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The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development
BACKGROUND: An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promisin...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552368/ https://www.ncbi.nlm.nih.gov/pubmed/37794461 http://dx.doi.org/10.1186/s12916-023-03075-3 |
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author | Savva, Katerina-Vanessa Kawka, Michal Vadhwana, Bhamini Penumaka, Rahul Patton, Imogen Khan, Komal Perrott, Claire Das, Saranya Giot, Maxime Mavroveli, Stella Hanna, George B. Ni, Melody Zhifang Peters, Christopher J. |
author_facet | Savva, Katerina-Vanessa Kawka, Michal Vadhwana, Bhamini Penumaka, Rahul Patton, Imogen Khan, Komal Perrott, Claire Das, Saranya Giot, Maxime Mavroveli, Stella Hanna, George B. Ni, Melody Zhifang Peters, Christopher J. |
author_sort | Savva, Katerina-Vanessa |
collection | PubMed |
description | BACKGROUND: An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promising biomarkers and promote successful biomarker translation. METHODS: All features associated with a clinically useful biomarker were identified using mixed-methodology, including systematic literature search, semi-structured interviews, and an online two-stage Delphi-Survey. Validation of the checklist was achieved by independent systematic literature searches using keywords/subheadings related to clinically and non-clinically utilised breast and colorectal cancer biomarkers. Composite aggregated scores were generated for each selected publication based on the presence/absence of an attribute listed in the Biomarker Toolkit checklist. RESULTS: Systematic literature search identified 129 attributes associated with a clinically useful biomarker. These were grouped in four main categories including: rationale, clinical utility, analytical validity, and clinical validity. This checklist was subsequently developed using semi-structured interviews with biomarker experts (n=34); and 88.23% agreement was achieved regarding the identified attributes, via the Delphi survey (consensus level:75%, n=51). Quantitative validation was completed using clinically and non-clinically implemented breast and colorectal cancer biomarkers. Cox-regression analysis suggested that total score is a significant driver of biomarker success in both cancer types (BC: p>0.0001, 95.0% CI: 0.869–0.935, CRC: p>0.0001, 95.0% CI: 0.918–0.954). CONCLUSIONS: This novel study generated a validated checklist with literature-reported attributes linked with successful biomarker implementation. Ultimately, the application of this toolkit can be used to detect biomarkers with the highest clinical potential and shape how biomarker studies are designed/performed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-03075-3. |
format | Online Article Text |
id | pubmed-10552368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105523682023-10-06 The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development Savva, Katerina-Vanessa Kawka, Michal Vadhwana, Bhamini Penumaka, Rahul Patton, Imogen Khan, Komal Perrott, Claire Das, Saranya Giot, Maxime Mavroveli, Stella Hanna, George B. Ni, Melody Zhifang Peters, Christopher J. BMC Med Research Article BACKGROUND: An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promising biomarkers and promote successful biomarker translation. METHODS: All features associated with a clinically useful biomarker were identified using mixed-methodology, including systematic literature search, semi-structured interviews, and an online two-stage Delphi-Survey. Validation of the checklist was achieved by independent systematic literature searches using keywords/subheadings related to clinically and non-clinically utilised breast and colorectal cancer biomarkers. Composite aggregated scores were generated for each selected publication based on the presence/absence of an attribute listed in the Biomarker Toolkit checklist. RESULTS: Systematic literature search identified 129 attributes associated with a clinically useful biomarker. These were grouped in four main categories including: rationale, clinical utility, analytical validity, and clinical validity. This checklist was subsequently developed using semi-structured interviews with biomarker experts (n=34); and 88.23% agreement was achieved regarding the identified attributes, via the Delphi survey (consensus level:75%, n=51). Quantitative validation was completed using clinically and non-clinically implemented breast and colorectal cancer biomarkers. Cox-regression analysis suggested that total score is a significant driver of biomarker success in both cancer types (BC: p>0.0001, 95.0% CI: 0.869–0.935, CRC: p>0.0001, 95.0% CI: 0.918–0.954). CONCLUSIONS: This novel study generated a validated checklist with literature-reported attributes linked with successful biomarker implementation. Ultimately, the application of this toolkit can be used to detect biomarkers with the highest clinical potential and shape how biomarker studies are designed/performed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-03075-3. BioMed Central 2023-10-04 /pmc/articles/PMC10552368/ /pubmed/37794461 http://dx.doi.org/10.1186/s12916-023-03075-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Savva, Katerina-Vanessa Kawka, Michal Vadhwana, Bhamini Penumaka, Rahul Patton, Imogen Khan, Komal Perrott, Claire Das, Saranya Giot, Maxime Mavroveli, Stella Hanna, George B. Ni, Melody Zhifang Peters, Christopher J. The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development |
title | The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development |
title_full | The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development |
title_fullStr | The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development |
title_full_unstemmed | The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development |
title_short | The Biomarker Toolkit — an evidence-based guideline to predict cancer biomarker success and guide development |
title_sort | biomarker toolkit — an evidence-based guideline to predict cancer biomarker success and guide development |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552368/ https://www.ncbi.nlm.nih.gov/pubmed/37794461 http://dx.doi.org/10.1186/s12916-023-03075-3 |
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