Patient Preferences in Targeted Pharmacotherapy for Cancers: A Systematic Review of Discrete Choice Experiments.


Journal

PharmacoEconomics
ISSN: 1179-2027
Titre abrégé: Pharmacoeconomics
Pays: New Zealand
ID NLM: 9212404

Informations de publication

Date de publication:
01 2023
Historique:
accepted: 18 09 2022
pubmed: 14 11 2022
medline: 7 1 2023
entrez: 13 11 2022
Statut: ppublish

Résumé

Targeted pharmacotherapy has been increasingly applied in cancer treatment due to its breakthroughs. However, the unmet needs of cancer patients are still significant, highlighting the urgency to investigate patient preferences. It is unclear how patients deliberate their choices between different aspects of targeted therapy, including cost, efficacy, and adverse events. Since discrete choice experiments (DCEs) have been widely applied to patient preference elicitation, we reviewed DCEs on targeted therapy for different cancers. We also synthesized evidence on the factors influencing patients' choices and their willingness-to-pay (WTP) for survival when treated by targeted therapy. We searched databases, including PubMed, EMBASE and MEDLINE, up to August 16, 2022, supplemented by a reference screening. The attributes from the selected studies were categorized into three groups: outcomes, costs, and process. We also calculated the relative importance of attributes and WTP for survival whenever possible. The purpose, respondents, explanation, findings, significance (PREFS) checklist was used to evaluate the quality of the included DCE studies. The review identified 34 eligible studies from 13 countries covering 14 cancers, such as breast, ovarian, kidney, prostate, and skin cancers. It also reveals a rising trend of DCEs on this topic, as most studies were published after 2018. We found that patients placed higher weights on the outcome (e.g., overall survival) and cost attributes than on process attributes. On average, patients were willing to pay $561 (95% confidence interval [CI]: $415-$758) and $716 (95% CI $524-$958) out-of-pocket for a 1-month increase in progression-free survival and overall survival, respectively. PREFS scores of the 34 studies ranged from 2 to 4, with a mean of 3.38 (SD: 0.65), suggesting a reasonable quality based on the checklist. However, most studies (n = 32, 94%) did not assess the impact of non-responses on the results. This is the first systematic review focusing on patient preferences for targeted cancer therapy. We showcased novel approaches for evidence synthesis of DCE results, especially the attribute relative importance and WTP. The results may inform stakeholders about patient preferences toward targeted therapy and their WTP estimates. More studies with improved study design and quality are warranted to generate more robust evidence to assist decision making.

Sections du résumé

BACKGROUND
Targeted pharmacotherapy has been increasingly applied in cancer treatment due to its breakthroughs. However, the unmet needs of cancer patients are still significant, highlighting the urgency to investigate patient preferences. It is unclear how patients deliberate their choices between different aspects of targeted therapy, including cost, efficacy, and adverse events. Since discrete choice experiments (DCEs) have been widely applied to patient preference elicitation, we reviewed DCEs on targeted therapy for different cancers. We also synthesized evidence on the factors influencing patients' choices and their willingness-to-pay (WTP) for survival when treated by targeted therapy.
METHODS
We searched databases, including PubMed, EMBASE and MEDLINE, up to August 16, 2022, supplemented by a reference screening. The attributes from the selected studies were categorized into three groups: outcomes, costs, and process. We also calculated the relative importance of attributes and WTP for survival whenever possible. The purpose, respondents, explanation, findings, significance (PREFS) checklist was used to evaluate the quality of the included DCE studies.
RESULTS
The review identified 34 eligible studies from 13 countries covering 14 cancers, such as breast, ovarian, kidney, prostate, and skin cancers. It also reveals a rising trend of DCEs on this topic, as most studies were published after 2018. We found that patients placed higher weights on the outcome (e.g., overall survival) and cost attributes than on process attributes. On average, patients were willing to pay $561 (95% confidence interval [CI]: $415-$758) and $716 (95% CI $524-$958) out-of-pocket for a 1-month increase in progression-free survival and overall survival, respectively. PREFS scores of the 34 studies ranged from 2 to 4, with a mean of 3.38 (SD: 0.65), suggesting a reasonable quality based on the checklist. However, most studies (n = 32, 94%) did not assess the impact of non-responses on the results.
CONCLUSIONS
This is the first systematic review focusing on patient preferences for targeted cancer therapy. We showcased novel approaches for evidence synthesis of DCE results, especially the attribute relative importance and WTP. The results may inform stakeholders about patient preferences toward targeted therapy and their WTP estimates. More studies with improved study design and quality are warranted to generate more robust evidence to assist decision making.

Identifiants

pubmed: 36372823
doi: 10.1007/s40273-022-01198-8
pii: 10.1007/s40273-022-01198-8
doi:

Types de publication

Systematic Review Research Support, Non-U.S. Gov't

Langues

eng

Pagination

43-57

Informations de copyright

© 2022. The Author(s).

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Auteurs

Shan Jiang (S)

School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.

Ru Ren (R)

Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China.
Center for Health Preference Research, Shandong University, Jinan, 250012, China.
Institute of Medical Sciences, The Second Hospital, Cheeloo College of Medicine, Shandong University, 247# Beiyuan Street, Jinan, 250033, China.

Yuanyuan Gu (Y)

Macquarie University Centre for the Health Economy, Macquarie Business School & Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, 2109, Australia. yuanyuan.gu@mq.edu.au.

Varinder Jeet (V)

Macquarie University Centre for the Health Economy, Macquarie Business School & Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, 2109, Australia.

Ping Liu (P)

Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China.
Center for Health Preference Research, Shandong University, Jinan, 250012, China.

Shunping Li (S)

Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China.
Center for Health Preference Research, Shandong University, Jinan, 250012, China.

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