Clinical and Pathological Characteristics as Prognostic Factors in Locally Advanced Cervical Cancer

Overview

Locally advanced cervical cáncer continues to be a public health problem in emergent economies, even though treatment is very well standardized, recurrence rate is still high, making necessary to evaluate prognostic clinical and pathological factors. The aim of this study is to evaluate clinical and pathological prognostic factor in terms of treatment outcomes, disease-free survival (DFS) and overall survival (OS) in a retrospective cohort of patients with LACC treated with standard chemoradiotherapy in a reference center in México.

This is a retrospective study, the data were obtained from clinical files of cervical cancer patients with clinical stages IB2-IVA(FIGO2009) treated at the Instituto Nacional de Cancerología in Mexico City from January 2005 to December 2014. A total of 1954 patients with LACC confirmed by pathology, clinical exams and computed tomography scan (CT) were identified. Demographic, clinical, pathological and follow-up as well as survival status of all patients was recorded. Treatment outcome was classified as complete response if the patient had no signs of tumor activity after 6 months of finishing treatment, persistence of disease was defined if tumor could be identified after treatment or before six months of treatment termination, progression was defined if tumor growth occurred or metastatic disease appeared. Disease-free survival (DFS) was defined as the period between finishing treatment and the occurrence of relapse, which was confirmed by pathological study and/or CT. Overall survival (OS) was defined as the time period between diagnosis and death or date at last visit. Quantitative variables were described with central tendency and dispersion measures and analyzed with Student's t or Mann-Whitney U test. Normality was determined with Shapiro-Wilk's test, Chi-squared for categorical comparisons between groups, Kaplan-Meir with the log-rank test for survival analysis were performed. The multivariate analysis was performed using Cox proportional Hazard regression model. Statistically significant differences were defined as a p value \<0.05. Statistical analyses were performed using IBM SPSS, version 23 (IBM Corp., Armonk, N.Y., USA).

Conditions

Interventions

Eligibility

Outcomes