Heinz Ludwig

48.2k total citations · 5 hit papers
372 papers, 16.8k citations indexed

About

Heinz Ludwig is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Heinz Ludwig has authored 372 papers receiving a total of 16.8k indexed citations (citations by other indexed papers that have themselves been cited), including 280 papers in Hematology, 151 papers in Molecular Biology and 143 papers in Oncology. Recurrent topics in Heinz Ludwig's work include Multiple Myeloma Research and Treatments (212 papers), Protein Degradation and Inhibitors (77 papers) and Cancer Treatment and Pharmacology (50 papers). Heinz Ludwig is often cited by papers focused on Multiple Myeloma Research and Treatments (212 papers), Protein Degradation and Inhibitors (77 papers) and Cancer Treatment and Pharmacology (50 papers). Heinz Ludwig collaborates with scholars based in Austria, Germany and United States. Heinz Ludwig's co-authors include E. Fritz, Jesús F. San Miguel, Niklas Zojer, Meletios Α. Dimopoulos, Heinz Gisslinger, Pieter Sonneveld, Carsten Bokemeyer, Joan Bladé, Pere Gascón and Mario Boccadoro and has published in prestigious journals such as New England Journal of Medicine, The Lancet and Journal of Clinical Oncology.

In The Last Decade

Heinz Ludwig

358 papers receiving 16.2k citations

Hit Papers

International Staging Sys... 2004 2026 2011 2018 2005 2008 2004 2017 2023 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heinz Ludwig Austria 65 10.8k 8.0k 6.9k 2.6k 1.3k 372 16.8k
Charles A. Schiffer United States 65 15.5k 1.4× 4.4k 0.5× 6.8k 1.0× 6.5k 2.5× 1.3k 1.0× 280 22.0k
Martin S. Tallman United States 92 23.3k 2.2× 6.6k 0.8× 14.9k 2.2× 7.0k 2.7× 1.2k 1.0× 716 34.8k
Alan K. Burnett United Kingdom 65 19.1k 1.8× 3.6k 0.5× 10.2k 1.5× 4.8k 1.8× 739 0.6× 353 23.6k
Wendy Stock United States 54 6.1k 0.6× 3.6k 0.5× 3.5k 0.5× 2.3k 0.9× 421 0.3× 463 12.1k
Stefan Faderl United States 88 17.0k 1.6× 5.3k 0.7× 8.2k 1.2× 10.9k 4.2× 1.1k 0.9× 570 27.0k
Srđan Verstovšek United States 84 18.6k 1.7× 4.4k 0.5× 12.1k 1.8× 18.7k 7.2× 1.1k 0.8× 1.1k 30.0k
Hartmut Goldschmidt Germany 68 12.5k 1.2× 8.0k 1.0× 10.1k 1.5× 2.2k 0.9× 627 0.5× 660 18.4k
Richard Greil Austria 67 2.3k 0.2× 10.9k 1.4× 5.3k 0.8× 3.0k 1.2× 4.1k 3.2× 731 20.1k
Daniel J. DeAngelo United States 60 9.0k 0.8× 4.3k 0.5× 6.2k 0.9× 3.9k 1.5× 482 0.4× 444 16.3k
Mario Cazzola Italy 73 17.6k 1.6× 2.3k 0.3× 9.2k 1.3× 15.1k 5.8× 1.1k 0.9× 428 25.3k

