A population-based nomogram to individualize treatment modality for pancreatic cancer patients underlying surgery

Abstract

As the most aggressive tumor, TNM staging does not accurately identify patients with pancreatic cancer who are sensitive to therapy. This study aimed to identify associated risk factors and develop a nomogram to predict survival in pancreatic cancer surgery patients and to select the most appropriate comprehensive treatment regimen. First, the survival difference between radiotherapy and no radiotherapy was calculated based on propensity score matching (PSM). Cox regression was conducted to select the predictors of overall survival (OS). The model was constructed using seven variables: histologic type, grade, T stage, N stage, stage, chemotherapy and radiotherapy. All patients were classified into high- or low-risk groups based on the nomogram. The nomogram model for OS was established and showed good calibration and acceptable discrimination (C-index 0.721). Receiver operating characteristic curve (ROC) and DCA curves showed that nomograms had better predictive performance than TNM stage. Patients were divided into low-risk and high-risk groups according to nomogram scores. Radiotherapy is recommended for high-risk patients but not for low-risk patients. We have established a well-performing nomogram to effectively predict the prognosis of pancreatic cancer patients underlying surgery. The web version of the nomogram https://rockeric.shinyapps.io/DynNomapp/ may contribute to treatment optimization in clinical practice.

Figure 1

The data selection steps of the present study.

Figure 2

Hazard ratio in OS Cox analysis after PSM. OS Overall survival, PSM Propensity score matching, HR Hazard ratio, CI Confidence interval;

Figure 3

Nomogram to estimate the risk of prognosis for pancreatic cancer after surgery.

Figure 4

Calibration curves of the nomogram in the training cohort and validation cohorts. Calibration curves of 1-year (A), 2-year (B), 3-year (C) and 5-year (D) OS for patients in the training and validation cohorts. The plots along the 45° line indicate an appropriate calibration model, in which the predicted probabilities were identical to the actual outcomes. OS Overall survival.

Figure 5

Receiver operating characteristic curve analysis in the training and validation cohorts of the nomograms and 7th edition AJCC-TNM staging system for predicting 1-, 2-, 3-, and 5-year OS. OS, overall survival.

Figure 5

Receiver operating characteristic curve analysis in the training and validation cohorts of the nomograms and 7th edition AJCC-TNM staging system for predicting 1-, 2-, 3-, and 5-year OS. OS, overall survival.

Figure 6

Decision curve analysis in the training cohort of the nomograms and 7th edition AJCC-TNM staging system for predicting 1-, 2-, 3-, and 5-year OS. OS Overall survival.

Figure 7

(A) Overall survival of pancreatic cancer patients with or without radiotherapy in the low‐risk group; (B) Overall survival of pancreatic cancer patients with or without radiotherapy in the high‐risk group.