A nomogram for predicting overall survival of women with endometrial cancer following primary therapy: Toward improving individualized cancer care
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 nomogra...
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Published in | Gynecologic oncology Vol. 116; no. 3; pp. 399 - 403 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.03.2010
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0090-8258 1095-6859 |
DOI: | 10.1016/j.ygyno.2009.11.027 |