Nos publications

@article{PERROT2025,

title = {Survival, Years of Life Lost and Attrition Rates in Multiple Myeloma Patients in France},

author = {Aurore Perrot and Fanny Raguideau and Helene Denis and Martin Prodel and Matthieu Javelot and Marie Pierres and Cyrille Touzeau},

url = {https://www.sciencedirect.com/science/article/pii/S2152265025000801},

doi = {https://doi.org/10.1016/j.clml.2025.03.004},

issn = {2152-2650},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Clinical Lymphoma Myeloma and Leukemia},

abstract = {Background 

In a context of strong evolution of multiple myeloma (MM) treatment paradigm, real-world data allow a better understandingthe patients' medical needs. 

Methods 

The present analyses from the MYLORD study were designed to provide recent data on MM patients: characteristics, overall survival (OS), years of life lost (YLL) and attrition rates, using the French National Health Insurance Database (SNDS). It is based on a cohort of 33,032 MM patients who initiated a frontline therapy from 2014 to 2021 in France and who were followed until 2021. 

Results 

The 5-year OS rate is estimated at 51.9% (95% CI: 51.2–52.6). This rate is 78.3% (95% CI: 77.1–79.5) for patients with frontline autologous stem cell transplant (L1T) and 43.6% (95% CI: 42.8–44.4) for those without transplant (L1NT). The excess of mortality in MM patients is revealed by 12.3 YLL versus the matched general population and is higher in L1T patients than those L1NT (17 vs. 11 years). The attrition rate is important in MM patients with 38% of patients who did not benefit from at least 2 lines of treatment and is higher in L1NT patients than those in L1T (41% vs. 29%). Also, the majority of L1NT patients did not receive a L2 because of death, whereas it is because of stay in line status for L1T patients. 

Conclusion 

These results emphasize the urgency to treat MM patients with the best and tailored treatment strategy available, for all MM patients beneficiating or not from a transplant in frontline therapy. Further studies will be needed to assess the impact of new therapeutic options in real life.},

keywords = {biostatistics, pathways},

pubstate = {published},

tppubtype = {article}

}

@article{luu2025lucien,

title = {LUCIEN–Étude non interventionnelle sur les délais et les coûts des parcours diagnostiques du cancer du poumon primitif: analyse de processus (process mining)},

author = {VP Luu and Hélène Denis and L Bensimon and I Durand-Zaleski and L Greillier and P Thomas and M Wislez and A Panes and Martin Prodel and M Apert and others},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Revue des Maladies Respiratoires Actualités},

volume = {17},

number = {1},

pages = {245–246},

publisher = {Elsevier Masson},

keywords = {pathways, process mining},

pubstate = {published},

tppubtype = {article}

}

@article{de2024correction,

title = {Correction: Explaining predictive factors in patient pathways using autoencoders},

author = {Hugo De Oliveira and Martin Prodel and Ludovic Lamarsalle and Vincent Augusto and Xiaolan Xie},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {PloS one},

volume = {19},

number = {12},

pages = {e0315113},

keywords = {auto-encoders, pathways},

pubstate = {published},

tppubtype = {article}

}

@article{laurent2023modelisation,

title = {Modélisation des parcours de soins dans la maladie d'Alzheimer: utilisation d'une méthode de «process mining»},

author = {Marie Laurent and Martin Prodel and Alexandre Civet and Alexandre Vainchtock and Claire Moutet and Virginie Dauphinot and Pierre Krolak-Salmon},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Revue d'Épidémiologie et de Santé Publique},

volume = {71},

pages = {101444},

publisher = {Elsevier},

keywords = {pathways, process mining},

pubstate = {published},

tppubtype = {article}

}

@article{de2024explaining,

title = {Explaining predictive factors in patient pathways using autoencoders},

author = {Hugo De Oliveira and Martin Prodel and Ludovic Lamarsalle and Vincent Augusto and Xiaolan Xie},

