• Cynthia D O'Malley, Sarah J Shema, Rosemary D Cress, Katrina Bauer, Amy R Kahn, Maria J Schymura, Jennifer M Wike, and Sherri L Stewart.
• Amgen Inc. , One Amgen Center Drive, Thousand Oaks, CA 91320, USA. comalley@amgen.com
• J Womens Health (Larchmt). 2012 Sep 1; 21 (9): 887-94.

BackgroundAdvances in treatment have improved ovarian cancer survival for most women, although less for the elderly. We report on this disparity and add further evidence about the relationship among age, comorbidity, and survival after ovarian cancer.MethodsTo examine age and comorbidity, Centers for Disease Control and Prevention (CDC)-funded cancer registries examined 2367 women residing in New York and Northern California diagnosed with epithelial ovarian cancer (1998-2000). Subjects were identified through tumor registries, treatment data were supplemented with physician survey, and comorbidity was identified through hospital discharge database linkages. Proportional hazards modeling was used to estimate the risk of death by age and comorbidity, adjusting for clinical and sociodemographic factors.ResultsCrude survival at 1 year and 3 years was 71.9% and 50.1%, respectively. Within stage, age-specific survival rates were lower in the oldest groups, particularly for those with advanced disease. For age 75+, 3-year survival was 13% vs. 50% in those <35 (stage IV). For all stages, women without comorbidity had higher survival rates than those with comorbidity. Older age and comorbidity were both associated with advanced stage and less aggressive treatment. The adjusted risk of death was 40%, and it was 80% higher for the 65-74 and 75+ groups, respectively, compared to women 35-64 (p<0.00). Comorbidity increased the risk of death by 40% (p<0.00).ConclusionsThis study confirmed the independent adverse effects of age and comorbidity on survival following ovarian cancer. As the population ages, the co-occurrence of ovarian cancer and comorbidity will increase. Further work identifying critical conditions that impact survival could potentially inform complex treatment decisions.

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