Identification of predictive factors of DKA using a subgroup discovery algorithm
Event : EASD (European Association for the Study of Diabetes) Annual Meeting 2019, Barcelona, SpainAuthors: Angela Ibald-Mulli, Margot Blanchon, Alexandre Civet, Julia Hermann, Simon Gosset, Oussama Berguiga, Dieter Paar View video View publication Background and aims: Diabetic ketoacidosis (DKA) is a serious complication of type 1 diabetes (T1D), which is difficult to diagnose due to […]
Unmet medical needs in people with type 2 diabetes treated by insulin: results from the International Diabetes Management Practices Survey (IDMPS)
Event: EASD (European Association for the Study of Diabetes) Annual Meeting 2019, Barcelona, SpainAuthors: A. Ramachandran, JC. Mbanya, P. Aschner, JJ. Gagliardino, H. Ilkova, F. Lavalle, M; Shestakova, J-M. Chantelot, A. Shaunik, A. Alvarez, M. Rollot, J. CN Chan View Poster Background and aims Limited data exist on the impact of different insulin therapy regimes on […]
Projeter l’efficacité d’un traitement en vie réelle (VR) à partir d’une étude clinique randomisée (ECR) : une approche utilisant le suréchantillonnage
Event: 11ème Colloque Données de Santé en vie réelle 2019, AFCROs, Paris, France Authors: C. Esnault, M. Génin, S. Ekhtiari, A. Civet View Poster Introduction Bien qu’il n’y ait pas encore de consensus formel sur l’emploi des modèles statistiques pour estimer l’efficacité d’un traitement en VR, le besoin de son évaluation plus systématique est largement reconnu [1] […]
Identification of subgroups of patients with type 2 diabetes with differences in renal function preservation, comparing patients receiving sodium-glucose co-transporter-2 inhibitors with those receiving dipeptidyl peptidase-4 inhibitors, using a supervised machine-learning algorithm (PROFILE study): A retrospective analysis of a Japanese commercial medical database
Publisher: DOM (Diabetes, Obesity and Metabolism)Authors: F.L. Zhou MD, H. Watada MD, Y; Tajima MS, M. Berthelot MS, D. Kang MS, C. Esnault MS, Y. Shuto MD, H. Maegawa MD, D. Koya MD View publication Aims To investigate the effects of sodium-glucose co-transporter-2 (SGLT2) inhibitors vs. dipeptidyl peptidase-4 (DPP-4) inhibitors on renal function preservation (RFP) using real-world data of patients with type 2 diabetes in […]
Compare renal function preservation outcome of SGLT2 Inhibitor vs. DPP4 Inhibitor in patients with type 2 diabetes: a retrospective cohort study of Japanese commercial database with advanced analytics approach
Event: ISPOR Europe 2018, Barcelona, Spain Authors: F.L. Zhou, H. Watada, Y. Tajima, M. Berthelot, D. Kang, C. Esnault, Y. Shuto, H. Maegawa, D. Koya View Poster Background Tofogliflozin, a highly selective sodium/glucose cotransporter 2 inhibitor (SGLT2i), was approved in Japan for Type 2 Diabetes Mellitus (T2DM) in May 2014. It is marketed as Apleway/Deberza, […]
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 […]
A predictive model for risk of early grade ≥ 3 infection in patients with multiple myeloma not eligible for transplant: analysis of the FIRST trial
Publisher: Leukemia (Nature)Authors: C. Dumontet, C; Hulin, M.A. Dimopoulos, A. Belch, A. Dispenzieri, H. Ludwig, P. Rodon, J.V. Droogenbroeck, L. Qiu, M. Cavo, A.V. de Velde, J.J. Lahuerta, O. Allangba, J.H. Lee, E.Boyle, A. Perrot, P. Moreau, S. Manier, M. Attal, M. Roussel, M. Mohty, J.Y. Mary, A. Civet, B. Costa, A. Tinel, Y. Gaston-Mathé, T. Facon […]
Bioinformatics modelling of baseline characteristics to predict clinical outcomes and responses in the LixiLan-L trial
Event: International Diabetes Federation (IDF) Congress, Abu Dhabi, UAE Authors: P. Fogel, A. Civet, T. Fan, A. Shaunik, C. Brulle-Wohlhueter, Y. Gaston-Mathe View Poster Background Identifying categories of patients with diabetes sharing common characteristics and analysing clinical outcomes in these groups may lead to better understanding of patient diversity and generate hypotheses on disease-driving mechanisms. […]
Using machine learning algorithms to identify predictive factors of clinical outcomes with iGlarLixi or iGlar in the LixiLan-L trial
Event: Annual Meeting of the European Association for the Study of Diabetes (EASD) 2017, Lisbon, Portugal Authors: Y. Gaston-Mathé, T. Fan, A. Shaunik, C.Brulle-Wohlhueter, A. Civet View Poster
MMS19 as a potential predictive marker of adjuvant chemotherapy benefit in resected non-small cell lung cancer
Publisher: Cancer BiomarkersAuthors: J. Adam, T. Sourisseau, K.A. Olaussen, A. Robin, C.Q. Zhu, A. Templier, A. Civet, P. Girard, V. Lazar, P. Validire, M. S. Tsao, J.-C. Soria, B. Besse View publication Background Resectable non-small cell lung cancer (NSCLC) treatment options most often consist of surgical resection along with adjuvant chemotherapy (ACT). The benefit of ACT however […]
