Kenneth J. Kopecky

14.5k total citations · 5 hit papers
162 papers, 10.5k citations indexed

About

Kenneth J. Kopecky is a scholar working on Hematology, Oncology and Economics and Econometrics. According to data from OpenAlex, Kenneth J. Kopecky has authored 162 papers receiving a total of 10.5k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Hematology, 30 papers in Oncology and 28 papers in Economics and Econometrics. Recurrent topics in Kenneth J. Kopecky's work include Acute Myeloid Leukemia Research (53 papers), Radiation Dose and Imaging (17 papers) and Chronic Myeloid Leukemia Treatments (15 papers). Kenneth J. Kopecky is often cited by papers focused on Acute Myeloid Leukemia Research (53 papers), Radiation Dose and Imaging (17 papers) and Chronic Myeloid Leukemia Treatments (15 papers). Kenneth J. Kopecky collaborates with scholars based in United States, Japan and Canada. Kenneth J. Kopecky's co-authors include Frederick R. Appelbaum, Cheryl L. Willman, Marilyn L. Slovak, David R. Head, Catherine P. Leith, Stephen J. Forman, Peter A. Cassileth, John E. Godwin, I‐Ming Chen and Thomas S. McConnell and has published in prestigious journals such as New England Journal of Medicine, JAMA and Journal of Clinical Oncology.

In The Last Decade

Kenneth J. Kopecky

160 papers receiving 10.1k citations

Hit Papers

Karyotypic analysis predicts outcome of preremis... 1980 2026 1995 2010 2000 1997 2009 2013 1980 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Karyotypic analysis predicts outcome of preremission and postremission therapy in adult acute myeloid leukemia: a Southwest Oncology Group/Eastern Cooperative Oncology Group study
    2000 1.2k citations Marilyn L. Slovak, Kenneth J. Kopecky et al. Blood profile →
  2. Acute Myeloid Leukemia in the Elderly: Assessment of Multidrug Resistance (MDR1) and Cytogenetics Distinguishes Biologic Subgroups With Remarkably Distinct Responses to Standard Chemotherapy. A Southwest Oncology Group Study
    1997 696 citations Catherine P. Leith, Kenneth J. Kopecky et al. Blood profile →
  3. Allogeneic Stem Cell Transplantation for Acute Myeloid Leukemia in First Complete Remission
    2009 604 citations Kenneth J. Kopecky, Frederick R. Appelbaum et al. profile →
  4. A phase 3 study of gemtuzumab ozogamicin during induction and postconsolidation therapy in younger patients with acute myeloid leukemia
    2013 460 citations Stephen H. Petersdorf, Kenneth J. Kopecky et al. Blood profile →
  5. An analysis of hepatic venocclusive disease and centrilobular hepatic degeneration following bone marrow transplantation
    1980 215 citations Kenneth J. Kopecky et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kenneth J. Kopecky United States 48 5.8k 2.9k 2.4k 2.2k 1.9k 162 10.5k
Renaud Capdeville Switzerland 29 6.8k 1.2× 3.0k 1.0× 2.8k 1.2× 1.1k 0.5× 5.0k 2.7× 52 13.0k
Martee L. Hensley United States 55 1.5k 0.3× 1.8k 0.6× 4.2k 1.7× 633 0.3× 1.1k 0.6× 223 13.3k
Edmund A. Gehan United States 54 999 0.2× 1.8k 0.6× 3.2k 1.3× 548 0.2× 1.5k 0.8× 143 10.2k
John Crowley United States 80 11.0k 1.9× 10.4k 3.5× 12.9k 5.4× 641 0.3× 2.0k 1.1× 341 28.4k
Frank Griesinger Germany 35 1.7k 0.3× 1.5k 0.5× 1.7k 0.7× 946 0.4× 948 0.5× 275 5.1k
Apostolia M. Tsimberidou United States 58 1.7k 0.3× 4.8k 1.6× 5.4k 2.3× 616 0.3× 2.5k 1.3× 445 14.5k
Richard F. Schlenk Germany 52 9.9k 1.7× 6.3k 2.1× 1.8k 0.8× 2.8k 1.3× 3.7k 2.0× 245 13.4k
Nelson Leung United States 65 5.2k 0.9× 9.6k 3.3× 3.2k 1.3× 366 0.2× 3.1k 1.7× 435 15.4k
Graça M. Dores United States 31 847 0.1× 1.6k 0.5× 2.9k 1.2× 806 0.4× 704 0.4× 83 8.1k
Lois E. Shepherd Canada 48 1.4k 0.2× 3.4k 1.2× 9.9k 4.1× 691 0.3× 1.3k 0.7× 204 15.9k

Countries citing papers authored by Kenneth J. Kopecky

Since Specialization
Citations

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

Fields of papers citing papers by Kenneth J. Kopecky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kenneth J. Kopecky

