Establishment and validation of a competitive risk model for predicting cancer-specific survival in patients with osteosarcoma: a population-based study

作者全名："Wu, Xin; Wang, Jinkui; He, Dawei"

作者地址："[Wu, Xin; Wang, Jinkui; He, Dawei] Chongqing Med Univ, Dept Urol, Childrens Hosp, 2 ZhongShan Rd, Chongqing 400013, Chongqing, Peoples R China; [Wu, Xin; Wang, Jinkui; He, Dawei] Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders,China In, Chongqing Key Lab Pediat,Chongqing Key Lab Childr, Minist Educ,Key Lab Child Dev & Disorders,Childre, Chongqing, Peoples R China"

通信作者："He, DW (通讯作者)，Chongqing Med Univ, Dept Urol, Childrens Hosp, 2 ZhongShan Rd, Chongqing 400013, Chongqing, Peoples R China.; He, DW (通讯作者)，Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders,China In, Chongqing Key Lab Pediat,Chongqing Key Lab Childr, Minist Educ,Key Lab Child Dev & Disorders,Childre, Chongqing, Peoples R China."

来源：JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001090171500005

JCR分区：Q3

影响因子：2.7

年份：2023

卷号：149

期号：17

开始页：15383

结束页：15394

文献类型：Article

关键词：Osteosarcoma; Competitive risk model; Cumulative incidence curves; Prognosis; SEER

摘要："BackgroundOsteosarcoma is the most common primary bone tumor with a poor prognosis. The aim of this study was to establish a competitive risk model nomogram to predict cancer-specific survival in patients with osteosarcoma.MethodsPatient data was obtained from the Surveillance, Epidemiology, and End Results database in the United States. A sub-distribution proportional hazards model was used to analyze independent risk factors affecting cancer-specific mortality (CSM) in osteosarcoma patients. Based on these risk factors, a competitive risk model was constructed to predict 1-year, 3-year, and 5-year cancer-specific survival (CSS) in osteosarcoma patients. The reliability and accuracy of the nomogram were evaluated using the concordance index (C-index), the area under the receiver operating characteristic curve (AUC), and calibration curves.ResultsA total of 2900 osteosarcoma patients were included. The analysis showed that age, primary tumor site, M stage, surgery, chemotherapy, and median household income were independent risk factors influencing CSM in patients. The competitive risk model was constructed to predict CSS in osteosarcoma patients. In the training and validation sets, the C-index of the model was 0.756 (95% CI 0.725-0.787) and 0.737 (95% CI 0.717-0.757), respectively, and the AUC was greater than 0.7 for both. The calibration curves also demonstrated a high consistency between the predicted survival rates and the actual survival rates, confirming the accuracy and reliability of the model.ConclusionWe established a competitive risk model to predict 1-year, 3-year, and 5-year CSS in osteosarcoma patients. The model demonstrated good predictive performance and can assist clinicians and patients in making clinical decisions and formulating follow-up strategies."

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