Validation of a Prediction Model for Post-chemotherapy Fibrosis in Nonseminoma Patients.

Abstract

Our purpose was to validate Vergouwe´s prediction model using the Swedish and Norwegian Testicular Cancer Group (SWENOTECA) RETROP database and define its clinical utility. The Vergouwe´s prediction model for benign histopathology in post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) uses the following variables: Presence of teratoma in orchiectomy specimen, pre-chemotherapy level of Alpha fetoprotein, ß-Human chorionic gonadotropin and Lactate dehydrogenase, and lymph node size pre- and post-chemotherapy. The validation cohort consisted of patients included in RETROP, a prospective population-based database of patients in Sweden and Norway with metastatic nonseminoma that underwent PC-RPLND 2007-2014. Discrimination and calibration analyses were used to validate Vergouwe´s prediction model results. Calibration plots were created and Hosmer-Lemeshow test was calculated. Clinical utility expressed as opt-out net benefit (NBoptout ) was analysed using decision curve analysis. Overall, 284 patients were included in the analysis, of whom 130 (46%) had benign histology after PC-RPLND. Discrimination analysis showed good reproducibility with AUC of 0.82 (95% CI 0.77-0.87) compared to Vergouwe´s prediction model (AUC between 0.77 and 0.84). Calibration was acceptable with no recalibration. Using a prediction threshold of 70% for benign histopathology, NBoptout was 0.098. Using the model and this threshold, 61 patients would have been spared surgery. However only 51 of 61 were correctly classified as benign. The model was externally validated with good reproducibility. In a clinical setting, the model may identify patients with a high chance of benign histopathology, thereby sparing patients of surgery. However, meticulous follow-up is required.