Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan

Abstract

Background: Cervical cancer can be invasive and advanced at diagnosis causing devastating suffering and premature death. The cancer stage at presentation is related to survival evaluation and several factors determine stage. The aim of the study was to examine predictors covariates associated with cervical cancer stage at diagnosis and its impact on patient prognosis and survival. Methods: This retrospective cross-sectional study was carried out at Khartoum oncology hospital, Sudan. Participants were 239 cervical cancer patients diagnosed and treated between 2011-2015. Patients’ pathological and socio-demographic data were extracted from their medical files and survival times were calculated from follow-up. Chi-square, Kaplan-Meier, Log-rank test and Cox regression model were used to examine relationships between demographic and clinical variables and survival outcome. Results: The mean age of the participants was 56.91 years and the majority were ≥45 years. Cancer survival analysis showed that the stage at diagnosis had limited association with socio-demographic factors, except where patients reside. Multivariate regression using the Cox proportional hazard model confirmed strongly that stage (p=0.035), chemotherapy (p=0.000) and radiotherapy (p=0.001) were the most likely predictor covariates of patient prognosis and survival time. Conclusions: The results of this study suggest cancer stage at diagnosis and certain treatments are the most important factors impacting the prognosis and survival of patients with cervical cancer. Early detection and vaccination of women against HPV infection provide enormous opportunities for early diagnosis, more effective treatment and better chances of survival.