Evidence map›Paper›PMID 28891251›Full record

Trial reportCPT: pharmacometrics & systems pharmacology2017

Dose/Exposure-Response Modeling to Support Dosing Recommendation for Phase III Development of Baricitinib in Patients with Rheumatoid Arthritis.

Xin Zhang, Laiyi Chua, Charles Ernest, William Macias, Terence Rooney, Lai San Tham

Abstract readClinical Trial, Phase IIMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in CPT: pharmacometrics & systems pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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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

6 authors.

Xin ZhangEli Lilly and Company, Indianapolis, Indiana, USA.
Laiyi ChuaEli Lilly and Company, Indianapolis, Indiana, USA.
Charles ErnestEli Lilly and Company, Indianapolis, Indiana, USA.
William MaciasEli Lilly and Company, Indianapolis, Indiana, USA.
Terence RooneyEli Lilly and Company, Indianapolis, Indiana, USA.
Lai San ThamEli Lilly and Company, Indianapolis, Indiana, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Baricitinib is an oral inhibitor of Janus kinases (JAKs), selective for JAK1 and 2. It demonstrated dose-dependent efficacy in patients with moderate-to-severe rheumatoid arthritis (RA) in a phase IIb study up to 24 weeks. Population pharmacokinetic/pharmacodynamic (PopPK/PD) models were developed to characterize concentration-time profiles and dose/exposure-response (D/E-R) relationships for the key efficacy (proportion of patients achieving American College of Rheumatology 20%, 50%, or 70% response rate) and safety endpoints (incidence of anemia) for the phase IIb study. The modeling suggested that 4 mg q.d. was likely to offer the optimum risk/benefit balance, whereas 2 mg q.d. had the potential for adequate efficacy. In addition, at the same total daily dose, a twice-daily regimen is not expected to provide an advantage over q.d. dosing for the efficacy or safety endpoints. The model-based simulations formed the rationale for key aspects of dosing, such as dose levels and dosing frequency for phase III development.

Indexed as

Models, BiologicalAdministration, OralAntirheumatic AgentsArthritis, RheumatoidAzetidinesClinical Trials, Phase III as TopicComputer SimulationDose-Response Relationship, DrugDouble-Blind MethodDrug Administration ScheduleHumansJanus Kinase 1Janus Kinase 2Predictive Value of TestsPurinesPyrazolesAntirheumatic AgentsAzetidinesbaricitinibJAK1 protein, humanJAK2 protein, humanJanus Kinase 1Janus Kinase 2PurinesPyrazolesSulfonamides

Identifiers

PMID28891251
PMCPMC5744177

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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.