Evidence map›Paper›PMID 20358280›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2010

Longitudinal aggregate data model-based meta-analysis with NONMEM: approaches to handling within treatment arm correlation.

Jae Eun Ahn, Jonathan L French

Abstract read
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In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 20 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 20 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

35 citing papers in PubMed, 20 syntheses or guidelines pooled it.

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  15. Quantitative analysis of efficacy and associated factors of calcium intake on bone mineral density in postmenopausal women.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2017
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  17. Comparative efficacy of nonhormonal drugs on menopausal hot flashes.European journal of clinical pharmacology · 2016
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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.

Jae Eun AhnGlobal Pharmacometrics, Pfizer Inc., 50 Pequot Ave. MS 6025-A2249, New London, CT 06320, USA. jaeeun.ahn@pfizer.com
Jonathan L French

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Literature data are often reported as multiple (longitudinal) mean outcomes observed in several groups of patients within a study. Observations within a study are correlated because the patients come from a common population, and the mean observations over time within a treatment arm are correlated because they are based on the same set of patients. As a result, model-based meta-analysis may require more than two levels of random effects to correctly characterize this correlation structure. Using simulation, we explored and evaluated ways to implement multi-level random effects in NONMEM. Simulation models that were linear and non-linear in the random effects were investigated. We compared estimation models that included study and/or treatment arm-level random effects, with and without residual correlation. With all estimation strategies, the fixed random effects parameters were accurately estimated. With regard to correctly characterizing the variability, models that accounted for correlation within a study and treatment arm over time were the best in some situations, while models that accounted for study-level correlation only were better in others. Models that included only treatment arm-level random effects were not superior in any scenario.

Indexed as

Meta-Analysis as TopicModels, StatisticalClinical Trials as TopicComputer SimulationData Interpretation, StatisticalDose-Response Relationship, DrugHumansLongitudinal StudiesOutcome Assessment, Health Care

Identifiers

PMID20358280

What OpenQuestion holds

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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.