Simon J. Harrison

11.4k total citations · 1 hit paper
246 papers, 5.6k citations indexed

About

Simon J. Harrison is a scholar working on Hematology, Oncology and Molecular Biology. According to data from OpenAlex, Simon J. Harrison has authored 246 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 151 papers in Hematology, 109 papers in Oncology and 96 papers in Molecular Biology. Recurrent topics in Simon J. Harrison's work include Multiple Myeloma Research and Treatments (139 papers), Protein Degradation and Inhibitors (54 papers) and CAR-T cell therapy research (34 papers). Simon J. Harrison is often cited by papers focused on Multiple Myeloma Research and Treatments (139 papers), Protein Degradation and Inhibitors (54 papers) and CAR-T cell therapy research (34 papers). Simon J. Harrison collaborates with scholars based in Australia, United States and United Kingdom. Simon J. Harrison's co-authors include H. Miles Prince, David Ritchie, Hang Quach, Mark Bishton, Paul J. Neeson, Mark J. Smyth, Monica A. Slavin, Benjamin W. Teh, A. Keith Stewart and Andrew Spencer and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Simon J. Harrison

231 papers receiving 5.5k citations

Hit Papers

Venetoclax or placebo in combination with bortezomib and ... 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simon J. Harrison Australia 38 2.8k 2.5k 2.5k 855 701 246 5.6k
Parameswaran Hari United States 43 3.6k 1.3× 4.4k 1.7× 3.8k 1.5× 1.2k 1.4× 746 1.1× 420 7.8k
Sung‐Soo Yoon South Korea 35 1.6k 0.6× 1.8k 0.7× 1.5k 0.6× 630 0.7× 733 1.0× 342 4.2k
Thomas C. Shea United States 38 1.6k 0.6× 1.8k 0.7× 2.5k 1.0× 576 0.7× 1.1k 1.5× 172 5.6k
Ulrich Jäger Austria 45 1.8k 0.7× 2.4k 0.9× 1.7k 0.7× 1.2k 1.3× 1.0k 1.5× 172 5.7k
Kwee Yong United Kingdom 46 2.6k 1.0× 3.9k 1.6× 2.9k 1.2× 1.9k 2.2× 464 0.7× 265 7.1k
Guy Pratt United Kingdom 41 2.4k 0.9× 1.9k 0.8× 1.8k 0.7× 1.2k 1.4× 803 1.1× 184 5.3k
Martin F. Fey Switzerland 49 3.1k 1.1× 2.1k 0.8× 3.0k 1.2× 1.0k 1.2× 1.2k 1.6× 189 8.0k
Bronno van der Holt Netherlands 51 2.1k 0.8× 3.1k 1.2× 3.0k 1.2× 853 1.0× 1.2k 1.7× 224 7.8k
P. Sève France 44 1.5k 0.6× 1.1k 0.5× 1.2k 0.5× 1.0k 1.2× 451 0.6× 280 6.9k
Christian Berthou France 37 1.5k 0.5× 2.0k 0.8× 1.5k 0.6× 1.0k 1.2× 984 1.4× 200 5.3k

Countries citing papers authored by Simon J. Harrison

Since Specialization
Citations

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

Fields of papers citing papers by Simon J. Harrison

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simon J. Harrison. 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 Simon J. Harrison. The network helps show where Simon J. Harrison may publish in the future.

