Evidence map›Paper›PMID 37270199›Full record

ArticleBMJ open2023

Assessment of patients' preferences for new anticancer drugs in China: a best-worst discrete choice experiment on three common cancer types.

Zhe Feng, Jingyi Meng, Yanjun Sun, Tongling Xie, Wenzhang Lu, Guohua Wang, Jinsong Geng

Abstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline 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

7 authors.

Zhe FengDepartment of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China.
Jingyi MengDepartment of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China.
Yanjun SunDepartment of Radiotherapy, Tinghu District People's Hospital, Yancheng, Jiangsu, China.
Tongling XieDepartment of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China.
Wenzhang LuDepartment of Respiratory, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China.
Guohua WangInstitute of Special Environmental Medicine, Nantong University, Nantong, Jiangsu, China wgh@ntu.edu.cn gjs@ntu.edu.cn.
Jinsong GengDepartment of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China wgh@ntu.edu.cn gjs@ntu.edu.cn.ORCID 0000-0003-3389-9051

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesDespite the advancement in anticancer drug therapies, cancer treatment decisions are often complex and preference-sensitive, making them well suited for studying shared decision-making (SDM). Our study aimed to assess preferences for new anticancer drugs among three common types of patients with cancer to inform SDM.

designWe identified five attributes of new anticancer drugs and used a Bayesian-efficient design to generate choice sets for a best-worst discrete choice experiment (BWDCE). The mixed logit regression model was applied to estimate patient-reported preferences for each attribute. The interaction model was used to investigate preference heterogeneity.

settingThe BWDCE was conducted in Jiangsu province and Hebei province in China.

participantsPatients aged 18 years or older, who had a definite diagnosis of lung cancer, breast cancer or colorectal cancer were recruited.

resultsData from 468 patients were available for analysis. On average, the most valued attribute was the improvement in health-related quality of life (HRQoL) (p<0.001). The low incidence of severe to life-threatening side effects, prolonged progression-free survival and the low incidence of mild to moderate side effects were also positive predictors of patients' preferences (p<0.001). Out-of-pocket cost was a negative predictor of their preferences (p<0.001). According to subgroup analysis by type of cancer, the improvement in HRQoL remained the most valuable attribute. However, the relative importance of other attributes varied by type of cancer. Whether patients were newly diagnosed or previously diagnosed cancer cases played a dominant role in the preference heterogeneity within each subgroup.

conclusionsOur study can assist in the implementation of SDM by providing evidence on patients' preferences for new anticancer drugs. Patients should be informed of the multiattribute values of new drugs and encouraged to make decisions reflecting their values.

Indexed as

Antineoplastic AgentsBreast NeoplasmsBayes TheoremChinaChoice BehaviorFemaleHumansPatient PreferenceQuality of LifeAntineoplastic AgentsDecision MakingONCOLOGYPatient-Centered Care

Identifiers

PMID37270199
PMCPMC10254615

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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.