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Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay

BACKGROUND: The increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identific...

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Autores principales: Trivedi, Neil N, Arjomandi, Mehrdad, Brown, James K, Rubenstein, Tess, Rostykus, Abigail D., Esposito, Stephanie, Axler, Eden, Beggs, Mike, Yu, Heng, Carbonell, Luis, Juang, Alice, Kamer, Sandy, Patel, Bhavin, Wang, Shan, Fish, Amanda L, Haddad, Zaid, Wu, Alan HB
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480946/
https://www.ncbi.nlm.nih.gov/pubmed/32913898
http://dx.doi.org/10.15761/brcp.1000173
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author Trivedi, Neil N
Arjomandi, Mehrdad
Brown, James K
Rubenstein, Tess
Rostykus, Abigail D.
Esposito, Stephanie
Axler, Eden
Beggs, Mike
Yu, Heng
Carbonell, Luis
Juang, Alice
Kamer, Sandy
Patel, Bhavin
Wang, Shan
Fish, Amanda L
Haddad, Zaid
Wu, Alan HB
author_facet Trivedi, Neil N
Arjomandi, Mehrdad
Brown, James K
Rubenstein, Tess
Rostykus, Abigail D.
Esposito, Stephanie
Axler, Eden
Beggs, Mike
Yu, Heng
Carbonell, Luis
Juang, Alice
Kamer, Sandy
Patel, Bhavin
Wang, Shan
Fish, Amanda L
Haddad, Zaid
Wu, Alan HB
author_sort Trivedi, Neil N
collection PubMed
description BACKGROUND: The increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identification of malignant nodules may represent a potentially curable form of lung cancer. OBJECTIVE: To develop and validate a plasma-based multiplexed protein assay for classifying IPN by discriminating between those with a lung cancer diagnosis established pathologically and those found to be clinically and radiographically stable for at least one year. METHODS: Using a novel technology, we developed assays for plasma proteins associated with lung cancer into a panel for characterizing the risk that an IPN found on chest imaging is malignant. The assay panel was evaluated with a cohort of 277 samples, all from current smokers with an IPN 4–30 mm. Subjects were divided into training and test sets to identify a Support Vector Machine (SVM) model for risk classification containing those proteins and clinical factors that added discriminatory information to the Veteran’s Affairs (VA) Clinical Factors Model. The algorithm was then evaluated in an independent validation cohort. RESULTS: Among the 97 validation study subjects, 68 were grouped as having intermediate risk by the VA model of which the SVM model correctly identified 44 (65%) of these intermediate-risk samples as low (n=16) or high risk (n=28). The SVM model negative predictive value (NPV) was 94% and its sensitivity was 94%. CONCLUSION: The performance of the novel plasma protein biomarker assay supports its use as a noninvasive risk assessment aid for characterizing IPN. The high NPV of the SVM model suggests its application as a rule-out test to increase the confidence of providers to avoid aggressive interventions for their patients for whom the VA model result is an inconclusive, intermediate risk.
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spelling pubmed-74809462020-09-09 Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay Trivedi, Neil N Arjomandi, Mehrdad Brown, James K Rubenstein, Tess Rostykus, Abigail D. Esposito, Stephanie Axler, Eden Beggs, Mike Yu, Heng Carbonell, Luis Juang, Alice Kamer, Sandy Patel, Bhavin Wang, Shan Fish, Amanda L Haddad, Zaid Wu, Alan HB Biomed Res Clin Pract Article BACKGROUND: The increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identification of malignant nodules may represent a potentially curable form of lung cancer. OBJECTIVE: To develop and validate a plasma-based multiplexed protein assay for classifying IPN by discriminating between those with a lung cancer diagnosis established pathologically and those found to be clinically and radiographically stable for at least one year. METHODS: Using a novel technology, we developed assays for plasma proteins associated with lung cancer into a panel for characterizing the risk that an IPN found on chest imaging is malignant. The assay panel was evaluated with a cohort of 277 samples, all from current smokers with an IPN 4–30 mm. Subjects were divided into training and test sets to identify a Support Vector Machine (SVM) model for risk classification containing those proteins and clinical factors that added discriminatory information to the Veteran’s Affairs (VA) Clinical Factors Model. The algorithm was then evaluated in an independent validation cohort. RESULTS: Among the 97 validation study subjects, 68 were grouped as having intermediate risk by the VA model of which the SVM model correctly identified 44 (65%) of these intermediate-risk samples as low (n=16) or high risk (n=28). The SVM model negative predictive value (NPV) was 94% and its sensitivity was 94%. CONCLUSION: The performance of the novel plasma protein biomarker assay supports its use as a noninvasive risk assessment aid for characterizing IPN. The high NPV of the SVM model suggests its application as a rule-out test to increase the confidence of providers to avoid aggressive interventions for their patients for whom the VA model result is an inconclusive, intermediate risk. 2018-10-29 2018-12 /pmc/articles/PMC7480946/ /pubmed/32913898 http://dx.doi.org/10.15761/brcp.1000173 Text en http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Article
Trivedi, Neil N
Arjomandi, Mehrdad
Brown, James K
Rubenstein, Tess
Rostykus, Abigail D.
Esposito, Stephanie
Axler, Eden
Beggs, Mike
Yu, Heng
Carbonell, Luis
Juang, Alice
Kamer, Sandy
Patel, Bhavin
Wang, Shan
Fish, Amanda L
Haddad, Zaid
Wu, Alan HB
Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay
title Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay
title_full Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay
title_fullStr Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay
title_full_unstemmed Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay
title_short Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay
title_sort risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480946/
https://www.ncbi.nlm.nih.gov/pubmed/32913898
http://dx.doi.org/10.15761/brcp.1000173
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