Guaranteed Income and Financial Treatment

Cancer-related financial hardship (i.e., financial toxicity) has been associated with anxiety and depression, greater pain and symptom burden, treatment nonadherence, and mortality. Out-of-pocket healthcare costs and lost income are primary drivers of financial toxicity, however, income loss is a pronounced risk factor for cancer patients with low incomes. There has been little progress in developing an income intervention to alleviate financial toxicity cancer patients with low incomes. Unconditional cash transfers (UCT), or guaranteed income, have produced positive health effects in experiments with general low-income populations, but have not yet been evaluated in people with cancer. The Guaranteed Income and Financial Treatment (GIFT) Trial will use a two-arm randomized controlled trial to compare the efficacy of a 12-month UCT intervention providing $1000/month to treatment as usual on financial toxicity, health-related quality of life and treatment adherence in people with cancer who have low-incomes. The study will recruit 250 Medicaid beneficiaries with advanced cancer from two comprehensive cancer centers in Philadelphia, obtain informed consent, and randomize patients to one of two conditions: (1) $1,000/month UCT or (2) treatment as usual. Both arms will receive information on financial toxicity and the contact information for their hospital social worker or financial advocate upon enrollment. Participants will complete online surveys at baseline, 3, 6, 9, and 12 months from enrollment to collect patient-reported data on primary (i.e., financial toxicity, health-related quality of life, and treatment adherence) and secondary outcomes (i.e., anxiety, depression, food insecurity, housing stability). Social security records will be used to explore the effect on mortality at 2, 3, and 5 years post-enrollment. Linear mixed-models will be used to analyze all primary and secondary continuous outcomes over time and general estimating equations with a logit link and binary distribution for all binary outcomes over time. Differences between treatment and control groups and treatment effects will be determined using models that control for age, gender, race, baseline food security, baseline housing stability, and baseline ECOG. Findings from this study will have significant implications for the development and implementation of programs and policies that address the financial burden of cancer and other serious illnesses.