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Blas L, Shiota M, Tanegashima T, Tsukahara S, Ueda S, Mutaguchi J, Goto S, Kobayashi S, Matsumoto T, Inokuchi J, Eto M. Validation of schedules for optimal prostate-specific antigen monitoring after radical prostatectomy. Int J Urol 2024; 31:404-408. [PMID: 38154806 DOI: 10.1111/iju.15379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 12/14/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Early detection of biochemical recurrence (BCR) after radical prostatectomy (RP) is crucial for early treatment and improving survival outcomes. The optimal prostate-specific antigen (PSA) monitoring remains unclear, and several models have been proposed. We aimed to externally validate four models for optimal PSA monitoring after RP and propose modifications to improve them. METHODS We reviewed the clinicopathological data of 896 patients who underwent robot-assisted RP between 2009 and 2022. We examined all PSA values and estimated the PSA value for four monitoring schedules at each time point in the virtual follow-up. We defined the ideal PSA for BCR detection between 0.2 and 0.4 ng/mL. RESULTS During the median follow-up of 21.4 months, 128 (14.3%) patients presented BCR. The original and modified Keio models, National Cancer Center Hospital model, and American Urological Association/American Society for Radiation Oncology model detected BCR in 14 (10.9%), three (2.3%), 12 (9.4%), and 11 (8.6%) patients with PSA >0.4 ng/mL. Most patients experienced BCR detected with PSA >0.4 ng/mL during the first year postoperative. The modification of interval within 6 months postoperative avoided BCR detection with PSA >0.4 ng/mL within the first year postoperative in 8/9 (88.9%), 1/2 (50.0%), 5/6 (83.3%), and 4/4 (100%) for the original and modified Keio models, National Cancer Center Hospital model, and American Urological Association/American Society for Radiation Oncology model, respectively. CONCLUSION We validated four models for PSA monitoring after RP to detect BCR and suggested modifications to avoid detections out of the desired range of PSA. These modifications could help to establish an optimal PSA monitoring schedule after RP.
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Affiliation(s)
- Leandro Blas
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masaki Shiota
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Tokiyoshi Tanegashima
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shigehiro Tsukahara
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shohei Ueda
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Jun Mutaguchi
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shunsuke Goto
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Satoshi Kobayashi
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takashi Matsumoto
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Junichi Inokuchi
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masatoshi Eto
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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Selby PJ, Banks RE, Gregory W, Hewison J, Rosenberg W, Altman DG, Deeks JJ, McCabe C, Parkes J, Sturgeon C, Thompson D, Twiddy M, Bestall J, Bedlington J, Hale T, Dinnes J, Jones M, Lewington A, Messenger MP, Napp V, Sitch A, Tanwar S, Vasudev NS, Baxter P, Bell S, Cairns DA, Calder N, Corrigan N, Del Galdo F, Heudtlass P, Hornigold N, Hulme C, Hutchinson M, Lippiatt C, Livingstone T, Longo R, Potton M, Roberts S, Sim S, Trainor S, Welberry Smith M, Neuberger J, Thorburn D, Richardson P, Christie J, Sheerin N, McKane W, Gibbs P, Edwards A, Soomro N, Adeyoju A, Stewart GD, Hrouda D. Methods for the evaluation of biomarkers in patients with kidney and liver diseases: multicentre research programme including ELUCIDATE RCT. PROGRAMME GRANTS FOR APPLIED RESEARCH 2018. [DOI: 10.3310/pgfar06030] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BackgroundProtein biomarkers with associations with the activity and outcomes of diseases are being identified by modern proteomic technologies. They may be simple, accessible, cheap and safe tests that can inform diagnosis, prognosis, treatment selection, monitoring of disease activity and therapy and may substitute for complex, invasive and expensive tests. However, their potential is not yet being realised.Design and methodsThe study consisted of three workstreams to create a framework for research: workstream 1, methodology – to define current practice and explore methodology innovations for biomarkers for monitoring disease; workstream 2, clinical translation – to create a framework of research practice, high-quality samples and related clinical data to evaluate the validity and clinical utility of protein biomarkers; and workstream 3, the ELF to Uncover Cirrhosis as an Indication for Diagnosis and Action for Treatable Event (ELUCIDATE) randomised controlled trial (RCT) – an exemplar RCT of an established test, the ADVIA Centaur® Enhanced Liver Fibrosis (ELF) test (Siemens Healthcare Diagnostics Ltd, Camberley, UK) [consisting of a panel of three markers – (1) serum hyaluronic