Development and validation of a nomogram to predict cancer-specific survival in nonsurgically treated elderly patients with prostate cancer.

Autor: Zhang Z; Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing Higher Institution Engineering Research Center of Children's Medical Big Data Intelligent Application, Chongqing, People's Republic of China., Cai Q; Department of Urology, Affiliated Hospital of Yunnan University (The Second People's Hospital of Yunnan Province, Ophthalmic Hospital of Yunnan Province), Kunming, Yunnan, People's Republic of China., Wang J; Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing Higher Institution Engineering Research Center of Children's Medical Big Data Intelligent Application, Chongqing, People's Republic of China., Yao Z; Department of Urology, Kunming Children's Hospital (Children's Hospital affiliated to Kunming Medical University), 288 Qianxing Road, Kunming, 650228, Yunnan, China., Ji F; Department of Urology, Kunming Children's Hospital (Children's Hospital affiliated to Kunming Medical University), 288 Qianxing Road, Kunming, 650228, Yunnan, China., Hang Y; Department of Urology, Kunming Children's Hospital (Children's Hospital affiliated to Kunming Medical University), 288 Qianxing Road, Kunming, 650228, Yunnan, China., Ma J; Yunnan Key Laboratory of Children's Major Disease Research, Kunming Children's Hospital (Children's Hospital Affiliated to Kunming Medical University), Yunnan Province Clinical Research Center for Children's Health and Disease, Kunming, People's Republic of China., Jiang H; Science and Education Department, Kunming Children's Hospital (Children's Hospital affiliated to Kunming Medical University), Kunming, People's Republic of China., Yan B; Department of Urology, Kunming Children's Hospital (Children's Hospital affiliated to Kunming Medical University), 288 Qianxing Road, Kunming, 650228, Yunnan, China. yanbing@etyy.cn.; Yunnan Key Laboratory of Children's Major Disease Research, Kunming Children's Hospital (Children's Hospital Affiliated to Kunming Medical University), Yunnan Province Clinical Research Center for Children's Health and Disease, Kunming, People's Republic of China. yanbing@etyy.cn., Zhanghuang C; Department of Urology, Kunming Children's Hospital (Children's Hospital affiliated to Kunming Medical University), 288 Qianxing Road, Kunming, 650228, Yunnan, China. zhanghuangchenghao@etyy.cn.; Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing Higher Institution Engineering Research Center of Children's Medical Big Data Intelligent Application, Chongqing, People's Republic of China. zhanghuangchenghao@etyy.cn.; Yunnan Key Laboratory of Children's Major Disease Research, Kunming Children's Hospital (Children's Hospital Affiliated to Kunming Medical University), Yunnan Province Clinical Research Center for Children's Health and Disease, Kunming, People's Republic of China. zhanghuangchenghao@etyy.cn.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Oct 18; Vol. 13 (1), pp. 17719. Date of Electronic Publication: 2023 Oct 18.
DOI: 10.1038/s41598-023-44911-z
Abstrakt: Prostate Cancer (PC) is the most common male nonskin tumour in the world, and most diagnosed patients are over 65 years old. The main treatment for PC includes surgical treatment and nonsurgical treatment. Currently, for nonsurgically treated elderly patients, few studies have evaluated their prognostic factors. Our aim was to construct a nomogram that could predict cancer-specific survival (CSS) in nonsurgically treated elderly PC patients to assess their prognosis-related independent risk factors. Patient information was obtained from the Surveillance, Epidemiology and End Results (SEER) database, and our target population was nonsurgically treated PC patients who were over 65 years old. Independent risk factors were determined using both univariate and multivariate Cox regression models. A nomogram was built using a multivariate Cox regression model. The accuracy and discrimination of the prediction model were tested using the consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve. Decision curve analysis (DCA) was used to examine the potential clinical value of this model. A total of 87,831 elderly PC patients with nonsurgical treatment in 2010-2018 were included in the study and were randomly assigned to the training set (N = 61,595) and the validation set (N = 26,236). Univariate and multivariate Cox regression model analyses showed that age, race, marital status, TNM stage, chemotherapy, radiotherapy modality, PSA and GS were independent risk factors for predicting CSS in nonsurgically treated elderly PC patients. The C-index of the training set and the validation set was 0.894 (95% CI 0.888-0.900) and 0.897 (95% CI 0.887-0.907), respectively, indicating the good discrimination ability of the nomogram. The AUC and the calibration curves also show good accuracy and discriminability. We developed a new nomogram to predict CSS in elderly PC patients with nonsurgical treatment. The model is internally validated with good accuracy and reliability, as well as potential clinical value, and can be used for clinical aid in decision-making.
(© 2023. Springer Nature Limited.)
Databáze: MEDLINE
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