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A nomogram to predict postresection 5-year overall survival for patients with uterine leiomyosarcoma
Oliver Zivanovic1, Lindsay M Jacks, Alexia Iasonos
1Gynecology Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA.
Background:
The clinical course of patients with uterine leiomyosarcoma (LMS) is difficult to predict with the currently available categorical staging systems of the American Joint Committee on Cancer (AJCC) and the International Federation of Gynecology and Obstetrics (FIGO). The objective of the current study was to develop and validate a novel, clinically relevant, individualized prognostic model for patients with uterine LMS.
Methods:
Patients with uterine LMS who presented at the authors' institution from 1982 to 2008 were analyzed. The nomogram model was chosen based on the clinical evidence and statistical significance of the predictors, including age at diagnosis, tumor size, histologic grade, uterine cervix involvement, extrauterine spread, distant metastases, and mitotic index. Five-year overall survival (OS) was the predicted endpoint. The concordance probability (CP) was used as a predictive accuracy measure and compared with the CP of current staging systems. The model was internally validated using 200 bootstrap samples to correct for over fitting.
Results:
One hundred eighty-five of 270 patients were eligible for the nomogram analysis. The median follow-up was 5.4 years, and the median OS was 3.75 years (95% confidence interval, 3-6 years). The CP of the newly developed nomogram was 0.67 (95% confidence interval, 0.63-0.72). This was superior to predictions based on AJCC and FIGO staging. The bootstrap-validated CP was 0.65 with good calibration accuracy.
Conclusions:
The authors developed and internally validated a uterine LMS-specific nomogram to predict 5-year OS. This novel, individualized prognostic model outperforms traditionally used categorical staging systems and may be useful for patient counseling and for better selection of patients for adjuvant therapy trials.
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