Literature DB >> 30830275

External validation of a nomogram for the prediction of 10-year life expectancy in candidates for radical prostatectomy.

Sophie Knipper1,2, David Pröwrock3, Zhe Tian4, Hans Heinzer3, Derya Tilki3,5, Pierre Karakiewicz4,6, Markus Graefen3.   

Abstract

PURPOSE: Accurate life expectancy prediction is essential in decision-making concerning treatment of clinically localized prostate cancer (PCa). Nomogram predictions are more precise and reproducible than clinician's estimations. The most accurate nomogram addressing 10-year life expectancy in PCa patients has not been externally validated to date. Therefore, we aimed to evaluate the performance of this nomogram in a contemporary external cohort. PATIENTS AND METHODS: For this, we enrolled all consecutive patients, who underwent radical prostatectomy at a single institution between 2005 and 2007. Age at surgery and Charlson Comorbidity Index (CCI) were assessed. PCa-related deaths and patients under 55 years were excluded as indicated by the nomogram. The prediction of 10-year life expectancy was calculated according to the nomogram and compared to actual survival data. Calibration and discrimination were assessed using calibration plots.
RESULTS: Overall, 1597 patients were evaluated, with a median age of 64 years (range 55-78 years) at surgery and a median follow-up of 134.4 months (range 0.1-161.7 months). Median CCI was 0 (range 0-10). At 10 years, 134 patients (8.4%) had died of other causes than PCa. The nomogram showed moderate discrimination capacities on receiver-operator characteristic analysis (c-index: 0.64). On calibration curves, the nomogram underestimated the actual life expectancy.
CONCLUSION: The performance accuracy of this prediction model was moderate and underestimated 10-year life expectancy of contemporary PCa patients. In conclusion, prediction of life expectancy remains challenging with a continued need for more precise tools.

Entities:  

Keywords:  External validation; Life expectancy; Nomogram; Prediction model; Prostate cancer

Mesh:

Year:  2019        PMID: 30830275     DOI: 10.1007/s00345-019-02706-w

Source DB:  PubMed          Journal:  World J Urol        ISSN: 0724-4983            Impact factor:   4.226


  23 in total

Review 1.  Everything you always wanted to know about evaluating prediction models (but were too afraid to ask).

Authors:  Andrew J Vickers; Angel M Cronin
Journal:  Urology       Date:  2010-10-27       Impact factor: 2.649

Review 2.  Predicting life expectancy in prostate cancer patients.

Authors:  Claudio Jeldres; Jean-Baptiste Latouff; Fred Saad
Journal:  Curr Opin Support Palliat Care       Date:  2009-09       Impact factor: 2.302

Review 3.  A systematic literature review of life expectancy prediction tools for patients with localized prostate cancer.

Authors:  Matthew Kent; Andrew J Vickers
Journal:  J Urol       Date:  2014-11-15       Impact factor: 7.450

4.  Impact of comorbidity on survival among men with localized prostate cancer.

Authors:  Peter C Albertsen; Dirk F Moore; Weichung Shih; Yong Lin; Hui Li; Grace L Lu-Yao
Journal:  J Clin Oncol       Date:  2011-02-28       Impact factor: 44.544

Review 5.  Comparisons of nomograms and urologists' predictions in prostate cancer.

Authors:  Phillip L Ross; Claudia Gerigk; Mithat Gonen; Ofer Yossepowitch; Ilias Cagiannos; Pramod C Sogani; Peter T Scardino; Michael W Kattan
Journal:  Semin Urol Oncol       Date:  2002-05

Review 6.  The impact of age and comorbidity on survival outcomes and treatment patterns in prostate cancer.

Authors:  W H Hall; A B Jani; J K Ryu; S Narayan; S Vijayakumar
Journal:  Prostate Cancer Prostatic Dis       Date:  2005       Impact factor: 5.554

7.  Challenging the 10-year rule: The accuracy of patient life expectancy predictions by physicians in relation to prostate cancer management.

Authors:  Kevin M Y B Leung; Wilma M Hopman; Jun Kawakami
Journal:  Can Urol Assoc J       Date:  2012-10       Impact factor: 1.862

8.  Long-term survival probability in men with clinically localized prostate cancer: a case-control, propensity modeling study stratified by race, age, treatment and comorbidities.

Authors:  Ashutosh Tewari; Christine Cole Johnson; George Divine; E David Crawford; Eduard J Gamito; Raymond Demers; Mani Menon
Journal:  J Urol       Date:  2004-04       Impact factor: 7.450

9.  Life tables adjusted for comorbidity more accurately estimate noncancer survival for recently diagnosed cancer patients.

Authors:  Angela B Mariotto; Zhuoqiao Wang; Carrie N Klabunde; Hyunsoon Cho; Barnali Das; Eric J Feuer
Journal:  J Clin Epidemiol       Date:  2013-09-10       Impact factor: 6.437

10.  Successful external validation of a model to predict other cause mortality in localized prostate cancer.

Authors:  Matthew Kent; David F Penson; Peter C Albertsen; Michael Goodman; Ann S Hamilton; Janet L Stanford; Antoinette M Stroup; Behfar Ehdaie; Peter T Scardino; Andrew J Vickers
Journal:  BMC Med       Date:  2016-02-09       Impact factor: 8.775

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  1 in total

1.  Treatment-Emergent Co-Morbidities and Survival in Patients With Metastatic Castration-Resistant Prostate Cancer Receiving Abiraterone or Enzalutamide.

Authors:  Yi-Ting Lin; Yen-Chun Huang; Chih-Kuan Liu; Tian-Shyug Lee; Mingchih Chen; Yu-Ning Chien
Journal:  Front Pharmacol       Date:  2021-05-18       Impact factor: 5.810

  1 in total

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