Dr. Hélène JACQUMIN GADDA,PhD, Research Director at Inserm, BIOSTAT Director
Objectives
The main objective of the team is the development of statistical methods for time-dependent data coming from either observational cohort studies, clinical trials or case-control studies with the aim to answer clinical and public health questions regarding chronic diseases: future burden, risk factors, individual prediction, underlying pathological mechanisms, and treatment effects.
Research area
In the past five years the team worked on two main topics: multivariate models for time-dependent data and model-based estimation of public health indicators. Our main domain of research focus on the development of multivariate dynamic models for the analysis of censored time-to-events and/or repeated measures of longitudinal data accounting for complex observation schemes. These works are motivated by the study of the natural history of chronic diseases such as the Alzheimer disease or the Multi-System Atrophy, the investigation of the impact of time-dependent exposures, or the validation of surrogate markers for clinical trials in cancer research. Parametric and semiparametric estimation procedures for frailty models for correlated time-to-events, clustered data and/or recurrent events as well as joint models for event times and longitudinal markers were implemented in the R-package Frailtypack. Another field of research regards the extension of mixed models using latent classes and/or latent processes for the analysis of multiple longitudinal outcomes with non-standard distributions in heterogeneous populations. We proposed the R-package LCMM that enables the estimation of latent class mixed models, joint latent class mixed models and mixed models for curvilinear univariate or multivariate longitudinal outcomes. These models were motivated by the analysis of cognitive decline in cohort studies. They account for the population heterogeneity and the issues raised by the metrologic properties of measurement tools of cognition and autonomy (high correlation between markers measuring one or several underlying processes, ordinal data, non-standard asymmetric distributions with floor and/or ceiling effects and unequal sensitivity to changes). We also developed methods for the estimation of Illness-Death model accounting for interval-censoring (Package SmoothHazard). Tools for computing individual prediction and evaluating predictive abilities of these models are also implemented.
Relying on multi-state methodology, we proposed several approaches to forecast the future burden of neurologic diseases and assess the expected impact of intervention scenarios targeting their modifiable risk factors. Depending on the complexity of the investigated scenarios, the indicators for the future burden of the disease are computed analytically or using micro-simulations.
Our current projects particularly focus on causal questions and big-data issues in the framework of dynamic models. On one hand, causal questions are related to our research about the mechanism underlying pathological processes in chronic diseases, the role of some long-term exposure and the impact of social inequalities in health. We will investigate the causal interpretation of the multivariate models we develop and we will propose new methods for studying causality for censored time-to-events and/or time-dependent risk factors. On the other hand, as technological progress allow collecting a very large amount of data (genetics, biology, imaging, IoT data), we investigate new approaches that tackle high-dimensionality issues with respect to the number of time-dependent predictors, markers and outcomes.
Software
Find here all our files
R packages :
- FRAILTYPACK: R package for Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints
https://cran.r-project.org/web/packages/frailtypack/index.html
https://github.com/socale/frailtypack
- LCMM : Estimation of various models for longitudinal and time-to-event data based on latent classes and latent processes
https://cran.r-project.org/web/packages/lcmm/index.html
https://github.com/CecileProust-Lima/lcmm
- SmoothHazard: A R package for the estimation of illness-death models for interval-censored data
- CinLPN: Estimation of a dynamic causal model based on a system of latent processes
- marqLevAlg: A Parallelized General-Purpose Optimization Based on Marquardt-Levenberg Algorithm
https://cran.r-project.org/web/packages/marqLevAlg/index.html
https://github.com/VivianePhilipps/marqLevAlgParallel/
- JLPM: estimation of different joint models based on latent processes
- NormPsy: Normalisation of Mini Mental State Examination (MMSE)
- weightQuant: Estimation of observation-specific weights for incomplete longitudinal data with selection by death and bootstrap inference procedure for weighted quantile regressions
- MCSPCD :Monte Carlo Simulation for Projections of epidemiological burden of Chronic Disease and evaluation of impact of changes in risk factor distribution for a given year
- QoLSEM: Estimation of a structural equation model for the global analysis of health-related quality of life data
- BQt: Bayesian estimation of quantile regression mixed models
- JMcuR: Estimation of joint models for repeated measurements and time-to-event data included a cure fraction
Other programs :
- CPMCGLM : correction de la p-valeur après plusieurs codages dans les modèles linéaires généralisés
- R code for sparse conditional logistic regression
- PSPMCM: Macro SAS pour l’estimation de modèles de survie de mélange avec une fraction non à risque (Mixture Cure Models)
- MKVPCI : Programme pour l’estimation des modèles de Markov avec intensités de transition constantes par morceaux et covariables.
- Projection with Semi-Markov Model
Carreer
If you are interested by research in Biostatistics and more generally Statistics applied to health, send a motivated application to sandrine.darmigny@u-bordeaux.fr. Our biostatistics team welcomes interns, PhD students and postdoctoral researchers each year.
