Clinicopathologic factors associated with short-term survival in advanced epithelial ovarian cancer.

BACKGROUND

Epithelial ovarian cancer (EOC) is the most lethal gynaecological malignancy, and there is a deficiency of information in the literature on the early recognition of short-term survivor (STS). This study aimed to identify the clinicopathological factors associated with STS in late-stage EOC and to establish a predictive model to identify STS.

METHODS

Selected patients with International Federation of Gynecology and Obstetrics (FIGO) stage III or IV EOC were included in the study, and a retrospective analysis was performed. The characteristics of the patients who survived not more than 2 years (STS) were compared to those who survived at least 2 years (defined as long-term survivors, LTS). Binary logistic regression and receiver operating characteristic curve (ROC) were used to identify the independent prognostic factors associated with EOC and assess the predictive accuracy for STS.

RESULTS

We identified 254 patients with advanced EOC including 57 STS and 197 LTS. A univariate analysis revealed that STS had a tendency to have omental metastasis and larger tumor size, to be platinum resistant, to have non-serous histology, to undergo suboptimal cytoreduction, to have comorbidity, and to undergo primary chemotherapy less than 6 courses. Binary regression analysis revealed that tumor size (P=0.033), platinum resistance (P<0.001), non-serous histology (P=0.048) and number of primary chemotherapy (P=0.028) were significant independent predictors of STS. A developed predictive model using these predictors had an AUC =0.831; platinum resistance alone had an AUC =0.732.

CONCLUSIONS

Tumor size, omental metastasis, platinum resistance, non-serous histology, and number of primary chemotherapy are predictors associated with STS when controlling other confounding factors. Tumor size and omental metastasis may be considered novel, important prognostic factors for advanced EOC patients. Platinum resistance was the most important prognosticator for STS; hence, more work is needed for the early identification and treatment of these EOC patients.