Abstract

Introduction We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. Methods The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes (C-indexes) and calibration plots. Results All 813 patients were randomly divided into a training group (n = 572) and a validation group (n = 241). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent C-indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. Conclusions The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making.

Highlights

  • We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas

  • A total of 5196 patients diagnosed with chondrosarcoma were registered in the SEER database from 1973 to 2016, of whom 2644 (50.9%) had primary tumors in the limb

  • We found that patients with chondrosarcoma in long bones had a worse prognosis

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Summary

Introduction

We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making. The disease demands concerted effort from researchers to undertake collaborative research if outcomes are to improve

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