localised prostate cancer: the ProtecT three-arm RCT. Health Technol Assess 2020; 24:1-176. [PMID: 32773013 PMCID: PMC7443739 DOI: 10.3310/hta24370] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Prostate cancer is the most common cancer among men in the UK. Prostate-specific antigen testing followed by biopsy leads to overdetection, overtreatment as well as undertreatment of the disease. Evidence of treatment effectiveness has lacked because of the paucity of randomised controlled trials comparing conventional treatments. OBJECTIVES To evaluate the effectiveness of conventional treatments for localised prostate cancer (active monitoring, radical prostatectomy and radical radiotherapy) in men aged 50-69 years. DESIGN A prospective, multicentre prostate-specific antigen testing programme followed by a randomised trial of treatment, with a comprehensive cohort follow-up. SETTING Prostate-specific antigen testing in primary care and treatment in nine urology departments in the UK. PARTICIPANTS Between 2001 and 2009, 228,966 men aged 50-69 years received an invitation to attend an appointment for information about the Prostate testing for cancer and Treatment (ProtecT) study and a prostate-specific antigen test; 82,429 men were tested, 2664 were diagnosed with localised prostate cancer, 1643 agreed to randomisation to active monitoring (n = 545), radical prostatectomy (n = 553) or radical radiotherapy (n = 545) and 997 chose a treatment. INTERVENTIONS The interventions were active monitoring, radical prostatectomy and radical radiotherapy. TRIAL PRIMARY OUTCOME MEASURE Definite or probable disease-specific mortality at the 10-year median follow-up in randomised participants. SECONDARY OUTCOME MEASURES Overall mortality, metastases, disease progression, treatment complications, resource utilisation and patient-reported outcomes. RESULTS There were no statistically significant differences between the groups for 17 prostate cancer-specific (p = 0.48) and 169 all-cause (p = 0.87) deaths. Eight men died of prostate cancer in the active monitoring group (1.5 per 1000 person-years, 95% confidence interval 0.7 to 3.0); five died of prostate cancer in the radical prostatectomy group (0.9 per 1000 person-years, 95% confidence interval 0.4 to 2.2 per 1000 person years) and four died of prostate cancer in the radical radiotherapy group (0.7 per 1000 person-years, 95% confidence interval 0.3 to 2.0 per 1000 person years). More men developed metastases in the active monitoring group than in the radical prostatectomy and radical radiotherapy groups: active monitoring, n = 33 (6.3 per 1000 person-years, 95% confidence interval 4.5 to 8.8); radical prostatectomy, n = 13 (2.4 per 1000 person-years, 95% confidence interval 1.4 to 4.2 per 1000 person years); and radical radiotherapy, n = 16 (3.0 per 1000 person-years, 95% confidence interval 1.9 to 4.9 per 1000 person-years; p = 0.004). There were higher rates of disease progression in the active monitoring group than in the radical prostatectomy and radical radiotherapy groups: active monitoring (n = 112; 22.9 per 1000 person-years, 95% confidence interval 19.0 to 27.5 per 1000 person years); radical prostatectomy (n = 46; 8.9 per 1000 person-years, 95% confidence interval 6.7 to 11.9 per 1000 person-years); and radical radiotherapy (n = 46; 9.0 per 1000 person-years, 95% confidence interval 6.7 to 12.0 per 1000 person years; p < 0.001). Radical prostatectomy had the greatest impact on sexual function/urinary continence and remained worse than radical radiotherapy and active monitoring. Radical radiotherapy's impact on sexual function was greatest at 6 months, but recovered somewhat in the majority of participants. Sexual and urinary function gradually declined in the active monitoring group. Bowel function was worse with radical radiotherapy at 6 months, but it recovered with the exception of bloody stools. Urinary voiding and nocturia worsened in the radical radiotherapy group at 6 months but recovered. Condition-specific quality-of-life effects mirrored functional changes. No differences in anxiety/depression or generic or cancer-related quality of life were found. At the National Institute for Health and Care Excellence threshold of £20,000 per quality-adjusted life-year, the probabilities that each arm was the most cost-effective option were 58% (radical radiotherapy), 32% (active monitoring) and 10% (radical prostatectomy). LIMITATIONS A single prostate-specific antigen test and transrectal ultrasound biopsies were used. There were very few non-white men in the trial. The majority of men had low- and intermediate-risk disease. Longer follow-up is needed. CONCLUSIONS At a median follow-up point of 10 years, prostate cancer-specific mortality was low, irrespective of the assigned treatment. Radical prostatectomy and radical radiotherapy reduced disease progression and metastases, but with side effects. Further work is needed to follow up participants at a median of 15 years. TRIAL REGISTRATION Current Controlled Trials ISRCTN20141297. FUNDING This project was funded by the National Institute for Health Research Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 37. See the National Institute for Health Research Journals Library website for further project information.
