Rethinking Autoantibody Signature Panels for Cancer Diagnosis.
Introduction: Most pulmonary nodules found on imaging studies are indeterminate, but because of the concern for lung cancer, all patients require further evaluation with resultant radiation risk, significant cost, and delays in diagnosis. We hypothesized that a diagnostic blood test based on detecti...
| Publicado en: | Journal of Thoracic Oncology Vol. 12; no. 6; pp. 1011 - 1015 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Jun2017
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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=123158822&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 123158822 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15560864 4Z2B jtl: Journal of Thoracic Oncology issn: 15560864 maglogo: N pubinfo: dt: Jun2017 vid: 12 iid: 6 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 123158822 123158822 NLM28126538 123158822 10.1016/j.jtho.2017.01.017 NLM28126538 123158822 ppf: 1011 ppct: 4 formats: tig: atl: Rethinking Autoantibody Signature Panels for Cancer Diagnosis. aug: au: Campa, Michael J. Gottlin, Elizabeth B. IIHerndon, James E. Jr.Patz, Edward F. Herndon, James E 2nd Patz, Edward F Jr affil: Department of Radiology, Duke University Medical Center, Durham, North Carolina sug: subj: Carcinoma, Non-Small-Cell Lung Diagnosis Autoantibodies Blood Lung Neoplasms Diagnosis Antigens, Tumor Immunology Lung Neoplasms Immunology Prognosis Lung Neoplasms Blood Carcinoma, Non-Small-Cell Lung Blood Algorithms Protein Array Analysis Carcinoma, Non-Small-Cell Lung Immunology Human ab: Introduction: Most pulmonary nodules found on imaging studies are indeterminate, but because of the concern for lung cancer, all patients require further evaluation with resultant radiation risk, significant cost, and delays in diagnosis. We hypothesized that a diagnostic blood test based on detection of autoantibodies against cancer antigens would be able to distinguish a benign nodule from lung cancer.Methods: We identified a panel of 25 serum autoantibodies associated with NSCLC and constructed a protein microarray containing the autoantigens. We tested the microarray with human sera (from 125 patients with NSCLC and 125 matched controls with a benign nodule) and attempted to develop a classification algorithm that would separate the two groups.Results: In the training data set the logistic regression c-index statistic was 0.691; in the validation data set, the model predicting the score generated from the training set model had a c-index of 0.490. The relationship between the score and outcome (final diagnosis) was not statistically significant (p = 0.460).Conclusions: When the current panel of antigens and assay format was used, classification algorithms based on levels of autoantibodies to cancer antigens did not prove to have statistically significant value for predicting the presence of cancer. We suggest that there are inherent biological limitations to this approach. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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