David Gruben

8.0k total citations · 6 hit papers
101 papers, 6.3k citations indexed

About

David Gruben is a scholar working on Rheumatology, Hematology and Immunology. According to data from OpenAlex, David Gruben has authored 101 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Rheumatology, 45 papers in Hematology and 21 papers in Immunology. Recurrent topics in David Gruben's work include Rheumatoid Arthritis Research and Therapies (68 papers), Autoimmune and Inflammatory Disorders Research (45 papers) and Chronic Lymphocytic Leukemia Research (19 papers). David Gruben is often cited by papers focused on Rheumatoid Arthritis Research and Therapies (68 papers), Autoimmune and Inflammatory Disorders Research (45 papers) and Chronic Lymphocytic Leukemia Research (19 papers). David Gruben collaborates with scholars based in United States, Canada and United Kingdom. David Gruben's co-authors include Samuel H. Zwillich, Gene V. Wallenstein, Sriram Krishnaswami, Roy Fleischmann, John Bradley, Joel M. Kremer, Bethanie Wilkinson, Tamás Koncz, Carol A. Connell and Eun Bong Lee and has published in prestigious journals such as New England Journal of Medicine, The Lancet and Annals of Internal Medicine.

In The Last Decade

David Gruben

97 papers receiving 6.1k citations

Hit Papers

Placebo-Controlled Trial of Tofacitinib Monotherapy in Rh... 2012 2026 2016 2021 2012 2012 2014 2013 2013 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Gruben United States 29 4.4k 2.5k 1.5k 1.4k 1.4k 101 6.3k
Sriram Krishnaswami United States 32 3.9k 0.9× 2.2k 0.9× 1.4k 1.0× 1.3k 0.9× 1.4k 1.0× 59 6.1k
Samuel H. Zwillich United States 34 5.3k 1.2× 2.8k 1.1× 1.8k 1.2× 1.7k 1.2× 1.8k 1.3× 89 7.7k
Patrick Durez Belgium 38 5.1k 1.2× 2.4k 1.0× 2.2k 1.5× 1.3k 0.9× 690 0.5× 205 7.2k
Maya H Buch United Kingdom 42 3.9k 0.9× 1.4k 0.5× 1.7k 1.2× 996 0.7× 575 0.4× 211 6.4k
Maria Greenwald United States 30 2.7k 0.6× 1.2k 0.5× 1.5k 1.0× 868 0.6× 1.2k 0.9× 76 5.1k
Andrea Rubbert‐Roth Germany 33 3.3k 0.7× 1.5k 0.6× 1.7k 1.1× 885 0.6× 647 0.5× 123 5.1k
Terence Rooney United States 28 2.9k 0.6× 1.4k 0.6× 806 0.5× 857 0.6× 932 0.7× 53 3.9k
Hideto Kameda Japan 38 2.6k 0.6× 1.2k 0.5× 1.2k 0.8× 631 0.5× 398 0.3× 196 4.3k
Xavier Le Loët France 42 3.3k 0.8× 1.3k 0.5× 1.4k 0.9× 644 0.5× 328 0.2× 198 5.4k
Sujatha Menon United States 22 2.3k 0.5× 1.1k 0.4× 1.3k 0.9× 327 0.2× 702 0.5× 55 3.6k

Countries citing papers authored by David Gruben

Since Specialization
Citations

This map shows the geographic impact of David Gruben'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 David Gruben with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Gruben more than expected).

Fields of papers citing papers by David Gruben

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Gruben. 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 David Gruben. The network helps show where David Gruben may publish in the future.

