Jonathan L. Kaufman

17.1k total citations · 2 hit papers
323 papers, 7.9k citations indexed

About

Jonathan L. Kaufman is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Jonathan L. Kaufman has authored 323 papers receiving a total of 7.9k indexed citations (citations by other indexed papers that have themselves been cited), including 253 papers in Hematology, 160 papers in Molecular Biology and 138 papers in Oncology. Recurrent topics in Jonathan L. Kaufman's work include Multiple Myeloma Research and Treatments (244 papers), Protein Degradation and Inhibitors (105 papers) and Cancer Treatment and Pharmacology (46 papers). Jonathan L. Kaufman is often cited by papers focused on Multiple Myeloma Research and Treatments (244 papers), Protein Degradation and Inhibitors (105 papers) and Cancer Treatment and Pharmacology (46 papers). Jonathan L. Kaufman collaborates with scholars based in United States, France and Canada. Jonathan L. Kaufman's co-authors include Sagar Lonial, Lawrence Boise, Ajay K. Nooka, Vikas A. Gupta, Edward A. Stadtmauer, Madhav V. Dhodapkar, Paul G. Richardson, Craig C. Hofmeister, Nisha S. Joseph and Ravi Vij and has published in prestigious journals such as Nature Communications, Neuron and Journal of Clinical Oncology.

In The Last Decade

Jonathan L. Kaufman

303 papers receiving 7.7k citations

Hit Papers

Tyrosine Phosphorylation Inhibits PKM2 to Promote the War... 2009 2026 2014 2020 2009 2009 200 400 600

Peers

Jonathan L. Kaufman
Suzanne Lentzsch United States
Henk M. Lokhorst Netherlands
A. Keith Stewart United States
Robert Schlossman United States
Melissa Alsina United States
Peter M. Voorhees United States
Suzanne Lentzsch United States
Jonathan L. Kaufman
Citations per year, relative to Jonathan L. Kaufman Jonathan L. Kaufman (= 1×) peers Suzanne Lentzsch

Countries citing papers authored by Jonathan L. Kaufman

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan L. Kaufman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan L. Kaufman. 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 Jonathan L. Kaufman. The network helps show where Jonathan L. Kaufman may publish in the future.

