A Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis analysis to evaluate the quality of reporting of postoperative pancreatic fistula prediction models after pancreatoduodenectomy:A systematic review

BACKGROUND: Postoperative pancreatic fistula is a frequent and potentially lethal complication after pancreatoduodenectomy. Several models have been developed to predict postoperative pancreatic fistula risk. This study was performed to evaluate the quality of reporting of postoperative pancreatic fistula prediction models after pancreatoduodenectomy using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist that provides guidelines on reporting prediction models to enhance transparency and to help in the decision-making regarding the implementation of the appropriate risk models into clinical practice.METHODS: Studies that described prediction models to predict postoperative pancreatic fistula after pancreatoduodenectomy were searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The TRIPOD checklist was used to evaluate the adherence rate. The area under the curve and other performance measures were extracted if reported. A quadrant matrix chart is created to plot the area under the curve against TRIPOD adherence rate to find models with a combination of above-average TRIPOD adherence and area under the curve.RESULTS: In total, 52 predictive models were included (23 development, 15 external validation, 4 incremental value, and 10 development and external validation). No risk model achieved 100% adherence to the TRIPOD. The mean adherence rate was 65%. Most authors failed to report on missing data and actions to blind assessment of predictors. Thirteen models had an above-average performance for TRIPOD checklist adherence and area under the curve.CONCLUSION: Although the average TRIPOD adherence rate for postoperative pancreatic fistula models after pancreatoduodenectomy was 65%, higher compared to other published models, it does not meet TRIPOD standards for transparency. This study identified 13 models that performed above average in TRIPOD adherence and area under the curve, which could be the appropriate models to be used in clinical practice.</p

External Validation of a Risk Model for Severe Complications following Pancreatoduodenectomy Based on Three Preoperative Variables

Background: Pancreatoduodenectomy (PD) is the only cure for periampullary and pancreatic cancer. It has morbidity rates of 40–60%, with severe complications in 30%. Prediction models to predict complications are crucial. A risk model for severe complications was developed by Schroder et al. based on BMI, ASA classification and Hounsfield Units of the pancreatic body on the preoperative CT scan. These variables were independent predictors for severe complications upon internal validation. Our aim was to externally validate this model using an independent cohort of patients. Methods: A retrospective analysis was performed on 318 patients who underwent PD at our institution from 2013 to 2021. The outcome of interest was severe complications Clavien–Dindo ≥ IIIa. Model calibration, discrimination and performance were assessed. Results: A total of 308 patients were included. Patients with incomplete data were excluded. A total of 89 (28.9%) patients had severe complications. The externally validated model achieved: C-index = 0.67 (95% CI: 0.60–0.73), regression coefficient = 0.37, intercept = 0.13, Brier score = 0.25. Conclusions: The performance ability, discriminative power, and calibration of this model were acceptable. Our risk calculator can help surgeons identify high-risk patients for post-operative complications to improve shared decision-making and tailor perioperative management