Evidence map›Paper›PMID 22300396›Full record

ArticleBritish journal of clinical pharmacology2012

Integration of data from multiple sources for simultaneous modelling analysis: experience from nevirapine population pharmacokinetics.

Elin Svensson, Jan-Stefan van der Walt, Karen I Barnes, Karen Cohen, Tamara Kredo, Alwin Huitema, Jean B Nachega, Mats O Karlsson, Paolo Denti

Abstract readValidation Study
In one paragraph

Article in British journal of clinical pharmacology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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

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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.

Elin SvenssonDepartment of Pharmaceutical Bioscience, Uppsala University, Sweden. elin.svensson@farmbio.uu.se
Jan-Stefan van der Walt
Karen I Barnes
Karen Cohen
Tamara Kredo
Alwin Huitema
Jean B Nachega
Mats O Karlsson
Paolo Denti

Funding

UNDERLYING MECHANISMS OF SCHISTOSOME/SNAIL COMPATIBILITYR01AI016137 · NIAID · OREGON STATE UNIVERSITY · PI BAYNE, CHRISTOPHER JEFFREY · 1989 to 2012
$3.1M
DOT-HAART for HIV-Infected South African AdultsR01AI055359 · NIAID · JOHNS HOPKINS UNIVERSITY · PI CHAISSON, RICHARD E. · 2003 to 2008
$2.6M
DOT-HARRT for HIV-Infected South African AdultsK23AI068582 · NIAID · JOHNS HOPKINS UNIVERSITY · PI NACHEGA, JEAN BISIMWA · 2006 to 2010
$652k
Underlying mechanisms of schistosome/snail compatibilityR21AI016137 · NIAID · OREGON STATE UNIVERSITY · PI BAYNE, CHRISTOPHER JEFFREY · 2001 to 2001
$273k
SCHISTOSOME-SNAIL COMPATIBILITY: UNDERLYING MECHANISMSR22AI016137 · NIAID · OREGON STATE UNIVERSITY · PI BAYNE, CHRISTOPHER JEFFREY · 1985 to 1991
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NIAID NIH HHS AI 016137NIAID NIH HHS AI 068582-01NIAID NIH HHS AI 5535901NIAID NIH HHS K23 AI068582NIAID NIH HHS R01 AI016137NIAID NIH HHS R21 AI016137
6 · The paper itself

Abstract

aimsTo propose a modelling strategy to efficiently integrate data from different sources in one simultaneous analysis, using nevirapine population pharmacokinetic data as an example.

methodsData from three studies including 115 human immunodeficiency virus-infected South African adults were used. Patients were on antiretroviral therapy regimens including 200 mg nevirapine twice daily and sampled at steady state. A development process was suggested, implemented in NONMEM7 and the final model evaluated with an external data set.

resultsA stepwise approach proved efficient. Model development started with the intensively sampled data. Data were added sequentially, using visual predictive checks for inspecting their compatibility with the existing model. Covariate exploration was carried out, and auxiliary regression models were designed for imputation of missing covariates. Nevirapine pharmacokinetics was described by a one-compartment model with absorption through two transit compartments. Body size was accounted for using allometric scaling. The model included a mixture of two subpopulations with different typical values of clearance, namely fast (3.12 l h(-1)) and slow metabolizers (1.45 l h(-1)), with 17% probability of belonging to the latter. Absorption displayed large between-occasion variability, and food slowed the absorption mean transit time from 0.6 to 2.5 h. Concomitant antitubercular treatment including rifampicin typically decreased bioavailability by 39%, with significant between-subject variability. Visual predictive checks of external validation data indicated good predictive performance.

conclusionsThe development strategy succeeded in integrating data from different sources to produce a model with robust parameter estimates. This work paves the way for the creation of a nevirapine mega-model, including additional data from numerous diverse sources.

Indexed as

Models, BiologicalAdultAgedAnti-HIV AgentsBiological AvailabilityDrug InteractionsFemaleFood-Drug InteractionsGastrointestinal TransitHIV InfectionsHumansMaleMiddle AgedNevirapineNonlinear DynamicsRegression AnalysisAnti-HIV AgentsNevirapine

Identifiers

PMID22300396
PMCPMC3477348

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.