Evidence map›Paper›PMID 27840606›Full record

ArticleFrontiers in pharmacology2016

Challenges from Variation across Regions in Cost Effectiveness Analysis in Multi-Regional Clinical Trials.

Yunbo Chu, Luyan Dai, Sheng Qi, Matthew Lee Smith, Hui Huang, Yang Li, Ye Shen

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yunbo ChuBoehringer Ingelheim (China) Investment Co. Ltd. Shanghai, China.
Luyan DaiBoehringer Ingelheim (China) Investment Co. Ltd. Shanghai, China.
Sheng QiBoehringer Ingelheim (China) Investment Co. Ltd. Shanghai, China.
Matthew Lee SmithDepartment of Health Promotion and Behavior, Institute of Gerontology, University of GeorgiaAthens, GA, USA; Texas A&M School of Public Health, Health Science Center, Texas A&M UniversityCollege Station, TX, USA.
Hui HuangDepartment of Probability and Statistics, Center for Statistical Science, Peking University Beijing, China.
Yang LiCenter for Applied Statistics and School of Statistics, Renmin University of China Beijing, China.
Ye ShenDepartment of Epidemiology and Biostatistics, University of Georgia Athens, GA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Economic evaluation in the form of cost-effectiveness analysis has become a popular means to inform decisions in healthcare. With multi-regional clinical trials in a global development program becoming a new venue for drug efficacy testing in recent decades, questions in methods for cost-effectiveness analysis in the multi-regional clinical trials setting also emerge. This paper addresses some challenges from variation across regions in cost effectiveness analysis in multi-regional clinical trials. Several discussion points are raised for further attention and a multi-regional clinical trial example is presented to illustrate the implications in industrial application. A general message is delivered to call for a depth discussion by all stakeholders to reach an agreement on a good practice in cost-effectiveness analysis in the multi-regional clinical trials. Meanwhile, we recommend an additional consideration of cost-effectiveness analysis results based on the clinical evidence from a certain homogeneous population as sensitivity or scenario analysis upon data availability.

Indexed as

clinical evidencecost-effectiveness analysisethnic factorsmulti-regional clinical trialssensitivity analysis

Identifiers

PMID27840606
PMCPMC5083708

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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 OpenQuestion graph.