Chamim Singoprawiro
Department of Obstetrics and Gynecology, Fatmawati General Hospital, Jakarta

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A Prognostic Model Based on XRCC1 Gene Polymorphisms and Clinicopathological Factors to Predict One-Year Survival of Advanced Epithelial Ovarian Cancer Patients Chamim Singoprawiro; Iswari Setianingsih; Bambang Sutrisna; Nuryati C Siregar; Andrijono Andrijono
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : CV. Ridwan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (148.308 KB) | DOI: 10.36418/syntax-literate.v7i1.5653

Abstract

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.