A prediction model for lymph node metastases using pathologic features in patients intraoperatively diagnosed as stage I non-small cell lung cancer

Autor: Fei Zhao, Yue Zhou, Peng-Fei Ge, Chen-Jun Huang, Yue Yu, Jun Li, Yun-Gang Sun, Yang-Chun Meng, Jian-Xia Xu, Ting Jiang, Zhi-Xuan Zhang, Jin-Peng Sun, Wei Wang
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: BMC Cancer, Vol 17, Iss 1, Pp 1-8 (2017)
Druh dokumentu: article
ISSN: 1471-2407
57541639
DOI: 10.1186/s12885-017-3273-x
Popis: Abstract Background There is little information on which pattern should be chosen to perform lymph node dissection for stage I non-small-cell lung cancer. This study aimed to develop a model for predicting lymph node metastasis using pathologic features of patients intraoperatively diagnosed as stage I non-small-cell lung cancer. Methods We collected pathology data from 284 patients intraoperatively diagnosed as stage I non-small-cell lung cancer who underwent lobectomy with complete lymph node dissection from 2013 through 2014, assessing various factors for an association with metastasis to lymph nodes (age, gender, pathology, tumour location, tumour differentiation, tumour size, pleural invasion, bronchus invasion, multicentric invasion and angiolymphatic invasion). After analysing these variables, we developed a multivariable logistic model to estimate risk of metastasis to lymph nodes. Results Univariate logistic regression identified tumour size >2.65 cm (p 2.65 cm (p 0.80, 0.43 2 cm and ŷ ≤0.43 plus tumour size ≤2 cm yielded positive lymph node metastasis predictive values of 44%, 18%, 14% and 0%, respectively. Conclusions A non-invasive prediction model including tumour size, tumour differentiation and bronchus invasion may be useful to give thoracic surgeons recommendations on lymph node dissection for patients intraoperatively diagnosed as Stage I non-small cell lung cancer.
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