Marques S N Ng1, Kai Chow Choi1, Dorothy N S Chan1, Cho Lee Wong1, Weijie Xing2, Pui Shan Ho3, Cecilia Au4, Mandy Chan5, Man Tong3, Wai Man Ling4, Maggie Chan4, Suzanne S S Mak5, Raymond J Chan6,7, Winnie K W So8. 1. The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China. 2. School of Nursing, Fudan University, Shanghai, China. 3. Department of Clinical Oncology, Tuen Mun Hospital, Hong Kong, China. 4. Department of Clinical Oncology, Pamela Youde Nethersole Eastern Hospital, Hong Kong, China. 5. Department of Clinical Oncology, Prince of Wales Hospital, Hong Kong, China. 6. School of Nursing and Cancer and Palliative Care Outcomes Centre, Queensland University of Technology, Brisbane, Australia. 7. Princess Alexandra Hospital, Metro South Health, Brisbane, Australia. 8. The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China. winnieso@cuhk.edu.hk.
Abstract
PURPOSE: To identify a cut-off score for the COmprehensive Score for financial Toxicity (COST) to predict a clinical implication of a high level of financial toxicity (FT). METHODS: A total of 640 cancer patients were recruited from three regional hospitals in Hong Kong. They completed a questionnaire comprising the COST measure and the Functional Assessment of Cancer Therapy - General (FACT-G) instrument. The cut-off score for the COST that predicts the lowest quartile of the FACT-G total score was identified by receiver operating characteristic (ROC) analysis. The sample was then stratified by this cut-off score, and characteristics were compared using Fisher's exact, chi-squared or independent sample t-test. RESULTS: The mean scores were 20.1 ± 8.8 for the COST and 71.6 ± 15.5 for the FACT-G. The ROC analysis suggested that the cut-off of 17.5 yielded an acceptable sensitivity and specificity. Characteristics of patients with a higher level of FT included being younger, having a monthly household income of < 10,000 HKD (approximately 1290 USD), being more likely not employed, having stage IV cancer and receiving targeted and/or immunotherapy. In terms of financial support, a higher proportion of these patients had discussed financial issues with health care professionals and had received financial assistance. In addition, fewer of them were covered by private health insurance. CONCLUSION: Our findings suggest a cut-off for the COST that can be used to screen for FT in clinical settings. In addition, while a considerable proportion of high-FT patients received targeted therapy, they often received financial assistance. There is a gap between financial hardship and assistance that warrants attention.
PURPOSE: To identify a cut-off score for the COmprehensive Score for financial Toxicity (COST) to predict a clinical implication of a high level of financial toxicity (FT). METHODS: A total of 640 cancerpatients were recruited from three regional hospitals in Hong Kong. They completed a questionnaire comprising the COST measure and the Functional Assessment of Cancer Therapy - General (FACT-G) instrument. The cut-off score for the COST that predicts the lowest quartile of the FACT-G total score was identified by receiver operating characteristic (ROC) analysis. The sample was then stratified by this cut-off score, and characteristics were compared using Fisher's exact, chi-squared or independent sample t-test. RESULTS: The mean scores were 20.1 ± 8.8 for the COST and 71.6 ± 15.5 for the FACT-G. The ROC analysis suggested that the cut-off of 17.5 yielded an acceptable sensitivity and specificity. Characteristics of patients with a higher level of FT included being younger, having a monthly household income of < 10,000 HKD (approximately 1290 USD), being more likely not employed, having stage IV cancer and receiving targeted and/or immunotherapy. In terms of financial support, a higher proportion of these patients had discussed financial issues with health care professionals and had received financial assistance. In addition, fewer of them were covered by private health insurance. CONCLUSION: Our findings suggest a cut-off for the COST that can be used to screen for FT in clinical settings. In addition, while a considerable proportion of high-FTpatients received targeted therapy, they often received financial assistance. There is a gap between financial hardship and assistance that warrants attention.
Entities:
Keywords:
Health expenditures; Health services; Health-related quality of life; Patient-reported outcomes; Treatment costs
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