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Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques

OBJECTIVE: Determine the interchangeability of various methods utilized for counting colonies in clonogenic assays. METHODS: Clonogenic assays of 2 head and neck cancer cell lines were counted through 4 different counting modalities: Manual counting pen, via microscope, 1 publicly available automate...

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Autores principales: Buryska, Seth, Arji, Sanjana, Wuertz, Beverly, Ondrey, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668582/
https://www.ncbi.nlm.nih.gov/pubmed/37997353
http://dx.doi.org/10.1177/15330338231214250
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author Buryska, Seth
Arji, Sanjana
Wuertz, Beverly
Ondrey, Frank
author_facet Buryska, Seth
Arji, Sanjana
Wuertz, Beverly
Ondrey, Frank
author_sort Buryska, Seth
collection PubMed
description OBJECTIVE: Determine the interchangeability of various methods utilized for counting colonies in clonogenic assays. METHODS: Clonogenic assays of 2 head and neck cancer cell lines were counted through 4 different counting modalities: Manual counting pen, via microscope, 1 publicly available automated algorithm, and a semiautomated algorithm presented by the authors. Each method counted individual wells (N = 24). Pen and microscopic counts were performed by 2 observers. Parameters included both low-growth (<150 colonies/well) and high-growth (>150 colonies/well) cell lines. Correlational and Bland–Altman analyses were performed using SPSS software. RESULTS: Interobserver manual pen count correlation R(2) value in both growth conditions was 0.902; controlling for only low-growth conditions decreased R(2) to 0.660. Correlation of microscopic versus pen counts R(2) values for observers 1 and 2 were 0.955 and 0.775, respectively. Comparing techniques, Bland–Altman revealed potential bias with respect to the magnitude of measurement (P < .001) for both observers. Correlation of microscopic counts for both interobserver (R(2 )= 0.902) and intraobserver (R(2 )= 0.916) were analyzed. Bland–Altman revealed no bias (P = .489). Automated versus microscopic counts revealed no bias between methodologies (P = .787) and a lower correlation coefficient (R(2 )= 0.384). Semiautomated versus microscopic counts revealed no bias with respect to magnitude of measurement for either observer (P = .327, .229); Pearson correlation was 0.985 (R(2 )= 0.970) and 0.965 (R(2 )= 0.931) for observer 1 and 2. Semiautomated versus manual pen colony counts revealed a significant bias with respect to magnitude of measurement (P < .001). CONCLUSION: Counting with a manual pen demonstrated significant bias when compared to microscopic and semiautomated colony counts; 2 methods were deemed to be interchangeable. Thus, training algorithms based on manual counts may introduce this bias as well. Algorithms trained to select colonies based on size (pixels(2)) and shape (circularity) should be prioritized. Solely relying on Bland–Altman or correlational analyses when determining method interchangeability should be avoided; they rather should be used in conjunction.
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spelling pubmed-106685822023-11-23 Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques Buryska, Seth Arji, Sanjana Wuertz, Beverly Ondrey, Frank Technol Cancer Res Treat Original Research Article OBJECTIVE: Determine the interchangeability of various methods utilized for counting colonies in clonogenic assays. METHODS: Clonogenic assays of 2 head and neck cancer cell lines were counted through 4 different counting modalities: Manual counting pen, via microscope, 1 publicly available automated algorithm, and a semiautomated algorithm presented by the authors. Each method counted individual wells (N = 24). Pen and microscopic counts were performed by 2 observers. Parameters included both low-growth (<150 colonies/well) and high-growth (>150 colonies/well) cell lines. Correlational and Bland–Altman analyses were performed using SPSS software. RESULTS: Interobserver manual pen count correlation R(2) value in both growth conditions was 0.902; controlling for only low-growth conditions decreased R(2) to 0.660. Correlation of microscopic versus pen counts R(2) values for observers 1 and 2 were 0.955 and 0.775, respectively. Comparing techniques, Bland–Altman revealed potential bias with respect to the magnitude of measurement (P < .001) for both observers. Correlation of microscopic counts for both interobserver (R(2 )= 0.902) and intraobserver (R(2 )= 0.916) were analyzed. Bland–Altman revealed no bias (P = .489). Automated versus microscopic counts revealed no bias between methodologies (P = .787) and a lower correlation coefficient (R(2 )= 0.384). Semiautomated versus microscopic counts revealed no bias with respect to magnitude of measurement for either observer (P = .327, .229); Pearson correlation was 0.985 (R(2 )= 0.970) and 0.965 (R(2 )= 0.931) for observer 1 and 2. Semiautomated versus manual pen colony counts revealed a significant bias with respect to magnitude of measurement (P < .001). CONCLUSION: Counting with a manual pen demonstrated significant bias when compared to microscopic and semiautomated colony counts; 2 methods were deemed to be interchangeable. Thus, training algorithms based on manual counts may introduce this bias as well. Algorithms trained to select colonies based on size (pixels(2)) and shape (circularity) should be prioritized. Solely relying on Bland–Altman or correlational analyses when determining method interchangeability should be avoided; they rather should be used in conjunction. SAGE Publications 2023-11-23 /pmc/articles/PMC10668582/ /pubmed/37997353 http://dx.doi.org/10.1177/15330338231214250 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research Article
Buryska, Seth
Arji, Sanjana
Wuertz, Beverly
Ondrey, Frank
Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques
title Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques
title_full Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques
title_fullStr Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques
title_full_unstemmed Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques
title_short Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques
title_sort using bland–altman analysis to identify appropriate clonogenic assay colony counting techniques
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668582/
https://www.ncbi.nlm.nih.gov/pubmed/37997353
http://dx.doi.org/10.1177/15330338231214250
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