Predictors of Survival Outcomes After Primary Treatment of Epithelial Ovarian Cancer in Lagos, Nigeria

Abstract

PURPOSE This study was designed to investigate the clinicopathologic predictors of progression-free survival (PFS) and overall survival (OS) in patients with epithelial ovarian cancer (EOC) following primary treatment in Lagos, Nigeria. MATERIALS AND METHODS Using data from a retrospective cohort of 126 patients who received treatment for EOC between 2010 and 2018, we identified 83 patients with a complete clinical record for subsequent data analysis. Patients' demographics and updated 2-year follow-up status were abstracted from medical records. Kaplan-Meier survival curves were compared using the log-rank test, and Cox proportional hazard models were used for multivariate analysis to identify independent predictors of survivals following treatment in EOC patients. RESULTS The median PFS and OS were 12 and 24 months, respectively. After adjusting for covariates in the multivariate analysis, younger age ≤ 55 years (hazard ratio [HR] = 0.40; 95% CI, 0.22 to 0.74; P = .01) and International Federation of Gynecology and Obstetrics (FIGO) stage I/II (HR = 0.02; 95% CI, 0.01 to 0.08; P = .01) were independent predictors of improved PFS, whereas being premenopausal (HR = 2.34; 95% CI, 1.16 to 4.75; P = .02) was an independent predictor of reduced OS after 2-year follow-up. CONCLUSION PFS could be predicted by the age and FIGO stage of the disease, whereas menopausal status was predictive of OS in patients with EOC. This knowledge should form the basis for counseling patients with ovarian cancer during their primary treatment and lend support to the importance of aggressive follow-up and monitoring for the older, premenopausal patients and those with an advanced stage of epithelial ovarian cancer. However, robust longitudinal research should be carried out to provide additional reliable insight to this information.

Pretreatment Neutrophil-to-Lymphocyte Ratio: A Prognostic Biomarker of Survival in Patients With Epithelial Ovarian Cancer

“…Currently, the estimate of the survival outcomes of patients with EOC relies mainly on various clinicopathological variables, such as the extent of tumor resectability during debulking surgery, FIGO stage, presence of ascites and serum cancer antigen 125 levels [22]. While reflecting the behavior and presentation of cancer in biology, these parameters may not necessarily represent the actual burden of the disease in patients with EOC.…”

“…Two outcomes were assessed: (1) progression-free survival (PFS), determined by estimating the time interval from the completion of primary treatment to the first relapse as evidenced by clinical examination, elevated tumor marker (serum cancer antigen-25 levels) and/or radiological studies; and (2) overall survival (OS), defined by determining the time interval from the completion of primary treatment until the death of the patients from all causes or last follow-up for patients who were still alive [22]. We censored the survival data after three-year follow-up.…”

Preoperative Predictors of Optimal Tumor Resectability in Patients With Epithelial Ovarian Cancer

“…Our results showed that the presence of pleural effusions on preoperative imaging increased the risk of suboptimal debulking by up to 14 times in patients with advanced EOC. In patients with OC, moderate-to-large pleural effusions have been reported to be more likely to be malignant [ 18 ], a finding that automatically upstages the disease to at least FIGO stage IV [ 19 ], thus suggesting the increased tendency of having a residual disease after PDS [ 20 ].…”

An Assessment of Ovarian Cancer Histotypes Across the African Diaspora

“…Black women in the US have lower incidence of ovarian cancer but continue to experience worse outcomes. Smaller studies in West African countries such as Nigeria have documented similar poor survival in women diagnosed with cancer (20,21). Known factors that both modify and predict development of ovarian cancer include family history of breast and/or ovarian cancer; fertility factors such as decreased parity, earlier onset of menses, smaller family size, later age at time of first pregnancy, reproductive behavior; and environment.…”