Evidence map›Paper›PMID 29963075›Full record

ArticleFrontiers in genetics2018

Jointly Modelling Single Nucleotide Polymorphisms With Longitudinal and Time-to-Event Trait: An Application to Type 2 Diabetes and Fasting Plasma Glucose.

Mickaël Canouil, Beverley Balkau, Ronan Roussel, Philippe Froguel, Ghislain Rocheleau

Abstract read
In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Mickaël CanouilUniversité de Lille, UMR 8199-EGID, Lille, France.
Beverley BalkauCentre for Research in Epidemiology and Population Health, Villejuif, France.
Ronan RousselInstitut National de la Santé et de la Recherche Médicale U1138 (équipe 2: Pathophysiology and Therapeutics of Vascular and Renal Diseases Related to Diabetes, Centre de Recherches des Cordeliers), Paris, France.
Philippe FroguelUniversité de Lille, UMR 8199-EGID, Lille, France.
Ghislain RocheleauUniversité de Lille, UMR 8199-EGID, Lille, France.

Funding

European Research Council 294785
6 · The paper itself

Abstract

In observational cohorts, longitudinal data are collected with repeated measurements at predetermined time points for many biomarkers, along with other variables measured at baseline. In these cohorts, time until a certain event of interest occurs is reported and very often, a relationship will be observed between some biomarker repeatedly measured over time and that event. Joint models were designed to efficiently estimate statistical parameters describing this relationship by combining a mixed model for the longitudinal biomarker trajectory and a survival model for the time until occurrence of the event, using a set of random effects to account for the relationship between the two types of data. In this paper, we discuss the implementation of joint models in genetic association studies. First, we check model consistency based on different simulation scenarios, by varying sample sizes, minor allele frequencies and number of repeated measurements. Second, using genotypes assayed with the Metabochip DNA arrays (Illumina) from about 4,500 individuals recruited in the French cohort D.E.S.I.R. (

Indexed as

diabetesgeneticglycaemiajoint modellinglongitudinal biomarkersurvival analysis

Identifiers

PMID29963075
PMCPMC6010582

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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.