High-value breast cancer care within resource limitations

Abstract

Breast cancer care is a costly global health issue where effective management depends on early detection and treatment. A breast cancer diagnosis can result in financial catastrophe especially in low- and middle-income countries (LMIC). Large inequities in breast cancer care are observed and represent a global challenge to caregivers and patients. Strategies to improve early diagnosis include awareness and clinical breast examination in LMIC, and screening in high-income countries (HIC). The use of clinical guidelines for the management of breast cancer is needed. Adapted guidelines from HIC can address disparities in populations with limited resources. Locally developed strategies still provide effective guidance in improving survival. Integrated practice units (IPU) with timely multidisciplinary breast care conferences and patient navigators are required to achieve high-value, personalized breast cancer management in HIC as well as LMIC. Breast cancer patient care should include a quality of life evaluation using ideally patient-reported outcomes (PROM) and experience measurements (PREM). Evaluation of breast cancer outcomes must include the financial cost of delivered care. The resulting value perspective should guide resource allocation and program priorities. The value of care must be improved by translating the findings of social and economic research into practice and resolving systemic inequity in clinical breast cancer research. Cancer survivorship programs must be put in place everywhere. The treatment of patients with metastatic breast cancer must require more attention in the future, especially in LMIC.

Keywords: breast cancer; community outreach; early diagnosis; economics; global health; health outcomes; value quotient.

Figure 1.

Relation between HDI and Stage I breast cancer Rene Aloisio da Costa Vieira et al.

Figure 2.

(A, B) Trends in advanced breast cancer incidence in the screen-detected, interval, and non-screened cohorts in The Netherlands. The solid line indicates the screen-detected cancers assuming 10% overdiagnosis. The shaded area indicates the percentage assuming 0% overdiagnosis (lower limit) to 30% overdiagnosis (upper limit; de Munck et al). (C, D) Trends in breast cancer incidence in the screening age groups and stage in Germany. Y-axis: age-specific rates/100 000 women on a logarithmic scale. Dots: observed rates, lines rates by join-point regression, vertical dotted line: year implementation of screening (Katalinic et al).

Figure 3.

Value-Based Health Care framework, from Teisberg.

Figure 4.

Health care spending per capita US dollar (World Bank Open data, 2019, retrieved January 30, 2022).