Predicting individual survival after potentially curative esophagectomy for adenocarcinoma of the esophagus or gastroesophageal junction.

INTRODUCTION

Even after potentially curative esophagectomy, the majority of patients with adenocarcinoma of the esophagus or gastroesophageal junction die due to cancer recurrence. To predict individual disease-specific survival, a nomogram has been developed in a high-volume center in the Netherlands. The validity of this nomogram was externally tested in patients treated in another country at a different high-volume institution.

METHODS

Clinicopathological data from patients who underwent a macroscopically radical resection in a high-volume center in Leuven, Belgium, were used to validate the original nomogram based on a Cox regression model. Moreover, it was examined whether adjusting the value of the original coefficients of the predictors or adding new predictors would improve the fit of the nomogram in the validation cohort. Calibration was evaluated by comparing the observed survival with the expected survival as predicted by the original nomogram across patients with different risk profiles. The discriminatory ability of the nomogram was determined in the validation cohort, using the concordance index and compared with the original estimate.

RESULTS

A total of 382 patients were used in the validation study. The median esophageal cancer-specific survival was 38 months. None of the coefficients re-estimated in the validation cohort differed significantly from the values of the original nomogram. Observed and expected survival curves showed good calibration. Discrimination of the original nomogram was preserved in the validation cohort: the concordance index hardly decreased from 0.77 in the original cohort to 0.76 in the validation cohort.

CONCLUSIONS

The nomogram model that was originally developed in a Dutch institute had good individual discriminatory properties and good overall calibration when applied to an independent series of patients. The nomogram was updated using the data from both cohorts to provide even more robust estimates of survival for individual patients. This tool is clinically helpful to supply more reliable prognostic information, to offer tailored follow-up schedules and/or novel therapeutic strategies in subgroups of patients with higher risk of recurrence.