ArticleBMC medical research methodology2016
Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues.
Article in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 4 of them syntheses that pooled it.
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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.
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Who cites it
91 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Joint modelling on clinical trials in clinical journals: a systematic review.BMC medical research methodology · 2026Pooled it
- Reflections on dynamic prediction of Alzheimer's disease: advancements in modeling longitudinal outcomes and time-to-event data.BMC medical research methodology · 2025Pooled it
- Informative presence and observation in routine health data: A review of methodology for clinical risk prediction.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- Getting the most out of intensive longitudinal data: a methodological review of workload-injury studies.BMJ open · 2018Pooled it
- Pairwise joint modeling of clustered and high-dimensional outcomes with covariate missingness in pediatric pneumonia care.Pharmaceutical statistics · 2022Trial
- Joint modelling of multivariate longitudinal clinical laboratory safety outcomes, concomitant medication and clinical adverse events: application to artemisinin-based treatment during pregnancy clinical trial.BMC medical research methodology · 2021Trial
- Interpreting ocular age estimates: source, output, evidence, and clinical meaning.Biogerontology · 2026Review
- DyVAESurv: A VAE-Enhanced Model for Dynamic Survival Analysis.Biometrical journal. Biometrische Zeitschrift · 2026Article
- On a Penalized Likelihood Approach for Joint Modeling of Longitudinal Covariates and Partly Interval-Censored Data-An Application to the Anti-PD1 Brain Collaboration Trial.Biometrical journal. Biometrische Zeitschrift · 2026Article
- Joint Models of Two Longitudinal Biomarkers and Clustered Survival Data for Cluster-Informed Dynamic Prediction With Application to Periodontitis.Statistics in medicine · 2026Article
- Methodological Considerations in Defining Disabling Disease Trajectories in Moderate-to-Severe Ulcerative Colitis.Journal of gastroenterology and hepatology · 2026Article
- Deep learning embedded latent class joint modelling of time-to-event and longitudinal data.Statistical methods in medical research · 2026Article
- Bayesian multivariate linear mixed-effects models with varied association structures.Statistical methods in medical research · 2026Article
- Time to Recovery From Severe Acute Malnutrition and Its Predictors Among Children Aged 6-59 Months in Ethiopia: A Bayesian Joint Modeling Approach.Maternal & child nutrition · 2026Article
- Multitask learning of longitudinal circulating biomarkers and clinical outcomes: identification of optimal machine-learning and deep-learning models.BMC medical informatics and decision making · 2026Article
- Joint modeling of longitudinal and time-to-event data for dynamic disease risk prediction using proteomics.Protein science : a publication of the Protein Society · 2026Article
- Detecting change-points in preclinical rheumatoid arthritis biomarkers using Bayesian multivariate segmented regression.medRxiv : the preprint server for health sciences · 2026Article
- Modelling longitudinal and time-to-event data: a phase IV simulation study comparing R package implementations of joint models with time-varying Cox proportional-hazards regression, and the two-stage approach.BMC medical research methodology · 2026Article
- Robustness of Joint Over Separate Models for Investigating Predictors of Blood Sugar Level and Time to First Remission Among Type I Diabetic Patients Under Treatment; a Retrospective Study Design.Health science reports · 2026Article
- Dynamic risk stratification in burn sepsis: methodological considerations and path forward.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
31 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundAvailable methods for the joint modelling of longitudinal and time-to-event outcomes have typically only allowed for a single longitudinal outcome and a solitary event time. In practice, clinical studies are likely to record multiple longitudinal outcomes. Incorporating all sources of data will improve the predictive capability of any model and lead to more informative inferences for the purpose of medical decision-making.
methodsWe reviewed current methodologies of joint modelling for time-to-event data and multivariate longitudinal data including the distributional and modelling assumptions, the association structures, estimation approaches, software tools for implementation and clinical applications of the methodologies.
resultsWe found that a large number of different models have recently been proposed. Most considered jointly modelling linear mixed models with proportional hazard models, with correlation between multiple longitudinal outcomes accounted for through multivariate normally distributed random effects. So-called current value and random effects parameterisations are commonly used to link the models. Despite developments, software is still lacking, which has translated into limited uptake by medical researchers.
conclusionAlthough, in an era of personalized medicine, the value of multivariate joint modelling has been established, researchers are currently limited in their ability to fit these models routinely. We make a series of recommendations for future research needs.
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Registered trials
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.