Willingness to pay per quality-adjusted life year of Non-Hodgkin Lymphoma patients in Vietnam

Phan Gia Huy; Pham Xuan Dung; Dang The Thap; Nguyen Tran Nhu Y

doi:10.59294/HIUJS.VOL.7.2024.681

Từ khóa:

Non-Hodgkin Lymphoma, Willingness to pay, quality-adjusted life year

Tóm tắt

Objectives: To estimate Willingness to pay per quality-adjusted life year (WTP/QALY) of patients with Non-Hodgkin Lymphoma (NHL) and analyze related factors to WTP/QALY of NHL patients. Patients and methods: Cross-sectional study has been conducted based on surveying NHL patients, satisfying inclusion and exclusion criteria in 5 specialized hospitals of Vietnam from March to August 2018. The structured questionnaire on socio-demographic and clinical characteristics, EQ-5D-5L and WTP were built to directly interview patients. Regression and correlation analysis have been conducted to estimate the related factors to WTP/QALY. The data were analyzed with relevant statistical tests and simple linear regression using SPSS 20.0 statistical software provided by International Business Machines (IBM) - New York, United State of America. A p-value <0.05 was considered statistically significant. Results: Sample included 516 NHL patients with the ratio of men: women of 1.37:1, the average age of 53.57 ± 14.37 years old, the average time of NHL onset of 1.32 ± 0.63 years. The median value of WTP/QALY was accounted for 45,604,698.96 (0.00 – 187,311,321.74) VND/QALY. With the confidence interval of 95%, the statistically significant differences in LogWTP/QALY have been found between men and women (0.179; 95% CI: 0.023 – 0.335; p = 0.025); fulltime- working patients and non-working patients (0.270; 95% CI: 0.275 – 0.512; p = 0.022), intellectual workers and unemployed/ housewife/ disability patients (0.555; 95% CI: 0.095 – 1.014; p = 0.009); lost-income and unlost-income status (0.267; 95% CI: 0.090 – 0.445; p = 0.003), family income (r = 0.272, p = 0.000) and patient income (r = 0.288, p = 0.000), HR-QoL (r = 0.436; p = 0.000). Linear regression analysis with 95% reliability showed R2= 0.291; p = 0.000 with two related factors to LogWTP/QALY including HR-QoL coefficient (β = 1.339; p = 0.000) and family income (β = 8.50 x 10-9; p = 0.014). Conclusion: The median value of WTP/QALY was accounted for 45,604,698.96 (0.00 – 187,311,321.74) VND/QALY. With the confidence interval of 95%, linear regression analysis showed two related factors to LogWTP/QALY including HR-QoL coefficient and family income.

Abstract

Objectives: To estimate Willingness to pay per quality-adjusted life year (WTP/QALY) of patients with Non-Hodgkin Lymphoma (NHL) and analyze related factors to WTP/QALY of NHL patients. Patients and methods: Cross-sectional study has been conducted based on surveying NHL patients, satisfying inclusion and exclusion criteria in 5 specialized hospitals of Vietnam from March to August 2018. The structured questionnaire on socio-demographic and clinical characteristics, EQ-5D-5L and WTP were built to directly interview patients. Regression and correlation analysis have been conducted to estimate the related factors to WTP/QALY. The data were analyzed with relevant statistical tests and simple linear regression using SPSS 20.0 statistical software provided by International Business Machines (IBM) - New York, United State of America. A p-value <0.05 was considered statistically significant. Results: Sample included 516 NHL patients with the ratio of men: women of 1.37:1, the average age of 53.57 ± 14.37 years old, the average time of NHL onset of 1.32 ± 0.63 years. The median value of WTP/QALY was accounted for 45,604,698.96 (0.00 – 187,311,321.74) VND/QALY. With the confidence interval of 95%, the statistically significant differences in LogWTP/QALY have been found between men and women (0.179; 95% CI: 0.023 – 0.335; p = 0.025); fulltime- working patients and non-working patients (0.270; 95% CI: 0.275 – 0.512; p = 0.022), intellectual workers and unemployed/ housewife/ disability patients (0.555; 95% CI: 0.095 – 1.014; p = 0.009); lost-income and unlost-income status (0.267; 95% CI: 0.090 – 0.445; p = 0.003), family income (r = 0.272, p = 0.000) and patient income (r = 0.288, p = 0.000), HR-QoL (r = 0.436; p = 0.000). Linear regression analysis with 95% reliability showed R2= 0.291; p = 0.000 with two related factors to LogWTP/QALY including HR-QoL coefficient (β = 1.339; p = 0.000) and family income (β = 8.50 x 10-9; p = 0.014). Conclusion: The median value of WTP/QALY was accounted for 45,604,698.96 (0.00 – 187,311,321.74) VND/QALY. With the confidence interval of 95%, linear regression analysis showed two related factors to LogWTP/QALY including HR-QoL coefficient and family income.

