Evidence map›Paper›PMID 36947282›Full record

SynthesisJournal of pharmacokinetics and pharmacodynamics2023

Joint longitudinal model-based meta-analysis of FEV

Carolina Llanos-Paez, Claire Ambery, Shuying Yang, Misba Beerahee, Elodie L Plan, Mats O Karlsson

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of pharmacokinetics and pharmacodynamics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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.

Carolina Llanos-PaezDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Claire AmberyClinical Pharmacology Modelling and Simulation, GSK, London, UK.
Shuying YangClinical Pharmacology Modelling and Simulation, GSK, London, UK.
Misba BeeraheeClinical Pharmacology Modelling and Simulation, GSK, London, UK.
Elodie L PlanDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Mats O KarlssonDepartment of Pharmacy, Uppsala University, Uppsala, Sweden. mats.karlsson@farmaci.uu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Model-based meta-analysis (MBMA) is an approach that integrates relevant summary level data from heterogeneously designed randomized controlled trials (RCTs). This study not only evaluated the predictability of a published MBMA for forced expiratory volume in one second (FEV

Indexed as

Pulmonary Disease, Chronic ObstructiveForced Expiratory VolumeHumansChronic obstructive pulmonary diseaseExacerbation rateForced expiratory volume in one secondModel-based meta-analysis

Identifiers

PMID36947282
PMCPMC10374752

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.