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Devlies W, Silversmit G, Ameye F, Dekuyper P, Quackels T, Roumeguère T, Van Cleynenbreugel B, Van Damme N, Claessens F, Everaerts W, Joniau S. Functional Outcomes and Quality of Life in High-risk Prostate Cancer Patients Treated by Robot-assisted Radical Prostatectomy with or Without Adjuvant Treatments. Eur Urol Oncol 2024:S2588-9311(24)00107-X. [PMID: 38755093 DOI: 10.1016/j.euo.2024.04.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/26/2024] [Accepted: 04/23/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND Robot-assisted laparoscopic prostatectomy (RALP) is used frequently to treat prostate cancer; yet, prospective data on the quality of life and functional outcomes are lacking. OBJECTIVE To assess the quality of life and functional outcomes after radical prostatectomy in different risk groups with or without adjuvant treatments. DESIGN, SETTING, AND PARTICIPANTS The Be-RALP database is a prospective multicentre database that covers 9235 RALP cases from 2009 until 2016. Of these 9235 patients, 2336 high-risk prostate cancer patients were matched with low/intermediate-risk prostate cancer patients. INTERVENTION Patients were treated with RALP only or followed by radiotherapy and/or hormone treatment. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS We used a mixed-model analysis to longitudinally analyse quality of life, urinary function, and erectile function between risk groups with or without additional treatments. RESULTS AND LIMITATIONS Risk group was not significant in predicting quality of life, erectile function, or urinary function after RALP. Postoperative treatment (hormone and/or radiotherapy treatment) was significant in predicting International Index of Erectile Function (IIEF-5), sexual activity, and sexual functioning. CONCLUSIONS Risk group was not linked with clinically relevant declines in functional outcomes after RALP. The observed functional outcomes and quality of life are in favour of considering RALP for high-risk prostate cancer. Postoperative treatment resulted in lower erectile function measures without clinically relevant changes in quality of life and urinary functions. Hormone therapy seems to have the most prominent negative effects on these outcomes. PATIENT SUMMARY This study investigated the quality of life, and urinary and erectile function in patients with aggressive and less aggressive prostate cancer after surgery only or in combination with hormones or radiation. We found that quality of life recovers completely, while erectile and urinary function recovers only partially after surgery. Aggressiveness of the disease had a minimal effect on the outcomes; yet, postoperative treatments lowered erectile function further.
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Affiliation(s)
- Wout Devlies
- Department of Urology, KU Leuven, Leuven, Belgium; Department of Development and Regeneration, KU Leuven, Leuven, Belgium.
| | | | - Filip Ameye
- Department of Urology, Maria Middelares Hospital, Ghent, Belgium
| | - Peter Dekuyper
- Department of Urology, Maria Middelares Hospital, Ghent, Belgium
| | - Thierry Quackels
- Department of Urology, Université Libre De Bruxelles, Brussels, Belgium
| | | | | | | | - Frank Claessens
- Laboratory of Molecular Endocrinology, KU Leuven, Leuven, Belgium
| | - Wouter Everaerts
- Department of Urology, KU Leuven, Leuven, Belgium; Department of Cellular and Molecular Medicine, KU Leuven, Belgium
| | - Steven Joniau
- Department of Urology, KU Leuven, Leuven, Belgium; Department of Development and Regeneration, KU Leuven, Leuven, Belgium
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Chen X, Li W, Yang J, Huang C, Zhou C, Chen Y, Lin Y, Hou J, Huang Y, Wei X. Extracapsular extension of transitional zone prostate cancer miss-detected by multiparametric magnetic resonance imaging. J Cancer Res Clin Oncol 2023; 149:6943-6952. [PMID: 36847840 DOI: 10.1007/s00432-023-04573-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/04/2023] [Indexed: 03/01/2023]
Abstract
OBJECTIVES To demonstrate the importance of extracapsular extension (ECE) of transitional zone (TZ) prostate cancer (PCa), examine the causes of its missed detection by Mp-MRI, and develop a new predictive model by integrating multi-level clinical variables. MATERIALS AND METHODS This retrospective study included 304 patients who underwent laparoscopic radical prostatectomy after 12 + X needle transperineal transrectal ultrasound (TRUS)-MRI-guided targeted prostate biopsy from 2018 to 2021 in our center was performed. RESULTS In this study, the incidence rates of ECE were similar in patients with MRI lesions in the peripheral zone (PZ) and TZ (P = 0.66). However, the missed detection rate was higher in patients with TZ lesions than in those with PZ lesions (P < 0.05). These missed detections result in a higher positive surgical margin rate (P < 0.05). In patients with TZ lesions, detected MP-MRI ECE may have grey areas: the longest diameters of the MRI lesions were 16.5-23.5 mm; MRI lesion volumes were 0.63-2.51 ml; MRI lesion volume ratios were 2.75-8.86%; PSA were 13.85-23.05 ng/ml. LASSO regression was used to construct a clinical prediction model for predicting the risk of ECE in TZ lesions from the perspective of MRI and clinical features, including four variables: the longest diameter of MRI lesions, TZ pseudocapsule invasion, ISUP grading of biopsy pathology, and number of positive biopsy needles. CONCLUSIONS Patients with MRI lesions in the TZ have the same incidence of ECE as those with lesions in the PZ, but a higher missed detection rate.
