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. 2022 Dec 26:14:17588359221141760.
doi: 10.1177/17588359221141760. eCollection 2022.

Cost-effectiveness analysis of Oncotype DX from a Brazilian private medicine perspective: a GBECAM multicenter retrospective study

Leandro Jonata Carvalho Oliveira  1   2 , Thais Baccili Cury Megid  3 , Daniela Dornelles Rosa  2   4 , Carlos Alberto da Silva Magliano  5 , Daniele Xavier Assad  2   6 , Daniel Fontes Argolo  2   7 , Solange Moraes Sanches  8   9 , Laura Testa  2   10   11 , José Bines  2   12   11 , Rafael Kaliks  2   13 , Maira Caleffi  4 , Debora de Melo Gagliato  2   14 , Marina Sahade  3 , Romualdo Barroso-Sousa  2   6 , Tatiana Strava Corrêa  6 , Andrea Kazumi Shimada  3   2 , Daniel Negrini Batista  10   11 , Daniel Musse Gomes  12   11 , Marcelle Goldner Cesca  15 , Débora Gaudêncio  7 , Larissa Matos Almeida Moura  7 , Julio Antonio Pereira de Araújo  14 , Artur Katz  3 , Max Senna Mano  3   2
Affiliations

Cost-effectiveness analysis of Oncotype DX from a Brazilian private medicine perspective: a GBECAM multicenter retrospective study

Leandro Jonata Carvalho Oliveira et al. Ther Adv Med Oncol. .

Abstract

Background: Oncotype DX (ODX) is a validated assay for the prediction of risk of recurrence and benefit of chemotherapy (CT) in both node negative (N0) and 1-3 positive nodes (N1), hormone receptor positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) early breast cancer (eBC). Due to limited access to genomic assays in Brazil, treatment decisions remain largely driven by traditional clinicopathologic risk factors. ODX has been reported to be cost-effective in different health system, but limited data are available considering the reality of middle-income countries such as Brazil. We aim to evaluate the cost-effectiveness of ODX across strata of clinical risk groups using data from a dataset of patients from Brazilian institutions.

Methods: Clinicopathologic and ODX information were analyzed for patients with T1-T3, N0-N1, HR+/HER2- eBC who had an ODX performed between 2005 and 2020. Projections of CT indication by clinicopathologic criteria were based on binary clinical risk categorization based on the Adjuvant! Algorithm. The ODX score was correlated with the indication of CT according to TAILORx and RxPONDER data. Two decision-tree models were developed. In the first model, low and high clinical risk patients were included while in the second, only high clinical risk patients were included. The cost for ODX and CT was based on the Brazilian private medicine perspective.

Results: In all, 645 patients were analyzed; 411 patients (63.7%) had low clinical risk and 234 patients (36.3%) had high clinical risk disease. The ODX indicated low (<11), intermediate (11-25), and high (>25) risk in 119 (18.4%), 415 (64.3%), and 111 (17.2%) patients, respectively. Among 645 patients analyzed in the first model, ODX was effective (5.6% reduction in CT indication) though with an incremental cost of United States Dollar (US$) 2288.87 per patient. Among 234 patients analyzed in the second model (high clinical risk only), ODX led to a 57.7% reduction in CT indication and reduced costs by US$ 4350.66 per patient.

Conclusions: Our study suggests that ODX is cost-saving for patients with high clinical risk HR+/HER2- eBC and cost-attractive for the overall population in the Brazilian private medicine perspective. Its incorporation into routine practice should be strongly considered by healthcare providers.

Keywords: Oncotype DX; cost-effectiveness analysis; early breast cancer; gene expression signatures; hormone receptor positive breast cancer.

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Conflict of interest statement

