A SEER data-based nomogram for the prognostic analysis of survival of patients with Kaposi’s sarcoma
Wanghai Li, Ling Wang, Yan Zhang, Yulong Liu, Yinsheng Lin, Chengzhi Li- Radiology, Nuclear Medicine and imaging
- Oncology
- General Medicine
ABSTRACT
Background:
This study developed the first comprehensive nomogram for predicting the cancer-specific survival (CSS) of patients with Kaposi’s sarcoma (KS).
Methods:
Data on the demographic and clinical characteristics of 4143 patients with KS were collected from the Surveillance, Epidemiology, and End Results (SEER) database and used for the prognostic analysis. The patients were randomly divided into two groups: training cohort (
Results:
A nomogram was developed for determining the 3-, 5-, 8-, and 10-year CSS probabilities for patients with KS. The nomogram showed that tumor stage had the greatest influence on the CSS of patients with KS, followed by demographic variables (race, marital status, and age at diagnosis) and other clinical characteristics (surgery status, chemotherapy status, tumor risk classification, and radiotherapy status). The nomogram exhibited excellent performance based on the values of the
Conclusions:
In this study, by using data from the SEER database, we developed the first comprehensive nomogram for analyzing the survival of patients with KS. This nomogram could serve as a convenient and reliable tool for clinicians to predict CSS probabilities for individual patients with KS.