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Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions
There is a need for industry-independent decision tools that integrate clinicopathologic features, comorbidities, and genomic information for women with node-negative, invasive, hormone receptor–positive, human epidermal growth factor receptor-2–negative (early-stage) breast cancer. METHODS: We adap...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425835/ https://www.ncbi.nlm.nih.gov/pubmed/34251881 http://dx.doi.org/10.1200/JCO.21.00651 |
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author | Jayasekera, Jinani Sparano, Joseph A. O'Neill, Suzanne Chandler, Young Isaacs, Claudine Kurian, Allison W. Kushi, Lawrence Schechter, Clyde B. Mandelblatt, Jeanne |
author_facet | Jayasekera, Jinani Sparano, Joseph A. O'Neill, Suzanne Chandler, Young Isaacs, Claudine Kurian, Allison W. Kushi, Lawrence Schechter, Clyde B. Mandelblatt, Jeanne |
author_sort | Jayasekera, Jinani |
collection | PubMed |
description | There is a need for industry-independent decision tools that integrate clinicopathologic features, comorbidities, and genomic information for women with node-negative, invasive, hormone receptor–positive, human epidermal growth factor receptor-2–negative (early-stage) breast cancer. METHODS: We adapted an extant Cancer Intervention and Surveillance Modeling Network simulation model to estimate the 10-year risk of distant recurrence, breast cancer–specific mortality, other-cause mortality, and life-years gained with chemoendocrine versus endocrine therapy. We simulated outcomes for 1,512 unique patient subgroups based on all possible combinations of age, tumor size, grade, and comorbidity level; simulations were performed with and without 21-gene recurrence scores (RSs). Model inputs were derived from clinical trials, large US cohort studies, registry, and claims data. External validation was performed by comparing results to observed rates in two independent sources. We highlight results for one scenario where treatment choice may be uncertain. RESULTS: Chemoendocrine versus endocrine therapy in a 65-69-year-old woman with a small (≤ 2 cm), intermediate-grade tumor, and mild comorbidities provides a 1.3% absolute reduction in 10-year distant recurrence risk, with 0.23 life-years gained. With these tumor features, a woman like this will have a 28% probability of having an RS 16-20, 18% RS 21-25, and 11% RS 26+. If testing is done, and her RS is 16-20, chemoendocrine therapy reduces 10-year distant recurrence risk to 1%, with 0.20 life-years gained, a similar result as without testing. The absolute benefits would increase to 4.8%-5.5% if the RS was 26+. The model closely reproduced observed rates in both independent data sets. CONCLUSION: Our validated clinical decision tool is flexible, readily adaptable to include new therapies, and can support discussions about genomic testing and early breast cancer treatment. |
format | Online Article Text |
id | pubmed-8425835 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-84258352022-09-10 Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions Jayasekera, Jinani Sparano, Joseph A. O'Neill, Suzanne Chandler, Young Isaacs, Claudine Kurian, Allison W. Kushi, Lawrence Schechter, Clyde B. Mandelblatt, Jeanne J Clin Oncol ORIGINAL REPORTS There is a need for industry-independent decision tools that integrate clinicopathologic features, comorbidities, and genomic information for women with node-negative, invasive, hormone receptor–positive, human epidermal growth factor receptor-2–negative (early-stage) breast cancer. METHODS: We adapted an extant Cancer Intervention and Surveillance Modeling Network simulation model to estimate the 10-year risk of distant recurrence, breast cancer–specific mortality, other-cause mortality, and life-years gained with chemoendocrine versus endocrine therapy. We simulated outcomes for 1,512 unique patient subgroups based on all possible combinations of age, tumor size, grade, and comorbidity level; simulations were performed with and without 21-gene recurrence scores (RSs). Model inputs were derived from clinical trials, large US cohort studies, registry, and claims data. External validation was performed by comparing results to observed rates in two independent sources. We highlight results for one scenario where treatment choice may be uncertain. RESULTS: Chemoendocrine versus endocrine therapy in a 65-69-year-old woman with a small (≤ 2 cm), intermediate-grade tumor, and mild comorbidities provides a 1.3% absolute reduction in 10-year distant recurrence risk, with 0.23 life-years gained. With these tumor features, a woman like this will have a 28% probability of having an RS 16-20, 18% RS 21-25, and 11% RS 26+. If testing is done, and her RS is 16-20, chemoendocrine therapy reduces 10-year distant recurrence risk to 1%, with 0.20 life-years gained, a similar result as without testing. The absolute benefits would increase to 4.8%-5.5% if the RS was 26+. The model closely reproduced observed rates in both independent data sets. CONCLUSION: Our validated clinical decision tool is flexible, readily adaptable to include new therapies, and can support discussions about genomic testing and early breast cancer treatment. Wolters Kluwer Health 2021-09-10 2021-07-12 /pmc/articles/PMC8425835/ /pubmed/34251881 http://dx.doi.org/10.1200/JCO.21.00651 Text en © 2021 by American Society of Clinical Oncology https://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | ORIGINAL REPORTS Jayasekera, Jinani Sparano, Joseph A. O'Neill, Suzanne Chandler, Young Isaacs, Claudine Kurian, Allison W. Kushi, Lawrence Schechter, Clyde B. Mandelblatt, Jeanne Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions |
title | Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions |
title_full | Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions |
title_fullStr | Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions |
title_full_unstemmed | Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions |
title_short | Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions |
title_sort | development and validation of a simulation model–based clinical decision tool: identifying patients where 21-gene recurrence score testing may change decisions |
topic | ORIGINAL REPORTS |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425835/ https://www.ncbi.nlm.nih.gov/pubmed/34251881 http://dx.doi.org/10.1200/JCO.21.00651 |
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