Internship – Quantitative, Patient Centered Outcomes
Office based in Lyon, France
3 month opportunity
¨ L’ENTREPRISE/COMPANY: MAPI SAS
¨ INTITULE DU THEME STAGE / TITLE OF THE INTERNSHIP
Classification of rare diseases using Orphanet database to enhance the potential of conducting significant studies on these diseases
¨ DOMAINE(S) COUVERT(S) PAR LE STAGE / FIELD COVERED BY THE INTERNSHIP
Objectif(s) du stage (problématique, missions, méthodologie…) / Objectives of the internship (issue to be solved, tasks, method…)
A rare disease, also referred to as an orphan disease, is any disease that affects a small percentage of the population.
Most rare diseases are genetic, and are present throughout a person’s entire life, even if symptoms do not immediately appear. In Europe, a disease or disorder is defined as rare when it affects less than 1 in 2000 citizens.
Rare diseases are characterized by a wide diversity of symptoms and signs that vary not only from disease to disease but also from patient to patient suffering from the same disease.
Relatively common symptoms can hide underlying rare diseases, leading to misdiagnosis.
As these diseases are rare, the understanding of their epidemiology and associated burden remains limited. For a better understanding of these diseases, COA (Clinical Outcomes Assessments) need to be used and specifically developed, if they do not exist. The limited population related to each rare disease limits the use and development of COA.
Orphanet is an international Consortium of 40 countries across the globe and a reference source of information on rare diseases whose mission is to improve the diagnosis, care and treatment of patients with rare diseases. Orphanet has developed a database describing more than 7000 rare diseases. Orphanet adapted the International Classification of Functioning, Disability and Health (ICF) developed by WHO in 2001 for a codification of rare diseases impacts on patient’s lives into 10 domains. A questionnaire was developed to cover these 10 domains and data were collected from medical experts, disability professionals and/or patient support groups/representatives. Functional consequences are collected by frequency, temporality, severity and loss of ability.
To overcome the lack of information, COA and patients in rare diseases, working on a classification of rare diseases using the data available in the Orphanet database would help considering conditions analogous in terms of symptoms, impacts, functional consequences, etc. that might serve as parallels to the experience in each specific rare disease. The first objective will be to find rare diseases that present similarities and define a proximity index of the rare diseases. The second objective will be to define homogeneous groups of rare diseases.
The proximity index and the homogeneous groups would facilitate investments and studies development (for instance, the possibility of using a larger population than only the population of one specific rare disease would facilitate the COA development and validation). This would also enhance the potential of conducting significant studies on these diseases.
Base de données / Databases
We have an on-going collaboration with Orphanet and the possibility of conducting analyses on their database.
Résultats attendus / Expected results
A proximity index of the rare diseases. Definition of homogeneous groups of rare diseases. A report summarizing the methods applied and the results obtained.
Principales méthodes statistiques utilisées (exemple : Analyse de données, régression logistique,….) / Main statistical methods to be used (e.g. : logistic regression…)
Different clustering approaches will be applied and the results obtained will be compared:
– Hierarchical clustering
– Hybrid clustering methods
– Model-based clustering
The clusters found will be then validated using statistical results but also using the clinical meaning of these clusters (discussions with experts).
Connaissances et aptitudes recherchées chez le stagiaire / Knowledge and abilities required for the intern
Knowledge : R programming, SAS programming and SPAD knowledge
Abilities : creative approach to problem solving, flexibility, communication skills, autonomy and rigor