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Affiliation(s)
- Xin Chen
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China
| | - Wei Li
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China
| | - Jiajian Yang
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China
| | - Chen Huang
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China
| | - Chenchao Zhou
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China
| | - Yongchang Chen
- Department of Urology, Changshu No. 2 People's Hospital, Suzhou, 215006, People's Republic of China
| | - Yuxin Lin
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China
| | - Jianquan Hou
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China.
- Department of Urology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, 215006, People's Republic of China.
| | - Yuhua Huang
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China.
| | - Xuedong Wei
- Department of Urology, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou, 215006, People's Republic of China.
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Meng S, Gan W, Chen L, Wang N, Liu A. Intravoxel incoherent motion predicts positive surgical margins and Gleason score upgrading after radical prostatectomy for prostate cancer. LA RADIOLOGIA MEDICA 2023:10.1007/s11547-023-01645-2. [PMID: 37277573 DOI: 10.1007/s11547-023-01645-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 05/02/2023] [Indexed: 06/07/2023]
Abstract
BACKGROUND Whether Intravoxel incoherent motion (IVIM) can be used as a predictive tool of positive surgical margins (PSMs) and Gleason score (GS) upgrading in prostate cancer (PCa) patients after radical prostatectomy (RP) still remains unclear. The aim of this study is to explore the ability of IVIM and clinical characteristics to predict PSMs and GS upgrading. METHODS A total of 106 PCa patients after RP who underwent pelvic mpMRI (multiparametric Magnetic Resonance Imaging) between January 2016 and December 2021 and met the requirements were retrospectively included in our study. IVIM parameters were obtained using GE Functool post-processing software. Logistic regression models were fitted to confirm the predictive risk factor of PSMs and GS upgrading. The area under the curve and fourfold contingency table were used to evaluate the diagnostic efficacy of IVIM and clinical parameters. RESULTS Multivariate logistic regression analyses revealed that percent of positive cores, apparent diffusion coefficient and molecular diffusion coefficient (D) were independent predictors of PSMs (Odds Ratio (OR) were 6.07, 3.62 and 3.16, respectively), Biopsy GS and pseudodiffusion coefficient (D*) were independent predictors of GS upgrading (OR were 0.563 and 7.15, respectively). The fourfold contingency table suggested that combined diagnosis increased the ability of predicting PSMs but had no advantage in predicting GS upgrading except the sensitivity from 57.14 to 91.43%. CONCLUSIONS IVIM showed good performance in predicting PSMs and GS upgrading. Combining IVIM and clinical factors enhanced the performance of predicting PSMs, which may contribute to clinical diagnosis and treatment.
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Affiliation(s)
- Shuang Meng
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Wanting Gan
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Lihua Chen
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Nan Wang
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Ailian Liu
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China.