Co-authorship network of co-authors of Simon J. Harrison

This figure shows the co-authorship network connecting the top 25 collaborators of Simon J. Harrison. A scholar is included among the top collaborators of Simon J. Harrison 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 Simon J. Harrison. Simon J. Harrison 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.
Liu, Alice, Monica A. Slavin, Simon J. Harrison, & Benjamin W. Teh. (2024). Infections during novel myeloma therapies. Leukemia & lymphoma. 66(3). 420–432. 1 indexed citations
2.
Kelemen, Martin, John Danesh, Emanuele Di Angelantonio, et al.. (2024). Evaluating the cost-effectiveness of polygenic risk score-stratified screening for abdominal aortic aneurysm. Nature Communications. 15(1). 8063–8063. 3 indexed citations
3.
Booth, Simon, Paul Norris, Gabriel Chow, et al.. (2023). Abstracts. Anaesthesia. 78(S3). 8–66. 2 indexed citations
4.
Kım, Kihyun, Zoe McQuilten, Peter Mollee, et al.. (2023). A Prospective, Multinational Study of Clinical and Biological Factors Associated with Short Overall Survival in Multiple Myeloma. Blood. 142(Supplement 1). 4731–4731. 1 indexed citations
6.
Kalff, Anna, Peter Mollee, P. Joy Ho, et al.. (2023). The importance of frailty assessment in multiple myeloma: a position statement from the Myeloma Scientific Advisory Group to Myeloma Australia. Internal Medicine Journal. 53(5). 819–824. 6 indexed citations
7.
Casey, Mika, Soi Cheng Law, Dillon Corvino, et al.. (2023). Regulatory T cells hamper the efficacy of T-cell-engaging bispecific antibody therapy. Haematologica. 109(3). 787–798. 11 indexed citations
8.
Reynolds, Gemma, Edward R. Scheffer Cliff, Ghulam Rehman Mohyuddin, et al.. (2023). Infections following bispecific antibodies in myeloma: a systematic review and meta-analysis. Blood Advances. 7(19). 5898–5903. 42 indexed citations
10.
Casey, Mika, et al.. (2022). Invariant NKT cells dictate antitumor immunity elicited by a bispecific antibody cotargeting CD3 and BCMA. Blood Advances. 6(17). 5165–5170. 7 indexed citations
11.
Beaumont, S., et al.. (2021). Review of Myeloma Therapies and Their Potential for Oral and Maxillofacial Side Effects. Cancers. 13(17). 4479–4479. 1 indexed citations
12.
Harrison, Simon J., Aurore Perrot, Adrían Alegre, et al.. (2021). Subgroup analysis of ICARIA‐MM study in relapsed/refractory multiple myeloma patients with high‐risk cytogenetics. British Journal of Haematology. 194(1). 120–131. 32 indexed citations
13.
Beaumont, S., et al.. (2020). A Wolf in Sheep’s clothing: A case report series of oral manifestations of multiple myeloma. Australian Dental Journal. 66(3). 324–331. 4 indexed citations
14.
Khot, Amit, Natalie Brajanovski, Donald P. Cameron, et al.. (2019). First-in-Human RNA Polymerase I Transcription Inhibitor CX-5461 in Patients with Advanced Hematologic Cancers: Results of a Phase I Dose-Escalation Study. Cancer Discovery. 9(8). 1036–1049. 132 indexed citations
15.
Douglas, Abby, Karin Thursky, Leon J. Worth, et al.. (2019). FDG-PET/CT in managing infection in patients with hematological malignancy: clinician knowledge and experience in Australia. Leukemia & lymphoma. 60(10). 2471–2476. 6 indexed citations
17.
Gherardin, Nicholas A., Liyen Loh, Alexander J. Davenport, et al.. (2018). Enumeration, functional responses and cytotoxic capacity of MAIT cells in newly diagnosed and relapsed multiple myeloma. Scientific Reports. 8(1). 4159–4159. 77 indexed citations
18.
Maclachlan, Kylee, Andrew Cuddihy, Nadine Hein, et al.. (2017). Novel Combination Therapies with the RNA Polymerase I Inhibitor CX-5461 Significantly Improve Efficacy in Multiple Myeloma. Blood. 130. 1805. 3 indexed citations
19.
Khot, Amit, Natalie Brajanovski, Donald P. Cameron, et al.. (2017). RNA Polymerase 1 Transcription Inhibitor CX-5461 in Patients with Advanced Hematologic Malignancies: Results of a Phase I First in Human Study. Blood. 130. 3835–3835. 2 indexed citations
20.
Tramontana, Adrian R, Biju George, Aeron C. Hurt, et al.. (2010). Oseltamivir Resistance in Adult Oncology and Hematology Patients Infected with Pandemic (H1N1) 2009 Virus, Australia. Emerging infectious diseases. 16(7). 1068–1075. 92 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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