MAScINSIGHT: A Real-World Data Study to Deepen Knowledge and Management of McCune-Albright Syndrome - Study Protocol for an Observational Study within OHDSI

Introduction McCune-Albright syndrome (MAS) is a rare congenital disorder affecting endocrine, skeletal and dermatological systems. MAS is often coded as fibrous dysplasia (FD) in routine health data, which includes other conditions and does not allow precise identification. This coding gap complicates reliable epidemiological estimates and clinical characterization. The study MAScINSIGHT aims to address this by investigating MAS features within FD-coded cohorts. Methods and analysis MAScINSIGHT is a retrospective observational study using a federated network of data in the OMOP Common Data Model. Routine data from multiple sites will be analyzed within a federated setting to assess endocrine abnormalities and treatment patterns in patients with FD or MAS. Ethics and dissemination Analyses will be performed locally at the data partner, with only aggregate statistics made available and centrally analyzed. The study protocol was approved by the ethics committee (reference number: 2026-18760-retrospektiv). Findings will be disseminated through open-access publications and patient-oriented reports.

Authors

Institutions

Publication Details

Journal
medRxiv
Published
2026-10-26
DOI
https://doi.org/10.64898/2026.10.24.26366390
Primary Topic
Bone Tumor Diagnosis and Treatments
Type
preprint

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

MAScINSIGHT: A Real-World Data Study to Deepen Knowledge and Management of McCune-Albright Syndrome - Study Protocol for an Observational Study within OHDSI

Ines Reinecke, Christian Reich, Corinna Grasemann, Michéle Zoch et al.
medRxiv
Bone Tumor Diagnosis and Treatments
preprint

MAScINSIGHT: A Real-World Data Study to Deepen Knowledge and Management of McCune-Albright Syndrome - Study Protocol for an Observational Study within OHDSI

Ines Reinecke, Christian Reich, Corinna Grasemann, Michéle Zoch, Jens Weidner, Georg Christof Schwabe, J Bauer, Martin Sedlmayr, Angela Huebner, Katja Hoffmann, Joline Wernsmann, Clemens Hentrich, Kaety E. O. Mothes
preprint en

Abstract

Introduction McCune-Albright syndrome (MAS) is a rare congenital disorder affecting endocrine, skeletal and dermatological systems. MAS is often coded as fibrous dysplasia (FD) in routine health data, which includes other conditions and does not allow precise identification. This coding gap complicates reliable epidemiological estimates and clinical characterization. The study MAScINSIGHT aims to address this by investigating MAS features within FD-coded cohorts. Methods and analysis MAScINSIGHT is a retrospective observational study using a federated network of data in the OMOP Common Data Model. Routine data from multiple sites will be analyzed within a federated setting to assess endocrine abnormalities and treatment patterns in patients with FD or MAS. Ethics and dissemination Analyses will be performed locally at the data partner, with only aggregate statistics made available and centrally analyzed. The study protocol was approved by the ethics committee (reference number: 2026-18760-retrospektiv). Findings will be disseminated through open-access publications and patient-oriented reports.

medRxiv
Northeastern University (US), Johannes Gutenberg University Mainz (DE), University Medical Center of the Johannes Gutenberg University Mainz (DE), Medizinische Universität Lausitz - Carl Thiem (DE), Technische Universität Dresden (DE), Ruhr University Bochum (DE)
Technische Universität Dresden, Sächsische Landesbibliothek – Staats- und Universitätsbibliothek Dresden
Bone Tumor Diagnosis and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon