title: Nomogram to Predict Occult N2 Lymph Nodes Metastases in Patients With Squamous Nonsmall Cell Lung Cancer.
abstract: For nonsmall cell lung cancer (NSCLC) patients without distant metastases, occult involvement of N2 lymph nodes would be of the utmost importance in determining both treatment and survival. The key to optimal treatment strategies relied on accurate diagnosis, in particular accurate clinical tumor staging. Patients with clinical N0 or N1 staging preoperatively had a sizeable risk to have occult N2 lymph nodes metastases.From November 2004 to March 2007, the entire database in a tertiary hospital of all patients with a pathologic diagnosis of squamous NSCLC underwent anatomical pulmonary resection and systematic mediastinal lymph node dissection were retrospectively collected and reviewed. A nomogram was developed on the basis of a multivariable logistic regression model with a combination of all potential variables. In order to surmount the potential of overestimating predictive performance, both bootstrapping for internal validation and an independent external validation set were employed.A nomogram incorporating the significant risk factors was created to predict the probability of occult N2 lymph nodes metastases. The calibration plot for the probability of occult N2 lymph nodes metastases showed an optimal agreement between the predicted probabilities by nomogram and actual observed probabilities. An objective and accurate nomogram predictive model for occult N2 lymph nodes metastases was drawn up and validated internally and externally in patients with squamous NSCLC.The nomogram model, as a robust tool in predicting occult N2 lymph nodes involvement, could be involved in a cost-effective application of specific diagnostic and therapeutic strategies.
authors.affiliation: From the Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China (LJ, SJ, YL, HY, ZX, YL, HL); Lung Cancer Institute of Sun Yat-sen University, Guangzhou, China (LJ, YL, HY, ZX, YL, HL); Department of Thoracic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China (LJ, YL, HY, ZX, YL, HL); and University of California, San Francisco, San Francisco, CA (LJ).
authors.forename: Long
authors.initials: L
authors.lastname: Jiang
authors.forename: Shanshan
authors.initials: S
authors.lastname: Jiang
authors.forename: Yongbin
authors.initials: Y
authors.lastname: Lin
authors.forename: Han
authors.initials: H
authors.lastname: Yang
authors.forename: Zehua
authors.initials: Z
authors.lastname: Xie
authors.forename: Yaobin
authors.initials: Y
authors.lastname: Lin
authors.forename: Hao
authors.initials: H
authors.lastname: Long
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002289:Carcinoma, Non-Small-Cell Lung / Q000473:pathology* / Q000601:surgery; D002294:Carcinoma, Squamous Cell / Q000473:pathology* / Q000601:surgery; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D016015:Logistic Models; D008175:Lung Neoplasms / Q000473:pathology* / Q000601:surgery; D008197:Lymph Node Excision; D008207:Lymphatic Metastasis; D008297:Male; D008482:Mediastinum; D008875:Middle Aged; D009367:Neoplasm Staging; D049451:Nomograms; D011013:Pneumonectomy; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012307:Risk Factors