Can differences in breast cancer utilities explain disparities in breast cancer care?

Schleinitz, Mark D.; DePalo, Dina M.; Blume, Jeffrey L.; Stein, Michael D.

doi:10.1111/j.1525-1497.2006.00609.x

Cited by 48 publications

(68 citation statements)

References 53 publications

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“…An area of great concern for all women, regardless of race, but particularly for poor women and for women of color, is the economic burden of breast cancer. Sociodemographic characteristics may have a significant impact on whether African American women would be more likely to utilize adjuvant chemotherapy as compared to other racial groups (Schleinitz, DePalo, Blume, & Stein, 2006). Breast cancer patients with limited financial resources are likely to face this additional economic burden (Arozullah et al, 2004).…”

Section: Socioeconomic Positionmentioning

confidence: 99%

Biopsychosocial Predictors of Psychological Functioning Among African American Breast Cancer Survivors

Davis

Myers

Nyamathi

et al. 2014

Journal of Psychosocial Oncology

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Section: Socioeconomic Positionmentioning

confidence: 99%

Biopsychosocial Predictors of Psychological Functioning Among African American Breast Cancer Survivors

Davis

Myers

Nyamathi

et al. 2014

Journal of Psychosocial Oncology

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“…Foram encontrados cinco estudos relevantes, um deles comparando diferentes estadiamentos e os demais avaliando somente pacientes com estadiamentos precoces ou tardios 20,21,22,23,24 . Após a avaliação crítica desses estudos, definiu-se os valores mostrados na Tabela 1.…”

Section: Pressupostos Do Modelounclassified

Custo-efetividade de um programa de rastreamento organizado de câncer de mama no Sul do Brasil

2013

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O objetivo deste estudo foi avaliar o custo-efetividade de um programa organizado de rastreamento mamográfico de câncer de mama implementado na cidade de Porto Alegre, Rio Grande do Sul, Brasil (Núcleo Mama Porto Alegre - NMPOA). Foi construído modelo de Markov para estimar a relação de custo-efetividade incremental do NMPOA em comparação à situação atual de atenção ao câncer de mama no SUS, em coorte hipotética de mulheres de 40-69 anos com risco de desenvolver câncer de mama. Os parâmetros foram coletados do NMPOA e da literatura nacional. Na estratégia NMPOA, a efetividade foi modelada levando-se em conta a real adesão da população participante do rastreamento. A efetividade foi medida em anos de vida ajustados para qualidade (QALY). A relação de custoefetividade incremental no caso base foi de R$ 13.426,00 por QALY. Esse resultado foi pouco sensível à variação dos principais parâmetros do modelo nas análises de sensibilidade. Considerando o limiar usualmente sugerido como bastante atrativo do ponto de vista econômico no Brasil, o rastreamento do câncer de mama nos moldes do NMPOA é custo-efetivo em cidades com alta incidência deste tipo de câncer.

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“…Social factors, including poverty and financial insecurity, lack of transportation, poor access to care, poor health literacy, low educational attainment, and lack of health insurance contribute substantially to differences in breast cancer outcomes [5,9,12,[51][52][53][54][55][56]. Lower income and uninsured cancer patients are especially sensitive to the high costs of cancer care and may be more likely to be from minority groups [57].…”

Section: Social Factors and Screening Behaviorsmentioning

confidence: 99%

Disparities in Breast Cancer Treatment and Outcomes: Biological, Social, and Health System Determinants and Opportunities for Research

2013

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Racial disparities in breast cancer mortality have been widely documented for several decades and persist despite advances in receipt of mammography across racial groups. This persistence leads to questions about the roles of biological, social, and health system determinants of poor outcomes. Cancer outcomes are a function not only of innate biological factors but also of modifiable characteristics of individual behavior and decision making as well as characteristics of patient-health system interaction and the health system itself. Attempts to explain persistent racial disparities have mostly been limited to discussion of differences in insurance coverage, socioeconomic status, tumor stage at diagnosis, comorbidity, and molecular subtype of the tumor. This article summarizes existing literature exploring reasons for racial disparities in breast cancer mortality, with an emphasis on treatment disparities and opportunities for future research. Because breast cancer care requires a high degree of multidisciplinary team collaboration, ensuring that guideline recommended treatment (such as endocrine therapy for hormone receptor positive patients) is received by all racial/ethnic groups is critical and requires coordination across multiple providers and health care settings. Recognition that variation in cancer care quality may be correlated with race (and socioeconomic and health system factors) may assist policy makers in identifying strategies to more equally distribute clinical expertise and health infrastructure across multiple user populations. The Oncologist 2013;18:986 -993 Implications for Practice: Disparities in breast cancer outcomes result not only from racially specific tumor differences, but also modifiable social and health system determinants, such as poor access to care and health education, lack of financial resources, problematic patient-provider interactions, and structural barriers within the health system itself. Breast cancer care requires a high degree of multidisciplinary team collaboration; therefore, ensuring that care is delivered in a coordinated, continuous, culturally and socioeconomically sensitive fashion is critical to ensuring equitable receipt of guideline recommended treatments, which in turn, will help improve outcomes across racial groups. Understanding how biological, social, and health system factors act in concert to influence outcomes may help clinicians, researchers, and policy makers to identify more innovative strategies to address breast cancer disparities going forward.

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Can differences in breast cancer utilities explain disparities in breast cancer care?

Abstract: BACKGROUND: Black, older, and less affluent women are less likely to receive adjuvant breast cancer therapy than their counterparts. Whereas preference contributes to disparities in other health care scenarios, it is unclear if preference explains differential rates of breast cancer care.

Cited by 48 publications

References 53 publications

Biopsychosocial Predictors of Psychological Functioning Among African American Breast Cancer Survivors

Biopsychosocial Predictors of Psychological Functioning Among African American Breast Cancer Survivors

Custo-efetividade de um programa de rastreamento organizado de câncer de mama no Sul do Brasil

Disparities in Breast Cancer Treatment and Outcomes: Biological, Social, and Health System Determinants and Opportunities for Research

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