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Gynecol Oncol. 2010 Mar;116(3):399-403. doi: 10.1016/j.ygyno.2009.11.027.

A nomogram for predicting overall survival of women with endometrial cancer following primary therapy: toward improving individualized cancer care.

Author information

  • 1Department of Surgery, Gynecology Service, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. gynbreast@mskcc.org

Abstract

OBJECTIVES:

Traditionally we have relied mainly on final FIGO stage to estimate overall oncologic outcome in endometrial cancer patients. However, it is well known that other patient factors may play equally important roles in outcome. Our objective was to develop a clinically useful nomogram in the hope of providing a more individualized and accurate estimation of overall survival (OS) following primary therapy.

METHODS:

Using a prospectively maintained endometrial cancer database, 1735 patients treated between 1993 and 2008 were analyzed. Characteristics known to predict OS were collected. For each patient, points were assigned to each of these 5 variables. A total score was calculated. The association between each predictor and the outcome was assessed by multivariable modeling. The corresponding 3-year OS probabilities were then determined from the nomogram.

RESULTS:

The median age was 62 years (range, 25-96). Final grade included: G1 (471), G2 (622), G3 (634), and missing (8). Stage included: IA (501), IB (590), IC (141), IIA (36), IIB (75), IIIA (116), IIIB (6), IIIC (135), IVA (7), and IVB (128). Histology included: adenocarcinoma (1376), carcinosarcoma (100), clear cell (62), and serous (197). Median follow-up for survivors was 29.2 months (0-162.2 months). Concordance probability estimator for the nomogram is 0.746+/-0.011.

CONCLUSION:

We developed a nomogram based on 5 easily available clinical characteristics to predict OS with a high concordance probability. This nomogram incorporates other individualized patient variables beyond FIGO stage to more accurately predict outcome. This new tool may be useful to clinicians in assessing patient risk when deciding on follow-up strategies.

PMID:
20022094
[PubMed - indexed for MEDLINE]
PMCID:
PMC3870336
Free PMC Article

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