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Wibmer AG, Kattan MW, Alessandrino F, Baur ADJ, Boesen L, Franco FB, Bonekamp D, Campa R, Cash H, Catalá V, Crouzet S, Dinnoo S, Eastham J, Fennessy FM, Ghabili K, Hohenfellner M, Levi AW, Ji X, Løgager V, Margolis DJ, Moldovan PC, Panebianco V, Penzkofer T, Puech P, Radtke JP, Rouvière O, Schlemmer HP, Sprenkle PC, Tempany CM, Vilanova JC, Weinreb J, Hricak H, Shukla-Dave A. International Multi-Site Initiative to Develop an MRI-Inclusive Nomogram for Side-Specific Prediction of Extraprostatic Extension of Prostate Cancer. Cancers (Basel) 2021; 13:cancers13112627. [PMID: 34071842 PMCID: PMC8198352 DOI: 10.3390/cancers13112627] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 04/29/2021] [Accepted: 05/21/2021] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND To develop an international, multi-site nomogram for side-specific prediction of extraprostatic extension (EPE) of prostate cancer based on clinical, biopsy, and magnetic resonance imaging- (MRI) derived data. METHODS Ten institutions from the USA and Europe contributed clinical and side-specific biopsy and MRI variables of consecutive patients who underwent prostatectomy. A logistic regression model was used to develop a nomogram for predicting side-specific EPE on prostatectomy specimens. The performance of the statistical model was evaluated by bootstrap resampling and cross validation and compared with the performance of benchmark models that do not incorporate MRI findings. RESULTS Data from 840 patients were analyzed; pathologic EPE was found in 320/840 (31.8%). The nomogram model included patient age, prostate-specific antigen density, side-specific biopsy data (i.e., Gleason grade group, percent positive cores, tumor extent), and side-specific MRI features (i.e., presence of a PI-RADSv2 4 or 5 lesion, level of suspicion for EPE, length of capsular contact). The area under the receiver operating characteristic curve of the new, MRI-inclusive model (0.828, 95% confidence limits: 0.805, 0.852) was significantly higher than that of any of the benchmark models (p < 0.001 for all). CONCLUSIONS In an international, multi-site study, we developed an MRI-inclusive nomogram for the side-specific prediction of EPE of prostate cancer that demonstrated significantly greater accuracy than clinical benchmark models.
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Affiliation(s)
- Andreas G. Wibmer
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; (H.H.); (A.S.-D.)
- Correspondence: ; Tel.: +1-646-888-5409
| | - Michael W. Kattan
- Department of Quantitative Health Sciences in the Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; (M.W.K.); (X.J.)
| | - Francesco Alessandrino
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA; (F.A.); (F.B.F.); (F.M.F.); (C.M.T.)
| | | | - Lars Boesen
- Herlev Gentofte University Hospital, 2730 Herlev, Denmark; (L.B.); (V.L.)
| | - Felipe Boschini Franco
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA; (F.A.); (F.B.F.); (F.M.F.); (C.M.T.)
| | - David Bonekamp
- DKFZ German Cancer Research Center, 69120 Heidelberg, Germany; (D.B.); (J.P.R.); (H.-P.S.)
| | - Riccardo Campa
- Department of Radiological Sciences, Oncology & Pathology, Sapienza University of Rome, 00185 Rome, Italy; (R.C.); (V.P.)
| | - Hannes Cash
- Charité University Hospital, 10117 Berlin, Germany; (A.D.J.B.); (H.C.); (T.P.)
- Department of Urology, University Magdeburg, 39120 Magdeburg, Germany
| | - Violeta Catalá
- Department of Radiology, Fundació Puigvert, 08025 Barcelona, Spain;
- Department of Uro-Radiology, Creu Blanca, 08034 Barcelona, Spain
| | - Sebastien Crouzet
- Hospices Civils de Lyon, Hôpital Edouard Herriot, 69003 Lyon, France; (S.C.); (P.C.M.); (O.R.)
| | - Sounil Dinnoo
- Genitourinary and Women’s Imaging Departments, Lille University Hospital, 59037 Lille, France; (S.D.); (P.P.)
| | - James Eastham
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - Fiona M. Fennessy
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA; (F.A.); (F.B.F.); (F.M.F.); (C.M.T.)
