Evidence map›Paper›PMID 30735569›Full record

ArticleBritish journal of clinical pharmacology2019

Population/regional differences in efficacy of 3 drug categories (antidiabetic, respiratory and psychotropic agents) among East Asians: A retrospective study based on multiregional clinical trials.

Kimie Sai, Akiomi Yoshida, Tadaaki Hanatani, Takuya Imatoh, Masahiro Takeuchi, Mamoru Narukawa, Hiroshi Watanabe, Yoshiaki Uyama, Yoshiro Saito

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in British journal of clinical pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Dostarlimab: A breakthrough in the field of oncology.Annals of medicine and surgery (2012) · 2022
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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

9 authors at 4 institutions in 1 country.

Kimie SaiDivision of Medicinal Safety Science, National Institute of Health Sciences, Kawasaki, Japan.ORCID 0000-0002-1586-6515
Akiomi YoshidaDepartment of Clinical Medicine (Biostatistics), School of Pharmacy, Kitasato University, Tokyo, Japan.
Tadaaki HanataniDivision of Medicinal Safety Science, National Institute of Health Sciences, Kawasaki, Japan.
Takuya ImatohDivision of Medicinal Safety Science, National Institute of Health Sciences, Kawasaki, Japan.ORCID 0000-0002-8160-7335
Masahiro TakeuchiDepartment of Clinical Medicine (Biostatistics), School of Pharmacy, Kitasato University, Tokyo, Japan.
Mamoru NarukawaDepartment of Clinical Medicine (Pharmaceutical Medicine), School of Pharmacy, Kitasato University, Tokyo, Japan.
Hiroshi WatanabeDepartment of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Yoshiaki UyamaOffice of Medical Informatics and Epidemiology, Pharmaceuticals & Medical Devices Agency, Tokyo, Japan.
Yoshiro SaitoDivision of Medicinal Safety Science, National Institute of Health Sciences, Kawasaki, Japan.
National Institute of Health Sciences · JPKitasato University · JPHamamatsu University School of Medicine · JPPharmaceuticals and Medical Devices Agency · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThis study aimed to identify population/regional differences in drug efficacy and the influencing factors among East Asians to be considered when planning multiregional clinical trials (MRCTs) to facilitate rapid drug approval in Asians.

methodsA retrospective analysis of efficacy (intergroup difference in endpoint between control and study drug treatment) among East Asian populations for 3 drug categories, antidiabetic, respiratory and psychotropic agents, was conducted in collaboration with pharmaceutical companies using their MRCT data. Common endpoints by drug category were selected; background factors that commonly affected the endpoints among regions were analysed first; then the population/regional differences were evaluated by the interaction term region-by-treatment using an analysis of covariance model after adjusting for background factors.

resultsAmong 17 endpoints for eight pharmaceutical products from 3 drug categories, no substantial population/regional differences were detected in the 3 drug categories examined (P > .05), except for haemoglobin A1c change between Japan and Korea for an antidiabetic drug, insulin glulisine (P = .0068). However, no such regional differences were evident in patients with clinically important higher haemoglobin A1c baseline values (majority subgroup). Variability in disease severity at baseline and concomitant drugs were determined to be potential influencing factors for regional differences.

conclusionsThis study suggests that the regional variability in efficacy of these 3 drug categories is not large among East Asians, and reveals the importance of considering background factors when planning MRCTs. Further studies are needed to evaluate regional variability in the efficacy of other drug categories and clarify the factors leading to regional differences in East Asians.

Indexed as

Asian PeopleBiomarkersBlood GlucoseClinical Trials as TopicEndpoint DeterminationFemaleForced Expiratory VolumeGlycated HemoglobinHealth Status DisparitiesHumansHypoglycemic AgentsLungMaleMental HealthMulticenter Studies as TopicPsychotropic DrugsBiomarkersBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsPsychotropic DrugsRespiratory System Agentsdrug developmenteffectivenessrandomised controlled trial

Identifiers

PMID30735569
PMCPMC6533431
OpenAlexW2911709817

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.