Literature DB >> 24094576

Predicting survival of patients with node-positive prostate cancer following multimodal treatment.

Firas Abdollah1, R Jeffrey Karnes2, Nazareno Suardi1, Cesare Cozzarini3, Giorgio Gandaglia1, Nicola Fossati1, Marco Bianchi1, Stephen A Boorjian2, Maxine Sun4, Pierre I Karakiewicz4, Francesco Montorsi1, Alberto Briganti5.   

Abstract

BACKGROUND: According to the TNM staging system, patients with prostate cancer (PCa) with lymph node invasion (LNI) are considered a single-risk group. However, not all LNI patients share the same cancer control outcomes.
OBJECTIVE: To develop and internally validate novel nomograms predicting cancer-specific mortality (CSM)-free rate in pN1 patients. DESIGN, SETTING, AND PARTICIPANTS: We evaluated 1107 patients with pN1 PCa treated with radical prostatectomy, pelvic lymph node dissection, and adjuvant therapy at two tertiary care centers between 1988 and 2010. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Univariable and multivariable Cox regression models tested the relationship between CSM and patient clinical and pathologic characteristics, which consisted of prostate-specific antigen (PSA) value, pathologic Gleason score, pathologic tumor stage, status of surgical margins, number of positive lymph nodes, and status of adjuvant therapy. A Cox regression coefficient-based nomogram was developed and internally validated. RESULTS AND LIMITATIONS: All 1107 patients received adjuvant hormonal therapy (aHT). Additionally, 35% of patients received adjuvant radiotherapy (aRT). The 10-yr CSM-free rate was 84% in the entire cohort and 87% in patients treated with aRT plus aHT versus 82% in patients treated with aHT alone (p=0.08). At multivariable analyses, PSA value, pathologic Gleason score, pathologic tumor stage, surgical margin status, number of positive lymph nodes, and aRT status were statistically significant predictors of CSM (all p ≤ 0.04). Based on these predictors, nomograms were developed to predict the 10-yr CSM-free rate in the overall patient population and in men with biochemical recurrence. These models showed high discrimination accuracy (79.5-83.3%) and favorable calibration characteristics. These results are limited by their retrospective nature.
CONCLUSIONS: Some patients with pN1 PCa have favorable CSM-free rates at 10 yr. We developed and internally validated the first nomograms that allow an accurate prediction of the CSM-free rate in these patients at an individual level.
Copyright © 2013. Published by Elsevier B.V.

Entities:  

Keywords:  Adjuvant; Lymph node invasion; Neoplasm recurrence; Prostatic neoplasms/mortality; Prostatic neoplasms/pathology; Prostatic neoplasms/surgery; Radiotherapy

Mesh:

Year:  2013        PMID: 24094576     DOI: 10.1016/j.eururo.2013.09.025

Source DB:  PubMed          Journal:  Eur Urol        ISSN: 0302-2838            Impact factor:   20.096


  21 in total

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2.  Can robot-assisted laparoscopic radical prostatectomy (RALP) be performed very soon after biopsy?

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7.  Development of ProCaRS Clinical Nomograms for Biochemical Failure-free Survival Following Either Low-Dose Rate Brachytherapy or Conventionally Fractionated External Beam Radiation Therapy for Localized Prostate Cancer.

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Journal:  Cureus       Date:  2015-06-11

8.  Association of molecular biomarkers expression with biochemical recurrence in prostate cancer through tissue microarray immunostaining.

Authors:  Ding Ma; Zhe Zhou; Bing Yang; Qun He; Qian Zhang; Xiang-Hua Zhang
Journal:  Oncol Lett       Date:  2015-07-31       Impact factor: 2.967

9.  Salvage pelvic lymph node dissection in recurrent prostate cancer: surgical and early oncological outcome.

Authors:  Tom Claeys; Charles Van Praet; Nicolaas Lumen; Piet Ost; Valérie Fonteyne; Gert De Meerleer; Bieke Lambert; Louke Delrue; Pieter De Visschere; Geert Villeirs; Karel Decaestecker
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10.  A clinicogenetic model to predict lymph node invasion by use of genome-based biomarkers from exome arrays in prostate cancer patients.

Authors:  Jong Jin Oh; Seunghyun Park; Sang Eun Lee; Sung Kyu Hong; Sangchul Lee; Hak Min Lee; Jeung Keun Lee; Jin-Nyoung Ho; Sungroh Yoon; Seok-Soo Byun
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