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Affiliation(s)
- Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | | | - J Athene Lane
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Malcolm Mason
- School of Medicine, University of Cardiff, Cardiff, UK
| | - Chris Metcalfe
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Peter Holding
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Julia Wade
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Sian Noble
- Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Grace Young
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Michael Davis
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Tim J Peters
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Emma L Turner
- Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Jon Oxley
- Department of Cellular Pathology, North Bristol NHS Trust, Bristol, UK
| | - Mary Robinson
- Department of Cellular Pathology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - John Staffurth
- Division of Cancer and Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - Eleanor Walsh
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Jane Blazeby
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Richard Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Prasad Bollina
- Department of Urology and Surgery, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - James Catto
- Academic Urology Unit, University of Sheffield, Sheffield, UK
| | - Andrew Doble
- Department of Urology, Addenbrooke's Hospital, Cambridge, UK
| | - Alan Doherty
- Department of Urology, Queen Elizabeth Hospital, Birmingham, UK
| | - David Gillatt
- Department of Urology, Southmead Hospital and Bristol Urological Institute, Bristol, UK
| | | | - Owen Hughes
- Department of Urology, Cardiff and Vale University Health Board, Cardiff, UK
| | - Roger Kockelbergh
- Department of Urology, University Hospitals of Leicester, Leicester, UK
| | - Howard Kynaston
- Department of Urology, Cardiff and Vale University Health Board, Cardiff, UK
| | - Alan Paul
- Department of Urology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Edgar Paez
- Department of Urology, Freeman Hospital, Newcastle upon Tyne, UK
| | - Philip Powell
- Department of Urology, Freeman Hospital, Newcastle upon Tyne, UK
| | - Stephen Prescott
- Department of Urology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Derek Rosario
- Academic Urology Unit, University of Sheffield, Sheffield, UK
| | - Edward Rowe
- Department of Urology, Southmead Hospital and Bristol Urological Institute, Bristol, UK
| | - David Neal
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
- Academic Urology Group, University of Cambridge, Cambridge, UK
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Madden JM, Browne LD, Li X, Kearney PM, Fitzgerald AP. Morning surge in blood pressure using a random-effects multiple-component cosinor model. Stat Med 2018; 37:1682-1695. [PMID: 29380409 PMCID: PMC5947147 DOI: 10.1002/sim.7607] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 10/20/2017] [Accepted: 12/13/2017] [Indexed: 12/30/2022]
Abstract
Blood pressure (BP) fluctuates throughout the day. The pattern it follows represents one of the most important circadian rhythms in the human body. For example, morning BP surge has been suggested as a potential risk factor for cardiovascular events occurring in the morning, but the accurate quantification of this phenomenon remains a challenge. Here, we outline a novel method to quantify morning surge. We demonstrate how the most commonly used method to model 24-hour BP, the single cosinor approach, can be extended to a multiple-component cosinor random-effects model. We outline how this model can be used to obtain a measure of morning BP surge by obtaining derivatives of the model fit. The model is compared with a functional principal component analysis that determines the main components of variability in the data. Data from the Mitchelstown Study, a population-based study of Irish adults (n = 2047), were used where a subsample (1207) underwent 24-hour ambulatory blood pressure monitoring. We demonstrate that our 2-component model provided a significant improvement in fit compared with a single model and a similar fit to a more complex model captured by b-splines using functional principal component analysis. The estimate of the average maximum slope was 2.857 mmHg/30 min (bootstrap estimates; 95% CI: 2.855-2.858 mmHg/30 min). Simulation results allowed us to quantify the between-individual SD in maximum slopes, which was 1.02 mmHg/30 min. By obtaining derivatives we have demonstrated a novel approach to quantify morning BP surge and its variation between individuals. This is the first demonstration of cosinor approach to obtain a measure of morning surge.
