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. 2017 Apr 13;17(1):267.
doi: 10.1186/s12885-017-3273-x.

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

Fei Zhao  1 , Yue Zhou  1 , Peng-Fei Ge  1 , Chen-Jun Huang  1 , Yue Yu  1 , Jun Li  1 , Yun-Gang Sun  1 , Yang-Chun Meng  1 , Jian-Xia Xu  1 , Ting Jiang  1 , Zhi-Xuan Zhang  1 , Jin-Peng Sun  1 , Wei Wang  2
Affiliations

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

Fei Zhao et al. BMC Cancer. .

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 < 0.001), tumour differentiation (p < 0.001), pleural invasion (p = 0.034) and bronchus invasion (p < 0.001) to be risk factors significantly associated with the presence of metastatic lymph nodes. On multivariable analysis, only tumour size >2.65 cm (p < 0.001), tumour differentiation (p = 0.006) and bronchus invasion (p = 0.017) were independent predictors for lymph node metastasis. We developed a model based on these three pathologic factors that determined that the risk of metastasis ranged from 3% to 44% for patients intraoperatively diagnosed as stage I non-small-cell lung cancer. By applying the model, we found that the values ŷ > 0.80, 0.43 < ŷ ≤ 0.80, ŷ ≤ 0.43 plus tumour size >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.

Keywords: Lymph node; Metastasis; Multivariable logistic model; Non-small-cell lung cancer.

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Figures

Fig. 1
Fig. 1
The ROC (Receiver Operating Characteristic) curve of tumor size between group I and group II
Fig. 2
Fig. 2
The ROC (Receiver Operating Characteristic) curve of the selected model
See this image and copyright information in PMC

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