A predictive model with a risk-classification system for cancer-specific survival in patients with primary osteosarcoma of long bone.

ABSTRACT:

Background

Osteosarcoma (OS), most commonly occurring in long bone, is a group of malignant tumors with high incidence in adolescents. No individualized model has been developed to predict the prognosis of primary long bone osteosarcoma (PLBOS) and the current AJCC TNM staging system lacks accuracy in prognosis prediction. We aimed to develop a nomogram based on the clinicopathological factors affecting the prognosis of PLBOS patients to help clinicians predict the cancer-specific survival (CSS) of PLBOS patients.

Method

We studied 1199 PLBOS patients from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and randomly divided the dataset into training and validation cohorts at a proportion of 7:3. Independent prognostic factors determined by s

SUBMITTER: Tian S 

PROVIDER: S-EPMC8844746 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature