Nomogram Predicting Locally Advanced Prostate Cancer in Patients with Clinically Organ-Confined Disease Who Underwent Robot-Assisted Radical Prostatectomy: A Retrospective Multicenter Cohort Study in Japan (The MSUG94 Group).


Journal

Annals of surgical oncology
ISSN: 1534-4681
Titre abrégé: Ann Surg Oncol
Pays: United States
ID NLM: 9420840

Informations de publication

Date de publication:
Oct 2023
Historique:
received: 14 02 2023
accepted: 28 05 2023
medline: 20 9 2023
pubmed: 20 6 2023
entrez: 20 6 2023
Statut: ppublish

Résumé

We created a clinically applicable nomogram to predict locally advanced prostate cancer using preoperative parameters and performed external validation using an external independent validation cohort. From a retrospective multicenter cohort study of 3622 Japanese patients with prostate cancer who underwent robot-assisted radical prostatectomy at ten institutions, the patients were divided into two groups (MSUG cohort and validation cohort). Locally advanced prostate cancer was defined as pathological T stage ≥ 3a. A multivariable logistic regression model was used to identify factors strongly associated with locally advanced prostate cancer. Bootstrap area under the curve was calculated to assess the internal validity of the prediction model. A nomogram was created as a practical application of the prediction model, and a web application was released to predict the probability of locally advanced prostate cancer. A total of 2530 and 427 patients in the MSUG and validation cohorts, respectively, met the criteria for this study. On multivariable analysis, initial prostate-specific antigen, prostate volume, number of cancer-positive and cancer-negative biopsy cores, biopsy grade group, and clinical T stage were independent predictors of locally advanced prostate cancer. The nomogram predicting locally advanced prostate cancer was demonstrated (area under the curve 0.72). Using a nomogram cutoff of 0.26, 464 of 1162 patients (39.9%) could be correctly diagnosed with pT3, and 2311 of 2524 patients (91.6%) could avoid underdiagnosis. We developed a clinically applicable nomogram with external validation to predict the probability of locally advanced prostate cancer in patients undergoing robot-assisted radical prostatectomy.

Identifiants

pubmed: 37338747
doi: 10.1245/s10434-023-13747-2
pii: 10.1245/s10434-023-13747-2
doi:

Substances chimiques

Prostate-Specific Antigen EC 3.4.21.77

Types de publication

Multicenter Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

6925-6933

Informations de copyright

© 2023. Society of Surgical Oncology.

