Biomarkers to help guide management of patients with pulmonary nodules.
Rationale: Indeterminate pulmonary nodules are a common radiographic finding and require further evaluation because of the concern for lung cancer. Objectives: We developed an algorithm to assign patients to a low- or high-risk category for lung cancer, based on a combination of serum biomarker leve...
| Publicado en: | American Journal of Respiratory & Critical Care Medicine Vol. 188; no. 4; pp. 461 - 466 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Oxford University Press / USA
8/15/2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=107909821&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 107909821 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1073449X 1FG jtl: American Journal of Respiratory & Critical Care Medicine issn: 1073449X maglogo: N pubinfo: dt: 8/15/2013 vid: 188 iid: 4 pid: 622 pub: Oxford University Press / USA artinfo: ui: 107909821 107909821 2012227051 10.1164/rccm.201210-1760OC NLM23306547 107909821 ppf: 461 ppct: 5 formats: tig: atl: Biomarkers to help guide management of patients with pulmonary nodules. aug: au: Patz Jr, Edward F Campa, Michael J Gottlin, Elizabeth B Trotter, Priscilla R Herndon 2nd, James E Kafader, Don Grant, Russell P Eisenberg, Marcia affil: 1 Department of Radiology and. sug: subj: Biological Markers Blood Lung Diseases Diagnosis Lung Neoplasms Diagnosis Solitary Pulmonary Nodule Blood Solitary Pulmonary Nodule Therapy Adult Aged Aged, 80 and Over Algorithms Antigens, Tumor Blood Diagnosis, Differential Female Human Logistic Regression Male Middle Age Sensitivity and Specificity Proteins Blood alpha 1-Antitrypsin Blood Adult: 19-44 years Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: Rationale: Indeterminate pulmonary nodules are a common radiographic finding and require further evaluation because of the concern for lung cancer. Objectives: We developed an algorithm to assign patients to a low- or high-risk category for lung cancer, based on a combination of serum biomarker levels and nodule size. Methods: For the serum biomarker assay, we determined levels of carcinoembryonic antigen, [alpha]1-antitrypsin, and squamous cell carcinoma antigen. Serum data and nodule size from a training set of 509 patients with (n = 298) and without (n = 211) lung cancer were subjected to classification and regression tree and logistic regression analyses. Multiple models were developed and tested in an independent, masked validation set for their ability to categorize patients with (n = 203) or without (n = 196) lung cancer as being low- or high-risk for lung cancer. Measurements and Main Results: In all models, a large percentage of individuals in the validation study with small nodules (<1 cm) were assigned to the low-risk group, and a large percentage of individuals with large nodules (>=3 cm) were assigned to the high-risk group. In the validation study, the classification and regression tree algorithm had overall sensitivity, specificity, and positive and negative predictive values for determining lung cancer of 88%, 82%, 84%, and 87%, respectively. The logistic regression model had overall sensitivity, specificity, and positive and negative predictive values of 80%, 89%, 89%, and 81%, respectively. Conclusion: Integration of biomarkers with lung nodule size has the potential to help guide the management of patients with indeterminate pulmonary nodules. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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