Construction of nomograms for survival prediction in high-grade chondrosarcoma based on multivariable analysis: A SEER database study.
Chondrosarcoma is the second most common malignant primary bone tumor. Given the poorer prognosis of high-grade chondrosarcomas and the lack of prognostic tools, this study aimed to develop a nomogram for better prognosis evaluation.
A comprehensive approach was adopted, involving Kaplan-Meier analysis for survival curve generation, log-rank test for comparing survival differences, and multivariate Cox regression analysis for identifying independent prognostic determinants. Utilizing the "rms" package, nomograms were constructed to predict overall survival (OS) and cancer-specific survival (CSS) of patients with high-grade chondrosarcoma. Nomogram reliability was validated through the concordance index (C-index) and calibration curves, which quantitatively and graphically evaluated the predictive accuracy.
A total of 1,198 high-grade chondrosarcoma cases retrieved from the SEER database were retrospectively analyzed. Following Kaplan-Meier survival analysis, several variables (age, sex, tumor size, stage, metastasis, surgery, chemotherapy, and radiation for OS) were incorporated into the multivariate Cox regression models for OS and CSS. Nomograms for OS and CSS were established based on the derived independent prognostic factors. The C-indices of the training and validation cohorts were 0.8117 and 0.7642 for the OS and 0.8475 and 0.8173 for the CSS analysis, respectively. The calibration plots further corroborated the nomograms' accurate predictive capacity for both OS and CSS.
Nomograms capable of precisely estimating OS and CSS in high-grade chondrosarcoma were successfully developed. These nomograms offer clinicians a valuable tool for more accurate survival prediction of patients with high-risk chondrosarcoma, which optimizes postoperative treatment strategies and improves patient management and outcomes.
A comprehensive approach was adopted, involving Kaplan-Meier analysis for survival curve generation, log-rank test for comparing survival differences, and multivariate Cox regression analysis for identifying independent prognostic determinants. Utilizing the "rms" package, nomograms were constructed to predict overall survival (OS) and cancer-specific survival (CSS) of patients with high-grade chondrosarcoma. Nomogram reliability was validated through the concordance index (C-index) and calibration curves, which quantitatively and graphically evaluated the predictive accuracy.
A total of 1,198 high-grade chondrosarcoma cases retrieved from the SEER database were retrospectively analyzed. Following Kaplan-Meier survival analysis, several variables (age, sex, tumor size, stage, metastasis, surgery, chemotherapy, and radiation for OS) were incorporated into the multivariate Cox regression models for OS and CSS. Nomograms for OS and CSS were established based on the derived independent prognostic factors. The C-indices of the training and validation cohorts were 0.8117 and 0.7642 for the OS and 0.8475 and 0.8173 for the CSS analysis, respectively. The calibration plots further corroborated the nomograms' accurate predictive capacity for both OS and CSS.
Nomograms capable of precisely estimating OS and CSS in high-grade chondrosarcoma were successfully developed. These nomograms offer clinicians a valuable tool for more accurate survival prediction of patients with high-risk chondrosarcoma, which optimizes postoperative treatment strategies and improves patient management and outcomes.