Anna Lantz1, Ugo Giovanni Falagario2, Parita Ratnani3, Ivan Jambor4, Zach Dovey3, Alberto Martini5, Sara Lewis6, Dara Lundon3, Sujit Nair3, Deron Phillip3, Kenneth Haines7, Luigi Cormio8, Giuseppe Carrieri9, Natasha Kryprianou3, Ash Tewari3. 1. Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Urology, Karolinska University Hospital Solna, Sweden. Electronic address: anna.lantz@sll.se. 2. Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Urology and Organ Transplantation, University of Foggia, Foggia, Italy. 3. Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. 4. Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Radiology, University of Turku, Turku, Finland. 5. Department of Urology, Vita-Salute San Raffaele University, Milan, Italy. 6. Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. 7. Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. 8. Department of Urology and Organ Transplantation, University of Foggia, Foggia, Italy; Department of Urology, Bonomo Teaching Hospital, Andria (BAT), Italy. 9. Department of Urology and Organ Transplantation, University of Foggia, Foggia, Italy.
Abstract
BACKGROUND: Current European Association of Urology, American Urological Association, and National Comprehensive Cancer Network guidelines recommend active surveillance (AS) for selected intermediate-risk prostate cancer (PCa) patients. However, limited evidence exists regarding which men can be selected safely. OBJECTIVE: To externally validate the Gandaglia risk calculator (Gandaglia-RC), designed to predict adverse pathology (AP) at radical prostatectomy (RP) and thus able to improve selection of intermediate-risk PCa patients suitable for AS, and to assess whether addition of magnetic resonance imaging (MRI) findings (MAP model) improves the predictive ability of Gandaglia-RC. DESIGN, SETTING, AND PARTICIPANTS: This is a retrospective analysis of a single-center cohort of 1284 consecutive men with low- and intermediate-risk PCa treated with RP between 2013 and 2019. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: AP was defined as non-organ-confined disease and/or lymph node invasion and/or pathological grade group≥3 at RP. Logistic regression was used to calculate the predictors of AP; calculated coefficients were used to develop a risk score. Receiver operating characteristic curve analysis and decision curve analysis were performed to evaluate the net benefit within models. RESULTS AND LIMITATIONS: At multivariable analysis, age at surgery, prostate-specific antigen, systematic and targeted biopsy Gleason grade group, MRI prostate volume, Prostate Imaging Reporting and Data System score, and MRI extraprostatic extension were significantly associated with AP. The model significantly improved the ability of Gandaglia-RC to predict AP (area under the curve 0.71 vs 0.63 [p<0.0001]). Using a 30% threshold, the proportions of men eligible for AS were 45% and 77% and the risks of AP were 16% and 17%, for Gandaglia-RC and MAP model, respectively. CONCLUSIONS: Compared with Gandaglia-RC, the MAP model significantly increased the number of patients eligible for AS without significantly increasing the risk of AP at RP. PATIENT SUMMARY: In this report, we have developed a risk prediction tool to select men for conservative treatment of prostate cancer. Using the novel tool, more men could safely be allocated to conservative treatment rather than surgery or radiation.
BACKGROUND: Current European Association of Urology, American Urological Association, and National Comprehensive Cancer Network guidelines recommend active surveillance (AS) for selected intermediate-risk prostate cancer (PCa) patients. However, limited evidence exists regarding which men can be selected safely. OBJECTIVE: To externally validate the Gandaglia risk calculator (Gandaglia-RC), designed to predict adverse pathology (AP) at radical prostatectomy (RP) and thus able to improve selection of intermediate-risk PCa patients suitable for AS, and to assess whether addition of magnetic resonance imaging (MRI) findings (MAP model) improves the predictive ability of Gandaglia-RC. DESIGN, SETTING, AND PARTICIPANTS: This is a retrospective analysis of a single-center cohort of 1284 consecutive men with low- and intermediate-risk PCa treated with RP between 2013 and 2019. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: AP was defined as non-organ-confined disease and/or lymph node invasion and/or pathological grade group≥3 at RP. Logistic regression was used to calculate the predictors of AP; calculated coefficients were used to develop a risk score. Receiver operating characteristic curve analysis and decision curve analysis were performed to evaluate the net benefit within models. RESULTS AND LIMITATIONS: At multivariable analysis, age at surgery, prostate-specific antigen, systematic and targeted biopsy Gleason grade group, MRI prostate volume, Prostate Imaging Reporting and Data System score, and MRI extraprostatic extension were significantly associated with AP. The model significantly improved the ability of Gandaglia-RC to predict AP (area under the curve 0.71 vs 0.63 [p<0.0001]). Using a 30% threshold, the proportions of men eligible for AS were 45% and 77% and the risks of AP were 16% and 17%, for Gandaglia-RC and MAP model, respectively. CONCLUSIONS: Compared with Gandaglia-RC, the MAP model significantly increased the number of patients eligible for AS without significantly increasing the risk of AP at RP. PATIENT SUMMARY: In this report, we have developed a risk prediction tool to select men for conservative treatment of prostate cancer. Using the novel tool, more men could safely be allocated to conservative treatment rather than surgery or radiation.
Authors: Gabriele Sorce; Rocco Simone Flammia; Benedikt Hoeh; Francesco Chierigo; Lukas Hohenhorst; Andrea Panunzio; Armando Stabile; Giorgio Gandaglia; Zhe Tian; Derya Tilki; Carlo Terrone; Michele Gallucci; Felix K H Chun; Alessandro Antonelli; Fred Saad; Shahrokh F Shariat; Francesco Montorsi; Alberto Briganti; Pierre I Karakiewicz Journal: Prostate Date: 2022-04-01 Impact factor: 4.012
Authors: Rocco S Flammia; Benedikt Hoeh; Lukas Hohenhorst; Gabriele Sorce; Francesco Chierigo; Andrea Panunzio; Zhe Tian; Fred Saad; Costantino Leonardo; Alberto Briganti; Alessandro Antonelli; Carlo Terrone; Shahrokh F Shariat; Umberto Anceschi; Markus Graefen; Felix K H Chun; Francesco Montorsi; Michele Gallucci; Pierre I Karakiewicz Journal: Int Urol Nephrol Date: 2022-07-15 Impact factor: 2.266
Authors: Salvatore M Bruno; Ugo G Falagario; Nicola d'Altilia; Marco Recchia; Vito Mancini; Oscar Selvaggio; Francesca Sanguedolce; Francesco Del Giudice; Martina Maggi; Matteo Ferro; Angelo Porreca; Alessandro Sciarra; Ettore De Berardinis; Carlo Bettocchi; Gian Maria Busetto; Luigi Cormio; Giuseppe Carrieri Journal: Front Oncol Date: 2021-05-20 Impact factor: 6.244