J Cancer 2020; 11(8):2080-2090. doi:10.7150/jca.36861 This issue

Research Paper

Nomograms for the Prediction of Survival for Patients with Pediatric Adrenal Cancer after Surgery

Junjiong Zheng1*, Jinhua Cai2*, Xiayao Diao1*, Jianqiu Kong1, Xiong Chen1, Hao Yu1, Weibin Xie1, Jian Huang1✉, Tianxin Lin1,3✉

1. Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
2. Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
3. State Key Laboratory of Oncology in South China
*Co-first authors

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Citation:
Zheng J, Cai J, Diao X, Kong J, Chen X, Yu H, Xie W, Huang J, Lin T. Nomograms for the Prediction of Survival for Patients with Pediatric Adrenal Cancer after Surgery. J Cancer 2020; 11(8):2080-2090. doi:10.7150/jca.36861. Available from https://www.jcancer.org/v11p2080.htm

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Abstract

Purpose: To develop and validate a nomogram to postoperatively evaluate overall survival (OS) and cancer-specific survival (CSS) in patients with pediatric adrenal cancer.

Methods: In total, 847 eligible patients diagnosed between 1988 and 2015 form the Surveillance Epidemiology, and End Results (SEER) database were enrolled in this study according to the specified inclusion and exclusion criteria. They were divided into a training set (n = 661) and a validation set (n = 186). Multivariate Cox proportional hazards regression algorithm was used to identify the independent predictors of OS and CSS in the training set, and develop the predicting models, which were presented two nomograms. The performance of the nomograms (discrimination, calibration and clinical usefulness) was assessed in the training set and validated in the validation set.

Results: Based on the multivariate Cox proportional hazards regression analyses, three independent predictors including age at diagnosis, tumor size and M stage were identified for both OS and CSS. Then, an OS nomogram and a CSS nomogram were developed incorporating these three predictors, respectively. The OS nomogram showed good calibration and discrimination in the training set (C-index [95% CI], 0.744 [0.711-0.777]), which was confirmed in the validation set (C-index [95% CI], 0.746 [0.656-0.836]). Favorable calibration and discrimination of the CSS nomogram were also observed in the training set (C-index [95% CI], 0.749 [0.715-0.783]) and validation set (C-index [95% CI], 0.789 [0.710-0.868]). Moreover, the nomograms successfully distinguished patients with high risk of all-cause and cancer-specific mortality in all patients and in the stratified analyses. Decision curve analysis demonstrated the usefulness of the nomograms.

Conclusion: The presented nomograms show favorable predictive accuracy for OS and CSS in patients with pediatric adrenal cancer after surgery. Further validation is warranted prior to clinical implementation.

Keywords: adrenal cancer, pediatric, survival, nomogram