Fabian Model

3.7k total citations · 1 hit paper
42 papers, 2.6k citations indexed

About

Fabian Model is a scholar working on Pathology and Forensic Medicine, Molecular Biology and Oncology. According to data from OpenAlex, Fabian Model has authored 42 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Pathology and Forensic Medicine, 12 papers in Molecular Biology and 10 papers in Oncology. Recurrent topics in Fabian Model's work include Multiple Sclerosis Research Studies (21 papers), Epigenetics and DNA Methylation (7 papers) and Peripheral Neuropathies and Disorders (6 papers). Fabian Model is often cited by papers focused on Multiple Sclerosis Research Studies (21 papers), Epigenetics and DNA Methylation (7 papers) and Peripheral Neuropathies and Disorders (6 papers). Fabian Model collaborates with scholars based in Switzerland, United States and Canada. Fabian Model's co-authors include Catherine Lofton–Day, Andrew Sledziewski, Christian Pilarsky, Theo deVos, Robert Grützmann, Stephen L. Hauser, Ludwig Kappos, Volker Liebenberg, Matthias Schuster and Reimo Tetzner and has published in prestigious journals such as New England Journal of Medicine, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Fabian Model

40 papers receiving 2.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Contribution of Relapse-Independent Progression vs Relapse-Associated Worsening to Overall Confirmed Disability Accumulation in Typical Relapsing Multiple Sclerosis in a Pooled Analysis of 2 Randomized Clinical Trials

2020 344 citations Ludwig Kappos, Jerry S. Wolinsky et al. JAMA Neurology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Fabian Model Switzerland	16	1.2k	1.1k	832	653	369	42	2.6k
Thomas Zwingers Germany	16	1.0k 0.8×	386 0.3×	1.2k 1.4×	446 0.7×	224 0.6×	30	2.2k
Silke Laßmann Germany	31	387 0.3×	1.2k 1.1×	1.1k 1.3×	431 0.7×	453 1.2×	87	2.7k
Huimin Geng United States	31	821 0.7×	1.9k 1.6×	768 0.9×	372 0.6×	820 2.2×	115	3.3k
Claudia Döring Germany	28	849 0.7×	1.1k 0.9×	712 0.9×	686 1.1×	461 1.2×	82	2.3k
Delphine Loussouarn France	28	265 0.2×	976 0.9×	694 0.8×	574 0.9×	333 0.9×	76	2.3k
Florian Scherer Germany	12	536 0.4×	1.6k 1.4×	1.1k 1.3×	1.5k 2.3×	789 2.1×	45	3.5k
Chloé B. Steen United States	17	438 0.4×	1.7k 1.5×	1.2k 1.5×	851 1.3×	1.2k 3.3×	29	3.8k
Benoît Lhermitte France	18	336 0.3×	821 0.7×	710 0.9×	647 1.0×	160 0.4×	77	2.5k
Juan Manuel Sepúlveda-Sánchez Spain	29	252 0.2×	1.2k 1.1×	1.5k 1.8×	637 1.0×	844 2.3×	181	3.9k
Andrew M. Donson United States	35	290 0.2×	1.7k 1.5×	632 0.8×	536 0.8×	462 1.3×	112	3.0k

Countries citing papers authored by Fabian Model

Since Specialization

Citations

This map shows the geographic impact of Fabian Model's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fabian Model with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabian Model more than expected).

Fields of papers citing papers by Fabian Model

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fabian Model. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fabian Model. The network helps show where Fabian Model may publish in the future.

Co-authorship network of co-authors of Fabian Model

This figure shows the co-authorship network connecting the top 25 collaborators of Fabian Model. A scholar is included among the top collaborators of Fabian Model based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fabian Model. Fabian Model is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Burton, Barbara K., Deepa Rajan, Simon A. Jones, et al.. (2025). An Intravenous Brain-Penetrant Enzyme Therapy for Mucopolysaccharidosis II. New England Journal of Medicine. 394(1). 39–50.

Rouzic, Erwan Muros‐Le, Stefan Braune, Arnfin Bergmann, et al.. (2024). Five-year efficacy outcomes of ocrelizumab in relapsing multiple sclerosis: A propensity-matched comparison of the OPERA studies with other disease-modifying therapies in real-world lines of treatments. SHILAP Revista de lepidopterología. 16. 2699787795–2699787795. 1 indexed citations

Hauser, Stephen L., Amit Bar‐Or, Martin S. Weber, et al.. (2023). Association of Higher Ocrelizumab Exposure With Reduced Disability Progression in Multiple Sclerosis. Neurology Neuroimmunology & Neuroinflammation. 10(2). 28 indexed citations

Bar‐Or, Amit, Christopher Harp, Corrado Bernasconi, et al.. (2023). Blood neurofilament light levels predict non-relapsing progression following anti-CD20 therapy in relapsing and primary progressive multiple sclerosis: findings from the ocrelizumab randomised, double-blind phase 3 clinical trials. EBioMedicine. 93. 104662–104662. 46 indexed citations

