Literature DB >> 22449735

External validation of a nomogram predicting overall survival of patients diagnosed with endometrial cancer.

Stephan Polterauer1, Qin Zhou, Christoph Grimm, Veronika Seebacher, Alexander Reinthaller, Gerda Hofstetter, Nicole Concin, Mario M Leitao, Richard R Barakat, Nadeem R Abu-Rustum, Alexia Iasonos.   

Abstract

OBJECTIVES: Nomograms are predictive models that provide the overall probability of a specific outcome. Nomograms have shown better individual discrimination than currently used staging systems in numerous tumor entities. Recently, a nomogram for predicting overall survival (OS) in women with endometrial cancer was introduced by Memorial Sloan-Kettering Cancer Center (MSKCC). The aim of this study was to test the validity of the MSKCC endometrial cancer nomogram using an independent, external patient cohort.
METHODS: The MSKCC nomogram is based on five readily available clinical characteristics. A multi-institutional endometrial cancer database was used to test the nomogram's validity. All consecutive patients treated for endometrial cancer between December 1995 and May 2011 and who had all nomogram variables documented were identified for analysis.
RESULTS: Seven hundred sixty-five eligible patients were identified and used for external validation analysis. In the Austrian patient cohort, median OS was 134 months, and 3-year and 5-year OS rates were 83.8% (95% CI, 80.6-86.5%) and 77.2% (95% CI, 43.5-80.5%), respectively. The nomogram concordance index was 0.71 (SE=0.017; 95% CI, 0.68-0.74). The correspondence between the actual OS and the nomogram predictions suggests a good calibration of the nomogram in the validation cohort.
CONCLUSION: The MSKCC endometrial cancer nomogram was externally validated and was shown to be generalizable to a new and independent patient population. The nomogram provides a more individualized and accurate estimation of OS for patients diagnosed with endometrial cancer following primary therapy. The nomogram can be used for counseling patients more accurately and for better stratifying patients for clinical trials.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22449735      PMCID: PMC4831718          DOI: 10.1016/j.ygyno.2012.03.030

Source DB:  PubMed          Journal:  Gynecol Oncol        ISSN: 0090-8258            Impact factor:   5.482


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