Quantifying treatment preferences and their association with financial toxicity in women with breast cancer

Abstract

BackgroundThe objective of the current study was to understand treatment preferences and their association with financial toxicity in Patient Advocate Foundation clients with breast cancer.MethodsThis choice‐based conjoint analysis used data from a nationwide sample of women with breast cancer who received assistance from the Patient Advocate Foundation. Choice sets created from 13 attributes of 3 levels each elicited patient preferences and trade‐offs. Latent class analysis segmented respondents into distinct preference archetypes. The Comprehensive Score for Financial Toxicity (COST) tool captured financial toxicity. Adjusted generalized linear models estimated COST score differences by preference archetype.ResultsOf 220 respondents (for a response rate of 10%), the median age was 58 years (interquartile range, 49‐66 years); 28% of respondents were Black, indigenous, or people of color; and approximately 60% had household incomes <$40,000. The majority of respondents were diagnosed with early‐stage cancer (91%), 38% had recurrent disease, and 61% were receiving treatment. Treatment choice was most affected by preferences related to affordability and impact on activities of daily living. Two distinct treatment preference archetypes emerged. The “cost‐prioritizing group” (75% of respondents) was most concerned about affordability, impact on activities of daily living, and burdening care partners. The “functional independence–prioritizing group” (25% of respondents) was most concerned about their ability to work, physical side effects, and interference with life events. COST scores were found to be similar between the archetypes in adjusted models (cost‐prioritizing group COST score, 12 [95% confidence interval, 9‐14]; and functional independence–prioritizing COST score, 11 [95% confidence interval, 9‐13]).ConclusionsPatients with breast cancer prioritized affordability or maintaining functional independence when making treatment decisions. Because of this variability, preference evaluation during treatment decision making could optimize patients' treatment experiences.

Financial toxicity and psychological distress in adults with cancer: A treatment-based analysis

“…The ranges of median COST scores were large, from 10 to 29, in the various studies. 10 , 34 , 35 , 36 It is necessary to calculate the clinically significant cut-off value for financial toxicity in the various medical and health systems.…”

Examining the association among fear of COVID‐19, psychological distress, and delays in cancer care

“…However, our population is similar to samples of underresourced patients with cancer receiving financial aid. 38 A study using SEER data by Clegg et al found that cancer incidence and socioeconomic statuses (SES) differed among types of cancer: higher SES was found to be associated with prostate and breast cancer incidence, while lower SES was found to be associated with lung and colorectal cancer incidence. The lack of detailed information about current cancer treatment limits ability to evaluate impact by treatment type or phase of care nor if cancer care was delayed specifically.…”

Differences in Preferences for Drug Therapy Between Patients with Metastatic Versus Early-Stage Breast Cancer: A Systematic Literature Review

“…Excluded studies and reasons for exclusion are displayed in Supplementary Table 2. Hence, 34 studies were included in the analysis [ 19 , 31 – 63 ]. Figure 1 shows the flow chart of study selection according to the PRISMA statement.…”

“…The characteristics of the included studies are described in Supplementary Table 3. The studies were conducted in a variety of countries covering different health care systems: Australia [ 35 , 37 , 38 , 55 , 61 ], Belgium [ 54 ], Canada [ 42 , 45 , 58 , 60 ], France [ 54 , 59 ], Germany [ 53 , 54 , 57 , 62 ], Ireland [ 59 ], Italy [ 48 , 54 ], Japan [ 40 , 50 , 52 ], Lebanon [ 54 ], Peru [ 54 ], Poland [ 54 , 59 ], Portugal [ 54 ], Serbia [ 54 ], Slovenia [ 54 ], South Africa [ 54 ], South Korea [ 51 ], Spain [ 59 ], Switzerland [ 54 ], Taiwan [ 34 ], Thailand, the Netherlands [ 39 , 41 , 54 ], Turkey [ 54 ], the UK [ 36 , 54 ] and the USA [ 19 , 31 – 33 , 43 , 44 , 46 , 47 , 56 , 63 ]. Sample sizes ranged from 35 to 452 respondents included in the data analyses.…”

“…Regarding the BC stage, 18 studies included patients with eBC (0–III) [ 32 , 33 , 35 – 41 , 44 , 45 , 47 , 48 , 54 , 55 , 58 , 61 , 62 ]; ten studies investigated the preferences of advanced and/or patients with mBC [ 19 , 31 , 34 , 43 , 46 , 51 , 53 , 56 , 57 , 60 ]. In six studies, patients with any BC stage were included [ 42 , 49 , 50 , 52 , 59 , 63 ].…”