Katja Weisel
About
Katja Weisel is a scholar working on Hematology, Oncology and Molecular Biology.
According to data from OpenAlex, Katja Weisel has authored 335 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 297 papers in Hematology, 189 papers in Oncology and 174 papers in Molecular Biology. Recurrent topics in Katja Weisel's work include Multiple Myeloma Research and Treatments (286 papers), Protein Degradation and Inhibitors (117 papers) and Cancer Treatment and Pharmacology (70 papers). Katja Weisel is often cited by papers focused on Multiple Myeloma Research and Treatments (286 papers), Protein Degradation and Inhibitors (117 papers) and Cancer Treatment and Pharmacology (70 papers). Katja Weisel collaborates with scholars based in Germany, United States and Spain. Katja Weisel's co-authors include María‐Victoria Mateos, Meletios Α. Dimopoulos, Vânia Hungria, Pieter Sonneveld, Ajay K. Nooka, Andrew Spencer, Antonio Palumbo, Xiang Qin, Jordan M. Schecter and Anita Zahlten‐Kumeli and has published in prestigious journals such as New England Journal of Medicine, The Lancet and Journal of Clinical Oncology.
In The Last Decade
Katja Weisel
311 papers receiving 5.6k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Katja Weisel Germany | 33 | 4.3k | 3.2k | 3.0k | 711 | 683 | 335 | 5.7k | ||
| Natalie S. Callander United States | 41 | 4.0k 0.9× | 3.2k 1.0× | 2.8k 0.9× | 716 1.0× | 258 0.4× | 199 | 5.9k | ||
| Ajai Chari United States | 32 | 3.4k 0.8× | 2.7k 0.8× | 2.6k 0.9× | 490 0.7× | 677 1.0× | 217 | 4.7k | ||
| Ajay K. Nooka United States | 36 | 3.5k 0.8× | 2.9k 0.9× | 3.4k 1.1× | 623 0.9× | 551 0.8× | 282 | 6.0k | ||
| Elena Zamagni Italy | 39 | 4.7k 1.1× | 2.9k 0.9× | 2.9k 1.0× | 671 0.9× | 371 0.5× | 165 | 5.4k | ||
| Francesca Gay Italy | 34 | 3.6k 0.8× | 2.9k 0.9× | 2.6k 0.9× | 485 0.7× | 292 0.4× | 183 | 5.1k | ||
| Rubén Niesvizky United States | 45 | 6.0k 1.4× | 5.6k 1.7× | 4.6k 1.6× | 1.1k 1.6× | 507 0.7× | 290 | 9.0k | ||
| Jeffrey A. Zonder United States | 35 | 2.7k 0.6× | 2.9k 0.9× | 1.9k 0.6× | 661 0.9× | 390 0.6× | 194 | 4.6k | ||
| Paula Rodríguez‐Otero Spain | 29 | 2.0k 0.5× | 1.7k 0.5× | 1.7k 0.6× | 284 0.4× | 576 0.8× | 181 | 3.4k | ||
| Raymond L. Comenzo United States | 44 | 2.9k 0.7× | 6.7k 2.1× | 2.4k 0.8× | 2.1k 2.9× | 337 0.5× | 230 | 8.3k | ||
| Keith Stockerl‐Goldstein United States | 36 | 3.3k 0.8× | 1.7k 0.5× | 1.8k 0.6× | 671 0.9× | 243 0.4× | 200 | 5.2k |
Countries citing papers authored by Katja Weisel
Since
Specialization
Citations
This map shows the geographic impact of Katja Weisel'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 Katja Weisel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katja Weisel more than expected).
Fields of papers citing papers by Katja Weisel
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Katja Weisel. 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 Katja Weisel. The network helps show where Katja Weisel may publish in the future.
Co-authorship network of co-authors of Katja Weisel
This figure shows the co-authorship network connecting the top 25 collaborators of Katja Weisel. A scholar is included among the top collaborators of Katja Weisel 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 Katja Weisel. Katja Weisel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Kumar, Shaji, Xavier Leleu, Katja Weisel, et al.. (2025). Ranking the Importance of Prognostic Factors for Relapsed/Refractory Multiple Myeloma: International Physician Panel Consensus Following a Systematic Literature Review. Clinical Lymphoma Myeloma & Leukemia. 25(10). 730–738.e11.
2.
Costa, Luciano J., Francesca Gay, Ola Landgren, et al.. (2025). Evolution of frontline treatment for multiple myeloma: clinical investigation of quadruplets containing carfilzomib and anti-CD38 monoclonal antibodies. Annals of Hematology. 104(3). 1329–1351.
3.
Terpos, Evangelos, Suzanne Trudel, María‐Victoria Mateos, et al.. (2025). Practical Guidance on Clinical Management of Belantamab Mafodotin‐Associated Ocular Events. American Journal of Hematology. 100(10). 1839–1850.
4.
Leypoldt, Lisa, Xiang Zhou, Winfried Alsdorf, et al.. (2024). Activity of CAR-T Cells and Bispecific Antibodies in Multiple Myeloma with Extramedullary Involvement. Blood. 144(Supplement 1). 3792.4–3792.4.
5.
