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Comparative effectiveness and cost-effectiveness of cardioprotective glucose-lowering therapies for type 2 diabetes in Brazil: a Bayesian network model

Author

Listed:
  • Ana Claudia Cavalcante Nogueira

    (Unicamp Medical School
    Escola Superior de Ciências da Saúde (ESCS))

  • Joaquim Barreto

    (Unicamp Medical School)

  • Filipe A. Moura

    (Unicamp Medical School
    Brigham and Women’s Hospital, Harvard Medical School)

  • Beatriz Luchiari

    (Unicamp Medical School)

  • Abrão Abuhab

    (Heart Institute (InCor), Do Hospital das Clínicas - FMUSP)

  • Isabella Bonilha

    (Unicamp Medical School)

  • Wilson Nadruz

    (Unicamp Medical School)

  • J. Michael Gaziano

    (Harvard Medical School)

  • Thomas Gaziano

    (Department of Cardiovascular Medicine, Brigham & Women’s Hospital)

  • Luiz Sergio F. Carvalho

    (Unicamp Medical School
    Clarity Healthcare Intelligence)

  • Andrei C. Sposito

    (Unicamp Medical School
    State University of Campinas (Unicamp))

Abstract

Background The escalating prevalence of type 2 diabetes (T2DM) poses an unparalleled economic catastrophe to developing countries. Cardiovascular diseases remain the primary source of costs among individuals with T2DM, incurring expenses for medications, hospitalizations, and surgical interventions. Compelling evidence suggests that the risk of cardiovascular outcomes can be reduced by three classes of glucose-lowering therapies (GLT), including SGLT2i, GLP-1A, and pioglitazone. However, an evidence-based and cost-effective protocol is still unavailable for many countries. The objective of the current study is to compare the effectiveness and cost-effectiveness of GLT in individuals with T2DM in Brazil. Methods We employed Bayesian Networks to calculate the incremental cost-effectiveness ratios (ICER), expressed in international dollars (Int$) per disease-adjusted life years [DALYs] averted. To determine the effectiveness of GLT, we conducted a systematic review with network meta-analysis (NMA) to provide insights for our model. Additionally, we obtained cardiovascular outcome incidence data from two real-world cohorts comprising 851 and 1337 patients in primary and secondary prevention, respectively. Our cost analysis took into account the perspective of the Brazilian public health system, and all values were converted to Int$. Results In the NMA, SGLT2i [HR: 0.81 (95% CI 0.69–0.96)], GLP-1A [HR: 0.79 (95% CI 0.67–0.94)], and pioglitazone [HR: 0.73 (95% CI 0.59–0.91)] demonstrated reduced relative risks of non-fatal cardiovascular events. In the context of primary prevention, pioglitazone yielded 0.2339 DALYs averted, with an ICER of Int$7,082 (95% CI 4,521–10,770) per DALY averted when compared to standard care. SGLT2i and GLP-1A also increased effectiveness, resulting in 0.261 and 0.259 DALYs averted, respectively, but with higher ICERs of Int$12,061 (95% CI: 7,227–18,121) and Int$29,119 (95% CI: 23,811–35,367) per DALY averted. In the secondary prevention scenario, all three classes of treatments were deemed cost-effective at a maximum willingness-to-pay threshold of Int$26,700. Notably, pioglitazone consistently exhibited the highest probability of being cost-effective in both scenarios. Conclusions In Brazil, pioglitazone presented a higher probability of being cost-effective both in primary and secondary prevention, followed by SGLT2i and GLP-1A. Our findings support the use of cost-effectiveness models to build optimized and hierarchical therapeutic strategy in the management of T2DM. Trial registration CRD42020194415.

Suggested Citation

  • Ana Claudia Cavalcante Nogueira & Joaquim Barreto & Filipe A. Moura & Beatriz Luchiari & Abrão Abuhab & Isabella Bonilha & Wilson Nadruz & J. Michael Gaziano & Thomas Gaziano & Luiz Sergio F. Carvalho, 2023. "Comparative effectiveness and cost-effectiveness of cardioprotective glucose-lowering therapies for type 2 diabetes in Brazil: a Bayesian network model," Health Economics Review, Springer, vol. 13(1), pages 1-16, December.
  • Handle: RePEc:spr:hecrev:v:13:y:2023:i:1:d:10.1186_s13561-023-00466-3
    DOI: 10.1186/s13561-023-00466-3
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    References listed on IDEAS

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    1. Frank A. Sonnenberg & J. Robert Beck, 1993. "Markov Models in Medical Decision Making," Medical Decision Making, , vol. 13(4), pages 322-338, December.
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