Tài liệu tham khảo

[1] Sheets SSF. Non-Hodgkin Lymphoma. Natl Cancer Inst 2015.

[2] K. R. Shankland, J. O Armitage and B. W. Hancock, “Non-Hodgkin lymphoma”, The Lancet 380, p. 848–857, 2012

DOI: https://doi.org/10.1016/S0140-6736(12)60605-9

[3] J. O. Armitage, R. D. Gascoyne,… and F. Cavalli, “Non-Hodgkin lymphoma”, The Lancet 390, p. 298–310, 2017.

DOI: https://doi.org/10.1016/S0140-6736(16)32407-2

[4] S. M. Ansell and J. Armitage, “Non-Hodgkin lymphoma: Diagnosis and treatment”, In Mayo Clinic Proceedings 2005.

DOI: https://doi.org/10.4065/80.8.1087

[5] A. W. Glaser, L. K. Fraser and J. Corner, “Patient-reported outcomes of cancer survivors in England 1–5 years after diag- nosis: A cross-sectional survey””, BMJ open 3, pii: e002317, 2013. URL 10.1136/bmjopen- 2012-002317.

DOI: https://doi.org/10.1136/bmjopen-2012-002317

[6] S. Masaki, R. Tatsukawa and M. Uryu, “Treatment satisfaction, willingness to pay and quality of life in Japanese patients with psoriasis”, The Journal of dermatology, 44, 2017, 143–146.

DOI: https://doi.org/10.1111/1346-8138.13541

[7] J. Brazier, J. Roberts, and M. Deverill, “The estimation of a preference-based measure of health from the SF-36”, Journal of health economics, 21, p.271–292, 2002.

DOI: https://doi.org/10.1016/S0167-6296(01)00130-8

[8] W. J. Furlong, D. H. Feeny,… and R. D. Barr, “The Health utilities index (HUI®) system for assessing health-related quality of life in clinical studies”, Annals of medicine, 33, p. 375–384, 2001.

DOI: https://doi.org/10.3109/07853890109002092

[9] G. Richardson and A. Manca, “Calculation of quality adjusted life years in the published literature: a review of methodology and transparency”, Health economics, 13, p.1203–1210, 2004.

DOI: https://doi.org/10.1002/hec.901

[10] S. J. Walters and J. E. Brazier, “Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D”, Quality of life research, 14, p. 1523–1532, 2005.

[11] R. E. Jensen, N. K. Arora,... and K. M. Bellizzi, “Health-related quality of life among survivors of aggressive non-Hodgkin lymphoma”, Cancer, 119, 672–680, 2013. URL 10.1002/cncr.27781.

DOI: https://doi.org/10.1002/cncr.27781

[12] K. M. Bellizzi, J. H. Rowland,… and N. M. Aziz, “Physical activity and quality of life in adult survivors of Non-Hodgkin's lymphoma”, Journal of Clinical Oncology, 960, 2009.

