David M. Kurtz

10.3k total citations · 1 hit paper
112 papers, 2.9k citations indexed

About

David M. Kurtz is a scholar working on Cancer Research, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, David M. Kurtz has authored 112 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Cancer Research, 51 papers in Pathology and Forensic Medicine and 35 papers in Oncology. Recurrent topics in David M. Kurtz's work include Cancer Genomics and Diagnostics (58 papers), Lymphoma Diagnosis and Treatment (46 papers) and CAR-T cell therapy research (24 papers). David M. Kurtz is often cited by papers focused on Cancer Genomics and Diagnostics (58 papers), Lymphoma Diagnosis and Treatment (46 papers) and CAR-T cell therapy research (24 papers). David M. Kurtz collaborates with scholars based in United States, Germany and Switzerland. David M. Kurtz's co-authors include Jayant A. Talwalkar, Scott J. Schoenleber, Víctor M. Montori, Ash A. Alizadeh, Maximilian Diehn, Colin P. West, Florian Scherer, Jacob J. Chabon, Chih Long Liu and Aaron M. Newman and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

David M. Kurtz

95 papers receiving 2.9k citations

Hit Papers

Integrated digital error suppression for improved detecti... 2016 2026 2019 2022 2016 200 400 600

Peers

David M. Kurtz
Sun‐Young Kong South Korea
David M. Kurtz
Citations per year, relative to David M. Kurtz David M. Kurtz (= 1×) peers Sun‐Young Kong

Countries citing papers authored by David M. Kurtz

Since Specialization
Citations

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

Fields of papers citing papers by David M. Kurtz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David M. Kurtz

This figure shows the co-authorship network connecting the top 25 collaborators of David M. Kurtz. A scholar is included among the top collaborators of David M. Kurtz 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 David M. Kurtz. David M. Kurtz 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.
Strati, Paolo, Lei Feng, Jason R. Westin, et al.. (2025). Frontline acalabrutinib, lenalidomide and rituximab for advanced stage follicular lymphoma with high tumor burden: phase II trial. Nature Communications. 16(1). 7300–7300.
2.
Roschewski, Mark, David M. Kurtz, Jason R. Westin, et al.. (2025). Remission Assessment by Circulating Tumor DNA in Large B-Cell Lymphoma. Journal of Clinical Oncology. 43(34). 3652–3661.
3.
Kurtz, David M., et al.. (2024). Dry Heat Sterilization of a Pelleted, Natural Ingredient Rodent Diet. Journal of the American Association for Laboratory Animal Science. 63(4). 377–384.
4.
Durán, George E., Sebastian Fernandez‐Pol, Shufeng Li, et al.. (2024). Genetic alteration of class I HLA in cutaneous T-cell lymphoma. Blood. 145(3). 311–324. 1 indexed citations
5.
Cabel, Luc, David M. Kurtz, Daniel W. Ross, et al.. (2024). 293P Ultra-sensitive ctDNA detection and monitoring in early breast cancer using PhasED-Seq. Annals of Oncology. 35. S338–S338. 1 indexed citations
6.
Goldstein, Jordan, Christopher Abbosh, Ash A. Alizadeh, Maximilian Diehn, & David M. Kurtz. (2024). Abstract 986: Mathematical modeling of ctDNA dynamics to predict utility of ultrasensitive MRD assays in early stage non-small cell lung cancer (NSCLC). Cancer Research. 84(6_Supplement). 986–986. 1 indexed citations
7.
Goldstein, Jordan, Mark Roschewski, Won-Seog Kim, et al.. (2024). Baseline Prognostic Factors Do Not Predict End of Treatment Ctdna MRD Status and Have Limited Impact on MRD Prognostic Performance in DLBCL. Blood. 144(Supplement 1). 651–651.
8.
Roschewski, Mark, David M. Kurtz, Jason R. Westin, et al.. (2023). MRD‐NEGATIVITY AFTER FRONTLINE DLBCL THERAPY: POOLED ANALYSIS OF 6 CLINICAL TRIALS. Hematological Oncology. 41(S2). 177–179. 5 indexed citations
9.
Schroers‐Martin, Joseph G., Jurik Mutter, Mohammad Shahrokh Esfahani, et al.. (2023). Longitudinal Noninvasive Surveillance & Fragmentomic Characterization of Follicular Lymphoma. Blood. 142(Supplement 1). 528–528.
10.
Schroers‐Martin, Joseph G., Joanne Soo, Florian Scherer, et al.. (2023). Tracing Founder Mutations in Circulating and Tissue-Resident Follicular Lymphoma Precursors. Cancer Discovery. 13(6). 1310–1323. 23 indexed citations
11.
Nagy, Ákos, Gregory J. Hogan, Jacob J. Chabon, et al.. (2023). Phased Variants Allow Robust Profiling of Circulating Tumor DNA in Untreated Follicular Lymphomas. Blood. 142(Supplement 1). 1626–1626. 1 indexed citations
13.
Gunaratne, Ruwan, Matthew Schwede, Matthew S. Alkaitis, et al.. (2023). Development of Circulating Tumor DNA (ctDNA) for Molecular Measurable Residual Disease (MRD) in Acute Myeloid Leukemia (AML). Blood. 142(Supplement 1). 4307–4307. 1 indexed citations
14.
Shree, Tanaya, Vishnu Shankar, Debra K. Czerwinski, et al.. (2022). CD20-Targeted Therapy Ablates De Novo Antibody Response to Vaccination but Spares Preestablished Immunity. Blood Cancer Discovery. 3(2). 95–102. 27 indexed citations
15.
Steen, Chloé B., Bogdan Luca, Mohammad Shahrokh Esfahani, et al.. (2021). The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma. Cancer Cell. 39(10). 1422–1437.e10. 149 indexed citations
16.
Sills, Robert C., G. Allan Johnson, Robert J. Anderson, et al.. (2020). Qualitative and Quantitative Neuropathology Approaches Using Magnetic Resonance Microscopy (Diffusion Tensor Imaging) and Stereology in a Hexachlorophene Model of Myelinopathy in Sprague-Dawley Rats. Toxicologic Pathology. 48(8). 965–980. 3 indexed citations
17.
Schroers‐Martin, Joseph G., Florian Scherer, Joanne Soo, et al.. (2017). Hierarchy in Somatic Mutations Detected in Circulating and Tissue-Resident Follicular Lymphoma Precursors before Clinical Diagnosis. Blood. 130. 308–308. 1 indexed citations
18.
Soo, Joanne, Florian Scherer, David M. Kurtz, et al.. (2017). Reproducibility of m7-FLIPI Risk Scores in Follicular Lymphoma Using Tumor Biopsies and Blood Specimens. Blood. 130. 1466. 1 indexed citations
19.
O’Neill, Brian Patrick, Mark E. Law, Paul A. Decker, et al.. (2008). Del(6)(q22) and BCL6 Rearrangements in Primary CNS Lymphoma Are Indicators of an Aggressive Clinical Course. Journal of Clinical Oncology. 26(29). 4814–4819. 78 indexed citations
20.
Kurtz, David M., Ravi Tolwani, & Philip A. Wood. (1998). Structural characterization of the mouse long-chain acyl-CoA dehydrogenase gene and 5′ regulatory region. Mammalian Genome. 9(5). 361–365. 17 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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