Clustering des trajectoires thérapeutiques pour la bronchopneumopathie chronique obstructive (BPCO) : comparaison des méthodes d’encodage de séquences
Event: 17ème Colloque Données de Santé en Vie Réelle de l’AFCROs, Paris, France Authors: Romane Pean, Nina Temam, Diane Vincent, Marie Génin, Pauline Guilmin View Presentation Introduction L’analyse des séquences thérapeutiques et évènements médicauxest essentielle pour optimiser la prise en charge des patients. Cependant, lacomplexité et variabilité de ces séquences posent un défi méthodologique. Leclustering […]
Real-World Data analysis on Fabry’s disease provide insights that may contribute to a more personalized patient care
The article “Cluster analysis of kidney function decline among males with Fabry disease in a large United States electronic health records database” has been published on April 14th 2023 in the Oxford Academic Journal on behalf of the European Renal Association. It was written in collaboration with Alexandra Chiorean, Nicole Lyn, Shaum Kabadi, Margot Blanchon, […]
Cluster Algorithm for Credible Subgroup Identification in Patients with Erectile Dysfunction Receiving Tadalafil: A Real-World Data Study
Event: ISPOR Global 2023, Boston, MA, USA Authors: KT. McVary, C. Daluwatte, RA Kloner, M. Montmerle, M. Rollot, P. Guilmin, M. Blanchon, N. Lambert, C. Esnault, A. Stewart, T. McGraw View Poster Objectives: This non-comparative, retrospective study aimed to characterize the profiles of erectile disfunction (ED) patients prescribed with tadalafil by clustering the homogenous subpopulations with different […]
Cluster analysis of kidney function decline among males with Fabry disease in a large United States electronic health records database
Publisher: ndt (Nephrology Dialysis Transplantation)Authors: A. Chiorean, N. Lyn, S. Kabadi, M. Blanchon, P. Hayat, P. Loustalot, M. Maski, M. Montmerle, E. Ponce View publication Background Fabry disease (FD) is an X-linked lysosomal storage disorder caused by deficient α-galactosidase A activity. The spectrum of disease includes phenotypes ranging from ‘classic’ to ‘later-onset’, with varying kidney disease progression. Identifying patterns of declining kidney function […]
Qluster: An easy-to-implement generic workflow for robust clustering of health data
Publisher: Frontiers in Artificial IntelligenceAuthors: C. Esnault, M. Rollot, P. Guilmin, J-D. Zucker View publication Background The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted population in real life. Nevertheless, […]
Epidemiology, treatment patterns, clinical outcomes, and disease burden among patients with immune‐mediated thrombotic thrombocytopenic purpura in the United States
Publisher: Research and practice in thrombosis and haemostasis (rpth)Authors: A. Adeyemi, F. Razakariasa, A. Chiorean, R. de Passos Sousa View publication Background Immune‐mediated thrombotic thrombocytopenic purpura (iTTP) is a life‐threatening thrombotic microangiopathy. Due to its rarity, epidemiology and real‐world outcomes data are scarce. Objectives The aim was to assess epidemiology, treatment patterns, clinical outcomes, and […]
Clustered analysis of Fabry disease progression in a large US electronic health records database (Optum Market Clarity): A retrospective observational cohort study
Event: WORLD Symposium 2022, San Diego, CA, USA Authors: A. Chiorean, S. Kabadi, P. Hayat, M. Montmerle, E. Ponce, M. Blanchon, N. Lyn, M. Maski View Poster Introduction: As the spectrum of Fabry phenotypes remains uncertain, the study objective was to describe patterns of progression in untreated Fabry disease (FD) patients from a large electronic […]
A machine learning algorithm can identify clusters of patients with favourable glycaemic outcomes in a pooled European Gla-300 studies (REALI): Novel signposts for clinicians?
Event: EASD Annual Meeting 2018, Berlin, Germany Authors: M. Rollot, M. Bonnemaire, C. Brulle-Wohlhueter, L. Pedrazzini, E. Boëlle-Le Corfec, G. Bigot, M. Didac, R. Bonadonna, P. Gourdy, D. Müller-Wieland, O. Hacman, A. Chiorean, N. Freemantle View Poster Background and aims Detecting consistent patterns of interest can be performed using data-driven subgroup discovery algorithms. These may be instrumental […]