• Dr Oliveira has no conflicts of interest to report. • Dr Megid has no conflicts of interest to report. • Dr Mano has provided compensated consultancy services and lectures for Roche, MSD, Astra Zeneca, Novartis, Lilly-Inclone, DASA (including one for Endopredict), Fleury, Daiichi-Sankyo, Oncologia Brasil, Onconews, Instituto Oncoclínicas, and Pfizer. • Dr Magliano has no conflicts of interest to report. • Dr Sanches has provided compensated consultancy services and lectures for MSD, Astra Zeneca, Novartis, Lilly-Inclone, Daiichi-Sankyo, and Amgen. • Dr Kaliks has provided compensated consultancy services and lectures for Daiichi Sankio, Astra Zeneca, Roche, Pfizer, Fleury, BMS, and Novartis. • Dr Caleffi has provided compensated consultancy services and lectures for Novartis, Roche, Astra Zeneca, Daishii Sankyo, and Lilly. • Dr Assad has provided compensated consultancy services and lectures for Roche, MSD, Astra Zeneca, and Novartis. • Dr Correa TS has provided lectures for Libbs, Daiichi Sankio, Astra Zeneca, Pfizer, Novartis, and Lilly-Inclone. • Dr Gagliato has provided compensated consultancy services and lectures for Roche, MSD, Astra Zeneca, Novartis, Lilly, Fleury, Daiichi-Sankyo, Oncologia Brasil, Zodiac, Pfizer, Novartis, and Manual de Oncologia Clinica do Brasil. • Dr R.BS reported receiving speaker bureau fees from Agilent, AstraZeneca, Daichi-Sankyo, Eli Lilly, Pfizer, Novartis, MSD, and Roche. He has also served as a consultant/advisor for AstraZeneca, Daichi-Sankyo, Eli Lilly, Libbs, Pfizer, Roche, MSD and has received support for attending medical conferences from Astrazeneca, Roche, Eli Lilly, Daichi-Sankyo, and MSD. • Dr Testa has provided compensated consultancy services and lectures for Novartis, Roche, Pfizer, Zodiac, Lilly, MSD, Daichii-Sankyo, and AstraZeneca. She has received educational support from Pfizer, Libbs, United Medical, Lilly, Zodiac, AstraZeneca and has an institutional grant from Novartis. • Dr Bines has provided compensated consultancy services and lectures for Astra Zeneca, Daiichi-Sankyo, Gilead, Lilly, MSD, Novartis, Pfizer, Roche, and Sanofi. • Dr Daniela has provided compensated consultancy for Roche, Novartis, AstraZeneca, Lilly, GSK, Sanofi, Libbs, Eisai, Pfizer, Dr Reddy’s, United Medical, Daiichi Sankyo. She has received research funding from Amgen, Roche, GSK, L’Òreal. She has served as expert testimony for: Roche, Novartis, Pfizer, AstraZeneca, Lilly, Teva. • Dr Shimada has provided compensated consultancy for AstraZeneca, Daichii-Sankyo, Novartis, Pfizer, MSD, Lilly, Janssen, Zodiac, Grünenthal, Amgen e Roche. She has received research funding from AstraZeneca, Lilly, Novartis, Roche, MSD, Pfizer. She has received educational support from Lilly, Novartis, Roche, Fleury, Daiichi-Sankyo, Pfizer. • Dr Sahade has provided compensated consultancy services and lectures for MSD, AstraZeneca, Novartis, Daiichi-Sankyo, Oncologia Brasil and Pfizer. • Dr Argolo has provided compensated consultancy services and lectures for Novartis, Pfizer, Amgen, Roche, Libbs, AstraZeneca, Daiichi-Sankyo, Fleury and Instituto Oncoclínicas. • Dr Batista has no conflicts of interest to report. • Dr. Musse has no conflicts of interest to report. • Dr Cesca has no conflicts of interest to report. • Dr Gaudencio has no conflicts of interest to report. • Dr Araujo has no conflicts of interest to report. • Dr Moura has no conflicts of interest to report. • Dr Katz has no conflicts of interest to report.

Figures

Figure 1.
Figure 1.
Decision tree in the overall population.
Figure 2.
Figure 2.
Tornado diagram summarizing changes in the ICER of genomic stratification (ODX) versus clinical stratification strategies for overall population. ICER, incremental cost-effectiveness ratio; ODX, Oncotype DX
Figure 3.
Figure 3.
ICER scatterplot per CT spared in the overall population. ICER, incremental cost-effectiveness ratio; CT, chemotherapy.
Figure 4.
Figure 4.
Cost-effectiveness acceptability curve in the overall population.
Figure 5.
Figure 5.
Decision tree in high clinical risk population.
Figure 6.
Figure 6.
Tornado diagram summarizing changes in the ICER of genomic stratification (ODX) versus clinical stratification strategies for high clinical risk population. ICER, incremental cost-effectiveness ratio; ODX, Oncotype DX.
Figure 7.
Figure 7.
ICER scatterplot per CT spared in the high clinical risk population. ICER, incremental cost-effectiveness ratio; CT, chemotherapy.
See this image and copyright information in PMC

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