Ashraf Badros

15.3k total citations
173 papers, 7.1k citations indexed

About

Ashraf Badros is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Ashraf Badros has authored 173 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 132 papers in Hematology, 80 papers in Molecular Biology and 75 papers in Oncology. Recurrent topics in Ashraf Badros's work include Multiple Myeloma Research and Treatments (121 papers), Protein Degradation and Inhibitors (58 papers) and Chronic Lymphocytic Leukemia Research (28 papers). Ashraf Badros is often cited by papers focused on Multiple Myeloma Research and Treatments (121 papers), Protein Degradation and Inhibitors (58 papers) and Chronic Lymphocytic Leukemia Research (28 papers). Ashraf Badros collaborates with scholars based in United States, United Kingdom and Canada. Ashraf Badros's co-authors include Guido Tricot, Bart Barlogie, Maurizio Zangari, Olga Goloubeva, Raman Desikan, Christopher Morris, Elias Anaissie, Aaron P. Rapoport, Athanasios Fassas and Timothy F. Meiller and has published in prestigious journals such as Journal of Clinical Oncology, Blood and JNCI Journal of the National Cancer Institute.

In The Last Decade

Ashraf Badros

165 papers receiving 7.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashraf Badros United States 46 4.4k 3.5k 3.3k 1.1k 689 173 7.1k
Donna Reece Canada 48 5.2k 1.2× 3.8k 1.1× 4.9k 1.5× 1.1k 1.0× 574 0.8× 349 8.2k
Mohamad A. Hussein United States 33 2.5k 0.6× 2.2k 0.6× 2.2k 0.7× 916 0.8× 592 0.9× 129 4.8k
Patrizia Tosi Italy 35 5.2k 1.2× 3.0k 0.9× 3.6k 1.1× 1.0k 0.9× 394 0.6× 146 6.6k
Laura Rosiñol Spain 41 5.1k 1.2× 2.9k 0.8× 3.7k 1.1× 846 0.8× 486 0.7× 219 6.2k
Maurizio Zangari United States 52 8.6k 2.0× 4.6k 1.3× 6.5k 2.0× 1.5k 1.4× 617 0.9× 277 11.0k
Melissa Alsina United States 44 4.6k 1.1× 3.3k 1.0× 4.1k 1.2× 602 0.5× 556 0.8× 221 6.7k
Jean‐Paul Fermand France 34 1.8k 0.4× 1.4k 0.4× 2.3k 0.7× 890 0.8× 792 1.1× 105 4.4k
Rubén Niesvizky United States 45 6.0k 1.4× 4.6k 1.3× 5.6k 1.7× 1.1k 1.0× 761 1.1× 290 9.0k
Luen Bik To Australia 30 2.4k 0.5× 1.7k 0.5× 1.1k 0.3× 751 0.7× 759 1.1× 78 3.9k
Elena Zamagni Italy 39 4.7k 1.1× 2.9k 0.8× 2.9k 0.9× 671 0.6× 211 0.3× 165 5.4k

Countries citing papers authored by Ashraf Badros

Since Specialization
Citations

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

Fields of papers citing papers by Ashraf Badros

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashraf Badros

This figure shows the co-authorship network connecting the top 25 collaborators of Ashraf Badros. A scholar is included among the top collaborators of Ashraf Badros 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 Ashraf Badros. Ashraf Badros 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.
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.
3.
Kocoglu, Mehmet H., Tim Luetkens, Jacqueline Bork, et al.. (2024). Coordinated antiviral immune response in a patient with myeloma and systemic adenovirus infection post-BCMA CAR T cells. Blood Advances. 8(22). 5880–5884.
4.
5.
Holtzman, Noa G., Hao Xie, Søren M. Bentzen, et al.. (2020). Immune effector cell–associated neurotoxicity syndrome after chimeric antigen receptor T-cell therapy for lymphoma: predictive biomarkers and clinical outcomes. Neuro-Oncology. 23(1). 112–121. 71 indexed citations
6.
Soleimani, Arshia, et al.. (2020). Biologic Implications of t(11;14) in Multiple Myeloma Explained With a Case of Refractory Disease Sensitive to Venetoclax. Clinical Lymphoma Myeloma & Leukemia. 20(9). e556–e559. 2 indexed citations
7.
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
8.
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
9.
10.
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
11.
12.
Dell, Cameron, Olga Goloubeva, Aaron P. Rapoport, et al.. (2017). Similar Survival for African American and Caucasian Multiple Myeloma Patients Receiving Auto-SCT. Blood. 130. 2177–2177. 1 indexed citations
13.
Hansson, Markus, Peter Gimsing, Ashraf Badros, et al.. (2015). A Phase I Dose-Escalation Study of Antibody BI-505 in Relapsed/Refractory Multiple Myeloma. Clinical Cancer Research. 21(12). 2730–2736. 42 indexed citations
14.
Bao, Ting, Lixing Lao, Michelle Medeiros, et al.. (2012). Improvement of Painful Bortezomib-Induced Peripheral Neuropathy Following Acupuncture Treatment in a Case Series of Multiple Myeloma Patients. Medical Acupuncture. 24(3). 181–187. 10 indexed citations
15.
Wang, Zhengping, Jinfu Yang, Christopher J. Kirk, et al.. (2012). Clinical Pharmacokinetics, Metabolism, and Drug-Drug Interaction of Carfilzomib. Drug Metabolism and Disposition. 41(1). 230–237. 123 indexed citations
16.
Bao, Ting, Rui-Xin Zhang, Ashraf Badros, & Lixing Lao. (2011). Acupuncture Treatment for Bortezomib-Induced Peripheral Neuropathy: A Case Report. Pain Research and Treatment. 2011. 1–4. 38 indexed citations
17.
Badros, Ashraf. (2010). The Role of Maintenance Therapy in the Treatment of Multiple Myeloma. Journal of the National Comprehensive Cancer Network. 8(Suppl 1). S–21. 6 indexed citations
18.
Scheper, Mark A., Ashraf Badros, Risa Chaisuparat, Kevin J. Cullen, & Timothy F. Meiller. (2008). Effect of zoledronic acid on oral fibroblasts and epithelial cells: a potential mechanism of bisphosphonate‐associated osteonecrosis. British Journal of Haematology. 144(5). 667–676. 122 indexed citations
19.
Inoue, Yoshio, et al.. (2005). Multiple myeloma presenting initially as a solitary pleural effusion later complicated by malignant plasmacytic ascites. Leukemia Research. 29(6). 715–718. 19 indexed citations
20.
Tricot, Guido, Raman Desikan, Ashraf Badros, et al.. (2002). Clinical activity of arsenic trioxide for the treatment of multiple myeloma. Leukemia. 16(9). 1835–1837. 120 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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