Costa, Luciano J., Katja Weisel, Surbhi Sidana, et al.. (2024). Ciltacabtagene autoleucel vs standard of care in patients with functional high-risk multiple myeloma: CARTITUDE-4 subgroup analysis.. Journal of Clinical Oncology. 42(16_suppl). 7504–7504.
6.
Costa, Luciano J., Katja Weisel, Surbhi Sidana, et al.. (2024). MM-549 Ciltacabtagene Autoleucel vs Standard of Care in Patients With Functional High-Risk Multiple Myeloma: CARTITUDE-4 Subgroup Analysis. Clinical Lymphoma Myeloma & Leukemia. 24. S569–S570.
7.
Pawlyn, Charlotte, Fredrik Schjesvold, David A. Cairns, et al.. (2024). Progression-free survival as a surrogate endpoint in myeloma clinical trials: an evolving paradigm. Blood Cancer Journal. 14(1). 134–134.
8.
Frenzel, Christian, et al.. (2023). Increased incidence of immune thrombocytopenia (ITP ) in 2021 correlating with the ongoing vaccination campaign against COVID ‐19 in a tertiary center – A monocentric analysis. British Journal of Haematology. 201(2). 222–226.
9.
Leypoldt, Lisa, Maria Gavriatopoulou, Britta Besemer, et al.. (2023). Daratumumab, Bortezomib, and Dexamethasone for Treatment of Patients with Relapsed or Refractory Multiple Myeloma and Severe Renal Impairment: Results from the Phase 2 GMMG-DANTE Trial. Cancers. 15(18). 4667–4667.
10.
D’Souza, Anita, Nina Shah, Cesar Rodriguez, et al.. (2022). A Phase I First-in-Human Study of ABBV-383, a B-Cell Maturation Antigen × CD3 Bispecific T-Cell Redirecting Antibody, in Patients With Relapsed/Refractory Multiple Myeloma. Journal of Clinical Oncology. 40(31). 3576–3586.
11.
Schönlein, Martin, Marc Lütgehetmann, Julian Schulze zur Wiesch, et al.. (2021). Post-Vaccination Anti-SARS-CoV-2-Antibody Response in Patients with Multiple Myeloma Correlates with Low CD19+ B-Lymphocyte Count and Anti-CD38 Treatment. Cancers. 13(15). 3800–3800.
12.
Seckinger, Anja, Michael Heider, Martina Rudelius, et al.. (2021). MCT1 is a predictive marker for lenalidomide maintenance therapy in multiple myeloma. Blood Advances. 6(2). 515–520.
13.
Weisel, Katja, et al.. (2021). Current Treatment Approaches to Newly Diagnosed Multiple Myeloma. Oncology Research and Treatment. 44(12). 690–699.
14.
Vij, Ravi, Rajneesh Nath, Daniel Afar, et al.. (2020). First-in-Human Phase I Study of ABBV-838, an Antibody–Drug Conjugate Targeting SLAMF7/CS1 in Patients with Relapsed and Refractory Multiple Myeloma. Clinical Cancer Research. 26(10). 2308–2317.
15.
Weisel, Katja, George F. Geils, Lionel Karlin, et al.. (2020). Carfilzomib, Dexamethasone, and Daratumumab Versus Carfilzomib and Dexamethasone in Relapsed or Refractory Multiple Myeloma: Subgroup Analysis of the Phase 3 Candor Study in Patients with Early or Late Relapse. Blood. 136(Supplement 1). 37–38.
16.
Medaglia, Alice Annalisa, Ajay K. Nooka, Nizar J. Bahlis, et al.. (2020). Dreamm-4: evaluating safety and clinical activity of belantamab mafodotin (belamaf) in combination with pembrolizumab in patients with relapsed/refractory multiple myeloma (rrmm). SHILAP Revista de lepidopterología.
17.
Qian, Xiaozhong, Meletios Α. Dimopoulos, Michael Amatangelo, et al.. (2017). Correlative Analyses of Cereblon (CRBN), cMYC, IRF4, BLIMP1, and XBP1 with Clinical Outcomes in Stratus (MM-010), a Phase 3b Study of Pomalidomide (POM) + Low-Dose Dexamethasone (LoDEX) in Patients (pts) with Relapsed/Refractory Multiple Myeloma (RRMM). Blood. 130. 3109–3109.
18.
Schneidawind, Corina, Christoph Faul, Lothar Kanz, et al.. (2017). Follow‐up of patients with refractory or relapsed multiple myeloma after allogeneic hematopoietic cell transplantation. Clinical Transplantation. 31(7).
19.
Morgan, Gareth J., Antonio Palumbo, Sujith Dhanasiri, et al.. (2014). Overall survival of relapsed and refractory multiple myeloma patients after adjusting for crossover in the MM ‐003 trial for pomalidomide plus low‐dose dexamethasone. British Journal of Haematology. 168(6). 820–823.
20.
Morgan, Gillian, Jesús F. San Miguel, Sujith Dhanasiri, et al.. (2014). Overall survival of patients with relapsed and refractory multiple myeloma: adjusting for crossover in the MM-003 trial for pomalidomide plus low-dose dexamethasone vs. high-dose dexamethasone. Ghent University Academic Bibliography (Ghent University).
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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