Multicentre Validation of the RESECT-90 Prediction Model for 90-Day Mortality After Lung Resection

Abstract

BackgroundThe RESECT-90 model was developed to predict 90-day mortality for patients undergoing lung resection but hasn't been externally validated. The aim of this study was to validate the RESECT-90 clinical prediction model using multicentre patient data from across the United Kingdom (UK). Materials and MethodsData from 12 UK thoracic surgery centers for patients undergoing lung resection between 2016 and 2020 with available 90-day mortality status were used to externally validate the RESECT-90 model. Measures of discrimination (area under the receiving operator characteristic curve [AUC]) and calibration (calibration slope, calibration intercept and flexible calibration plot) were assessed as measures of model performance. Model recalibration was also performed by updating the original model intercept and coefficients. ResultsA total of 12,241 patients were included. Overall 90-day mortality was 2.9% (n = 360). Acceptable model discrimination was demonstrated (AUC 0.74 [0.73, 0.75]). Calibration varied between centers with some evidence of overall model miscalibration (calibration slope 0.80 [0.66, 0.95] and calibration intercept 0.40 [0.29, 0.52]) despite acceptable appearances of the flexible calibration plot. The model was subsequently recalibrated, after which all measures of calibration indicated excellent performance. ConclusionsAfter external validation and recalibration using a large contemporary cohort of patients undergoing surgery in multiple geographical locations across the UK, the RESECT-90 model demonstrated satisfactory statistical performance for the prediction of 90-day mortality after lung resection. Whilst the recalibrated model will require ongoing validation, the results of this study suggest that routine use of the RESECT-90 model in UK thoracic surgery practice should be considered.