Vincent J Gnanapragasam1,2,3, Tristan Barrett4, Vineetha Thankapannair2, David Thurtle1, Jose Rubio-Briones5, Jose Domínguez-Escrig5, Ola Bratt6, Par Statin7, Kenneth Muir8, Artitaya Lophatananon8. 1. Academic Urology Group, Department of Surgery, University of Cambridge, Cambridge, UK. 2. Department of Urology, Cambridge University Hospitals NHS Trust, Cambridge, UK. 3. Cambridge Urology Translational Research and Clinical Trials Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK. 4. Department of Radiology, University of Cambridge, Cambridge, UK. 5. Fundacion Insituto Valenciano de Oncologica, Valencia, Spain. 6. Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden. 7. Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. 8. Department of Public Health and Epidemiology, University of Manchester, Manchester, UK.
Abstract
OBJECTIVES: To test whether using disease prognosis can inform a rational approach to active surveillance (AS) for early prostate cancer. PATIENTS AND METHODS: We previously developed the Cambridge Prognostics Groups (CPG) classification, a five-tiered model that uses prostate-specific antigen (PSA), Grade Group and Stage to predict cancer survival outcomes. We applied the CPG model to a UK and a Swedish prostate cancer cohort to test differences in prostate cancer mortality (PCM) in men managed conservatively or by upfront treatment in CPG2 and 3 (which subdivides the intermediate-risk classification) vs CPG1 (low-risk). We then applied the CPG model to a contemporary UK AS cohort, which was optimally characterised at baseline for disease burden, to identify predictors of true prognostic progression. Results were re-tested in an external AS cohort from Spain. RESULTS: In a UK cohort (n = 3659) the 10-year PCM was 2.3% in CPG1, 1.5%/3.5% in treated/untreated CPG2, and 1.9%/8.6% in treated/untreated CPG3. In the Swedish cohort (n = 27 942) the10-year PCM was 1.0% in CPG1, 2.2%/2.7% in treated/untreated CPG2, and 6.1%/12.5% in treated/untreated CPG3. We then tested using progression to CPG3 as a hard endpoint in a modern AS cohort (n = 133). During follow-up (median 3.5 years) only 6% (eight of 133) progressed to CPG3. Predictors of progression were a PSA density ≥0.15 ng/mL/mL and CPG2 at diagnosis. Progression occurred in 1%, 8% and 21% of men with neither factor, only one, or both, respectively. In an independent Spanish AS cohort (n = 143) the corresponding rates were 3%, 10% and 14%, respectively. CONCLUSION: Using disease prognosis allows a rational approach to inclusion criteria, discontinuation triggers and risk-stratified management in AS.
OBJECTIVES: To test whether using disease prognosis can inform a rational approach to active surveillance (AS) for early prostate cancer. PATIENTS AND METHODS: We previously developed the Cambridge Prognostics Groups (CPG) classification, a five-tiered model that uses prostate-specific antigen (PSA), Grade Group and Stage to predict cancer survival outcomes. We applied the CPG model to a UK and a Swedish prostate cancer cohort to test differences in prostate cancermortality (PCM) in men managed conservatively or by upfront treatment in CPG2 and 3 (which subdivides the intermediate-risk classification) vs CPG1 (low-risk). We then applied the CPG model to a contemporary UK AS cohort, which was optimally characterised at baseline for disease burden, to identify predictors of true prognostic progression. Results were re-tested in an external AS cohort from Spain. RESULTS: In a UK cohort (n = 3659) the 10-year PCM was 2.3% in CPG1, 1.5%/3.5% in treated/untreated CPG2, and 1.9%/8.6% in treated/untreated CPG3. In the Swedish cohort (n = 27 942) the10-year PCM was 1.0% in CPG1, 2.2%/2.7% in treated/untreated CPG2, and 6.1%/12.5% in treated/untreated CPG3. We then tested using progression to CPG3 as a hard endpoint in a modern AS cohort (n = 133). During follow-up (median 3.5 years) only 6% (eight of 133) progressed to CPG3. Predictors of progression were a PSA density ≥0.15 ng/mL/mL and CPG2 at diagnosis. Progression occurred in 1%, 8% and 21% of men with neither factor, only one, or both, respectively. In an independent Spanish AS cohort (n = 143) the corresponding rates were 3%, 10% and 14%, respectively. CONCLUSION: Using disease prognosis allows a rational approach to inclusion criteria, discontinuation triggers and risk-stratified management in AS.
Authors: Tristan Barrett; Simon Pacey; Kelly Leonard; Jerome Wulff; Ionut-Gabriel Funingana; Vincent Gnanapragasam Journal: Eur Urol Open Sci Date: 2022-02-10
Authors: M G Parry; T E Cowling; A Sujenthiran; J Nossiter; B Berry; P Cathcart; A Aggarwal; H Payne; J van der Meulen; N W Clarke; V J Gnanapragasam Journal: BMC Med Date: 2020-05-28 Impact factor: 8.775