Open AccessA Prognostic Model Based on XRCC1 Gene Polymorphisms and Clinicopathological Factors to Predict One-Year Survival of Advanced Epithelial Ovarian Cancer Patients
Author(s) -
Chamim Singoprawiro,
Iswari Setianingsih,
Bambang Sutrisna,
Nuryati Chairani Siregar,
Andrijono Andrijono
Publication year - 2022
Publication title -
syntax literate
Language(s) - English
Resource type - Journals
eISSN - 2548-1398
pISSN - 2541-0849
DOI - 10.36418/syntax-literate.v7i1.5653
Subject(s) - xrcc3 , xrcc1 , medicine , oncology , proportional hazards model , ovarian cancer , survival analysis , stage (stratigraphy) , biology , receiver operating characteristic , cancer , gastroenterology , gene , genotype , genetics , single nucleotide polymorphism , paleontology
Prognosis of advanced stage epithelial ovarian cancer (EOC) patients remains poor due to recurrence and disease progression after surgery and chemotherapy. Polymorphism in the genes involved in DNA repair, i.e. x-ray repair cross complementing protein-1 (XRCC1) and XRCC3 could alter function, diminish repair kinetics and may play a role in tumor resistance to therapy. This study was aimed to predict the prognosis of advanced stage EOC patients based on the polymorphism of XRCC1 and XRCC3 genes and the clinicopathology. This was an ambispective cohort study in EOC patients treated in Fatmawati General Central Hospital and its network hospitals in Jakarta between 2011 and 2016. Demographic data and clinicopathology was obtained from the medical record. Polymorphisms of XRCC1 and XRCC3 genes were detected by using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Survival analyses were performed using the Kaplan-Meier curve and Cox proportional hazard test. Multivariate analyses were performed to obtain prediction model for 1-year survival. Scoring system was developed and tested using the receiver operating characteristic (ROC) curve analyses. A total of 129 eligible cases were included. Patients’ mean age was 49.6 years. Most patients (93.8%) were having stage III disease. Mortality at 1-year was associated with three independent variables, i.e. histopathology subtype, residual tumor > 1 cm, and XRCC1 gene Arg399Gln polymorphisms (Arg/Gln or Gln/Gln alleles). These prediction models gave 85.3% accuracy by ROC curve analysis and 82.7% posttest probability. Prognosis of advanced stage EOC patients can be predicted from several clinicopathological factors and XRCC1 gene polymorphisms. Validation study is needed to confirm these findings.