Kai Qian1, Wenyu Sun1, Kai Guo1, Xiaoke Zheng1, Tuanqi Sun1, Lili Chen1, Jun Xiang1, Duanshu Li1, Yi Wu1, Qinghai Ji1, Zhuoying Wang2. 1. Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai, 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China. 2. Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai, 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China. Electronic address: zhuoyingwang@hotmail.com.
Abstract
INTRODUCTION: To investigate whether the positive lymph node number (PLNN) and positive lymph node ratio (PLNR) could predict the prognosis of patients with major salivary gland cancer (MSGC) and to identify the optimal cutoff points for these variables that stratify patients according to their risk of survival. METHODS: We used the Surveillance, Epidemiology, and End Results (SEER) database to identify all patients with MSGC between 1988 and 2014. A logistic regression analysis was carried out to evaluate the risk factors for lymph node metastasis (LNM) in MSGC. The X-tile program was used to identify the cutoff values for the PLNN and PLNR in MSGC patients with LNM. Cox proportional hazards regression models were performed to identify the predictors of cancer-specific survival (CSS). RESULTS: In the SEER database, 8668 eligible patients were identified and 3046 of them had LNM. The logistic regression analysis indicated that older age, male sex, larger tumor size, higher grade, tumor extension and high-risk pathology were associated with LNM. The X-tile program showed that a PLNN>4 and a PLNR>0.15 were prognostic indicators of CSS. A multivariable analysis indicated that, after the factors that might potentially affect the prognosis were adjusted for, the PLNN and PLNR were still associated with CSS. CONCLUSIONS: Our Results demonstrated that the PLNN and PLNR were independent prognostic indicators for MSGC patients with lymph node metastasis.
INTRODUCTION: To investigate whether the positive lymph node number (PLNN) and positive lymph node ratio (PLNR) could predict the prognosis of patients with major salivary gland cancer (MSGC) and to identify the optimal cutoff points for these variables that stratify patients according to their risk of survival. METHODS: We used the Surveillance, Epidemiology, and End Results (SEER) database to identify all patients with MSGC between 1988 and 2014. A logistic regression analysis was carried out to evaluate the risk factors for lymph node metastasis (LNM) in MSGC. The X-tile program was used to identify the cutoff values for the PLNN and PLNR in MSGC patients with LNM. Cox proportional hazards regression models were performed to identify the predictors of cancer-specific survival (CSS). RESULTS: In the SEER database, 8668 eligible patients were identified and 3046 of them had LNM. The logistic regression analysis indicated that older age, male sex, larger tumor size, higher grade, tumor extension and high-risk pathology were associated with LNM. The X-tile program showed that a PLNN>4 and a PLNR>0.15 were prognostic indicators of CSS. A multivariable analysis indicated that, after the factors that might potentially affect the prognosis were adjusted for, the PLNN and PLNR were still associated with CSS. CONCLUSIONS: Our Results demonstrated that the PLNN and PLNR were independent prognostic indicators for MSGC patients with lymph node metastasis.
Authors: Douglas R Farquhar; Andrew J Coniglio; Maheer M Masood; Nicholas Lenze; Paul Brennan; Devasena Anantharaman; Behnoush Abedi-Ardekani; Adam M Zanation; Mark C Weissler; Andrew F Olshan; Siddharth Sheth; Trevor G Hackman Journal: Oral Oncol Date: 2020-05-31 Impact factor: 5.337
Authors: Mussab Kouka; Benjamin Koehler; Jens Buentzel; Holger Kaftan; Daniel Boeger; Andreas H Mueller; Andrea Wittig; Stefan Schultze-Mosgau; Thomas Ernst; Peter Schlattmann; Orlando Guntinas-Lichius Journal: Cancers (Basel) Date: 2022-06-07 Impact factor: 6.575
Authors: Guoshu Bi; Tao Lu; Guangyu Yao; Yunyi Bian; Mengnan Zhao; Yiwei Huang; Yi Zhang; Liang Xue; Cheng Zhan; Hong Fan Journal: Cancer Manag Res Date: 2019-11-06 Impact factor: 3.989