Development and validation of a novel nomogram for predicting the prognosis of patients with resected pancreatic adenocarcinoma

Development and validation of a network calculator model for safety and efficacy after pancreaticoduodenectomy in the elderly patients with pancreatic head cancer

BACKGROUND

Benefiting from increased life expectancy and improved perioperative management, more elderly patients with pancreatic head cancer (PHC) underwent pancreaticoduodenectomy (PD). However, individualized predictive models for the safety and efficacy of PD is still lacking. this study aimed to developed three safety- and efficacy-related risk calculators for elderly (> = 65 years) PHC patients.

METHODS

This study was designed with two research cohorts, namely, the training cohort and the validation cohort, and comprises four general steps: (1) Risk factors were analyzed for the incidence of postoperative complications, cancer-specific survival (CSS), and overall survival (OS) in the training cohort (N = 271) using logistic and Cox-regression analysis. (2) Nomograms were then plotted based on the above results. (3) The accuracy of the developed nomogram models was then verified with the validation cohort (N = 134) data using consistency index (C-index) and calibration curves. (4) We then evaluated the efficacy of these nomograms using decision curve analysis (DCA) in both the training and validation cohorts, and ultimately constructed three online calculators based on these nomograms.

RESULTS

We identified ASA, diabetes, smoking, and lymph node invasion as predisposing risk factors for postoperative complications, and the predictive factors that affected both OS and CSS were ASA, diabetes, BMI, CA19-9 level, and tumor diameter. By integrating the above risk factors, we constructed three nomograms on postoperative complication, CSS, and OS. The C-index for complication, CSS, and OS were 0.824, 0.784, and 0.801 in the training cohort and 0.746, 0.718, and 0.708 in the validation cohort. Moreover, the validation curves and DCA demonstrated good calibration and robust compliance in both training and validation cohorts. We then developed three web calculators (https://caiming.shinyapps.io/CMCD/, https://caiming.shinyapps.io/CMCSS/, and https://caiming.shinyapps.io/CMOS/) to facilitate the use of the nomograms.

CONCLUSIONS

The calculators demonstrated promising performance as an tool for predicting the safety and efficacy of PD in elderly PHC patients.

Development and Validation of a Nomogram to Predict Survival in Pancreatic Head Ductal Adenocarcinoma After Pancreaticoduodenectomy

Background

Pancreatic head ductal adenocarcinoma (PHDAC) patients with the same tumor-node-metastasis (TNM) stage may share different outcomes after pancreaticoduodenectomy (PD). Therefore, a novel method to identify patients with poor prognosis after PD is urgently needed. We aimed to develop a nomogram to estimate survival in PHDAC after PD.

Methods

To estimate survival after PD, a nomogram was developed using the Tongji Pancreatic cancer cohort comprising 355 PHDAC patients who underwent PD. The nomogram was validated under the same conditions in another cohort (N = 161) from the National Taiwan University Hospital. Prognostic factors were assessed using LASSO and multivariate Cox regression models. The nomogram was internally validated using bootstrap resampling and then externally validated. Performance was assessed using concordance index (c-index) and calibration curve. Clinical utility was evaluated using decision curve analysis (DCA), X-tile program, and Kaplan-Meier curve in both training and validation cohorts.

Results

Overall, the median follow-up duration was 32.17 months, with 199 deaths (64.82%) in the training cohort. Variables included in the nomogram were age, preoperative CA 19-9 levels, adjuvant chemotherapy, Tongji classification, T stage, N stage, and differentiation degree. Harrell's c-indices in the internal and external validation cohorts were 0.79 (95% confidence interval [CI], 0.76-0.82) and 0.83 (95% CI, 0.78-0.87), respectively, which were higher than those in other staging systems. DCA showed better clinical utility.

Conclusion

The nomogram was better than TNM stage and Tongji classification in predicting PHDAC patients' prognosis and may improve prognosis-based selection of patients who would benefit from PD.