This figure shows the co-authorship network connecting the top 25 collaborators of Kenneth J. Kopecky. A scholar is included among the top collaborators of Kenneth J. Kopecky 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 Kenneth J. Kopecky. Kenneth J. Kopecky 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.
Kopecky, Kenneth J., et al.. (2018). Revisiting M&M with Taxes: An Alternative Equilibrating Process. International Journal of Financial Studies. 6(1). 10–10. 10 indexed citations
2.
Pogosova‐Agadjanyan, Era L., Anna Moseley, Megan Othus, et al.. (2017). Impact of Specimen Heterogeneity on Biomarkers in Repository Samples from Patients with Acute Myeloid Leukemia: A SWOG Report. Biopreservation and Biobanking. 16(1). 42–52. 6 indexed citations
3.
4.
Coutré, Steven, Megan Othus, Bayard L. Powell, et al.. (2014). Arsenic trioxide during consolidation for patients with previously untreated low/intermediate risk acute promyelocytic leukaemia may eliminate the need for maintenance therapy. British Journal of Haematology. 165(4). 497–503. 28 indexed citations
5.
Roos, Anneclaire J. De, Otoniel Martı́nez-Maza, Keith R. Jerome, et al.. (2013). Investigation of Epstein–Barr Virus as a Potential Cause of B-Cell Non-Hodgkin Lymphoma in a Prospective Cohort. Cancer Epidemiology Biomarkers & Prevention. 22(10). 1747–1755. 14 indexed citations
6.
Schwartz, Jeffrey L., Kenneth J. Kopecky, Robert Mathes, et al.. (2009). Basal Cell Skin Cancer after Total-Body Irradiation and Hematopoietic Cell Transplantation. Radiation Research. 171(2). 155–163. 49 indexed citations
7.
Kuptsova‐Clarkson, Nataliya, Christine B. Ambrosone, Joli Weiss, et al.. (2009). XPD DNA Nucleotide Excision Repair (NER) Gene Polymorphisms Associated with DNA Repair Deficiency May Predict Better Treatment Outcomes in Secondary Acute Myeloid Leukemia (AML).. Blood. 114(22). 168–168. 23 indexed citations
8.
Pullarkat, Vinod, Marilyn L. Slovak, Kenneth J. Kopecky, Stephen J. Forman, & Frederick R. Appelbaum. (2007). Impact of cytogenetics on the outcome of adult acute lymphoblastic leukemia: results of Southwest Oncology Group 9400 study. Blood. 111(5). 2563–2572. 157 indexed citations
9.
10.
Choi, Jongmoo Jay, et al.. (1996). Common factors in international stock prices: Evidence from a cointegration study. International Review of Financial Analysis. 5(1). 39–53. 43 indexed citations
11.
Gurney, James G., Beth A. Mueller, S. Scott Davis, et al.. (1996). Childhood Brain Tumor Occurrence in Relation to Residential Power Line Configurations, Electric Heating Sources, and Electric Appliance Use. American Journal of Epidemiology. 143(2). 120–128. 58 indexed citations
12.
Bigelow, Carolyn, Kenneth J. Kopecky, Joe C. Files, et al.. (1995). Treatment of acute myelogenous leukemia in patients over 50 years of age with V‐TAD: A southwest oncology group study. American Journal of Hematology. 48(4). 228–232. 3 indexed citations
13.
Slovak, Marilyn L., S. Thomas Traweek, Cheryl L. Willman, et al.. (1995). Trisomy 11: an association with stem/progenitor cell immunophenotype. British Journal of Haematology. 90(2). 266–273. 34 indexed citations
14.
Grever, Michael R., Kenneth J. Kopecky, David Head, et al.. (1995). Randomized comparison of pentostatin versus interferon alfa-2a in previously untreated patients with hairy cell leukemia: an intergroup study.. Journal of Clinical Oncology. 13(4). 974–982. 194 indexed citations
15.
Slavik, Milan, Kenneth J. Kopecky, Vernon K. Sondak, John B. Craig, & Michael K. Samson. (1993). Evaluation of amonafide in disseminated malignant melanoma. Investigational New Drugs. 11(2-3). 223–226. 5 indexed citations
16.
17.
Ryan, Donna H., Kenneth J. Kopecky, David Head, et al.. (1992). Analysis of Treatment Failure in Acute Nonlymphocytic Leukemia Patients over Fifty Years of Age. American Journal of Clinical Oncology. 15(1). 69–75. 14 indexed citations
18.
Whitehead, Robert P., Kenneth J. Kopecky, Michael K. Samson, et al.. (1991). Phase II Study of Intravenous Bolus Recombinant Interleukin-2 in Advanced Malignant Melanoma: Southwest Oncology Group Study. JNCI Journal of the National Cancer Institute. 83(17). 1250–1252. 35 indexed citations
19.
Miller, Richard C., Michael N. Gould, Kenneth J. Kopecky, et al.. (1985). Survival of Human Normal Thyroid Cells after X-ray Irradiation. International Journal of Radiation Biology and Related Studies in Physics Chemistry and Medicine. 47(3). 299–307. 13 indexed citations
20.
Froyen, Richard T. & Kenneth J. Kopecky. (1983). A note on reserve requirements and monetary control with a flexible deposit rate. Journal of Banking & Finance. 7(1). 101–109. 9 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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