Your browser doesn't support javascript.
loading
A Nomogram for Predicting Prostate Cancer with Lymph Node Involvement in Robot-Assisted Radical Prostatectomy Era: A Retrospective Multicenter Cohort Study in Japan (The MSUG94 Group).
Kawase, Makoto; Ebara, Shin; Tatenuma, Tomoyuki; Sasaki, Takeshi; Ikehata, Yoshinori; Nakayama, Akinori; Toide, Masahiro; Yoneda, Tatsuaki; Sakaguchi, Kazushige; Ishihara, Takuma; Teishima, Jun; Makiyama, Kazuhide; Inoue, Takahiro; Kitamura, Hiroshi; Saito, Kazutaka; Koga, Fumitaka; Urakami, Shinji; Koie, Takuya.
Afiliação
  • Kawase M; Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan.
  • Ebara S; Department of Urology, Hiroshima City Hiroshima Citizens Hospital, Hiroshima 7308518, Japan.
  • Tatenuma T; Department of Urology, Yokohama City University, Yokohama 2360004, Japan.
  • Sasaki T; Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu 5148507, Japan.
  • Ikehata Y; Department of Urology, University of Toyama, Toyama 9300194, Japan.
  • Nakayama A; Department of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya 3438555, Japan.
  • Toide M; Department of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo 1138677, Japan.
  • Yoneda T; Department of Urology, Seirei Hamamatsu General Hospital, Hamamatsu 4308558, Japan.
  • Sakaguchi K; Department of Urology, Toranomon Hospital, Tokyo 1058470, Japan.
  • Ishihara T; Innovative and Clinical Research Promotion Center, Gifu University Hospital, Gifu 5011194, Japan.
  • Teishima J; Department of Urology, Kobe City Hospital Organization Kobe City Medical Center West Hospital, Kobe 6530013, Japan.
  • Makiyama K; Department of Urology, Yokohama City University, Yokohama 2360004, Japan.
  • Inoue T; Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu 5148507, Japan.
  • Kitamura H; Department of Urology, University of Toyama, Toyama 9300194, Japan.
  • Saito K; Department of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya 3438555, Japan.
  • Koga F; Department of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo 1138677, Japan.
  • Urakami S; Department of Urology, Toranomon Hospital, Tokyo 1058470, Japan.
  • Koie T; Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan.
Diagnostics (Basel) ; 12(10)2022 Oct 20.
Article em En | MEDLINE | ID: mdl-36292234
BACKGROUND: To create a nomogram for predicting prostate cancer (PCa) with lymph node involvement (LNI) in the robot-assisted radical prostatectomy (RARP) era. METHODS: A retrospective multicenter cohort study was conducted on 3195 patients with PCa who underwent RARP at nine institutions in Japan between September 2012 and August 2021. A multivariable logistic regression model was used to identify factors strongly associated with LNI. The Bootstrap-area under the curve (AUC) was calculated to assess the internal validity of the prediction model. RESULTS: A total of 1855 patients were enrolled in this study. Overall, 93 patients (5.0%) had LNI. On multivariable analyses, initial prostate-specific antigen, number of cancer-positive and-negative biopsy cores, biopsy Gleason grade, and clinical T stage were independent predictors of PCa with LNI. The nomogram predicting PCa with LNI has been demonstrated (AUC 84%). Using a nomogram cut-off of 6%, 492 of 1855 patients (26.5%) would avoid unnecessary pelvic lymph node dissection, and PCa with LNI would be missed in two patients (0.1%). The sensitivity, specificity, and negative predictive values associated with a cutoff of 6% were 74%, 80%, and 99.6%, respectively. CONCLUSIONS: We developed a clinically applicable nomogram for predicting the probability of patients with PCa with LNI.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2022 Tipo de documento: Article