Diana Abbott

3.9k total citations · 1 hit paper
62 papers, 1.8k citations indexed

About

Diana Abbott is a scholar working on Hematology, Oncology and Molecular Biology. According to data from OpenAlex, Diana Abbott has authored 62 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Hematology, 15 papers in Oncology and 13 papers in Molecular Biology. Recurrent topics in Diana Abbott's work include Acute Myeloid Leukemia Research (20 papers), Chronic Myeloid Leukemia Treatments (9 papers) and Lymphoma Diagnosis and Treatment (9 papers). Diana Abbott is often cited by papers focused on Acute Myeloid Leukemia Research (20 papers), Chronic Myeloid Leukemia Treatments (9 papers) and Lymphoma Diagnosis and Treatment (9 papers). Diana Abbott collaborates with scholars based in United States, France and Australia. Diana Abbott's co-authors include Daniel A. Pollyea, Craig T. Jordan, Amanda Winters, Kai Wang, Clayton A. Smith, Jonathan A. Gutman, Brett M. Stevens, Shanshan Pei, Courtney L. Jones and Angelo D’Alessandro and has published in prestigious journals such as Nature Medicine, Blood and Annals of Internal Medicine.

In The Last Decade

Diana Abbott

56 papers receiving 1.7k citations

Hit Papers

Venetoclax with azacitidine disrupts energy metabolism an... 2018 2026 2020 2023 2018 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Diana Abbott United States 19 750 745 280 258 186 62 1.8k
Dorothy McCabe United States 17 706 0.9× 541 0.7× 88 0.3× 362 1.4× 86 0.5× 37 2.5k
Scott W. Baumgartner United States 16 1.0k 1.3× 343 0.5× 124 0.4× 255 1.0× 90 0.5× 18 2.5k
Paola Conigliaro Italy 27 389 0.5× 363 0.5× 165 0.6× 173 0.7× 91 0.5× 97 2.0k
Ken J. Bulpitt United States 21 888 1.2× 380 0.5× 148 0.5× 217 0.8× 70 0.4× 33 2.9k
Philipp B. Staber Austria 23 390 0.5× 804 1.1× 130 0.5× 593 2.3× 189 1.0× 88 1.9k
Antonio Manzo Italy 30 246 0.3× 449 0.6× 131 0.5× 599 2.3× 86 0.5× 72 3.0k
Thierry Lequerré France 21 504 0.7× 457 0.6× 102 0.4× 141 0.5× 50 0.3× 87 1.5k
Joseph A. Markenson United States 20 1.0k 1.4× 192 0.3× 170 0.6× 170 0.7× 48 0.3× 42 3.0k
Mei‐Jie Zhang United States 19 1.5k 2.1× 240 0.3× 171 0.6× 481 1.9× 88 0.5× 67 2.3k
Lalitha Nayak United States 19 237 0.3× 839 1.1× 132 0.5× 205 0.8× 195 1.0× 57 2.0k

Countries citing papers authored by Diana Abbott

Since Specialization
Citations

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

Fields of papers citing papers by Diana Abbott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diana Abbott