Countries citing papers authored by Heinz Ludwig

Since Specialization
Citations

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

Fields of papers citing papers by Heinz Ludwig

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heinz Ludwig

This figure shows the co-authorship network connecting the top 25 collaborators of Heinz Ludwig. A scholar is included among the top collaborators of Heinz Ludwig 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 Heinz Ludwig. Heinz Ludwig 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.
Łuczak, Magdalena, Magdalena Kostrzewska‐Poczekaj, Arnold Bolomsky, et al.. (2025). Carfilzomib resistance in multiple myeloma: A comparative metabolomic analysis. Journal of Applied Genetics.
2.
Ludwig, Heinz, Nikhil Munshi, Evangelos Terpos, et al.. (2024). Proposal for harmonizing the reporting of infections during treatment with bispecific antibodies in multiple myeloma. Blood Advances. 8(18). 4979–4982. 5 indexed citations
3.
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. 4 indexed citations
4.
Quinn, Barry, et al.. (2021). Physical, Emotional and Social Pain Communication by Patients Diagnosed and Living with Multiple Myeloma. Pain Management. 12(1). 59–74. 5 indexed citations
5.
Terpos, Evangelos, Monika Engelhardt, Gordon Cook, et al.. (2020). Management of patients with multiple myeloma in the era of COVID-19 pandemic: a consensus paper from the European Myeloma Network (EMN). Leukemia. 34(8). 2000–2011. 81 indexed citations
6.
Ludwig, Heinz, Philippe Moreau, Meletios Α. Dimopoulos, et al.. (2019). Health-related quality of life in the ENDEAVOR study: carfilzomib-dexamethasone vs bortezomib-dexamethasone in relapsed/refractory multiple myeloma. Blood Cancer Journal. 9(3). 23–23. 28 indexed citations
7.
Caers, Jo, Bruno Paiva, Elena Zamagni, et al.. (2018). Diagnosis, treatment, and response assessment in solitary plasmacytoma: updated recommendations from a European Expert Panel. Journal of Hematology & Oncology. 11(1). 10–10. 152 indexed citations
11.
Bolomsky, Arnold, Roy Heusschen, Joséphine Muller, et al.. (2017). Preclinical Evaluation of the First in Class BMI1 Inhibitor PTC-028 Confirms Potent Efficacy to Target BMI1-Addiction in Multiple Myeloma. Blood. 130. 1804–1804. 1 indexed citations
12.
Furchtgott, Leon, Arnold Bolomsky, Fred K. Gruber, et al.. (2017). Multiple Myeloma Drivers of High Risk and Response to Stem Cell Transplantation Identified By Causal Machine Learning: Out-of-Cohort and Experimental Validation. Blood. 130. 3029–3029. 2 indexed citations
13.
Ludwig, Heinz, Luísa Viterbo, Richard Greil, et al.. (2012). Randomized Phase II Study of Bortezomib, Thalidomide, and Dexamethasone With or Without Cyclophosphamide As Induction Therapy in Previously Untreated Multiple Myeloma. Journal of Clinical Oncology. 31(2). 247–255. 58 indexed citations
14.
Aapro, Matti, Anders Österborg, Pere Gascón, Heinz Ludwig, & Yves Béguin. (2012). Anaemia and cancer: oral or intravenous iron?. Open Repository and Bibliography (University of Liège). 1 indexed citations
15.
Glaspy, John A., Jeffrey Crawford, Johan Vansteenkiste, et al.. (2010). Erythropoiesis-stimulating agents in oncology: a study-level meta-analysis of survival and other safety outcomes. British Journal of Cancer. 102(2). 301–315. 176 indexed citations
16.
Ludwig, Heinz, Roman Hájek, Elena Tóthová, et al.. (2008). Thalidomide-dexamethasone compared with melphalan-prednisolone in elderly patients with multiple myeloma. Blood. 113(15). 3435–3442. 148 indexed citations
17.
Croockewit, Alexandra, Miguel H. Bronchud, Matti Aapro, et al.. (1997). A European perspective on haematopoietic growth factors in haemato-oncology: Report of an expert meeting of the EORTC. European Journal of Cancer. 33(11). 1732–1746. 12 indexed citations
18.
Scheithauer, Werner, et al.. (1987). VAD protocol for treatment of advanced refractory multiple myeloma. Annals of Hematology. 55(3). 145–152. 5 indexed citations
19.
Ludwig, Heinz, et al.. (1981). Clinical immunology and allergology : proceedings of the symposia at the XIth Congress of the European Academy of Allergology and Clinical Immunology held in Vienna, Austria, 6-10 October 1980. Elsevier eBooks. 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.

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