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Prediction of cancer-specific survival and overall survival in middle-aged and older patients with rectal adenocarcinoma using a nomogram model.
Liu, Hao; Lv, Liang; Qu, Yidan; Zheng, Ziweng; Zhao, Junjiang; Liu, Bo; Zhang, Dasen; Wang, Hexiang; Zhang, Jian.
Afiliación
  • Liu H; General Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Lv L; General Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Qu Y; Rheumatology and Immunology Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Zheng Z; General Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Zhao J; General Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Liu B; General Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Zhang D; General Surgery Department, Zaozhuang Municipal Hospital, Qingdao, Shandong, China.
  • Wang H; Radiology Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. Electronic address: 18661808669@126.com.
  • Zhang J; General Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. Electronic address: drjianzhang@126.com.
Transl Oncol ; 14(1): 100938, 2021 Jan.
Article en En | MEDLINE | ID: mdl-33186890
ABSTRACT

OBJECTIVE:

To develop a new nomogram tool for predicting survival in middle-aged and elderly patients with rectal adenocarcinoma.

METHODS:

A total of 6,116 patients were randomly assigned in a 73 ratio to training and validation cohorts. Univariate and multivariate Cox proportional hazards regression analyses were used to identify independent prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS) in the training set, and two nomogram prognostic models were constructed. The validity, accuracy, discrimination, predictive ability, and clinical utility of the models were assessed based on the concordance index (C-index), area under the receiver operating characteristics (ROC) curve, time-dependent area under the ROC curve (AUC), Kaplan-Meier survival curve, and decision curve analyses.

RESULTS:

Predictors of OS and CSS were identified, and nomograms were successfully constructed. The calibration discrimination for both the OS and CSS nomogram prediction models was good (C-index 0.763 and 0.787, respectively). The AUC showed excellent predictive performance, and the calibration curve exhibited significant predictive power for both nomograms. The time-dependent AUC showed that the predictive ability of the predictor-based nomogram was better than that of the TNM stage. The nomograms successfully discriminated high-, medium-, and low-risk patients for all-cause and cancer-specific mortality. The decision curve demonstrated that the nomograms are useful with respect to good decision power.

CONCLUSION:

Our nomogram survival prediction models may aid in evaluating the prognosis of middle-aged and older patients with rectal adenocarcinoma and guiding the selection of the clinical treatment measures.
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Transl Oncol Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Transl Oncol Año: 2021 Tipo del documento: Article País de afiliación: China