DOI: https://doi.org/10.1200/JCO.2008.17.5026

[13] D. Kang, J. Cho, M. K. K. Im Ryung, …and S. J. Kim, “Health-Related quality of life in Non-Hodgkin lymphoma survivors: A prospective cohort study”, Cancer research and treatment: official journal of Korean Cancer Association, 50, 1051, 2018.

DOI: https://doi.org/10.4143/crt.2017.207

[14] L. H. Nguyen and A. T. D. Hoang, “Willingness to pay for social health insurance in central Vietnam”, Frontiers in public health, 5, 89, 2017.

DOI: https://doi.org/10.3389/fpubh.2017.00089

[15] K. Nimdet and S. Ngorsuraches, “Willingness to pay per quality-adjusted life year for life-saving treatments in Thailand”, BMJ open, 5, e008123, 2015.

DOI: https://doi.org/10.1136/bmjopen-2015-008123

[16] J. Doorduijn, I. Buijt,...and P. Sonneveld, “Self-reported quality of life in elderly patients with aggressive non-Hodgkin's lymphoma treated with CHOP chemotherapy”, European journal of haematology, 75, 116–123, 2005.

DOI: https://doi.org/10.1111/j.1600-0609.2005.00438.x

[17] Group TE., “EuroQoL-A new facility for the measurement of health-related quality of life”, Health policy, 16, 199–208, 1990

DOI: https://doi.org/10.1016/0168-8510(90)90421-9

[18] N. K. Aaronson, S. Ahmedzai,... and B. Bergman, “The European organization for research and Treatment of can- cer QLQ-C30: A quality of life instrument for use in international clinical trials in oncology,” JNCI: Journal of the National Cancer Institute, 85, 365–376, 1993.

DOI: https://doi.org/10.1093/jnci/85.5.365

[19] E. Smets, B. Garssen, A. Cull and J. De Haes, “Application of the multidimensional fatigue inventory (MFI-20) in cancer patients receiving radiotherapy”, British journal of cancer, 73, 241, 1996

DOI: https://doi.org/10.1038/bjc.1996.42

[20] M. Jefford, A. C. Ward,…and K. Lisy, “Patient-reported outcomes in cancer survivors: a population-wide cross-sectional study”, Supportive Care in Cancer, 25, p. 3171–3179, 2017

DOI: https://doi.org/10.1007/s00520-017-3725-5

[21] K. Blumenschein and M. Johannesson, “Relationship between quality-of-life instruments, health state utilities, and willingness to pay in patients with asthma. Annals of allergy, asthma,” Annals of allergy, asthma & immunology, 80, p.189–194, 1998.

DOI: https://doi.org/10.1016/S1081-1206(10)62954-7

[22] T. T. Nguyen, T. T Nguyen and T. T Than, “Willingness to pay for a quality-adjusted life year of outpatients with cardiovascular diseases”, Value in Health, 19, A658–A659, 2016.

DOI: https://doi.org/10.1016/j.jval.2016.09.1794

[23] T. A. Lieu, G. T. Ray,… and D. Rusinak, “Willingness to pay for a QALY based on community member and patient preferences for temporary health states associated with herpes zoster”, Pharmacoeconomics, 27, 1005–1016, 2009.

DOI: https://doi.org/10.2165/11314000-000000000-00000

[24] S. J. Walter and J. E. Brazier, “Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D”, Quality of life research, 14, p. 1523–1532, 2005.

DOI: https://doi.org/10.1007/s11136-004-7713-0

[25] A. Oppe, M. Devlin and N. J. Szende, “EQ-5D value sets: inventory, comparative review and user guide”, EQ-5D value sets: Inventory, comparative review and user guide, 2007.
[26] S. J. Whitehead and S. Ali, “Health outcomes in economic evaluation: the QALY and utilities”, British medical bulletin, 96, p. 5–21, 2010.
[27] J. Martín-Fernández, E. Polentinos-Castro,...and M. I. Cura-González, “Willingness to pay for a quality-adjusted life year: An evaluation of attitudes towards risk and preferences”, BMC health services research, 287, 2014.