Development and Validation of Nomograms Predicting Overall and Cancer-specific Survival for Non-metastatic Primary Malignant Bone Tumor of Spine Patients

Overview

Journal Sci Rep

Specialty Science

Date 2023 Mar 1

PMID 36859465

Authors

Yiming Shao

Zhonghao Wang

Xiaoya Shi

Yexin Wang

Affiliations

Soon will be listed here.

Abstract

At present, no study has established a survival prediction model for non-metastatic primary malignant bone tumors of the spine (PMBS) patients. The clinical features and prognostic limitations of PMBS patients still require further exploration. Data on patients with non-metastatic PBMS from 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate regression analysis using Cox, Best-subset and Lasso regression methods was performed to identify the best combination of independent predictors. Then two nomograms were structured based on these factors for overall survival (OS) and cancer-specific survival (CSS). The accuracy and applicability of the nomograms were assessed by area under the curve (AUC) values, calibration curves and decision curve analysis (DCA). Results: The C-index indicated that the nomograms of OS (C-index 0.753) and CSS (C-index 0.812) had good discriminative power. The calibration curve displays a great match between the model's predictions and actual observations. DCA curves show our models for OS (range: 0.09-0.741) and CSS (range: 0.075-0.580) have clinical value within a specific threshold probability range compared with the two extreme cases. Two nomograms and web-based survival calculators based on established clinical characteristics was developed for OS and CSS. These can provide a reference for clinicians to formulate treatment plans for patients.

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