Evidence map›Paper›PMID 34354590›Full record

ArticleFrontiers in pharmacology2021

Patient Preferences for Attributes of Chemotherapy for Lung Cancer: Discrete Choice Experiment Study in Japan.

Yasuo Sugitani, Kyoko Ito, Shunsuke Ono

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

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

3 authors.

Yasuo SugitaniBiometrics Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.
Kyoko ItoSustainability Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.
Shunsuke OnoLaboratory of Pharmaceutical Regulation and Sciences, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our study objective was to determine lung cancer chemotherapy attributes that are important to patients in Japan. A discrete choice experiment survey in an anonymous web-based questionnaire format with a reward was completed by 200 lung cancer patients in Japan from November 25, 2019, to November 27, 2019. The relative importance of patient preferences for each attribute was estimated using a conditional logit model. A hierarchical Bayesian logit model was also used to estimate the impact of each demographic characteristic on the relative importance of each attribute. Of the 200 respondents, 191 with consistent responses were included in the analysis. In their preference, overall survival was the most important, followed by diarrhea, nausea, rash, bone marrow suppression (BMS), progression-free survival, fatigue, interstitial lung disease, frequency of administration, and duration of administration. The preferences were influenced by demographic characteristics (e.g., gender and age) and disease background (e.g., cancer type and stage). Interestingly, the experience of cancer drug therapies and adverse events had a substantial impact on the hypothetical drug preferences. For the Japanese lung cancer patients, improved survival was the most important attribute that influenced their preference for chemotherapy, followed by adverse events, including diarrhea, nausea, rash, and BMS. The preferences varied depending on the patient's demographic and experience. As drug attributes can affect patient preferences, pharmaceutical companies should be aware of the patient preferences and develop drugs that respond to segmented market needs.

Indexed as

conjoint analysisdiscrete choice experimenthierarchical bayes modelJapanese patient preferenceslung cancerpatient centricity

Identifiers

PMID34354590
PMCPMC8329447

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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 OpenQuestion graph.