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 automated...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2023-11-01
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| Series: | Technology in Cancer Research & Treatment |
| Online Access: | https://doi.org/10.1177/15330338231214250 |
| _version_ | 1797454317889781760 |
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| author | Seth Buryska BS Sanjana Arji BS Beverly Wuertz BA Frank Ondrey MD, PhD |
| author_facet | Seth Buryska BS Sanjana Arji BS Beverly Wuertz BA Frank Ondrey MD, PhD |
| author_sort | Seth Buryska BS |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T15:35:33Z |
| format | Article |
| id | doaj.art-e8cc99ce4fd74456a508dd1078800fb9 |
| institution | Directory Open Access Journal |
| issn | 1533-0338 |
| language | English |
| last_indexed | 2024-03-09T15:35:33Z |
| publishDate | 2023-11-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Technology in Cancer Research & Treatment |
| spelling | doaj.art-e8cc99ce4fd74456a508dd1078800fb92023-11-26T08:33:19ZengSAGE PublishingTechnology in Cancer Research & Treatment1533-03382023-11-012210.1177/15330338231214250Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting TechniquesSeth Buryska BSSanjana Arji BSBeverly Wuertz BAFrank Ondrey MD, PhDObjective 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.https://doi.org/10.1177/15330338231214250 |
| spellingShingle | Seth Buryska BS Sanjana Arji BS Beverly Wuertz BA Frank Ondrey MD, PhD Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques Technology in Cancer Research & Treatment |
| 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 |
| url | https://doi.org/10.1177/15330338231214250 |
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