| | - Kamyar Ghabili
- Department of Urology, Yale School of Medicine, New Haven, CT 06510, USA; (K.G.); (P.C.S.)
| | - Markus Hohenfellner
- Department of Urology, University Hospital of Heidelberg, 69120 Heidelberg, Germany;
| | - Angelique W. Levi
- Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA;
| | - Xinge Ji
- Department of Quantitative Health Sciences in the Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; (M.W.K.); (X.J.)
| | - Vibeke Løgager
- Herlev Gentofte University Hospital, 2730 Herlev, Denmark; (L.B.); (V.L.)
| | - Daniel J. Margolis
- Weill Cornell Medicine, Weill Cornell Imaging, New York-Presbyterian Hospital, New York, NY 10021, USA;
| | - Paul C. Moldovan
- Hospices Civils de Lyon, Hôpital Edouard Herriot, 69003 Lyon, France; (S.C.); (P.C.M.); (O.R.)
| | - Valeria Panebianco
- Department of Radiological Sciences, Oncology & Pathology, Sapienza University of Rome, 00185 Rome, Italy; (R.C.); (V.P.)
| | - Tobias Penzkofer
- Charité University Hospital, 10117 Berlin, Germany; (A.D.J.B.); (H.C.); (T.P.)
- Berlin Institute of Health (BIH), 10178 Berlin, Germany
| | - Philippe Puech
- Genitourinary and Women’s Imaging Departments, Lille University Hospital, 59037 Lille, France; (S.D.); (P.P.)
| | - Jan Philipp Radtke
- DKFZ German Cancer Research Center, 69120 Heidelberg, Germany; (D.B.); (J.P.R.); (H.-P.S.)
- Department of Urology, University Hospital of Heidelberg, 69120 Heidelberg, Germany;
| | - Olivier Rouvière
- Hospices Civils de Lyon, Hôpital Edouard Herriot, 69003 Lyon, France; (S.C.); (P.C.M.); (O.R.)
- Faculté de Médecine Lyon Est, Université de Lyon, 69003 Lyon, France
| | - Heinz-Peter Schlemmer
- DKFZ German Cancer Research Center, 69120 Heidelberg, Germany; (D.B.); (J.P.R.); (H.-P.S.)
| | - Preston C. Sprenkle
- Department of Urology, Yale School of Medicine, New Haven, CT 06510, USA; (K.G.); (P.C.S.)
| | - Clare M. Tempany
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA; (F.A.); (F.B.F.); (F.M.F.); (C.M.T.)
| | - Joan C. Vilanova
- Clínica Girona, Institute Catalan of Health-IDI, University of Girona, 17004 Girona, Spain;
| | - Jeffrey Weinreb
- Department of Radiology, Yale School of Medicine, New Haven, CT 06510, USA;
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; (H.H.); (A.S.-D.)
| | - Amita Shukla-Dave
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; (H.H.); (A.S.-D.)
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Hou Y, Zhang YH, Bao J, Bao ML, Yang G, Shi HB, Song Y, Zhang YD. Artificial intelligence is a promising prospect for the detection of prostate cancer extracapsular extension with mpMRI: a two-center comparative study. Eur J Nucl Med Mol Imaging 2021; 48:3805-3816. [PMID: 34018011 DOI: 10.1007/s00259-021-05381-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 04/25/2021] [Indexed: 12/23/2022]
Abstract
PURPOSE A balance between preserving urinary continence as well as sexual potency and achieving negative surgical margins is of clinical relevance while implementary difficulty. Accurate detection of extracapsular extension (ECE) of prostate cancer (PCa) is thus crucial for determining appropriate treatment options. We aimed to develop and validate an artificial intelligence (AI)-based tool for detecting ECE of PCa using multiparametric magnetic resonance imaging (mpMRI). METHODS Eight hundred and forty nine consecutive PCa patients who underwent mpMRI and prostatectomy without previous radio- or hormonal therapy from two medical centers were retrospectively included. The AI tool was built on a ResNeXt network embedded with a spatial attention map of experts' prior knowledge (PAGNet) from 596 training patients. Model validation was performed in 150 internal and 103 external patients. Performance comparison was made between AI, two experts using a criteria-based ECE grading system, and expert-AI interaction. RESULTS An index PAGNet model using a single-slice image yielded the highest areas under the receiver operating characteristic curve (AUC) of 0.857 (95% confidence interval [CI], 0.827-0.884), 0.807 (95% CI, 0.735-0.867), and 0.728 (95% CI, 0.631-0.811) in training, internal, and external validation data, respectively. The performance of two experts (AUC, 0.632 to 0.741 vs 0.715 to 0.857) was lower (paired comparison, all p values < 0.05) than that of AI assessment. When experts' interpretations were adjusted by AI assessments, the performance of two experts was improved. CONCLUSION Our AI tool, showing improved accuracy, offers a promising alternative to human experts for ECE staging using mpMRI.
