External validation of a lung cancer-based prediction model for two-year mortality in esophageal cancer patient cohorts

PURPOSE/OBJECTIVE: Chemo-radiotherapy can improve the oncological outcome of esophageal cancer (EC) patients, but may cause long term radiation-induced toxicity, including an increased risk of non-cancer related death. For lung cancer patients, a model to predict 2-year total mortality using mean heart dose (MHD) and gross tumor volume (GTV) has previously been developed and validated. This project aimed to externally validate this model in EC patients.

METHODS: Five EC patient cohorts from 3 different Dutch centres were used for model validation. External validity of the model was assessed separately in definitive (n=170) and neo-adjuvant (n=568) chemoradiotherapy (dCRT and nCRT) patients. External validity was assessed in terms of calibration by calibration plots, calibration-in-the-large (CITL) and calibration slope (CS), and discrimination by assessment of the c-statistic. If suboptimal model performance was observed, the model was further updated accordingly.

RESULTS: For the dCRT patients, good calibration was found after adjustment of the intercept (CITL 0.00; CS 1.08). The c-statistic of the adjusted model was 0.67 (95%CI: 0.58 to 0.75). For nCRT patients the model needed adjustment of both the slope and the intercept because of initial miscalibration in the validation population (CITL 0.00; CS 1.72). After recalibration, the model showed perfect calibration (i.e., CITL 0, CS 1), as is common after recalibration. The c-statistic of the recalibrated model equaled 0.62 (95%CI: 0.57 to 0.67).

CONCLUSION: The existing model for 2-year mortality prediction in lung cancer patients, based on the predictive factors MHD and GTV, showed good performance in EC patients after updating the intercept and/or slope of the original model.