Evidence map›Paper›PMID 39256322›Full record

ArticleApplied health economics and health policy2024

Public Preference for Off-Label Use of Drugs for Cancer Treatment and Relative Importance of Associated Adverse Events: A Discrete Choice Experiment and Best-Worst Scaling.

Kailu Wang, Ho-Man Shum, Carrie Ho-Kwan Yam, Yushan Wu, Eliza Lai-Yi Wong, Eng-Kiong Yeoh

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Article in Applied health economics and health policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kailu WangCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Sha Tin, N.T., Hong Kong, China. kailuwang@cuhk.edu.hk.ORCID 0000-0002-3462-4677
Ho-Man ShumCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Sha Tin, N.T., Hong Kong, China.
Carrie Ho-Kwan YamCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Sha Tin, N.T., Hong Kong, China.
Yushan WuCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Sha Tin, N.T., Hong Kong, China.
Eliza Lai-Yi WongCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Sha Tin, N.T., Hong Kong, China.
Eng-Kiong YeohCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Sha Tin, N.T., Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivePatients may get more treatment options with off-label use of drugs while exposed to unknown risks of adverse events. Little is known about the public or demand-side perspective on off-label drug use, which is important to understand how to use off-label treatment and devise financial assistance. This study aimed to quantify public preference for off-label cancer treatment outcomes, process, and costs, and perceived importance of associated adverse events.

methodsA discrete choice experiment and a best-worst scaling were conducted in Hong Kong in December 2022. Quota sampling was used to randomly select the study sample from a territory-wide panel of working-age adults. Preferences and willingness to pay (WTP) for treatment effectiveness, risk of adverse events, mode of drug administration, and availability of off-label treatment guidelines were estimated using a random parameter logit model and latent class model. The relative importance of different adverse events was elicited using Case 1 best-worst scaling.

resultsA total of 435 respondents provided valid responses. In the discrete choice experiment, the respondents indicated that extra overall survival as treatment effectiveness (WTP: HK$448,000/US$57,400 for 12-month vs 3-month extra survival) was the most important attribute for off-label drugs, followed by the risk of adverse events (WTP: HK$318,000/US$40,800 for 10% chance to have adverse event vs 55%), mode of drug administration (WTP: HK$42,000/US$5300 for oral intake vs injection), and availability of guidelines (WTP: HK$31,000/US$4000 for available versus not available). Four groups with distinct preferences were identified, including effectiveness oriented, off-label use refusal, oral intake oriented, and adverse event risk aversion. In the best-worse scaling, hypothyroidism, nausea/vomiting, and arthralgia/joint pain were the three most important adverse events based on the perceptions of respondents. Risk-averse respondents, who were identified from the discrete choice experiment, had different perceived importance of the adverse events compared with those with other preferences.

conclusionsKnowing the preference and WTP for cancer treatment-related characteristics from a societal perspective facilitates doctors' communications with patients on decision making and treatment goal-setting for off-label treatment, and enables devising financial assistance for related treatments. This study also provides important insight to inform evaluations of public acceptance and information dissemination in drug development as well as future economic evaluations.

Indexed as

NeoplasmsOff-Label UsePatient PreferenceAdultAntineoplastic AgentsChoice BehaviorFemaleHong KongHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultAntineoplastic Agents

Identifiers

PMID39256322
PMCPMC11470847

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.