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Affiliation(s)
- Ying Hou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210029, Jiangsu Province, China
| | - Yi-Hong Zhang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, 3663 N. Zhongshan Rd., Shanghai, 200062, China
| | - Jie Bao
- Department of Radiology, The First Affiliated Hospital of Soochow University, 188#, Shizi Road, Jiangsu Province, 215006, Suzhou, China
| | - Mei-Ling Bao
- Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Jiangsu Province, 210029, Nanjing, China
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, 3663 N. Zhongshan Rd., Shanghai, 200062, China
| | - Hai-Bin Shi
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210029, Jiangsu Province, China
| | - Yang Song
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, 3663 N. Zhongshan Rd., Shanghai, 200062, China.
| | - Yu-Dong Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210029, Jiangsu Province, China.
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Stolzenbach LF, Nocera L, Collà-Ruvolo C, Tian Z, Knipper S, Maurer T, Tilki D, Graefen M, Karakiewicz PI. Improving the Stratification of Patients With Intermediate-risk Prostate Cancer. Clin Genitourin Cancer 2020; 19:e120-e128. [PMID: 33358891 DOI: 10.1016/j.clgc.2020.11.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 11/06/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND Intermediate-risk prostate cancer (IR PCa) phenotypes may vary from favorable to unfavorable. National Comprehensive Cancer Network (NCCN) criteria help distinguish between those groups. We studied and attempted to improve this stratification. PATIENTS AND METHODS A total of 4048 (NCCN favorable: 2015 [49.8%] vs. unfavorable 2033 [50.2%]) patients with IR PCa treated with radical prostatectomy were abstracted from an institutional database (2000-2018). Multivariable logistic regression models predicting upstaging and/or upgrading (Gleason Grade Group [GGG] IV-V and/or ≥ pT3 or pN1) in IR PCa were developed, validated, and directly compared with the NCCN IR PCa stratification. RESULTS All 4048 patients were randomly divided between development (n = 2024; 50.0%) and validation cohorts (n = 2024; 50.0%). The development cohort was used to fit basic (age, prostate-specific antigen, clinical T stage, biopsy GGG, and percentage of positive cores [all P < .001]) and extended models (age, prostate-specific antigen, clinical T stage, biopsy GGG, prostate volume, and percentage of tumor within all biopsy cores [all P < .001]). In the validation cohort, the basic and the extended models were, respectively, 71.4% and 74.7% accurate in predicting upstaging and/or upgrading versus 66.8% for the NCCN IR PCa stratification. Both models outperformed NCCN IR PCa stratification in calibration and decision curve analyses (DCA). Use of NCCN IR PCa stratification would have misclassified 20.1% of patients with ≥ pT3 or pN1 and/or GGG IV to V versus 18.3% and 16.4% who were misclassified using the basic or the extended model, respectively. CONCLUSION Both newly developed and validated models better discriminate upstaging and/or upgrading risk than the NCCN IR PCa stratification.
