Predicting 6- and 12-Month Risk of Mortality in Patients With Platinum-Resistant Advanced-Stage Ovarian Cancer: Prognostic Model to Guide Palliative Care Referrals.
OBJECTIVE: Predictive models are increasingly being used in clinical practice. The aim of the study was to develop a predictive model to identify patients with platinum-resistant ovarian cancer with a prognosis of less than 6 to 12 months who may benefit from immediate referral to hospice care. METHODS: A retrospective chart review identified patients with platinum-resistant epithelial ovarian cancer who were treated at our institution between 2000 and 2011. A predictive model for survival was constructed based on the time from development of platinum resistance to death. Multivariate logistic regression modeling was used to identify significant survival predictors and to develop a predictive model. The following variables were included: time from diagnosis to platinum resistance, initial stage, debulking status, number of relapses, comorbidity score, albumin, hemoglobin, CA-125 levels, liver/lung metastasis, and the presence of a significant clinical event (SCE). An SCE was defined as a malignant bowel obstruction, pleural effusion, or ascites occurring on or before the diagnosis of platinum resistance. RESULTS: One hundred sixty-four patients met inclusion criteria. In the regression analysis, only an SCE and the presence of liver or lung metastasis were associated with poorer short-term survival (P < 0.001). Nine percent of patients with an SCE or liver or lung metastasis survived 6 months or greater and 0% survived 12 months or greater, compared with 85% and 67% of patients without an SCE or liver or lung metastasis, respectively. CONCLUSIONS: Patients with platinum-resistant ovarian cancer who have experienced an SCE or liver or lung metastasis have a high risk of death within 6 months and should be considered for immediate referral to hospice care.
Foote, J; Lopez-Acevedo, M; Samsa, G; Lee, PS; Kamal, AH; Alvarez Secord, A; Havrilesky, LJ
Volume / Issue
Start / End Page
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)