A new study suggested it is by using baseline sociodemographic and financial measures. The research was presented recently at a poster spotlight discussion session at the 2023 San Antonio Breast Cancer Symposium.
Analyzing data from the Southwest Oncology Group (SWOG) S1105 clinical trial, they were able to create measures of patient adherence to AI therapy for hormone-sensitive BC. Their model included individual sociodemographic and financial factors (e.g., measures of area-level deprivation and rural/urban location) that were found to be statistically significantly associated with adherence.
In fact, the presence of each additional risk factor increased the risk of nonadherence by 47%, according to the researchers. Patients with more than two risk factors had a 64% greater likelihood of AI nonadherence, they added.
“We recognize that non-adherence to endocrine therapy is multifactorial. Predicting who is at risk will help us target personalized interventions to the right patients,” said lead author and presenter Dawn L. Hershman, MD, MS, who is an American Cancer Society professor of medicine and epidemiology at Columbia University Irving Medical Center, deputy director of the Herbert Irving Comprehensive Cancer Center, and group co-chair-elect of SWOG Cancer Research Network, a clinical trials group funded by the National Cancer Institute, part of the National Institutes of Health.
Background information in the presentation noted that approximately two-thirds of patients treated for BC have hormone receptor–positive disease, which means that the growth of their tumors is driven by estrogen or progesterone. Women with this type of cancer are often prescribed drugs AIs to reduce hormone production.
Taking an AI daily for several years can significantly reduce the chance of BC returning, according to past studies, but for a range of reasons (including common side effects such as bone pain and hot flashes) many patients opt to stop taking AIs early.
The SWOG S1105 clinical trial was a randomized study that enrolled more than 700 postmenopausal women to test whether text message reminders could improve adherence to AI therapy. All patients had been prescribed AI therapy for BC, and they were assessed in the study every 3 months for continued use of their AI medication.
To develop the predictive model, the researchers analyzed a set of demographic and financial measures collected when patients joined the S1105 trial. Four of the measures were found to have statistically significant associations with increased nonadherence to AI therapy:
• Younger age
• Less education
• Lower out-of-pocket costs
• Living in urban areas.
Race and ethnicity were not associated with nonadherence, according to the researchers.
“These findings provide further evidence that an individual’s social and economic background can contribute vital information in predicting the course of their treatment,” said senior author Joseph Unger, PhD, associate professor at the Fred Hutchinson Cancer Center and a biostatistician and health services researcher with the SWOG Cancer Research Network.
The authors recommended that interventions and efforts to reduce side effects should target those at highest risk of nonadherence.
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