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Affiliation(s)
- Lara Franziska Stolzenbach
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada.
| | - Luigi Nocera
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada; Department of Urology and Division of Experimental Oncology, URI, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Claudia Collà-Ruvolo
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada; Department of Urology, Federico II University of Naples, Naples, Italy
| | - Zhe Tian
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada
| | - Sophie Knipper
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias Maurer
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Department of Urology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Derya Tilki
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Department of Urology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Markus Graefen
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Pierre I Karakiewicz
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada
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How Does the Skeletal Oncology Research Group Algorithm's Prediction of 5-year Survival in Patients with Chondrosarcoma Perform on International Validation? Clin Orthop Relat Res 2020; 478:2300-2308. [PMID: 32433107 PMCID: PMC7491905 DOI: 10.1097/corr.0000000000001305] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
BACKGROUND The Skeletal Oncology Research Group (SORG) machine learning algorithm for predicting survival in patients with chondrosarcoma was developed using data from the Surveillance, Epidemiology, and End Results (SEER) registry. This algorithm was externally validated on a dataset of patients from the United States in an earlier study, where it demonstrated generally good performance but overestimated 5-year survival. In addition, this algorithm has not yet been validated in patients outside the United States; doing so would be important because external validation is necessary as algorithm performance may be misleading when applied in different populations. QUESTIONS/PURPOSES Does the SORG algorithm retain validity in patients who underwent surgery for primary chondrosarcoma outside the United States, specifically in Italy? METHODS A total of 737 patients were treated for chondrosarcoma between January 2000 and October 2014 at the Italian tertiary care center which was used for international validation. We excluded patients whose first surgical procedure was performed elsewhere (n = 25), patients who underwent nonsurgical treatment (n = 27), patients with a chondrosarcoma of the soft tissue or skull (n = 60), and patients with peripheral, periosteal, or mesenchymal chondrosarcoma (n = 161). Thus, 464 patients were ultimately included in this external validation study, as the earlier performed SEER study was used as the training set. Therefore, this study-unlike most of this type-does not have a training and validation set. Although the earlier study overestimated 5-year survival, we did not modify the algorithm in this report, as this is the first international validation and the prior performance in the single-institution validation study from the United States may have been driven by a small sample or non-generalizable patterns related to its single-center setting. Variables needed for the SORG algorithm were manually collected from electronic medical records. These included sex, age, histologic subtype, tumor grade, tumor size, tumor extension, and tumor location. By inputting these variables into the algorithm, we calculated the predicted probabilities of survival for each patient. The performance of the SORG algorithm was assessed in this study through discrimination (the ability of a model to distinguish between a binary outcome), calibration (the agreement of observed and predicted outcomes), overall performance (the accuracy of predictions), and decision curve analysis (establishment on the ability of a model to make a decision better than without using the model). For discrimination, the c-statistic (commonly known as the area under the receiver operating characteristic curve for binary classification) was calculated; this ranged from 0.5 (no better than chance) to 1.0 (excellent discrimination). The agreement between predicted and observed outcomes was visualized with a calibration plot, and the calibration slope and intercept were calculated. Perfect calibration results in a slope of 1 and an intercept of 0. For overall performance, the Brier score and the null-model Brier score were calculated. The Brier score ranges from 0 (perfect prediction) to 1 (poorest prediction). Appropriate interpretation of the Brier score requires comparison with the null-model Brier score. The null-model Brier score is the score for an algorithm that predicts a probability equal to the population prevalence of the outcome for every patient. A decision curve analysis was performed to compare the potential net benefit of the algorithm versus other means of decision support, such as treating all or none of the patients. There were several differences between this study and the earlier SEER study, and such differences are important because they help us to determine the performance of the algorithm in a group different from the initial study population. In this study from Italy, 5-year survival was different from the earlier SEER study (71% [319 of 450 patients] versus 76% [1131 of 1487 patients]; p = 