• Ann. Thorac. Surg. · Nov 2013

    Development and validation of a clinical prediction model for N2 lymph node metastasis in non-small cell lung cancer.

    • Kezhong Chen, Fang Yang, Guanchao Jiang, Jianfeng Li, and Jun Wang.
    • Department of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.
    • Ann. Thorac. Surg. 2013 Nov 1;96(5):1761-8.

    BackgroundThe true incidence of occult N2 lymph node metastasis in patients with clinical N0 non-small cell lung cancer (NSCLC) remains controversial. Estimation of the probability of N2 lymph node metastasis can assist physicians when making diagnosis and treatment decisions.MethodsWe reviewed the medical records of 605 patients (group A) and 211 patients (group B) with computed tomography-defined N0 NSCLC that had an exact tumor-node-metastasis stage after surgery. Logistic regression analysis of group A's clinical characteristics was used to estimate the independent predictors of N2 lymph node metastasis. A prediction model was then built and internally validated by using cross validation and externally validated in group B. The model was also compared with 2 previously described models.ResultsWe identified 4 independent predictors of N2 disease: a younger age; larger tumor size; central tumor location; and adenocarcinoma or adenosquamous carcinoma pathology. The model showed good calibration (Hosmer-Lemeshow test: p = 0.96) with an area under the receiver operating characteristic curve (AUC) of 0.756 (95% confidence interval, 0.699 to 0.813). The AUC of our model was better than those of the other models when validated with independent data.ConclusionsOur prediction model estimated the pretest probability of N2 disease in computed tomography-defined N0 NSCLC and was more accurate than the existing models. Use of our model can be of assistance when making clinical decisions about invasive or expensive mediastinal staging procedures.Copyright © 2013 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…