acid, (2) amino-terminal propeptide of type III procollagen and (3) tissue inhibitor of metalloproteinase 1], for liver cirrhosis to determine its impact on diagnostic timing and the management of cirrhosis and the process of care and improving outcomes.ResultsThe methodology workstream evaluated the quality of recommendations for using prostate-specific antigen to monitor patients, systematically reviewed RCTs of monitoring strategies and reviewed the monitoring biomarker literature and how monitoring can have an impact on outcomes. Simulation studies were conducted to evaluate monitoring and improve the merits of health care. The monitoring biomarker literature is modest and robust conclusions are infrequent. We recommend improvements in research practice. Patients strongly endorsed the need for robust and conclusive research in this area. The clinical translation workstream focused on analytical and clinical validity. Cohorts were established for renal cell carcinoma (RCC) and renal transplantation (RT), with samples and patient data from multiple centres, as a rapid-access resource to evaluate the validity of biomarkers. Candidate biomarkers for RCC and RT were identified from the literature and their quality was evaluated and selected biomarkers were prioritised. The duration of follow-up was a limitation but biomarkers were identified that may be taken forward for clinical utility. In the third workstream, the ELUCIDATE trial registered 1303 patients and randomised 878 patients out of a target of 1000. The trial started late and recruited slowly initially but ultimately recruited with good statistical power to answer the key questions. ELF monitoring altered the patient process of care and may show benefits from the early introduction of interventions with further follow-up. The ELUCIDATE trial was an ‘exemplar’ trial that has demonstrated the challenges of evaluating biomarker strategies in ‘end-to-end’ RCTs and will inform future study designs.ConclusionsThe limitations in the programme were principally that, during the collection and curation of the cohorts of patients with RCC and RT, the pace of discovery of new biomarkers in commercial and non-commercial research was slower than anticipated and so conclusive evaluations using the cohorts are few; however, access to the cohorts will be sustained for future new biomarkers. The ELUCIDATE trial was slow to start and recruit to, with a late surge of recruitment, and so final conclusions about the impact of the ELF test on long-term outcomes await further follow-up. The findings from the three workstreams were used to synthesise a strategy and framework for future biomarker evaluations incorporating innovations in study design, health economics and health informatics.Trial registrationCurrent Controlled Trials ISRCTN74815110, UKCRN ID 9954 and UKCRN ID 11930.FundingThis project was funded by the NIHR Programme Grants for Applied Research programme and will be published in full inProgramme Grants for Applied Research; Vol. 6, No. 3. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Peter J Selby
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Rosamonde E Banks
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Walter Gregory
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Jenny Hewison
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - William Rosenberg
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK
| | - Douglas G Altman
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
| | - Jonathan J Deeks
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Christopher McCabe
- Department of Emergency Medicine, University of Alberta Hospital, Edmonton, AB, Canada
| | - Julie Parkes
- Primary Care and Population Sciences Academic Unit, University of Southampton, Southampton, UK
| | | | | | - Maureen Twiddy
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Janine Bestall
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | | | - Tilly Hale
- LIVErNORTH Liver Patient Support, Newcastle upon Tyne, UK
| | - Jacqueline Dinnes
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Marc Jones
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | | | | | - Vicky Napp
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Alice Sitch
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Sudeep Tanwar
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK
| | - Naveen S Vasudev
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Paul Baxter
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Sue Bell
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - David A Cairns
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | | | - Neil Corrigan
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Francesco Del Galdo
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK
| | - Peter Heudtlass
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Nick Hornigold
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Claire Hulme
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Michelle Hutchinson
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Carys Lippiatt