Références

Mottet N, van den Bergh RCN, Briers E, et al. EAU-EANM-ESTRO-ESUR-SIOG Guidelines on prostate cancer-2020 update. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol. 2021;79:243–62.
doi: 10.1016/j.eururo.2020.09.042 pubmed: 33172724
Prostate cancer. NCCN guidelines® 2022. July 2021. Accessed April 4, 2022.
Du Y, Long Q, Guan B, et al. Robot-assisted radical prostatectomy is more beneficial for prostate cancer patients: a system review and meta-analysis. Med Sci Monit. 2018;24:272–87.
doi: 10.12659/MSM.907092 pubmed: 29332100 pmcid: 5776881
Preston MA, Breau RH, Lantz AG, et al. The association between nerve sparing and a positive surgical margin during radical prostatectomy. Urol Oncol. 2015;33:18.e1-e6.
doi: 10.1016/j.urolonc.2014.09.006 pubmed: 25308562
Saika T, Miura N, Fukumoto T, Yanagihara Y, Miyauchi T, Kikugawa T. Role of robot-assisted radical prostatectomy in locally advanced prostate cancer. Int J Urol. 2018;25:30–5.
doi: 10.1111/iju.13441 pubmed: 28901630
Sanchez-Chapado M, Angulo JC, Ibarburen C, et al. Comparison of digital rectal examination, transrectal ultrasonography, and multicoil magnetic resonance imaging for preoperative evaluation of prostate cancer. Eur Urol. 1997;32:140–9.
doi: 10.1159/000480848 pubmed: 9286643
Ravi P, Kwak J, Xie W, et al. Neoadjuvant novel hormonal therapy followed by prostatectomy versus up-front prostatectomy for high-risk prostate cancer: a comparative analysis. J Urol. 2022;208:838–45.
doi: 10.1097/JU.0000000000002803 pubmed: 36082554
Hsu CY, Joniau S, Oyen R, Roskams T, Van Poppel H. Detection of clinical unilateral T3a prostate cancer – by digital rectal examination or transrectal ultrasonography? BJU Int. 2006;98:982–5.
doi: 10.1111/j.1464-410X.2006.06452.x pubmed: 16945120
Kato D, Ozawa K, Takeuchi S, et al. The utility of combined target and systematic prostate biopsies in the diagnosis of clinically significant prostate cancer using prostate imaging reporting and data system version 2 based on biparametric magnetic resonance imaging. Curr Oncol. 2021;28:1294–301.
doi: 10.3390/curroncol28020123 pubmed: 33809967 pmcid: 8025823
Popita C, Popita AA, Andrei A, et al. Local staging of prostate cancer with multiparametric-MRI: accuracy and inter-reader agreement. Med Pharm Rep. 2020;93:150–61.
pubmed: 32478321 pmcid: 7243891
Jansen BHE, Oudshoorn FHK, Tijans AM, et al. Local staging with multiparametric MRI in daily clinical practice: diagnostic accuracy and evaluation of a radiologic learning curve. World J Urol. 2018;36:1409–15.
doi: 10.1007/s00345-018-2295-6 pubmed: 29680949 pmcid: 6105169
de Rooij M, Hamoen EH, Witjes JA, Barentsz JO, Rovers MM. Accuracy of magnetic resonance imaging for local staging of prostate cancer: a diagnostic meta-analysis. Eur Urol. 2016;70:233–45.
doi: 10.1016/j.eururo.2015.07.029 pubmed: 26215604
Morlacco A, Modonutti D, Motterle G, Martino F, Moro FD, Novara G. Nomograms in urologic oncology: lights and shadows. J Clin Med. 2021;10:980.
doi: 10.3390/jcm10050980 pubmed: 33801184 pmcid: 7957873
Bravi CA, Mazzone E, Dell’oglio P, et al. A nomogram to predict pathologic T2 stage in candidates to robot-assisted radical prostatectomy with iT3 prostate cancer on preoperative multiparametric MRI: results from a multi-institutional collaboration. Minerva Urol Nephrol. 2023;75:231–4.
doi: 10.23736/S2724-6051.22.04992-8 pubmed: 36286397
Hashimoto T, Komori O, Nakashima J, et al. Prostate-specific antigen nomogram to predict advanced prostate cancer using area under the receiver operating characteristic curve boosting. Urol Oncol. 2022;40:162.e9-162.e16.
doi: 10.1016/j.urolonc.2021.12.017 pubmed: 35065881
Buyyounouski MK, Choyke PL, Mckenney JK, et al. Prostate cancer - major changes in the American Joint Committee on cancer staging manual. CA Cancer J Clin. 2017;67:245–53.
doi: 10.3322/caac.21391 pubmed: 28222223 pmcid: 6375094
Clark T, Parekh DJ, Cookson MS, et al. Randomized prospective evaluation of extended versus limited lymph node dissection in patients with clinically localized prostate cancer. J Urol. 2003;169:145–8.
doi: 10.1016/S0022-5347(05)64055-4 pubmed: 12478123
Epstein JI, Allsbrook WC, Amin MB, Egevad LL, ISUP Grading Committee. The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma. Am J Surg Pathol. 2005;29:1228–42.
doi: 10.1097/01.pas.0000173646.99337.b1 pubmed: 16096414
Zou KH, O’Malley J, Mauri L. Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models. Circulation. 2007;115:654–7.
doi: 10.1161/CIRCULATIONAHA.105.594929 pubmed: 17283280
Jakobsen JC, Gluud C, Wetterslev J, Winkel P. When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts. BMC Med Res Methodol. 2017;17:162.
doi: 10.1186/s12874-017-0442-1 pubmed: 29207961 pmcid: 5717805
Yan G, Li Y, Du Y, Ma X, Xie Y, Zeng X. Survival nomogram for endometrial cancer with lung metastasis: a SEER database analysis. Front Oncol. 2022;12:978140.
doi: 10.3389/fonc.2022.978140 pubmed: 36276130 pmcid: 9585205
Balachandran VP, Gonen M, Smith JJ, DeMatteo RP. Nomograms in oncology: more than meets the eye. Lancet Oncol. 2015;16:e173-180.
doi: 10.1016/S1470-2045(14)71116-7 pubmed: 25846097 pmcid: 4465353
Steyerberg EW, Vickers AJ. Decision curve analysis: a discussion. Med Decis Making. 2008;28:146–9.
doi: 10.1177/0272989X07312725 pubmed: 18263565 pmcid: 2577563
Kato D, Ebara S, Tatenuma T, et al. Short-term oncological and surgical outcomes of robot-assisted radical prostatectomy: a retrospective multicenter cohort study in Japan (the MSUG94 group). Asian J Endosc Surg. 2022;15:745–52.
doi: 10.1111/ases.13074 pubmed: 35508895
Liss MA, Lusch A, Morales B, et al. Robot-assisted radical prostatectomy: 5-year oncological and biochemical outcomes. J Urol. 2012;188:2205–10.
doi: 10.1016/j.juro.2012.08.009 pubmed: 23083657
Wang L, Wang B, Ai Q, et al. Long-term cancer control outcomes of robot-assisted radical prostatectomy for prostate cancer treatment: a meta-analysis. Int Urol Nephrol. 2017;49:995–1005.
doi: 10.1007/s11255-017-1552-8 pubmed: 28238148
Eissa A, Elsherbiny A, Zoeir A, et al. Reliability of the different versions of Partin tables in predicting extraprostatic extension of prostate cancer: a systematic review and meta-analysis. Minerva Urol Nephrol. 2019;71:457–78.
Memorial Sloan Kettering Cancer Center. Pre-radical prostatectomy tool to predict probability of lymph node involvement in prostate cancer patients. Available at: www.mskcc.org/nomograms/prostate/pre_op . Accessed June 15, 2020.
Naito S, Kuroiwa K, Kinukawa N, et al. Validation of Partin tables and development of a preoperative nomogram for Japanese patients with clinically localized prostate cancer using 2005 International Society of Urological Pathology Consensus on Gleason Grading: data from the Clinicopathological Research Group for Localized Prostate Cancer. J Urol. 2008;180:904–9.
doi: 10.1016/j.juro.2008.05.047 pubmed: 18635221
Hashimoto T, Komori O, Nakashima J, et al. Prostate-specific antigen nomogram to predict advanced prostate cancer using area under the receiver operating characteristic curve boosting. Urol Oncol. 2022;40(162):e9-16.
Nyarangi-Dix J, Wiesenfarth M, Bonekamp D, et al. Combined clinical parameters and multiparametric magnetic resonance imaging for the prediction of extraprostatic disease-a risk model for patient-tailored risk stratification when planning radical prostatectomy. Eur Urol Focus. 2020;15:1205–12.
doi: 10.1016/j.euf.2018.11.004
Soeterik TFW, van Melick HHE, Dijksman LM, et al. Development and external validation of a novel nomogram to predict side-specific extraprostatic extension in patients with prostate cancer undergoing radical prostatectomy. Eur Urol Oncol. 2022;5:328–37.
doi: 10.1016/j.euo.2020.08.008 pubmed: 32972895
Ghadjar P, Hayoz S, Genitsch V, et al. Importance and outcome relevance of central pathology review in prostatectomy specimens: data from the SAKK 09/10 randomized trial on prostate cancer. BJU Int. 2017;120:e45–51.
doi: 10.1111/bju.13742 pubmed: 27987524

