Evidence map›Paper›PMID 29569841›Full record

ReviewCPT: pharmacometrics & systems pharmacology2018

Many Flavors of Model-Based Meta-Analysis: Part II - Modeling Summary Level Longitudinal Responses.

Martin Boucher, Meg Bennetts

Abstract readReview
In one paragraph

Review in CPT: pharmacometrics & systems pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 8 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

15 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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  14. Model-informed drug discovery and development approaches to inform clinical trial design and regulatory decisions: A primer for the MENA region.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024
    Review
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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

2 authors.

Martin BoucherDepartment of Pharmacometrics, Pfizer Ltd, Sandwich, Kent, UK.
Meg BennettsDepartment of Pharmacometrics, Pfizer Ltd, Sandwich, Kent, UK.ORCID 0000-0001-5198-5274

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Meta-analyses typically assess comparative treatment response for an end point at specific timepoints across studies. However, during drug development, it is often of interest to understand the response time-course of competitor compounds for a variety of purposes. Examples of such application include informing study design and characterizing the onset, maintenance, and offset of action. This tutorial acts as a "points for consideration" document, reviews relevant literature, and fits a longitudinal model to an example dataset.

Indexed as

Drug DevelopmentHumansLongitudinal StudiesMeta-Analysis as TopicModels, TheoreticalResearch DesignTreatment Outcome

Identifiers

PMID29569841
PMCPMC5980518

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.