Co-authorship network of co-authors of Jonathan L. Kaufman

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan L. Kaufman. A scholar is included among the top collaborators of Jonathan L. Kaufman 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 Jonathan L. Kaufman. Jonathan L. Kaufman 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.
Suvannasankha, Attaya, Jonathan L. Kaufman, Ashraf Badros, et al.. (2025). Safety and efficacy of elranatamab in combination with iberdomide in patients with relapsed or refractory multiple myeloma: Results from the phase 1b MagnetisMM-30 trial. Blood. 146(Supplement 1). 100–100.
2.
Roberts, Danielle, Vikas A. Gupta, Nisha S. Joseph, et al.. (2025). Feasibility and Safety of Outpatient Model for Administration of Bispecific Antibodies: Proceedings from an International Myeloma Society 21st Annual Meeting Oral Abstract. Clinical Lymphoma Myeloma & Leukemia. 25(9). 656–660.
4.
Moreno, Alberto, Kelly E. Manning, Ajay K. Nooka, et al.. (2024). Divergence of variant antibodies following SARS-CoV-2 booster vaccines in myeloma and impact of hybrid immunity. npj Vaccines. 9(1). 201–201.
5.
Nooka, Ajay K., Jonathan L. Kaufman, César A. Rodríguez, et al.. (2024). Post hoc analysis of daratumumab plus lenalidomide, bortezomib and dexamethasone in Black patients from final data of the GRIFFIN study. British Journal of Haematology. 204(6). 2227–2232.
6.
Switchenko, Jeffrey M., Madhusmita Behera, Mehmet Asım Bilen, et al.. (2023). Shifting Sociodemographic Characteristics of a Phase I Clinical Trial Population at an NCI-Designated Comprehensive Cancer Center in the Southeast. The Oncologist. 28(12). 1055–1063.
8.
Liu, Yuan, Nisha S. Joseph, Craig C. Hofmeister, et al.. (2023). Impact of Black Race on Peripheral Neuropathy in Patients With Newly Diagnosed Multiple Myeloma Receiving Bortezomib Induction. JCO Oncology Practice. 19(9). 793–798. 7 indexed citations
9.
Auclair, Daniel, Carol Mansfield, Mark A. Fiala, et al.. (2022). Preferences and Priorities for Relapsed Multiple Myeloma Treatments Among Patients and Caregivers in the United States. SHILAP Revista de lepidopterología. 9 indexed citations
10.
Kaushal, Akhilesh, Ajay K. Nooka, Katherine E. Pendleton, et al.. (2021). Aberrant Extrafollicular B Cells, Immune Dysfunction, Myeloid Inflammation, and MyD88-Mutant Progenitors Precede Waldenstrom Macroglobulinemia. Blood Cancer Discovery. 2(6). 600–615. 14 indexed citations
11.
Joseph, Nisha S., Jonathan L. Kaufman, Madhav V. Dhodapkar, et al.. (2020). Long-Term Follow-Up Results of Lenalidomide, Bortezomib, and Dexamethasone Induction Therapy and Risk-Adapted Maintenance Approach in Newly Diagnosed Multiple Myeloma. Journal of Clinical Oncology. 38(17). 1928–1937. 132 indexed citations
12.
Kaufman, Jonathan L., Roberto Mina, Jatin J. Shah, et al.. (2020). Phase 1 Trial Evaluating Vorinostat Plus Bortezomib, Lenalidomide, and Dexamethasone in Patients With Newly Diagnosed Multiple Myeloma. Clinical Lymphoma Myeloma & Leukemia. 20(12). 797–803. 5 indexed citations
13.
Ghobrial, Irene M., Ravi Vij, David S. Siegel, et al.. (2019). A Phase Ib/II Study of Oprozomib in Patients with Advanced Multiple Myeloma and Waldenström Macroglobulinemia. Clinical Cancer Research. 25(16). 4907–4916. 39 indexed citations
14.
Shah, Nirav N., Amrita Krishnan, Nina Shah, et al.. (2019). Preliminary Results of a Phase 1 Dose Escalation Study of the First-in-Class Anti-CD74 Antibody Drug Conjugate (ADC), STRO-001, in Patients with Advanced B-Cell Malignancies. Blood. 134(Supplement_1). 5329–5329. 16 indexed citations
15.
Bailur, Jithendra Kini, Samuel S. McCachren, Deon B. Doxie, et al.. (2019). Early alterations in stem-like/marrow-resident T cells and innate and myeloid cells in preneoplastic gammopathy. JCI Insight. 4(11). 117 indexed citations
16.
Mina, Roberto, Nisha S. Joseph, Jonathan L. Kaufman, et al.. (2018). Survival outcomes of patients with primary plasma cell leukemia (pPCL) treated with novel agents. Cancer. 125(3). 416–423. 34 indexed citations
17.
Joseph, Nisha S., Charise Gleason, Leonard T. Heffner, et al.. (2017). Lenalidomide, Bortezomib, and Dexamethasone (RVD) As Induction Therapy in Newly Diagnosed Multiple Myeloma (MM). Blood. 130. 3139–3139.
18.
Kaufman, Jonathan L., Cristina Gasparetto, Joseph Mıkhael, et al.. (2017). Phase 1 Study of Venetoclax in Combination with Dexamethasone As Targeted Therapy for t(11;14) Relapsed/Refractory Multiple Myeloma. Blood. 130. 3131–3131. 12 indexed citations
20.
Shah, Nishi, Ajay K. Nooka, Jonathan L. Kaufman, et al.. (2013). Evaluating Risk Factors and Outcomes For Clostridium Difficile Infection (CDI) In Stem Cell Transplant (SCT) Recipients. Blood. 122(21). 2986–2986. 1 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026