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

Date 18 December 2016
Event ESMO Asia 2016 Congress
Session Poster lunch
Topics Cervical Cancer
Presenter sugashwaran Jagadeesan
Citation Annals of Oncology (2016) 27 (suppl_9): ix94-ix103. 10.1093/annonc/mdw585
Authors S. Jagadeesan
  • Radiation Oncology, Kidwai Memorial Institute of Oncology, 560029 - Bangalore/IN

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.

Clinical trial indentification

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.