Preoperative Nomogram to Risk Stratify Patients for the Benefit of Trimodality Therapy in Esophageal Adenocarcinoma

Abstract

PurposeTo develop a nomogram that estimates 1-year recurrence-free survival (RFS) after trimodality therapy for esophageal adenocarcinoma and to assess the overall survival (OS) benefit of esophagectomy after chemoradiotherapy (CRT) on the basis of 1-year recurrence risk.MethodsIn total, 568 consecutive patients with potentially resectable esophageal adenocarcinoma who underwent CRT were included for analysis, including 373 patients who underwent esophagectomy after CRT (trimodality therapy), and 195 who did not undergo surgery (bimodality therapy). A nomogram for 1-year RFS was created using a Cox regression model. The upper tertile of the nomogram score was used to stratify patients in low-risk and high-risk groups for 1-year recurrence. The 5-year OS was compared between trimodality and bimodality therapy in low-risk and high-risk patients after propensity score matching, respectively.ResultsMedian follow-up for the entire cohort was 62 months. The 5-year OS in the trimodality and bimodality treatment groups was 56.3% (95% confidence interval [CI] 47.9–64.7) and 36.9% (95% CI 31.4–42.4), respectively. The final nomogram for the prediction of 1-year RFS included male gender, poor histologic grade, signet ring cell adenocarcinoma, cN1, cN2-3, and baseline SUVmax, with accurate calibration and reasonable discrimination (C-statistic: 0.66). Trimodality therapy was associated with improved 5-year OS in low-risk patients (p = 0.003), whereas it showed no significant survival benefit in high-risk patients (p = 0.302).ConclusionsThe proposed nomogram estimates early recurrence risk. The addition of surgery to CRT provides a clear OS benefit in low-risk patients. The OS benefit of surgery in high-risk patients is less pronounced.Electronic supplementary materialThe online version of this article (10.1245/s10434-018-6435-4) contains supplementary material, which is available to authorized users.

Machine learning to predict early recurrence after oesophageal cancer surgery

“…This cohort exhibited an early recurrence rate of 29·1 per cent, which is similar to that in previous reports where this outcome was specified explicitly. There was also an R1 resection rate of 28·4 per cent, in line with previously reported data based on an RCP definition of CRM positivity (CRM less than 1 mm is positive).…”

ASO Author Reflections: Predicting Early Recurrence After Trimodality Therapy for Esophageal Adenocarcinoma

“…The current study identified gender, poor tumor differentiation grade, signet ring cell adenocarcinoma, baseline clinical nodal status, and SUV max of the initial positron emission tomography/computed tomography as independent prognostic factors for early recurrence after trimodality therapy 3. Based on the subsequent prediction model, patients at high-risk of early recurrence had no survival benefit of trimodality therapy compared with definitive chemoradiotherapy.…”

Machine learning to predict early recurrence after oesophageal cancer surgery

“…The primary outcome measure was early recurrence, defined as confirmed local, regional or distant recurrence at less than 1 year from the date of surgery 5,8,13 . Missing Data was treated as being missing completely at random and handled by list wise deletion.…”