doi = {10.1371/journal.pone.0277135},

year  = {2022},

date = {2022-11-10},

urldate = {2024-01-01},

journal = {PLOS ONE},

volume = {17},

number = {12},

publisher = {PUBLIC LIBRARY SCIENCE 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA},

keywords = {auto-encoders, pathways},

pubstate = {published},

tppubtype = {article}

}

@article{de2022explaining,

title = {Explaining predictive factors in patient pathways using autoencoders},

author = {Hugo De Oliveira and Martin Prodel and Ludovic Lamarsalle and Vincent Augusto and Xiaolan Xie},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Plos one},

volume = {17},

number = {11},

pages = {e0277135},

publisher = {Public Library of Science San Francisco, CA USA},

keywords = {auto-encoders, pathways},

pubstate = {published},

tppubtype = {article}

}

@article{de2020bow,

title = {“Bow-tie” optimal pathway discovery analysis of sepsis hospital admissions using the Hospital Episode Statistics database in England},

author = {Hugo De Oliveira and Martin Prodel and Ludovic Lamarsalle and Matt Inada-Kim and Kenny Ajayi and Julia Wilkins and Sara Sekelj and Sue Beecroft and Sally Snow and Ruth Slater and others},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {JAMIA open},

volume = {3},

number = {3},

pages = {439–448},

publisher = {Oxford University Press},

keywords = {pathways, process mining},

pubstate = {published},

tppubtype = {article}

}

@article{prodel2019etude,

title = {Étude des parcours de soins des patients diabétiques éligibles au programme «Sophia» par une technique de «Process Mining», à partir des données du Système national des données de santé},

author = {Martin Prodel and Claire Leboucher and Alexandre Vainchtock and Marie Cavillon and Roland Cash and A-S Aguade and Emmanuel Gomez},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

journal = {Revue d'Épidémiologie et de Santé Publique},

volume = {67},

pages = {S195},

publisher = {Elsevier},

keywords = {pathways, process mining},

pubstate = {published},

tppubtype = {article}

}

@article{prodel2018diversite,

title = {Diversité des parcours de soins des patients atteints de cancer du poumon entre quatre régions françaises: définition de mesures de dissimilarité},

author = {Martin Prodel and Cécile Blein and J Fernandez and C Chouaid},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Revue d'Épidémiologie et de Santé Publique},

volume = {66},

pages = {S24},

publisher = {Elsevier},

keywords = {pathways},

pubstate = {published},

tppubtype = {article}

}

@article{prodel2018pcn278,

title = {Diversity of patients pathways with lung cancer between 4 French regions: definition of dissimilarity measures},

author = {Martin Prodel and Cécile Blein and J Fernandes and C Chouaid},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Value in Health},

volume = {21},

pages = {S61},

publisher = {Elsevier},

keywords = {pathways},

pubstate = {published},

tppubtype = {article}

}

@article{prodel2017analyses,

title = {Analyses de sensibilité des comorbidités sur le parcours de soin des patients implantés d’un défibrillateur cardiaque à partir des données PMSI},

author = {Martin Prodel and Ludovic Lamarsalle and Alexandre Vainchtock},

year  = {2017},

date = {2017-01-01},

urldate = {2017-01-01},

journal = {Revue d'Épidémiologie et de Santé Publique},

volume = {65},

pages = {S112–S113},

publisher = {Elsevier},

keywords = {pathways, process mining, simulation},

pubstate = {published},

tppubtype = {article}

}

@article{prodel2015modeling,

title = {Modeling Of Clinical Pathways In The Implantation Of Cardioverter Defibrillators From 2006 To 2013 Using The French Hospital PMSI Database},

author = {Martin Prodel and Vincent Augusto and Baptiste Jouaneton and Ludovic Lamarsalle and Xiaolan Xie},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {Value in Health},

volume = {18},

number = {7},

pages = {A366},

publisher = {Elsevier},

keywords = {pathways, process mining},

pubstate = {published},

tppubtype = {article}

}