2021 Key Publications
Carles S, Tadde BO, Berr C, Helmer C, Jacqmin-Gadda H, Carriere I, Proust-Lima C. Dynamic reciprocal relationships between cognitive and functional declines along the Alzheimer’s disease continuum in the prospective COGICARE study. Alzheimers Res Ther. 2021 Sep 3;13(1):148. https://doi.org/10.1186/s13195-021-00887-4
Castel C, Sommen C, Strat YL, Alioum A. A multi-state Markov model using notification data to estimate HIV incidence, number of undiagnosed individuals living with HIV, and delay between infection and diagnosis: Illustration in France, 2008-2018. Stat Methods Med Res. 2021 Nov:9622802211032697. https://doi.org/10.1177/09622802211032697
de Courson H, Ferrer L, Barbieri A, Tully PJ, Woodward M, Chalmers J, Tzourio C, Leffondre K. Impact of Model Choice When Studying the Relationship Between Blood Pressure Variability and Risk of Stroke Recurrence. Hypertension. 2021 Nov;78(5):1520-6. https://doi.org/10.1161/hypertensionaha.120.16807
Dinart D, Bellera C, Rondeau V. Sample size estimation for cancer randomized trials in the presence of heterogeneous populations. Biometrics. 2021 Jul 9. https://doi.org/10.1111/biom.13527
Emura T, Sofeu CL, Rondeau V. Conditional copula models for correlated survival endpoints: Individual patient data meta-analysis of randomized controlled trials. Stat Methods Med Res. 2021 Oct 9:9622802211046390. https://doi.org/10.1177/09622802211046390
Kabore R, Ferrer L, Couchoud C, Hogan J, Cochat P, Dehoux L, Roussey-Kesler G, Novo R, Garaix F, Brochard K, Fila M, Parmentier C, Fournier MC, Macher MA, Harambat J, Leffondre K. Dynamic prediction models for graft failure in paediatric kidney transplantation. Nephrol Dial Transplant. 2021 Apr 26;36(5):927-35. https://doi.org/10.1093/ndt/gfaa180
Philipps VH, Boris P. Prague, Melanie Commenges, Daniel Proust-Lima, Cecile. Robust and Efficient Optimization Using a Marquardt-Levenberg Algorithm with R Package marqLevAlg. R Journal. 2021 Dec;13(2):365-79.
Wagner M, Grodstein F, Leffondre K, Samieri C, Proust-Lima C. Time-varying associations between an exposure history and a subsequent health outcome: a landmark approach to identify critical windows. BMC Med Res Methodol. 2021 Nov 27;21(1):266. https://doi.org/10.1186/s12874-021-01403-w
Ben-Hassen C, Helmer C, Berr C, Jacqmin-Gadda H. Five-Year Dynamic Prediction of Dementia Using Repeated Measures of Cognitive Tests and a Dependency Scale. Am J Epidemiol. 2022 Feb 19;191(3):453-64. https://doi.org/10.1093/aje/kwab269
Rouanet A, Avila-Rieger J, Dugravot A, Lespinasse J, Stuckwisch R, Merrick R, Anderson E, Long L, Helmer C, Jacqmin-Gadda H, Dufouil C, Judd S, Manly J, Sabia S, Gross A, Proust-Lima C. How Selection Over Time Contributes to the Inconsistency of the Association Between Sex/Gender and Cognitive Decline Across Cognitive Aging Cohorts. Am J Epidemiol. 2022 Feb 19;191(2):441-52. https://doi.org/10.1093/aje/kwab227
Details
Centre de recherche INSERM U1219
Université de Bordeaux – ISPED
146 rue Léo-Saignat
33076 BORDEAUX cedex
Tél : +33 (0)5 57 57 13 93
Tél : +33 (0)5 57 57 95 68
Fax : +33 (0)5 56 24 00 81
Informations
News
- 12 Feb 2020
Biostatistics Conferences 2020
These events have been organised by Bordeaux Population Health – UMR 1219 and the Public Health Department of…
- 11 Feb 2020
Inserm Workshop 261 – Recent advances in statistical analysis of survival data – May and Sept 2020
Registration deadline: March 6, 2020 Organizers: Hélène JACQMIN-GADDA (Inserm U1219, Bordeaux), Aurélien LATOUCHE (Inserm U900/Cnam, Paris), Virginie RONDEAU…
Members
- Ahmadou Alioum
- Antoine Barbieri
- Ariane Bercu
- Jérémy Chéradame
- Leonie Courcoul
- Sandrine Darmigny
- Hugues de Courson
- Anthony Devaux
- Bénédicte Driollet
- Helene Jacqmin-Gadda
- Pierre Joly
- Johann KUHN
- Kateline Le Bourdonnec
- Quentin Le Coënt
- Lisa Le Gall
- Karen Leffondre
- Gaelle Munsch
- Bessekon Serge NIANGORAN
- Viviane Philipps
- Cécile Proust-Lima
- Manel Rakez
- Virginie Rondeau
- Anaïs Rouanet
- Tiphaine SAULNIER
