Log odds of positive lymph nodes predicts survival in patients treated with neoadjuvant therapy followed by esophagectomy. Issue 7 (5th March 2020)

• Record Type: Journal Article
• Authors: Ye, Guanzhi; Chen, Zhencong; Wang, Lin; Hu, Zhengyang; Bian, Yunyi; Yang, Xiaodong; Lu, Tao; Zhan, Cheng; Lin, Zongwu; Wang, Qun
• Is Part Of: Journal of surgical oncology. Volume 121:Issue 7(2020)
• Page Start: 1074
• Page End: 1083
• Publication Date: 2020-03-05
• Subjects: esophageal carcinoma -- log odds of positive lymph nodes -- neoadjuvant therapy; Cancer -- Surgery -- Periodicals; Neoplasms -- Periodicals; 616
• DOI: 10.1002/jso.25888
• Languages: English
• ISSNs: 0022-4790

Abstract

Abstract: Background and Objectives: We aimed to evaluate the efficacy of the log odds of positive lymph nodes (LODDS) in survival prediction of patients with esophageal carcinoma receiving neoadjuvant therapy, compared with N descriptor and positive lymph node ratio (LNR). Methods: Patients with esophageal carcinoma receiving neoadjuvant therapy from 2004 to 2015 were reviewed in Surveillance, Epidemiology, and End Results database. The receiver operating characteristics curve and area under the curve (AUC) were used to compare discriminatory power among N descriptor, LNR, and LODDS. The goodness of fit was measured using the −2 log‐likelihood ratio (–2LLR). Results: About 2239 patients with a 22 months median follow‐up and a 37.8% 5‐year overall survival rate were included. LODDS had the best discriminatory power and goodness of fit (LODDS vs N descriptor, AUC 0.666 vs 0.626, −2LLR 15 680.402 vs 15 746.162; LODDS vs LNR, AUC 0.666 vs 0.635, −2LLR 15 680.402 vs 15 712.379; all P < .001). LODDS was the best for fewer than 15 lymph nodes retrieved (LODDS vs N descriptor, AUC 0.652 vs 0.618, P < .001; LODDS vs LNR, AUC 0.652 vs 0.625, P = .005). The prognosis of patients without metastatic nodes could be discriminated by LODDS. Conclusions: LODDS could better predict survival of patients with esophageal carcinoma receiving neoadjuvant therapy.