Evidence map›Paper›PMID 33154677›Full record

ReviewClinical epidemiology2020

Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches.

Hermine Lore Nguena Nguefack, M Gabrielle Pagé, Joel Katz, Manon Choinière, Alain Vanasse, Marc Dorais, Oumar Mallé Samb, Anaïs Lacasse

Abstract readReview
In one paragraph

Review in Clinical epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 300 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
300citing papers in PubMed, 4 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

300 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Life Course Trajectories of Body Mass Index and Risk of Cancer in Adulthood: Systematic Review and Meta-Analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
    Pooled it
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  12. Built Environment and Loneliness Trajectories Among Middle-Aged and Older Adults in China.Journal of urban health : bulletin of the New York Academy of Medicine · 2026
    Article
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  15. Identifying the trajectory of SPPADE symptoms in patients with cancer using electronic health record data.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
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  17. Trajectory analysis in clinical research.Clinical kidney journal · 2026
    Review
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  20. Article

240 more citing papers are in PubMed but not listed here.

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

8 authors.

Hermine Lore Nguena NguefackDépartement des Sciences de la santé, Université du Québec en Abitibi-Témiscamingue (UQAT), Rouyn-Noranda, Québec, Canada.
M Gabrielle PagéCentre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada.ORCID 0000-0002-7742-2717
Joel KatzDepartment of Psychology, Faculty of Health, York University, Toronto, Ontario, Canada.ORCID 0000-0002-8686-447X
Manon ChoinièreCentre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada.ORCID 0000-0001-9593-8883
Alain VanasseDépartement de médecine de famille et de médecine d'urgence, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Marc DoraisStatSciences Inc., Notre-Dame-de-lL'île-Perrot, Québec, Canada.
Oumar Mallé SambDépartement des Sciences de la santé, Université du Québec en Abitibi-Témiscamingue (UQAT), Rouyn-Noranda, Québec, Canada.
Anaïs LacasseDépartement des Sciences de la santé, Université du Québec en Abitibi-Témiscamingue (UQAT), Rouyn-Noranda, Québec, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trajectory modelling techniques have been developed to determine subgroups within a given population and are increasingly used to better understand intra- and inter-individual variability in health outcome patterns over time. The objectives of this narrative review are to explore various trajectory modelling approaches useful to epidemiological research and give an overview of their applications and differences. Guidance for reporting on the results of trajectory modelling is also covered. Trajectory modelling techniques reviewed include latent class modelling approaches, ie, growth mixture modelling (GMM), group-based trajectory modelling (GBTM), latent class analysis (LCA), and latent transition analysis (LTA). A parallel is drawn to other individual-centered statistical approaches such as cluster analysis (CA) and sequence analysis (SA). Depending on the research question and type of data, a number of approaches can be used for trajectory modelling of health outcomes measured in longitudinal studies. However, the various terms to designate latent class modelling approaches (GMM, GBTM, LTA, LCA) are used inconsistently and often interchangeably in the available scientific literature. Improved consistency in the terminology and reporting guidelines have the potential to increase researchers' efficiency when it comes to choosing the most appropriate technique that best suits their research questions.

Indexed as

cluster analysisgroup-based trajectory modellinggrowth mixture modellinglatent class analysislatent transition analysismodelling techniquessequence analysis

Identifiers

PMID33154677
PMCPMC7608582

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.