Background: Esophageal cancer patients with pathologic lymph-node involvement (pN1) generally have a poor prognosis with surgery alone. We, therefore, constructed a nomogram to predict the risk of pN1 prior to surgical resection and externally validated the clinical utility of the model.
Methods: A total of 273 esophageal adenocarcinoma patients treated with surgery alone were reviewed from 2 different institutions (University of Texas M. D. Anderson Cancer Center = 164, training set; University of Rochester School of Medicine and Dentistry = 109, validation set). Pretreatment clinical parameters were used to construct a nomogram for predicting the risk of pN1. Internal and external validation of the nomogram was performed to assess clinical utility.
Results: Of the 164 patients in the training set, 56 patients (34%) had lymph-node involvement (pN1). Significant factors associated with pN1 on univariable logistic regression analysis (using a P < 0.05) included endoscopically determined clinical tumor depth (cT), clinical nodal (cN) status, and clinical tumor length (cL). Multivariable analysis suggested the significant independent factors were cT (odds ratio, 5.6; 95% confidence interval, 1.7-18.6; P < 0.01) and cL >2 cm (odds ratio, 7.0; 95% confidence interval, 2.7-18.1; P < 0.001). Regression tree analysis was used to determine the best cutoff for cL. A nomogram was created for pN1 using these clinical parameters and was internally validated by bootstrapping with a predicted accuracy of 85.1%. External validation performed on the validation set demonstrated an original C-index of 0.777 suggesting good clinical utility.
Conclusions: Our analyses demonstrate that the risk of pathologic nodal involvement in esophageal adenocarcinoma patients can be estimated by this clinical nomogram, which will allow the identification of patients at high-risk of harboring positive lymph-nodes, who may be candidates for en bloc resection and/or neoadjuvant treatment.
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http://dx.doi.org/10.1097/SLA.0b013e3181f56419 | DOI Listing |
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