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The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa

BACKGROUND: MammaPrint (MP) has been applied in South Africa (SA) for decision-making in early-stage hormone receptor-positive breast cancer since 2006. The cost-impact of MP in SA has not been assessed. AIM: To assess different MP testing strategies for cost-minimization in early-stage breast carci...

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Autores principales: Myburgh, Ettienne J., de Jager, Josephus J., Murray, Elizabeth, Grant, Kathleen A., Kotze, Maritha J., de Klerk, Hermanus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8259301/
https://www.ncbi.nlm.nih.gov/pubmed/34217105
http://dx.doi.org/10.1016/j.breast.2021.05.010
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author Myburgh, Ettienne J.
de Jager, Josephus J.
Murray, Elizabeth
Grant, Kathleen A.
Kotze, Maritha J.
de Klerk, Hermanus
author_facet Myburgh, Ettienne J.
de Jager, Josephus J.
Murray, Elizabeth
Grant, Kathleen A.
Kotze, Maritha J.
de Klerk, Hermanus
author_sort Myburgh, Ettienne J.
collection PubMed
description BACKGROUND: MammaPrint (MP) has been applied in South Africa (SA) for decision-making in early-stage hormone receptor-positive breast cancer since 2006. The cost-impact of MP in SA has not been assessed. AIM: To assess different MP testing strategies for cost-minimization in early-stage breast carcinoma using a funder perspective. METHODS: Clinico-pathologic information was extracted from a prospectively collected database. Clinical risk stratification was done using Adjuvant Online! (AOL) and the Predict V2.1 algorithm (www.predict.nhs.uk). An unselected MP testing strategy was compared to a selective strategy, testing only clinically high risk (cHigh) patients. Excluding human epidermal growth factor receptor-2 positive tumours, the costs for chemotherapy treatment and MP using funding data were used to evaluate the financial impact of these strategies. RESULTS: In 583 patients with 601 tumours, 52% were clinically low risk (cLow) (AOL) while the average Predict 10-year survival with chemotherapy was 2.9%. MP correlated strongly with Predict and 318 (60%) patients were MP low risk. Unselective testing allowed omission of chemotherapy in 44 (8.4%) patients but escalated cost by 57.7%. Using a selective testing strategy, only 251 would be tested, de-escalating treatment in 138 (55%) and reducing cost by 19.5%. Considering a Predict value up to 3.2% as cHigh, cost would be up to 7.3% (p = 0.0467) lower with a selective testing strategy. CONCLUSION: MP allowed reduction in the use of adjuvant chemotherapy. Unselective use of MP increases overall costs. A selective testing strategy through clinical risk stratification using AOL/Predict results in substantial cost saving.
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spelling pubmed-82593012021-07-12 The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa Myburgh, Ettienne J. de Jager, Josephus J. Murray, Elizabeth Grant, Kathleen A. Kotze, Maritha J. de Klerk, Hermanus Breast Original Article BACKGROUND: MammaPrint (MP) has been applied in South Africa (SA) for decision-making in early-stage hormone receptor-positive breast cancer since 2006. The cost-impact of MP in SA has not been assessed. AIM: To assess different MP testing strategies for cost-minimization in early-stage breast carcinoma using a funder perspective. METHODS: Clinico-pathologic information was extracted from a prospectively collected database. Clinical risk stratification was done using Adjuvant Online! (AOL) and the Predict V2.1 algorithm (www.predict.nhs.uk). An unselected MP testing strategy was compared to a selective strategy, testing only clinically high risk (cHigh) patients. Excluding human epidermal growth factor receptor-2 positive tumours, the costs for chemotherapy treatment and MP using funding data were used to evaluate the financial impact of these strategies. RESULTS: In 583 patients with 601 tumours, 52% were clinically low risk (cLow) (AOL) while the average Predict 10-year survival with chemotherapy was 2.9%. MP correlated strongly with Predict and 318 (60%) patients were MP low risk. Unselective testing allowed omission of chemotherapy in 44 (8.4%) patients but escalated cost by 57.7%. Using a selective testing strategy, only 251 would be tested, de-escalating treatment in 138 (55%) and reducing cost by 19.5%. Considering a Predict value up to 3.2% as cHigh, cost would be up to 7.3% (p = 0.0467) lower with a selective testing strategy. CONCLUSION: MP allowed reduction in the use of adjuvant chemotherapy. Unselective use of MP increases overall costs. A selective testing strategy through clinical risk stratification using AOL/Predict results in substantial cost saving. Elsevier 2021-06-01 /pmc/articles/PMC8259301/ /pubmed/34217105 http://dx.doi.org/10.1016/j.breast.2021.05.010 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Myburgh, Ettienne J.
de Jager, Josephus J.
Murray, Elizabeth
Grant, Kathleen A.
Kotze, Maritha J.
de Klerk, Hermanus
The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa
title The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa
title_full The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa
title_fullStr The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa
title_full_unstemmed The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa
title_short The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa
title_sort cost impact of unselective vs selective mammaprint testing in early-stage breast cancer in southern africa
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8259301/
https://www.ncbi.nlm.nih.gov/pubmed/34217105
http://dx.doi.org/10.1016/j.breast.2021.05.010
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