Auteurs

Makoto Kawase (M)

Department of Urology, Gifu University Graduate School of Medicine, Gifu, Japan.

Takayuki Goto (T)

Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Shin Ebara (S)

Department of Urology, Hiroshima City Hiroshima Citizens Hospital, Hiroshima, Japan.

Tomoyuki Tatenuma (T)

Department of Urology, Yokohama City University, Yokohama, Japan.

Takeshi Sasaki (T)

Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu, Japan.

Takuma Ishihara (T)

Innovative and Clinical Research Promotion Center, Gifu University Hospital, Gifu, Japan.

Yoshinori Ikehata (Y)

Department of Urology, University of Toyama, Toyama, Japan.

Akinori Nakayama (A)

Department of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan.

Masahiro Toide (M)

Department of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan.

Tatsuaki Yoneda (T)

Department of Urology, Seirei Hamamatsu General Hospital, Hamamatsu, Japan.

Kazushige Sakaguchi (K)

Department of Urology, Toranomon Hospital, Tokyo, Japan.

Jun Teishima (J)

Department of Urology, Kobe City Hospital Organization Kobe City Medical Center West Hospital, Kobe, Japan.

Takashi Kobayashi (T)

Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Kazuhide Makiyama (K)

Department of Urology, Yokohama City University, Yokohama, Japan.

Takahiro Inoue (T)

Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu, Japan.

Hiroshi Kitamura (H)

Department of Urology, University of Toyama, Toyama, Japan.

Kazutaka Saito (K)

Department of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan.

Fumitaka Koga (F)

Department of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan.

Shinji Urakami (S)

Department of Urology, Toranomon Hospital, Tokyo, Japan.

Takuya Koie (T)

Department of Urology, Gifu University Graduate School of Medicine, Gifu, Japan. koie.takuya.h2@f.gifu-u.ac.jp.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH