# Development and validation of nomograms to forecast overall survival and cancer-specific survival in Asian patients diagnosed with epithelial ovarian cancer

## TL;DR

This study created and tested tools to predict survival outcomes for Asian women with ovarian cancer, which could help improve clinical decision-making.

## Contribution

The study introduces nomograms and a risk stratification system tailored for Asian patients with epithelial ovarian cancer.

## Key findings

- The nomograms showed strong predictive accuracy with C-indices of 0.768 and 0.778 in the training cohort.
- Validation cohort results showed even higher C-indices of 0.804 and 0.812 for overall and cancer-specific survival.
- The nomograms outperformed the American Joint Commission on Cancer staging system in predictive accuracy.

## Abstract

Asian females with ovarian cancer have different clinicopathological characteristics compared with other races. However, an effective prognostic prediction tool is lacking. The goal of our study was to develop and evaluate nomograms for estimating overall survival and cancer-specific survival in Asian patients with ovarian cancer.

We extracted data from 2010 to 2018 in the Surveillance, Epidemiology, and End Results database, focusing on Asian/Pacific Islander females that had been diagnosed with epithelial ovarian cancer. To find prognostic factors, least absolute shrinkage and selection operator Cox regression and multivariate Cox regression analyses were used. Based on the outcomes, nomograms were then constructed. Numerous techniques, such as the C-index, calibration plots, decision curve analysis, and risk subgroup stratification, were used to assess the performance of the nomograms.

Nomograms were created to evaluate overall survival and cancer-specific survival rates over three and five years. The C-indices for overall survival and cancer-specific survival in the training cohort were 0.768 and 0.778, respectively. The C-indices for overall survival and cancer-specific survival in the validation cohort were 0.804 and 0.812, respectively. The calibration plots showed that the nomogram forecasts and actual survival results agreed. Additionally, the decision curve analysis curves indicated that the nomogram outperformed the American Joint Commission on Cancer staging system in terms of predictive accuracy.

Nomograms and a risk classification system were created to forecast the overall survival and cancer-specific survival of Asian females with ovarian cancer. The nomograms and risk stratification system have the potential to provide valuable assistance in making future clinical decisions.