- Department of Specialist Laboratory Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | | | - Roberta Longo
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Matthew Potton
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Stephanie Roberts
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Sheryl Sim
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Sebastian Trainor
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Matthew Welberry Smith
- Clinical and Biomedical Proteomics Group, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - James Neuberger
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | | | - Paul Richardson
- Royal Liverpool and Broadgreen University Hospitals NHS Trust, Liverpool, UK
| | - John Christie
- Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Neil Sheerin
- Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - William McKane
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Paul Gibbs
- Portsmouth Hospitals NHS Trust, Portsmouth, UK
| | | | - Naeem Soomro
- Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | | | - Grant D Stewart
- NHS Lothian, Edinburgh, UK
- Academic Urology Group, University of Cambridge, Cambridge, UK
| | - David Hrouda
- Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK
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Jayadevappa R, Chhatre S, Gallo JJ, Wittink M, Morales KH, Bruce Malkowicz S, Lee D, Guzzo T, Caruso A, Van Arsdalen K, Wein AJ, Sanford Schwartz J. Treatment preference and patient centered prostate cancer care: Design and rationale. Contemp Clin Trials 2015; 45:296-301. [PMID: 26435200 DOI: 10.1016/j.cct.2015.09.024] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Revised: 09/27/2015] [Accepted: 09/30/2015] [Indexed: 11/28/2022]
Abstract
Prostate cancer is a slow progressing cancer that affects millions of men in the US. Due to uncertainties in outcomes and treatment complications, it is important that patients engage in informed decision making to choose the "optimal treatment". Patient centered care that encompasses informed decision-making can improve treatment choice and quality of care. Thus, assessing patient treatment preferences is critical for developing an effective decision support system. The objective of this patient-centered randomized clinical trial was to study the comparative effectiveness of a conjoint analysis intervention compared to usual care in improving subjective and objective outcomes in prostate cancer patients. We identified preferred attributes of alternative prostate cancer treatments that will aid in evaluating attributes of treatment options. In this two-phase study, in Phase 1 we used mixed methods to develop an adaptive conjoint task instrument. The conjoint task required the patients to trade-off attributes associated with treatments by assessing their relative importance. Phase 2 consisted of a randomized controlled trial of men with localized prostate cancer. We analyzed the effect of conjoint task intervention on the association between preferences, treatment and objective and subjective outcomes. Our conjoint task instrument can lead to a values-based patient-centered decision aid tool and help tailor treatment decision making to the values of prostate cancer patients. This will ultimately improve clinical decision making, clinical policy process, enhance patient centered care and improve prostate cancer outcomes.
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Affiliation(s)
- Ravishankar Jayadevappa
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States; Division of Urology, Perelman School of Medicine, University of Pennsylvania, United States; Leonard Davis Institute of Health Economics, University of Pennsylvania, United States; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, United States.
| | - Sumedha Chhatre
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States
| | - Joseph J Gallo
- Bloomberg School of Public Health, Johns Hopkins University, United States
| | - Marsha Wittink
- Department of Psychiatry, University of Rochester Medical Center, United States
| | - Knashawn H Morales
- Department of Biostatistics and Epidemiology, University of Pennsylvania, United States
| | - S Bruce Malkowicz
- Division of Urology, Perelman School of Medicine, University of Pennsylvania, United States; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, United States
| | - David Lee
- Division of Urology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Thomas Guzzo
- Division of Urology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Adele Caruso
- Division of Urology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Keith Van Arsdalen
- Division of Urology, Perelman School of Medicine, University of Pennsylvania, United States; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, United States
| | - Alan J Wein
- Division of Urology, Perelman School of Medicine, University of Pennsylvania, United States
| | - J Sanford Schwartz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, United States; Leonard Davis Institute of Health Economics, University of Pennsylvania, United States
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