Contribution of cost to treatment nonadherence in the US breast cancer survivors: a population-based analysis

Social Characteristics and Adherence to Adjuvant Endocrine Therapy in Premenopausal Women With Breast Cancer

PURPOSE

Social characteristics, including cohabitation/marital status and socioeconomic position (SEP)-education level, employment status, and income-influence breast cancer prognosis. We investigated the impact of these social characteristics on adherence to adjuvant endocrine therapy (AET) from treatment initiation to 5 years after diagnosis.

METHODS

We assembled a nationwide, population-based cohort of premenopausal women diagnosed in Denmark with stage I-III, estrogen receptor-positive breast cancer during 2002-2011. We ascertained prediagnostic social characteristics from national registries. AET adherence was based on information from the Danish Breast Cancer Group and operationalized as (1) adherence trajectories (from group-based trajectory modeling) and (2) early discontinuation. We computed odds ratios (ORs) and associated 95% CI to estimate the association of cohabitation and SEP with AET adherence using multinomial and logistic regression models adjusted according to directed acyclic graphs.

RESULTS

Among 4,353 patients, we identified three adherence trajectories-high adherence (57%), slow decline (36%), and rapid decline (6.9%). Compared with cohabiting women, those living alone had higher ORs of slow (1.26 [95% CI, 1.08 to 1.46]) or rapid decline (1.66 [95% CI, 1.27 to 2.18]) versus high adherence. The corresponding ORs for women not working versus employed women were 1.22 (95% CI, 1.02 to 1.45) and 1.76 (95% CI, 1.30 to 2.38). For early discontinuation (17%), the ORs were 1.48 (95% CI, 1.23 to 1.78) for living alone and 1.44 (95% CI, 1.17 to 1.78) for women not working.

CONCLUSION

Adherence to AET was lower among women living alone or unemployed than cohabiting or employed women, respectively. These women may benefit from support programs to enhance AET adherence.

Evaluating Socioeconomic, Racial, and Ethnic Disparities in Survival Among Patients Undergoing Allogeneic Hematopoietic Stem Cell Transplants

This study was undertaken to monitor potential disparities in survival after allogeneic hematopoietic stem cell transplantation (HSCT) with the aim of optimizing access and outcomes for minority and low-income patients. We analyzed 463 patients transplanted over a 72-month study period with a median 19-month follow-up, focused on differences by individual patient race/ethnicity and patients' household income derived from geocoded addresses at the census block group level. Patient sociodemographic and clinical characteristics were abstracted from electronic health records and our HSCT registry, including disease category and status, donor age, transplant type, and conditioning. Approximately, 15% of HSCT patients were non-Hispanic Black or Hispanic with a similar proportion from block groups below the median metropolitan Index of Concentration at the Extremes income score. The overall survival probability was 61.8% at 36 months. Non-Hispanic white (63.6%) and especially Hispanic patients (49.2%) had lower survival probabilities at 36 months than non-Hispanic Black patients (75.6%, p = 0.04). There were no other patient characteristics significantly associated with survival at the p < 0.01 level. The lack of significant differences likely reflects the careful selection of patients for transplants. However, the proportion of minority and low-income patients relative to expected disease prevalence in our area population raises important considerations about which patients successfully make it to transplant. We conclude with recommendations to increase the diversity of patients who receive HSCT by reviewing potential barriers in the transplant referral and selection process and advocating for needed psychosocial and community resources.

Dynamic Projection of Medication Nonpersistence and Nonadherence Among Patients With Early Breast Cancer

Importance

Oral endocrine treatments have been shown to be effective when carefully adhered to. However, in patients with early breast cancer, adherence challenges are notable, with 17% experiencing nonpersistence and 41% nonadherence at least once.

Objective

To model the persistence of and adherence to oral anticancer treatment of a patient with localized breast cancer.

Design, Setting, and Participants

This cohort study was conducted using anonymous reimbursement data belonging to French female patients with breast cancer, extracted from the French Health Insurance database from January 2013 to December 2018. Data analysis was conducted from January 2021 to May 2022.

Main Outcomes and Measures

The main outcome was the detection of episodes of nonpersistence and nonadherence 6 months before they happened. Adherence was defined as the ratio between the time covered by a drug purchase and the time between 2 purchases; patients were considered nonadherent if the ratio of their next 3 purchases was less than 80%. Disparities in persistence and adherence based on criteria such as age, treatment type, and income were identified.

Results

A total of 229 695 female patients (median [IQR] age, 63 [52-72] years) with localized breast cancer were included. A deep learning model based on a gated-recurrent unit architecture was used to detect episodes of nonpersistence or nonadherence. This model demonstrated an area under the receiving operating curve of 0.71 for persistence and 0.73 for adherence. Analyzing the Shapley Additive Explanations values also gave insights into the contribution of the different features over the model's decision. Patients older than 70 years, with past nonadherence, taking more than 1 treatment in the previous 3 months, and with low income had greater risk of episodes of nonpersistence. Age and past nonadherence, including regularity of past adherence, were also important features in the nonadherence model.

Conclusions and Relevance

This cohort study found associations of patient age and past adherence with nonpersistence or nonadherence. It also suggested that regular intervals in treatment purchases enhanced adherence, in contrast to irregular purchasing patterns. This research offers valuable tools for improving persistence of and adherence to oral anticancer treatment among patients with early breast cancer.

Administrative Burden Associated with Cost-Related Delays in Care in U.S. Cancer Patients

BACKGROUND

U.S. cancer patients engage in administrative tasks to pay for their healthcare. This study investigated the relationship between payment tasks and timely access to cancer care.

METHODS

We analyzed online survey data from 510 U.S. cancer patients and survivors to understand the relationship between administrative payment tasks and cost-related delays and nonadherence. Two-part modelling was used to determine if, and to what extent, there was a relationship between administrative burden and cost-related delays/nonadherence.

RESULTS

Younger patients (≤44 years) reported more payment tasks and cost-related delays/nonadherence than older patients (≥ 55 years); African American patients reported more payment tasks and cost-related delays/nonadherence than white patients. After accounting for age, race/ethnicity, education, and out-of-pocket costs, patients who reported engaging in more tasks had greater log odds of delaying/forgoing care [b = 0.18; 95% confidence interval (CI), 0.12-0.24]. Cost-related delays/nonadherence increased by 32% for every unit increase in administrative payment burden (b = 0.32; 95% CI, 0.18-0.46).

CONCLUSIONS

Administrative payment burden increased the odds of cost-related delays and nonadherence by 49%, taking the form of delayed or skipped doctor appointments, tests and bloodwork, and prescription fulfillment. Younger patients and those identifying as African American were more likely to engage in payment tasks and to delay or forgo care due to cost. Administrative burdens can disrupt access to care and traditionally underserved patient populations are disproportionately exposed to these hardships.

IMPACT

Reducing the complexity of healthcare through universal, human-centered design could reduce burdens and increase access.