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Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients

BACKGROUND: CanAssist-Breast is an immunohistochemistry based test that predicts risk of distant recurrence in early-stage hormone receptor positive breast cancer patients within first five years of diagnosis. Immunohistochemistry gradings for 5 biomarkers (CD44, ABCC4, ABCC11, N-Cadherin and pan-Ca...

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Autores principales: Attuluri, Arun Kumar, Serkad, Chandra Prakash V., Gunda, Aparna, Ramkumar, Charusheila, Basavaraj, Chetana, Buturovic, Ljubomir, Madhav, Lekshmi, Naidu, Nirupama, Krishnamurthy, Naveen, Prathima, R., Kanaldekar, Suchita, Bakre, Manjiri M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425559/
https://www.ncbi.nlm.nih.gov/pubmed/30894144
http://dx.doi.org/10.1186/s12885-019-5443-5
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author Attuluri, Arun Kumar
Serkad, Chandra Prakash V.
Gunda, Aparna
Ramkumar, Charusheila
Basavaraj, Chetana
Buturovic, Ljubomir
Madhav, Lekshmi
Naidu, Nirupama
Krishnamurthy, Naveen
Prathima, R.
Kanaldekar, Suchita
Bakre, Manjiri M.
author_facet Attuluri, Arun Kumar
Serkad, Chandra Prakash V.
Gunda, Aparna
Ramkumar, Charusheila
Basavaraj, Chetana
Buturovic, Ljubomir
Madhav, Lekshmi
Naidu, Nirupama
Krishnamurthy, Naveen
Prathima, R.
Kanaldekar, Suchita
Bakre, Manjiri M.
author_sort Attuluri, Arun Kumar
collection PubMed
description BACKGROUND: CanAssist-Breast is an immunohistochemistry based test that predicts risk of distant recurrence in early-stage hormone receptor positive breast cancer patients within first five years of diagnosis. Immunohistochemistry gradings for 5 biomarkers (CD44, ABCC4, ABCC11, N-Cadherin and pan-Cadherins) and 3 clinical parameters (tumor size, tumor grade and node status) of 298 patient cohort were used to develop a machine learning based statistical algorithm. The algorithm generates a risk score based on which patients are stratified into two groups, low- or high-risk for recurrence. The aim of the current study is to demonstrate the analytical performance with respect to repeatability and reproducibility of CanAssist-Breast. METHODS: All potential sources of variation in CanAssist-Breast testing involving operator, run and observer that could affect the immunohistochemistry performance were tested using appropriate statistical analysis methods for each of the CanAssist-Breast biomarkers using a total 309 samples. The cumulative effect of these variations in the immunohistochemistry gradings on the generation of CanAssist-Breast risk score and risk category were also evaluated. Intra-class Correlation Coefficient, Bland Altman plots and pair-wise agreement were performed to establish concordance on IHC gradings, risk score and risk categorization respectively. RESULTS: CanAssist-Breast test exhibited high levels of concordance on immunohistochemistry gradings for all biomarkers with Intra-class Correlation Coefficient of ≥0.75 across all reproducibility and repeatability experiments. Bland-Altman plots demonstrated that agreement on risk scores between the comparators was within acceptable limits. We also observed > 90% agreement on risk categorization (low- or high-risk) across all variables tested. CONCLUSIONS: The extensive analytical validation data for the CanAssist-Breast test, evaluating immunohistochemistry performance, risk score generation and risk categorization showed excellent agreement across variables, demonstrating that the test is robust. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-019-5443-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-64255592019-03-29 Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients Attuluri, Arun Kumar Serkad, Chandra Prakash V. Gunda, Aparna Ramkumar, Charusheila Basavaraj, Chetana Buturovic, Ljubomir Madhav, Lekshmi Naidu, Nirupama Krishnamurthy, Naveen Prathima, R. Kanaldekar, Suchita Bakre, Manjiri M. BMC Cancer Research Article BACKGROUND: CanAssist-Breast is an immunohistochemistry based test that predicts risk of distant recurrence in early-stage hormone receptor positive breast cancer patients within first five years of diagnosis. Immunohistochemistry gradings for 5 biomarkers (CD44, ABCC4, ABCC11, N-Cadherin and pan-Cadherins) and 3 clinical parameters (tumor size, tumor grade and node status) of 298 patient cohort were used to develop a machine learning based statistical algorithm. The algorithm generates a risk score based on which patients are stratified into two groups, low- or high-risk for recurrence. The aim of the current study is to demonstrate the analytical performance with respect to repeatability and reproducibility of CanAssist-Breast. METHODS: All potential sources of variation in CanAssist-Breast testing involving operator, run and observer that could affect the immunohistochemistry performance were tested using appropriate statistical analysis methods for each of the CanAssist-Breast biomarkers using a total 309 samples. The cumulative effect of these variations in the immunohistochemistry gradings on the generation of CanAssist-Breast risk score and risk category were also evaluated. Intra-class Correlation Coefficient, Bland Altman plots and pair-wise agreement were performed to establish concordance on IHC gradings, risk score and risk categorization respectively. RESULTS: CanAssist-Breast test exhibited high levels of concordance on immunohistochemistry gradings for all biomarkers with Intra-class Correlation Coefficient of ≥0.75 across all reproducibility and repeatability experiments. Bland-Altman plots demonstrated that agreement on risk scores between the comparators was within acceptable limits. We also observed > 90% agreement on risk categorization (low- or high-risk) across all variables tested. CONCLUSIONS: The extensive analytical validation data for the CanAssist-Breast test, evaluating immunohistochemistry performance, risk score generation and risk categorization showed excellent agreement across variables, demonstrating that the test is robust. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-019-5443-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-20 /pmc/articles/PMC6425559/ /pubmed/30894144 http://dx.doi.org/10.1186/s12885-019-5443-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Attuluri, Arun Kumar
Serkad, Chandra Prakash V.
Gunda, Aparna
Ramkumar, Charusheila
Basavaraj, Chetana
Buturovic, Ljubomir
Madhav, Lekshmi
Naidu, Nirupama
Krishnamurthy, Naveen
Prathima, R.
Kanaldekar, Suchita
Bakre, Manjiri M.
Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients
title Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients
title_full Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients
title_fullStr Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients
title_full_unstemmed Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients
title_short Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients
title_sort analytical validation of canassist-breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425559/
https://www.ncbi.nlm.nih.gov/pubmed/30894144
http://dx.doi.org/10.1186/s12885-019-5443-5
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