Literature DB >> 23561706

Comparative validation of nomograms predicting clinically insignificant prostate cancer.

Viacheslav Iremashvili1, Mark S Soloway, Lisét Pelaez, Daniel L Rosenberg, Murugesan Manoharan.   

Abstract

OBJECTIVE: To validate and compare the accuracy and performance of nomograms predicting insignificant prostate cancer and to analyze their performance in patients with different cancer locations.
METHODS: Our cohort consisted of 370 radical prostatectomy patients with Gleason ≤6 prostate cancer diagnosed on transrectal biopsy with at least 10 cores. We quantified the performance of each nomogram with respect to discrimination, calibration, predictive accuracy at different cut points, and the clinical net benefit. We also evaluated these parameters in subgroups of patients with predominantly anterior-apical (AA) and posterior-basal (PB) tumor location.
RESULTS: Insignificant prostate cancer was present in 141 patients (38%). The Kattan and Steyerberg nomograms outperformed other studied models and demonstrated fair discrimination (areas under the receiver operating characteristics curve 0.768 and 0.770, respectively), good calibration, balanced predictive accuracy, and the highest net benefit. All nomograms were less accurate at higher levels of predicted probability. The performance of the nomograms was better in patients with PB tumors than in those with AA tumors. The loss of correlation with the actual prevalence of insignificant prostate cancer at higher levels of predicted probability was not seen in the PB subgroup but was particularly noticeable in the AA subgroup.
CONCLUSION: The Kattan and Steyerberg nomograms demonstrated the best performance in predicting the probability of insignificant prostate cancer in a contemporary cohort of patients with Gleason ≤6 cancer diagnosed on specimens from an extended transrectal biopsy. However, all studied nomograms were more accurate in identifying significant rather than insignificant disease, particularly for tumors located in the apical and anterior prostate.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23561706     DOI: 10.1016/j.urology.2013.01.062

Source DB:  PubMed          Journal:  Urology        ISSN: 0090-4295            Impact factor:   2.649


  8 in total

1.  Can nomograms improve our ability to select candidates for active surveillance for prostate cancer?

Authors:  V Iremashvili; M Manoharan; D J Parekh; S Punnen
Journal:  Prostate Cancer Prostatic Dis       Date:  2016-07-19       Impact factor: 5.554

Review 2.  Prostate cancer nomograms: a review of their use in cancer detection and treatment.

Authors:  R J Caras; Joseph R Sterbis
Journal:  Curr Urol Rep       Date:  2014-03       Impact factor: 3.092

3.  Evaluation of models predicting insignificant prostate cancer to select men for active surveillance of prostate cancer.

Authors:  L M Wong; D E Neal; A Finelli; S Davis; C Bonner; J Kapoor; J Trachtenberg; B Thomas; C M Hovens; A J Costello; N M Corcoran
Journal:  Prostate Cancer Prostatic Dis       Date:  2015-02-10       Impact factor: 5.554

4.  Validation of a 10-gene molecular signature for predicting biochemical recurrence and clinical metastasis in localized prostate cancer.

Authors:  Hatem Abou-Ouf; Mohammed Alshalalfa; Mandeep Takhar; Nicholas Erho; Bryan Donnelly; Elai Davicioni; R Jeffrey Karnes; Tarek A Bismar
Journal:  J Cancer Res Clin Oncol       Date:  2018-03-06       Impact factor: 4.553

5.  Long-term outcomes of nonpalpable prostate cancer (T1c) patients treated with radical prostatectomy.

Authors:  Yoshiyasu Amiya; Makoto Sasaki; Takayuki Shima; Yuusuke Tomiyama; Noriyuki Suzuki; Shino Murakami; Hiroomi Nakatsu; Jun Shimazaki
Journal:  Prostate Int       Date:  2015-02-10

6.  Rule-based versus probabilistic selection for active surveillance using three definitions of insignificant prostate cancer.

Authors:  Lionne D F Venderbos; Monique J Roobol; Chris H Bangma; Roderick C N van den Bergh; Leonard P Bokhorst; Daan Nieboer; Rebecka Godtman; Jonas Hugosson; Theodorus van der Kwast; Ewout W Steyerberg
Journal:  World J Urol       Date:  2015-07-10       Impact factor: 4.226

7.  Role of p73 Dinucleotide Polymorphism in Prostate Cancer and p73 Protein Isoform Balance.

Authors:  L Michael Carastro; Hui-Yi Lin; Hyun Y Park; Donghwa Kim; Selina Radlein; Kaia K Hampton; Ardeshir Hakam; Babu Zachariah; Julio Pow-Sang; Jong Y Park
Journal:  Prostate Cancer       Date:  2014-07-06

8.  Prediction models for prostate cancer to be used in the primary care setting: a systematic review.

Authors:  Mohammad Aladwani; Artitaya Lophatananon; William Ollier; Kenneth Muir
Journal:  BMJ Open       Date:  2020-07-19       Impact factor: 2.692

  8 in total

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