Affiliation:
1. Nara Medical University
Abstract
Abstract
Background: In recent years the pretreatment inflammatory responses have proven to predict the prognosis, but no report exists analyzing the combined inflammatory response both of the pre- and post-surgical treatment. The current study aims to extract the factors predicting the prognosis and create novel predictive scoring.
Methods: This retrospective study was conducted at our institution between November 2006 and December 2020. Demographic and clinicopathological data were collected from women who underwent primary surgical staging. We created the scoring system named the predictive prognosis score around primary debulking surgery(PPSP). Univariate and multivariate analyses were performed to assess its efficacy in predicting progression-free survival(PFS) and overall survival(OS). Cox regression analyses were used to assess its time dependent efficacy. Kaplan-Meier and the log-rank test were used to compare the survival rate.
Results: A total of 235 patients were included in the current study. The cut-off value of the scoring system was six. Multivariate analyses revealed that an advanced International Federation of Gynecology and Obstetrics(FIGO) stage (p<0.001 for PFS; p=0.038 for OS), the decreased white blood cell count difference (p=0.026 for PFS) and the high-PPSP (p=0.004for PFS; p=0.002 for OS) were the independent prognostic factors. Cox regression analysis also supported above results.
Conclusions: The PPSP showed good prognostic efficacy in predicting the ovarian cancer prognosis comparable to FIGO staging.
Publisher
Research Square Platform LLC