Alexander M. Lesokhin

24.3k total citations · 2 hit papers
195 papers, 7.5k citations indexed

About

Alexander M. Lesokhin is a scholar working on Hematology, Oncology and Molecular Biology. According to data from OpenAlex, Alexander M. Lesokhin has authored 195 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 133 papers in Hematology, 95 papers in Oncology and 65 papers in Molecular Biology. Recurrent topics in Alexander M. Lesokhin's work include Multiple Myeloma Research and Treatments (132 papers), CAR-T cell therapy research (44 papers) and Protein Degradation and Inhibitors (39 papers). Alexander M. Lesokhin is often cited by papers focused on Multiple Myeloma Research and Treatments (132 papers), CAR-T cell therapy research (44 papers) and Protein Degradation and Inhibitors (39 papers). Alexander M. Lesokhin collaborates with scholars based in United States, Canada and France. Alexander M. Lesokhin's co-authors include Jedd D. Wolchok, Li Zhu, Stephen M. Ansell, Philippe Armand, Martin Gutierrez, Margaret A. Shipp, John M. Timmerman, Ivan Borrello, Joseph F. Grosso and Michael Millenson and has published in prestigious journals such as New England Journal of Medicine, Nature Medicine and Nature Communications.

In The Last Decade

Alexander M. Lesokhin

179 papers receiving 7.3k 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.

PD-1 Blockade with Nivolumab in Relapsed or Refractory Hodgkin's Lymphoma

2014 2.7k citations Alexander M. Lesokhin et al. profile →
Monitoring, prophylaxis, and treatment of infections in patients with MM receiving bispecific antibody therapy: consensus recommendations from an expert panel

2023 77 citations Noopur Raje, Alexander M. Lesokhin et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alexander M. Lesokhin United States	36	5.3k	3.3k	1.8k	1.7k	1.4k	195	7.5k
Mark Kirschbaum United States	25	2.1k 0.4×	1.7k 0.5×	1.9k 1.1×	3.2k 1.9×	1.1k 0.8×	66	6.2k
Frederic I. Preffer United States	43	2.0k 0.4×	2.3k 0.7×	2.0k 1.1×	1.6k 0.9×	905 0.7×	112	7.0k
Thierry Lamy France	41	2.3k 0.4×	2.6k 0.8×	1.4k 0.8×	1.9k 1.1×	2.6k 1.9×	177	6.4k
Massimo Di Nicola Italy	37	2.7k 0.5×	2.1k 0.6×	2.0k 1.1×	1.3k 0.8×	1.3k 0.9×	160	7.5k
Anne J. Novak United States	41	2.4k 0.5×	3.2k 1.0×	1.2k 0.7×	547 0.3×	2.1k 1.5×	142	5.7k
Lisa M. Rimsza United States	42	2.6k 0.5×	1.2k 0.4×	1.4k 0.8×	1.2k 0.7×	3.5k 2.6×	199	6.2k
Felipe Samaniego United States	47	3.2k 0.6×	1.2k 0.4×	2.1k 1.2×	956 0.6×	3.1k 2.3×	217	7.3k
Andrei R. Shustov United States	34	2.5k 0.5×	2.0k 0.6×	907 0.5×	567 0.3×	3.3k 2.4×	158	5.3k
Bjoern Chapuy United States	32	5.5k 1.0×	3.2k 1.0×	2.5k 1.4×	667 0.4×	3.7k 2.7×	89	9.0k
Lorenz Trümper Germany	42	3.3k 0.6×	1.6k 0.5×	1.9k 1.1×	1.0k 0.6×	3.9k 2.9×	203	7.5k

Countries citing papers authored by Alexander M. Lesokhin

Since Specialization

Citations

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

Fields of papers citing papers by Alexander M. Lesokhin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexander M. Lesokhin. 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 Alexander M. Lesokhin. The network helps show where Alexander M. Lesokhin may publish in the future.

Co-authorship network of co-authors of Alexander M. Lesokhin

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander M. Lesokhin. A scholar is included among the top collaborators of Alexander M. Lesokhin 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 Alexander M. Lesokhin. Alexander M. Lesokhin 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

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.

Lesokhin, Alexander M., et al.. (2024). MagnetisMM-30: A phase 1b, open-label study of elranatamab in combination with iberdomide in patients with relapsed or refractory multiple myeloma (RRMM).. Journal of Clinical Oncology. 42(16_suppl). TPS7577–TPS7577. 3 indexed citations

Prince, H. Miles, Nizar J. Bahlis, Paula Rodríguez‐Otero, et al.. (2024). MagnetisMM-3: Long-Term Update and Efficacy and Safety of Less Frequent Dosing of Elranatamab in Patients with Relapsed or Refractory Multiple Myeloma. Blood. 144(Supplement 1). 4738–4738. 5 indexed citations

Shah, Urvi A., et al.. (2023). Dietary and microbiome evidence in multiple myeloma and other plasma cell disorders. Leukemia. 37(5). 964–980. 17 indexed citations

