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Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology
While several resources exist that interpret therapeutic significance of genomic alterations in cancer, many regional real-world issues limit access to drugs. There is a need for a pragmatic, evidence-based, context-adapted tool to guide clinical management based on molecular biomarkers. To this end...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222322/ https://www.ncbi.nlm.nih.gov/pubmed/34162978 http://dx.doi.org/10.1038/s41698-021-00194-z |
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author | Lin, Frank P. Thavaneswaran, Subotheni Grady, John P. Ballinger, Mandy Kansara, Maya Oakes, Samantha R. Desai, Jayesh Lee, Chee Khoon Simes, John Thomas, David M. |
author_facet | Lin, Frank P. Thavaneswaran, Subotheni Grady, John P. Ballinger, Mandy Kansara, Maya Oakes, Samantha R. Desai, Jayesh Lee, Chee Khoon Simes, John Thomas, David M. |
author_sort | Lin, Frank P. |
collection | PubMed |
description | While several resources exist that interpret therapeutic significance of genomic alterations in cancer, many regional real-world issues limit access to drugs. There is a need for a pragmatic, evidence-based, context-adapted tool to guide clinical management based on molecular biomarkers. To this end, we have structured a compendium of approved and experimental therapies with associated biomarkers following a survey of drug regulatory databases, existing knowledge bases, and published literature. Each biomarker-disease-therapy triplet was categorised using a tiering system reflective of key therapeutic considerations: approved and reimbursed therapies with respect to a jurisdiction (Tier 1), evidence of efficacy or approval in another jurisdiction (Tier 2), evidence of antitumour activity (Tier 3), and plausible biological rationale (Tier 4). Two resistance categories were defined: lack of efficacy (Tier R1) or antitumor activity (Tier R2). Based on this framework, we curated a digital resource focused on drugs relevant in the Australian healthcare system (TOPOGRAPH: Therapy Oriented Precision Oncology Guidelines for Recommending Anticancer Pharmaceuticals). As of November 2020, TOPOGRAPH comprised 2810 biomarker-disease-therapy triplets in 989 expert-appraised entries, including 373 therapies, 199 biomarkers, and 106 cancer types. In the 345 therapies catalogued, 84 (24%) and 65 (19%) were designated Tiers 1 and 2, respectively, while 271 (79%) therapies were supported by preclinical studies, early clinical trials, retrospective studies, or case series (Tiers 3 and 4). A companion algorithm was also developed to support rational, context-appropriate treatment selection informed by molecular biomarkers. This framework can be readily adapted to build similar resources in other jurisdictions to support therapeutic decision-making. |
format | Online Article Text |
id | pubmed-8222322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82223222021-07-09 Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology Lin, Frank P. Thavaneswaran, Subotheni Grady, John P. Ballinger, Mandy Kansara, Maya Oakes, Samantha R. Desai, Jayesh Lee, Chee Khoon Simes, John Thomas, David M. NPJ Precis Oncol Article While several resources exist that interpret therapeutic significance of genomic alterations in cancer, many regional real-world issues limit access to drugs. There is a need for a pragmatic, evidence-based, context-adapted tool to guide clinical management based on molecular biomarkers. To this end, we have structured a compendium of approved and experimental therapies with associated biomarkers following a survey of drug regulatory databases, existing knowledge bases, and published literature. Each biomarker-disease-therapy triplet was categorised using a tiering system reflective of key therapeutic considerations: approved and reimbursed therapies with respect to a jurisdiction (Tier 1), evidence of efficacy or approval in another jurisdiction (Tier 2), evidence of antitumour activity (Tier 3), and plausible biological rationale (Tier 4). Two resistance categories were defined: lack of efficacy (Tier R1) or antitumor activity (Tier R2). Based on this framework, we curated a digital resource focused on drugs relevant in the Australian healthcare system (TOPOGRAPH: Therapy Oriented Precision Oncology Guidelines for Recommending Anticancer Pharmaceuticals). As of November 2020, TOPOGRAPH comprised 2810 biomarker-disease-therapy triplets in 989 expert-appraised entries, including 373 therapies, 199 biomarkers, and 106 cancer types. In the 345 therapies catalogued, 84 (24%) and 65 (19%) were designated Tiers 1 and 2, respectively, while 271 (79%) therapies were supported by preclinical studies, early clinical trials, retrospective studies, or case series (Tiers 3 and 4). A companion algorithm was also developed to support rational, context-appropriate treatment selection informed by molecular biomarkers. This framework can be readily adapted to build similar resources in other jurisdictions to support therapeutic decision-making. Nature Publishing Group UK 2021-06-23 /pmc/articles/PMC8222322/ /pubmed/34162978 http://dx.doi.org/10.1038/s41698-021-00194-z Text en © Crown 2021 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lin, Frank P. Thavaneswaran, Subotheni Grady, John P. Ballinger, Mandy Kansara, Maya Oakes, Samantha R. Desai, Jayesh Lee, Chee Khoon Simes, John Thomas, David M. Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology |
title | Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology |
title_full | Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology |
title_fullStr | Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology |
title_full_unstemmed | Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology |
title_short | Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology |
title_sort | criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222322/ https://www.ncbi.nlm.nih.gov/pubmed/34162978 http://dx.doi.org/10.1038/s41698-021-00194-z |
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