Bar‐Or, Amit, Christopher Harp, Anne Cross, et al.. (2020). Factors associated with baseline serum neurofilament light concentrations in relapsing and primary progressive multiple sclerosis patients in the ocrelizumab OPERA 1 and ORATORIO Trials (2420). Neurology. 94(15_supplement). 1 indexed citations

Hauser, Stephen L., Ludwig Kappos, Douglas L. Arnold, et al.. (2020). Five years of ocrelizumab in relapsing multiple sclerosis. Neurology. 95(13). e1854–e1867. 106 indexed citations

Kappos, Ludwig, Jerry S. Wolinsky, Gavin Giovannoni, et al.. (2020). Contribution of Relapse-Independent Progression vs Relapse-Associated Worsening to Overall Confirmed Disability Accumulation in Typical Relapsing Multiple Sclerosis in a Pooled Analysis of 2 Randomized Clinical Trials. JAMA Neurology. 77(9). 1132–1132. 344 indexed citations breakdown →

Kappos, Ludwig, Jerry S. Wolinsky, Gavin Giovannoni, et al.. (2019). Progression Independent of Relapse Activity (PIRA) in Patients with Relapsing Multiple Sclerosis. SSRN Electronic Journal. 1 indexed citations

Hauser, Stephen L., Ludwig Kappos, Xavier Montalbán, et al.. (2019). Long-Term Reduction in 48-Week Confirmed Disability Progression After 5 Years of Ocrelizumab Treatment in Patients With Relapsing Multiple Sclerosis (P3.2-054). Neurology. 92(15_supplement). 1 indexed citations

10.

Arnold, Douglas L., Gavin Giovannoni, Hans‐Peter Hartung, et al.. (2019). Reduced Rate of Brain Atrophy in Patients With PPMS Receiving Ocrelizumab Earlier and Continuously Versus Those Initiating Ocrelizumab Later: Results of ORATORIO 5-Year Follow-Up (P3.2-042). Neurology. 92(15_supplement). 1 indexed citations

11.

Kletzl, Heidemarie, Ekaterina Gibiansky, Claire Petry, et al.. (2019). Pharmacokinetics, Pharmacodynamics and Exposure-Response Analyses of Ocrelizumab in Patients With Multiple Sclerosis (N4.001). Neurology. 92(15_supplement). 12 indexed citations

12.

Giovannoni, Gavin, Laura Airas, Riley Bove, et al.. (2019). Ocrelizumab Treatment Effect on Upper Limb Function in PPMS Patients with Disability: Subgroup Results of the ORATORIO Study to Inform the ORATORIO-HAND Study Design (P3.2-091). Neurology. 92(15_supplement). 3 indexed citations

13.

Elliott, Colm, Jerry S. Wolinsky, Stephen L. Hauser, et al.. (2018). Ocrelizumab May Reduce Tissue Damage in Chronic Active Lesions as Measured by Change in T1 Hypo-Intensity of Slowly Evolving Lesions in Patients With Primary Progressive Multiple Sclerosis (P3.376). Neurology. 90(15_supplement).

14.

Naismith, Robert T., Mark Cascione, Luigi Maria Edoardo Grimaldi, et al.. (2017). Preliminary Results of the OPERA I and OPERA II Open-Label Extension Study (S31.004). Neurology. 88(16_supplement). 2 indexed citations

15.

Model, Fabian, et al.. (2016). P3‐032: Identification of Predictors of Disease Progression in an Amyloid‐Beta 42 (Aβ42)‐Positive, Prodromal Alzheimer’s Disease Cohort: Analysis of the Scarlet Road Study. Alzheimer s & Dementia. 12(7S_Part_17). 1 indexed citations

16.

Payne, Shannon R., Jürgen Serth, Martin Schostak, et al.. (2009). DNA methylation biomarkers of prostate cancer: Confirmation of candidates and evidence urine is the most sensitive body fluid for non‐invasive detection. The Prostate. 69(12). 1257–1269. 83 indexed citations

17.

Grützmann, Robert, Béla Molnár, Christian Pilarsky, et al.. (2008). Sensitive Detection of Colorectal Cancer in Peripheral Blood by Septin 9 DNA Methylation Assay. PLoS ONE. 3(11). e3759–e3759. 304 indexed citations

18.

Model, Fabian, Neal Osborn, David A. Ahlquist, et al.. (2007). Identification and Validation of Colorectal Neoplasia–Specific Methylation Markers for Accurate Classification of Disease. Molecular Cancer Research. 5(2). 153–163. 45 indexed citations

19.

Lofton–Day, Catherine, Fabian Model, Theo deVos, et al.. (2007). DNA Methylation Biomarkers for Blood-Based Colorectal Cancer Screening. Clinical Chemistry. 54(2). 414–423. 385 indexed citations

20.

Martens, John W.M., Inko Nimmrich, Thomas Koenig, et al.. (2005). Association of DNA Methylation of Phosphoserine Aminotransferase with Response to Endocrine Therapy in Patients with Recurrent Breast Cancer. Cancer Research. 65(10). 4101–4117. 102 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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