0.03). There were more patients with dedifferentiated chondrosarcoma than in the earlier SEER study (25% [118 of 464 patients] versus 8.5% [131 of 1544 patients]; p < 0.001). In addition, in this study patients were older, tumor size was larger, and there were higher proportions of high-grade tumors than the earlier SEER study (age: 56 years [interquartile range {IQR} 42 to 67] versus 52 years [IQR 40 to 64]; p = 0.007; tumor size: 80 mm [IQR 50 to 120] versus 70 mm [IQR 42 to 105]; p < 0.001; tumor grade: 22% [104 of 464 had Grade 1], 42% [196 of 464 had Grade 2], and 35% [164 of 464 had Grade 3] versus 41% [592 of 1456 had Grade 1], 40% [588 of 1456 had Grade 2], and 19% [276 of 1456 had Grade 3]; p ≤ 0.001). RESULTS Validation of the SORG algorithm in a primarily Italian population achieved a c-statistic of 0.86 (95% confidence interval 0.82 to 0.89), suggesting good-to-excellent discrimination. The calibration plot showed good agreement between the predicted probability and observed survival in the probability thresholds of 0.8 to 1.0. With predicted survival probabilities lower than 0.8, however, the SORG algorithm underestimated the observed proportion of patients with 5-year survival, reflected in the overall calibration intercept of 0.82 (95% CI 0.67 to 0.98) and calibration slope of 0.68 (95% CI 0.42 to 0.95). The Brier score for 5-year survival was 0.15, compared with a null-model Brier of 0.21. The algorithm showed a favorable decision curve analysis in the validation cohort. CONCLUSIONS The SORG algorithm to predict 5-year survival for patients with chondrosarcoma held good discriminative ability and overall performance on international external validation; however, it underestimated 5-year survival for patients with predicted probabilities from 0 to 0.8 because the calibration plot was not perfectly aligned for the observed outcomes, which resulted in a maximum underestimation of 20%. The differences may reflect the baseline differences noted between the two study populations. The overall performance of the algorithm supports the utility of the algorithm and validation presented here. The freely available digital application for the algorithm is available here: https://sorg-apps.shinyapps.io/extremitymetssurvival/. LEVEL OF EVIDENCE Level III, prognostic study.
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Liu H, Tang K, Xia D, Wang X, Zhu W, Wang L, Yang W, Peng E, Chen Z. Added Value of Biparametric MRI and TRUS-Guided Systematic Biopsies to Clinical Parameters in Predicting Adverse Pathology in Prostate Cancer. Cancer Manag Res 2020; 12:7761-7770. [PMID: 32922077 PMCID: PMC7457849 DOI: 10.2147/cmar.s260986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 08/06/2020] [Indexed: 01/22/2023] Open
Abstract
Objective To develop novel models for predicting extracapsular extension (EPE), seminal vesicle invasion (SVI), or upgrading in prostate cancer (PCa) patients using clinical parameters, biparametric magnetic resonance imaging (bp-MRI), and transrectal ultrasonography (TRUS)-guided systematic biopsies. Patients and Methods We retrospectively collected data from PCa patients who underwent standard (12-core) systematic biopsy and radical prostatectomy. To develop predictive models, the following variables were included in multivariable logistic regression analyses: total prostate-specific antigen (TPSA), central transition zone volume (CTZV), prostate-specific antigen (PSAD), maximum diameter of the index lesion at bp-MRI, EPE at bp-MRI, SVI at bp-MRI, biopsy Gleason grade group, and number of positive biopsy cores. Three risk calculators were built based on the coefficients of the logit function. The area under the curve (AUC) was applied to determine the models with the highest discrimination. Decision curve analyses (DCAs) were performed to evaluate the net benefit of each risk calculator. Results A total of 222 patients were included in this study. Overall, 83 (37.4%), 75 (33.8%), and 107 (48.2%) patients had EPE, SVI, and upgrading at final pathology, respectively. The addition of bp-MRI data improved the discrimination of models for predicting SVI (0.807 vs 0.816) and upgrading (0.548 vs 0.625) but not EPE (0.766 vs 0.763). Similarly, models including clinical parameters, bp-MRI data, and information on systematic biopsies achieved the highest AUC in the prediction of EPE (0.842), SVI (0.913), and upgrading (0.794), and the three corresponding risk calculators yielded the highest net benefit. Conclusion We developed three easy-to-use risk calculators for the prediction of adverse pathological features based on patient clinical parameters, bp-MRI data, and information on systematic biopsies. This may be greatly beneficial to urologists in the decision-making process for PCa patients.
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Affiliation(s)
- Hailang Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Kun Tang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Ding Xia
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Xinguang Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Wei Zhu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Liang Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Weimin Yang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Ejun Peng
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
| | - Zhiqiang Chen
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People's Republic of China
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