Susan Geyer

5.5k total citations
73 papers, 2.3k citations indexed

About

Susan Geyer is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism and Surgery. According to data from OpenAlex, Susan Geyer has authored 73 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Genetics, 28 papers in Endocrinology, Diabetes and Metabolism and 26 papers in Surgery. Recurrent topics in Susan Geyer's work include Diabetes and associated disorders (27 papers), Diabetes Management and Research (26 papers) and Pancreatic function and diabetes (26 papers). Susan Geyer is often cited by papers focused on Diabetes and associated disorders (27 papers), Diabetes Management and Research (26 papers) and Pancreatic function and diabetes (26 papers). Susan Geyer collaborates with scholars based in United States, Australia and United Kingdom. Susan Geyer's co-authors include Jay M. Sosenko, Carmella Evans‐Molina, María J. Redondo, Haifeng Wu, Shangbin Yang, Spero R. Cataland, Ingrid Libman, Andrea K. Steck, Linda A. DiMeglio and Alberto Pugliese and has published in prestigious journals such as Journal of Clinical Oncology, Blood and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Susan Geyer

69 papers receiving 2.2k citations

Peers

Susan Geyer
John P. Bida United States
Michael T. Stang United States
Lulu Ren Sterling United States
J. D. Macfarlane Netherlands
Jolanta Kowalewska United States
Susan Geyer
Citations per year, relative to Susan Geyer Susan Geyer (= 1×) peers Hiroyuki Osawa

Countries citing papers authored by Susan Geyer

Since Specialization
Citations

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

Fields of papers citing papers by Susan Geyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Susan Geyer

This figure shows the co-authorship network connecting the top 25 collaborators of Susan Geyer. A scholar is included among the top collaborators of Susan Geyer 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 Susan Geyer. Susan Geyer 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.
Bergsland, Emily K., Susan Geyer, Timothy R. Asmis, et al.. (2025). Randomized Phase II Trial of Pazopanib Versus Placebo in Patients With Advanced Extrapancreatic Neuroendocrine Tumors (Alliance A021202). Journal of Clinical Oncology. 43(29). 3170–3183.
3.
Sims, Emily K., Susan Geyer, S. Alice Long, & Kevan C. Herold. (2023). High proinsulin:C-peptide ratio identifies individuals with stage 2 type 1 diabetes at high risk for progression to clinical diagnosis and responses to teplizumab treatment. Diabetologia. 66(12). 2283–2291. 6 indexed citations
4.
Redondo, María J., Megan Warnock, Ingrid Libman, et al.. (2021). TCF7L2 Genetic Variants Do Not Influence Insulin Sensitivity or Secretion Indices in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes. Diabetes Care. 44(9). 2039–2044. 1 indexed citations
5.
Sims, Emily K., Susan Geyer, Suzanne Bennett Johnson, et al.. (2019). Who Is Enrolling? The Path to Monitoring in Type 1 Diabetes TrialNet’s Pathway to Prevention. Diabetes Care. 42(12). 2228–2236. 24 indexed citations
6.
Tosur, Mustafa, Susan Geyer, Henry Rodriguez, et al.. (2018). Ethnic differences in progression of islet autoimmunity and type 1 diabetes in relatives at risk. Diabetologia. 61(9). 2043–2053. 29 indexed citations
7.
Evans‐Molina, Carmella, Emily K. Sims, Linda A. DiMeglio, et al.. (2018). β Cell dysfunction exists more than 5 years before type 1 diabetes diagnosis. JCI Insight. 3(15). 80 indexed citations
8.
Monk, Paul, Glenn Liu, Walter M. Stadler, et al.. (2018). Phase II randomized, double-blind, placebo-controlled study of tivantinib in men with asymptomatic or minimally symptomatic metastatic castration-resistant prostate cancer (mCRPC). Investigational New Drugs. 36(5). 919–926. 9 indexed citations
9.
Sallman, David A., Rami S. Komrokji, Kathy L. McGraw, et al.. (2017). Immune Checkpoint Profiling of TP53 Mutant and Wild-Type Myeloid Malignancies: TP53 Mutations Direct Immune Tolerance Via an Immunosuppressive Phenotype. Blood. 130. 423–423. 6 indexed citations
10.
Battaglia, Manuela, Mark S. Anderson, Jane H. Buckner, et al.. (2017). Understanding and preventing type 1 diabetes through the unique working model of TrialNet. Diabetologia. 60(11). 2139–2147. 54 indexed citations
11.
Konda, Bhavana, Michael V. Knopp, Peter R. Martin, et al.. (2017). Effect of cabozantinib on bone turnover markers (BTM) and bone metastases (BM) in radioiodine refractory (RAIR)-differentiated thyroid cancer (DTC).. Journal of Clinical Oncology. 35(15_suppl). e17580–e17580. 2 indexed citations
12.
Farren, Matthew R., Thomas A. Mace, Susan Geyer, et al.. (2015). Systemic Immune Activity Predicts Overall Survival in Treatment-Naïve Patients with Metastatic Pancreatic Cancer. Clinical Cancer Research. 22(10). 2565–2574. 69 indexed citations
13.
Sallman, David A., Rami S. Komrokji, Christine Vaupel, et al.. (2015). Impact of TP53 mutation variant allele frequency on phenotype and outcomes in myelodysplastic syndromes. Leukemia. 30(3). 666–673. 137 indexed citations
14.
Muszynski, Jennifer A., Ryan A. Nofziger, Kristin Greathouse, et al.. (2014). Innate Immune Function Predicts the Development of Nosocomial Infection in Critically Injured Children. Shock. 42(4). 313–321. 62 indexed citations
15.
Lustberg, Mark, Ronald P. Pelletier, Pierluigi Porcu, et al.. (2014). Human Leukocyte Antigen Type and Posttransplant Lymphoproliferative Disorder. Transplantation. 99(6). 1220–1225. 13 indexed citations
16.
Wu, Wenting, et al.. (2013). A phase II flexible screening design allowing for interim analysis and comparison with historical control. Contemporary Clinical Trials. 35(2). 128–137. 1 indexed citations
17.
Takahashi, Ikuno, Susan Geyer, Nobuo Nishi, et al.. (2011). Lifetime risk of stroke and impact of hypertension: estimates from the adult health study in Hiroshima and Nagasaki. Hypertension Research. 34(5). 649–654. 18 indexed citations
18.
Geyer, Susan, Lindsay M. Morton, Thomas M. Habermann, et al.. (2010). Smoking, alcohol use, obesity, and overall survival from non‐Hodgkin lymphoma. Cancer. 116(12). 2993–3000. 62 indexed citations
19.
Lust, John A., Martha Q. Lacy, Steven R. Zeldenrust, et al.. (2009). Induction of a Chronic Disease State in Patients With Smoldering or Indolent Multiple Myeloma by Targeting Interleukin 1β-Induced Interleukin 6 Production and the Myeloma Proliferative Component. Mayo Clinic Proceedings. 84(2). 114–122. 196 indexed citations
20.
Martin, William G., Roshini S. Abraham, Tait D. Shanafelt, et al.. (2007). Serum-free light chain—a new biomarker for patients with B-cell non-Hodgkin lymphoma and chronic lymphocytic leukemia. Translational research. 149(4). 231–235. 50 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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