Co-authorship network of co-authors of David Gruben

This figure shows the co-authorship network connecting the top 25 collaborators of David Gruben. A scholar is included among the top collaborators of David Gruben 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 David Gruben. David Gruben is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jairath, Vipul, Tim Raine, Thomas P. Leahy, et al.. (2025). Matching-adjusted indirect comparisons of efficacy outcomes between etrasimod and ozanimod for moderately to severely active ulcerative colitis. Journal of Comparative Effectiveness Research. 14(4). e240193–e240193.
3.
Armuzzi, Alessandro, David T. Rubin, S Schreiber, et al.. (2024). Health-Related Quality of Life Outcomes With Etrasimod Treatment in Patients With Ulcerative Colitis: A Post Hoc Analysis of Data From ELEVATE UC 52 and ELEVATE UC 12. Inflammatory Bowel Diseases. 31(6). 1583–1594. 1 indexed citations
4.
Jairath, Vipul, et al.. (2024). P849 Bayesian network meta-analysis of the efficacy of advanced therapies for patients with moderately to severely active ulcerative colitis naïve to advanced therapy. Journal of Crohn s and Colitis. 18(Supplement_1). i1566–i1567. 2 indexed citations
5.
6.
Eder, Lihi, Dafna D. Gladman, Philip J. Mease, et al.. (2023). Sex differences in the efficacy, safety and persistence of patients with psoriatic arthritis treated with tofacitinib: a post-hoc analysis of phase 3 trials and long-term extension. RMD Open. 9(1). e002718–e002718. 14 indexed citations
7.
Citera, Gustavo, Rakesh K. Jain, Fedra Irazoque-Palazuelos, et al.. (2020). THU0196 TOFACITINIB IN PATIENTS WITH RHEUMATOID ARTHRITIS AND INDICATIVE OF DEPRESSION AND/OR ANXIETY: A POST HOC ANALYSIS OF PHASE 3 AND PHASE 3B/4 CLINICAL TRIALS. Annals of the Rheumatic Diseases. 79. 318–319. 3 indexed citations
8.
Claxton, Lindsay, Matthew Taylor, Robert A. Gerber, et al.. (2018). Modelling the cost-effectiveness of tofacitinib for the treatment of rheumatoid arthritis in the United States. Current Medical Research and Opinion. 34(11). 1991–2000. 16 indexed citations
10.
Landewé, Robert, Carol A. Connell, John Bradley, et al.. (2016). Is radiographic progression in modern rheumatoid arthritis trials still a robust outcome? Experience from tofacitinib clinical trials. Arthritis Research & Therapy. 18(1). 212–212. 24 indexed citations
11.
Genovese, Mark C., Ronald van Vollenhoven, Bethanie Wilkinson, et al.. (2016). Switching from adalimumab to tofacitinib in the treatment of patients with rheumatoid arthritis. Arthritis Research & Therapy. 18(1). 145–145. 15 indexed citations
12.
Harnett, James, Jeffrey R. Curtis, R. Gerber, David Gruben, & Andrew Koenig. (2015). SAT0226 Early Experience with Tofacitinib: Treatment Patterns in Two us Healthcare Claims Databases. Annals of the Rheumatic Diseases. 74. 740–740. 2 indexed citations
13.
Lee, Eun Bong, Roy Fleischmann, Stephen Hall, et al.. (2014). Tofacitinib versus Methotrexate in Rheumatoid Arthritis. New England Journal of Medicine. 370(25). 2377–2386. 598 indexed citations breakdown →
14.
Strand, Vibeke, et al.. (2013). ORAL SCAN: Effects Of The Oral JAK Inhibitor Tofacitinib In Combination With Methotrexate On Patient Reported Outcomes In a 24-Month Phase 3 Trial Of Active Rheumatoid Arthritis. Data Archiving and Networked Services (DANS). 3 indexed citations
15.
Kremer, Joel, Zhanguo Li, Stephen Hall, et al.. (2013). Tofacitinib in Combination With Nonbiologic Disease-Modifying Antirheumatic Drugs in Patients With Active Rheumatoid Arthritis. Annals of Internal Medicine. 5 indexed citations
16.
Heijde, D. van der, Yoshiya Tanaka, R Fleischmann, et al.. (2012). Tofacitinib, an Oral Janus Kinase Inhibitor, in Combination with Methotrexate Reduced the Progression of Structural Damage in Patients with Rheumatoid Arthritis: Year 2 Efficacy and Safety Results From a 24-Month Phase 3 Study. Arthritis & Rheumatism. 64(10). 4 indexed citations
20.
Lawendy, Nervin, Sriram Krishnaswami, Rong Wang, et al.. (2009). Effect of CP‐690,550, an Orally Active Janus Kinase Inhibitor, on Renal Function in Healthy Adult Volunteers. The Journal of Clinical Pharmacology. 49(4). 423–429. 31 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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