Derkach, Andriy, et al.. (2023). Pre-diagnosis dietary patterns and risk of multiple myeloma in the NIH-AARP diet and health study. Leukemia. 38(2). 438–441. 4 indexed citations

Lin, Yi, Thomas Martin, Saad Z. Usmani, et al.. (2023). POSTER: MM-309 CARTITUDE-1 Final Results: Phase 1b/2 Study of Ciltacabtagene Autoleucel in Heavily Pretreated Patients With Relapsed/Refractory Multiple Myeloma. Clinical Lymphoma Myeloma & Leukemia. 23. S226–S226. 1 indexed citations

Manier, Salomon, Alexander M. Lesokhin, Mohamad Mohty, et al.. (2023). P870: EFFICACY AND SAFETY OF ELRANATAMAB IN PATIENTS WITH RELAPSED/REFRACTORY MULTIPLE MYELOMA AND PRIOR B-CELL MATURATION ANTIGEN (BCMA)-DIRECTED THERAPIES: A POOLED ANALYSIS FROM MAGNETISMM STUDIES. HemaSphere. 7(S3). e26808c7–e26808c7. 3 indexed citations

Firestone, Ross, Alexander M. Lesokhin, & Saad Z. Usmani. (2023). An Embarrassment of Riches: Three FDA-Approved Bispecific Antibodies for Relapsed Refractory Multiple Myeloma. Blood Cancer Discovery. 4(6). 433–436. 13 indexed citations

Bahlis, Nizar J., Caitlin Costello, Noopur Raje, et al.. (2023). Elranatamab in relapsed or refractory multiple myeloma: the MagnetisMM-1 phase 1 trial. Nature Medicine. 29(10). 2570–2576. 76 indexed citations

10.

Derkach, Andriy, Billel Gasmi, Theodora Anagnostou, et al.. (2023). T-Cell Exhaustion Signature Predicts Early Relapse after Autologous Stem Cell Transplant for Multiple Myeloma: BMT CTN 0702 Secondary Immune Analysis. Blood. 142(Supplement 1). 3326–3326. 1 indexed citations

11.

Hillengaß, Jens, Li Tang, Alexander M. Lesokhin, et al.. (2023). Dietary risk factors for monoclonal gammopathy of undetermined significance in a racially diverse population. Blood Advances. 8(3). 538–548. 4 indexed citations

12.

Shah, Urvi A., Andriy Derkach, Sham Mailankody, et al.. (2021). A Pilot Plant-Based Dietary Intervention in Overweight and Obese Patients with Monoclonal Gammopathy of Undetermined Significance and Smoldering Multiple Myeloma- the Nutrition Prevention (NUTRIVENTION) Study. Blood. 138(Supplement 1). 4759–4759.

13.

Lesokhin, Alexander M., Susan Bal, & Ashraf Badros. (2019). Lessons Learned from Checkpoint Blockade Targeting PD-1 in Multiple Myeloma. Cancer Immunology Research. 7(8). 1224–1229. 30 indexed citations

14.

Pianko, Matthew J., Sean M. Devlin, Eric R. Littmann, et al.. (2019). Minimal residual disease negativity in multiple myeloma is associated with intestinal microbiota composition. Blood Advances. 3(13). 2040–2044. 47 indexed citations

15.

Badros, Ashraf, Elizabeth Hyjek, Ning Ma, et al.. (2017). Pembrolizumab, pomalidomide, and low-dose dexamethasone for relapsed/refractory multiple myeloma. Blood. 130(10). 1189–1197. 146 indexed citations

16.

Devlin, Sean M., Jill Vanak, Heather Landau, et al.. (2016). Upfront plerixafor plus G-CSF versus cyclophosphamide plus G-CSF for stem cell mobilization in multiple myeloma: efficacy and cost analysis study. Bone Marrow Transplantation. 51(4). 546–552. 38 indexed citations

17.

Lendvai, Nikoletta, Patrick Hilden, Sean M. Devlin, et al.. (2014). A phase 2 single-center study of carfilzomib 56 mg/m2 with or without low-dose dexamethasone in relapsed multiple myeloma. Blood. 124(6). 899–906. 65 indexed citations

18.

Kitano, Shigehisa, Michael A. Postow, Carly G.K. Ziegler, et al.. (2014). Computational Algorithm-Driven Evaluation of Monocytic Myeloid-Derived Suppressor Cell Frequency for Prediction of Clinical Outcomes. Cancer Immunology Research. 2(8). 812–821. 111 indexed citations

19.

Hirschhorn-Cymerman, Daniel, Sadna Budhu, Shigehisa Kitano, et al.. (2012). Induction of tumoricidal function in CD4+ T cells is associated with concomitant memory and terminally differentiated phenotype. The Journal of Experimental Medicine. 209(11). 2113–2126. 115 indexed citations

20.

Lesokhin, Alexander M., Tobias M. Hohl, Shigehisa Kitano, et al.. (2011). Monocytic CCR2+ Myeloid-Derived Suppressor Cells Promote Immune Escape by Limiting Activated CD8 T-cell Infiltration into the Tumor Microenvironment. Cancer Research. 72(4). 876–886. 292 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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