Currently, there are no competing risk analyses of cause-specific mortality in patients with pancreatic neuroendocrine tumors.
We estimated a cumulative incidence function for cause-specific mortality. The first nomogram for predicting cause-specific mortality was constructed using a proportional subdistribution hazard model, validated using bootstrap cross-validation, and evaluated with decision curve analysis.
Sex, age, positive lymph node status, metastasis, surveillance, epidemiology, and end results historic stage, grade, and surgery strongly predicted cause-specific mortality. The discrimination performance of Fine–Gray models was evaluated using the c-index, which was 0.864. In addition, the calibration plot of the developed nomogram demonstrated good concordance between the predicted and actual outcomes. Decision curve analysis yielded a range of threshold probabilities (0.014–0.779) at which the clinical net benefit of the risk model was greater than that in hypothetical all-screening or no-screening scenarios.
Our nomogram allows selection of a patient population at high risk for cancer-specific mortality and thus facilitates the design of prevention trials for the affected population.
First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
Correspondence to Guoqing Zhang, MD, Department of Surgery, First Affiliated Hospital of Zhengzhou University, No. 1 Jian She Road, Zhengzhou 450052, Henan Province, China Tel: +86 371 6691 3114; fax: +86 371 6691 6261; e-mail: firstname.lastname@example.org
Received September 21, 2018
Accepted December 5, 2018