327P Nomogram prediction for overall survival of patients diagnosed with cervical cancer

Abstract

Background Nomograms are predictive tools that are widely used for estimating cancer prognosis. The aim of this study was to develop a nomogram for the prediction of overall survival (OS) in patients diagnosed with cervical cancer. Methods Cervical cancer databases of our institutie were analysed. Overall survival was defined as the clinical endpoint and OS probabilities were estimated using the Kaplan- Meier method. Based on the results of survival analyses and previous studies, relevant covariates were identified, a nomogram was constructed and validated using bootstrap cross-validation. Discrimination of the nomogram was quantified with the concordance probability. Results In total, 42 consecutive patients with invasive cervical cancer, who had all nomogram variables available, were identified. Mean 5-year OS rates for patients with International Federation of Gynecologists and Obstetricians (FIGO) stage IA, IB, II, III, and IV were 99.0%, 88.6%, 65.8%, 58.7%, and 41.5%, respectively. two cancer-related deaths were observed during the follow-up period. FIGO stage, tumour size, tumour type histologic subtype, ph, parametrial involvement, endometrial invasion and organ involvement were selected as nomogram covariates. In our study, the total bad prognostic score mean value is 12. So, we derived more than 12 as high risk, more than 10-12 as intermediate risk and; less than 10 as low risk group. Based on predictor Lin‘s statistic concordance index value is 0.61. The normal value of C index is ± 1. In our study we had achieved perfect concordance index value which is suggestive of perfect normogram. Conclusions Based on eight easily available parameters, a novel statistical model to predict OS of patients diagnosed with cervical cancer was constructed and validated. The model was implemented in a nomogram and provides accurate prediction of individual patients prognosis useful for patient counselling and deciding on follow-up strategies. Legal entity responsible for the study Dr. V. Lokesh, Dr. Bindhu Joseph, Dr. Tanvir, Dr. Varatharaj,. Funding Karnataka Disclosure All authors have declared no conflicts of interest.