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Affiliation(s)
- J M Madden
- RCSI Population and Health Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland.,Department of Epidemiology & Public Health, University College Cork, Cork, Ireland
| | - L D Browne
- Department of Epidemiology & Public Health, University College Cork, Cork, Ireland
| | - X Li
- Department of Mathematics and Statistics, La Trobe University, Melbourne, Australia
| | - P M Kearney
- Department of Epidemiology & Public Health, University College Cork, Cork, Ireland
| | - A P Fitzgerald
- Department of Epidemiology & Public Health, University College Cork, Cork, Ireland.,Department of Statistics, University College Cork, Cork, Ireland
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Simpkin AJ, Donovan JL, Tilling K, Athene Lane J, Martin RM, Albertsen PC, Bill-Axelson A, Ballentine Carter H, Bosch JLHR, Ferrucci L, Hamdy FC, Holmberg L, Jeffrey Metter E, Neal DE, Parker CC, Metcalfe C. Prostate-specific antigen patterns in US and European populations: comparison of six diverse cohorts. BJU Int 2016; 118:911-918. [PMID: 26799945 DOI: 10.1111/bju.13422] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To determine whether there are differences in prostate-specific antigen (PSA) levels at diagnosis or changes in PSA levels between US and European populations of men with and without prostate cancer (PCa). SUBJECTS AND METHODS We analysed repeated measures of PSA from six clinically and geographically diverse cohorts of men: two cohorts with PSA-detected PCa, two cohorts with clinically detected PCa and two cohorts without PCa. Using multilevel models, average PSA at diagnosis and PSA change over time were compared among study populations. RESULTS The annual percentage PSA change of 4-5% was similar between men without cancer and men with PSA-detected cancer. PSA at diagnosis was 1.7 ng/mL lower in a US cohort of men with PSA-detected PCa (95% confidence interval 1.3-2.0 ng/mL), compared with a UK cohort of men with PSA-detected PCa, but there was no evidence of a different rate of PSA change between these populations. CONCLUSION We found that PSA changes over time are similar in UK and US men diagnosed through PSA testing and even in men without PCa. Further development of PSA models to monitor men on active surveillance should be undertaken in order to take advantage of these similarities. We found no evidence that guidelines for using PSA to monitor men cannot be passed between US and European studies.
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Affiliation(s)
- Andrew J Simpkin
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Jenny L Donovan
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Kate Tilling
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - J Athene Lane
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Richard M Martin
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- NIHR Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK
| | - Peter C Albertsen
- Division of Urology, University of Connecticut Health Center, Farmington, CT, USA
| | - Anna Bill-Axelson
- Institution of Surgical Sciences, Department of Urology, Uppsala University, Uppsala, Sweden
| | | | - J L H Ruud Bosch
- Department of Urology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Luigi Ferrucci
- National Institute on Aging, National Institutes of Health, Baltimore, MA, USA
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Lars Holmberg
- Faculty of Life Sciences and Medicine, King's College London, London, UK
- Regional Cancer Centre, Uppsala/Örebro Region, Uppsala, Sweden
| | - E Jeffrey Metter
- Department of Neurology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - David E Neal
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Christopher C Parker
- Academic Urology Unit, Royal Marsden Hospital, Institute of Cancer Research, London, UK
| | - Chris Metcalfe
- School of Social and Community Medicine, University of Bristol, Bristol, UK
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Tilling K, Macdonald-Wallis C, Lawlor DA, Hughes RA, Howe LD. Modelling childhood growth using fractional polynomials and linear splines. ANNALS OF NUTRITION AND METABOLISM 2014; 65:129-38. [PMID: 25413651 PMCID: PMC4264511 DOI: 10.1159/000362695] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
BACKGROUND There is increasing emphasis in medical research on modelling growth across the life course and identifying factors associated with growth. Here, we demonstrate multilevel models for childhood growth either as a smooth function (using fractional polynomials) or a set of connected linear phases (using linear splines). METHODS We related parental social class to height from birth to 10 years of age in 5,588 girls from the Avon Longitudinal Study of Parents and Children (ALSPAC). Multilevel fractional polynomial modelling identified the best-fitting model as being of degree 2 with powers of the square root of age, and the square root of age multiplied by the log of age. The multilevel linear spline model identified knot points at 3, 12 and 36 months of age. RESULTS Both the fractional polynomial and linear spline models show an initially fast rate of growth, which slowed over time. Both models also showed that there was a disparity in length between manual and non-manual social class infants at birth, which decreased in magnitude until approximately 1 year of age and then increased. CONCLUSIONS Multilevel fractional polynomials give a more realistic smooth function, and linear spline models are easily interpretable. Each can be used to summarise individual growth trajectories and their relationships with individual-level exposures.
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Affiliation(s)
- Kate Tilling
- School of Social and Community Medicine and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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