This figure shows the co-authorship network connecting the top 25 collaborators of Diana Abbott. A scholar is included among the top collaborators of Diana Abbott 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 Diana Abbott. Diana Abbott 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.
McMahon, Christine M., Maria L. Amaya, Jonathan A. Gutman, et al.. (2024). Efficacy and Molecular Predictors of Response and Survival for Venetoclax/Azacitidine Therapy in Relapsed or Refractory Acute Myeloid Leukemia. Blood. 144(Supplement 1). 4266–4266. 1 indexed citations
2.
Allen, Jessica, Diana Abbott, Steven M. Bair, et al.. (2024). DA-R-EPOCH May Mitigate the Adverse Prognostic Implication of the Diagnosis-to-Treatment Interval (DTI) in Large B-Cell Lymphomas. Clinical Lymphoma Myeloma & Leukemia. 25(1). e26–e33.
3.
Winters, Amanda, Mohd Minhajuddin, Brett M. Stevens, et al.. (2023). Multi-gene measurable residual disease assessed by digital polymerase chain reaction has clinical and biological utility in acute myeloid leukemia patients receiving venetoclax/azacitidine. Haematologica. 109(6). 1766–1778. 5 indexed citations
4.
Haverkos, Bradley M., Jasmine M. Zain, Manali Kamdar, et al.. (2023). Frontline chemoimmunotherapy with nivolumab and dose-adjusted EPOCH in peripheral T-cell lymphoma: a phase 1 trial. Blood Advances. 8(3). 708–711. 2 indexed citations
5.
Abbott, Diana, Christine M. McMahon, Jonathan A. Gutman, et al.. (2023). Socioeconomic Status Is a Mediator of Overall Survival in Acute Myeloid Leukemia (AML). Blood. 142(Supplement 1). 5176–5176.
6.
Winters, Amanda, Diana Abbott, Mohd Minhajuddin, et al.. (2022). Outcomes Are Similar After Allogeneic Hematopoietic Stem Cell Transplant for Newly Diagnosed Acute Myeloid Leukemia Patients who Received Venetoclax + Azacitidine Versus Intensive Chemotherapy. Transplantation and Cellular Therapy. 28(10). 694.e1–694.e9. 32 indexed citations
7.
Stevens, Brett M., Courtney L. Jones, Daniel A. Pollyea, et al.. (2020). Fatty acid metabolism underlies venetoclax resistance in acute myeloid leukemia stem cells. Nature Cancer. 1(12). 1176–1187. 178 indexed citations
9.
Monte, Andrew A., Shelby K. Shelton, Jessica L. Saben, et al.. (2019). Acute Illness Associated With Cannabis Use, by Route of Exposure. Annals of Internal Medicine. 6 indexed citations
10.
Stevens, Brett M., Amanda Winters, Jonathan A. Gutman, et al.. (2019). Sequential azacitidine and lenalidomide for patients with relapsed and refractory acute myeloid leukemia: Clinical results and predictive modeling using computational analysis. Leukemia Research. 81. 43–49. 4 indexed citations
11.
Kohlmann, Wendy, Thomas M. Kollmeyer, Robert B. Jenkins, et al.. (2019). The contribution of the rs55705857 G allele to familial cancer risk as estimated in the Utah population database. BMC Cancer. 19(1). 190–190. 3 indexed citations
12.
Stevens, Brett M., Courtney L. Jones, Amanda Winters, et al.. (2018). PTPN11 Mutations Confer Unique Metabolic Properties and Increase Resistance to Venetoclax and Azacitidine in Acute Myelogenous Leukemia. Blood. 132(Supplement 1). 909–909. 20 indexed citations
13.
Pollyea, Daniel A., Brett M. Stevens, Courtney L. Jones, et al.. (2018). Venetoclax with azacitidine disrupts energy metabolism and targets leukemia stem cells in patients with acute myeloid leukemia. Nature Medicine. 24(12). 1859–1866. 481 indexed citations breakdown →
14.
15.
Sumner, Whitney, William A. Stokes, Ayman Oweida, et al.. (2017). Survival impact of pre-treatment neutrophils on oropharyngeal and laryngeal cancer patients undergoing definitive radiotherapy. Journal of Translational Medicine. 15(1). 168–168. 23 indexed citations
16.
Abbott, Diana, et al.. (2017). Safety of Outpatient Circumferential Body Lift: Evidence from 42 Consecutive Cases. Plastic & Reconstructive Surgery. 139(6). 1355–1362. 9 indexed citations
17.
Stokes, William A., Diana Abbott, Andy V. Phan, et al.. (2017). Patterns of Care for Patients With Early-Stage Glottic Cancer Undergoing Definitive Radiation Therapy: A National Cancer Database Analysis. International Journal of Radiation Oncology*Biology*Physics. 98(5). 1014–1021. 23 indexed citations
19.
Abbott, Diana, et al.. (2013). Cycle Time Metrics for Multisite Clinical Trials in the United States. Therapeutic Innovation & Regulatory Science. 47(2). 152–160. 14 indexed citations
20.
Wang, Kai & Diana Abbott. (2007). A principal components regression approach to multilocus genetic association studies. Genetic Epidemiology. 32(2). 108–118. 117 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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