Steve Lewitzky

2.4k total citations · 1 hit paper
14 papers, 1.8k citations indexed

About

Steve Lewitzky is a scholar working on Genetics, Economics and Econometrics and Molecular Biology. According to data from OpenAlex, Steve Lewitzky has authored 14 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Genetics, 3 papers in Economics and Econometrics and 2 papers in Molecular Biology. Recurrent topics in Steve Lewitzky's work include Healthcare Policy and Management (3 papers), Genetic Associations and Epidemiology (2 papers) and Autoimmune Bullous Skin Diseases (2 papers). Steve Lewitzky is often cited by papers focused on Healthcare Policy and Management (3 papers), Genetic Associations and Epidemiology (2 papers) and Autoimmune Bullous Skin Diseases (2 papers). Steve Lewitzky collaborates with scholars based in United States, Switzerland and Australia. Steve Lewitzky's co-authors include Wolfgang Hueber, Marc Vandemeulebroecke, Simon Travis, Jan Wehkamp, Peter Higgins, Walter Reinisch, Gerard Bruin, Jacek Karczewski, Arthur P. Bertolino and Marco Londei and has published in prestigious journals such as Nature Genetics, Journal of the American Statistical Association and Diabetes.

In The Last Decade

Steve Lewitzky

14 papers receiving 1.8k citations

Hit Papers

align trajectories

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.

Secukinumab, a human anti-IL-17A monoclonal antibody, for moderate to severe Crohn's disease: unexpected results of a randomised, double-blind placebo-controlled trial

2012 1.2k citations Wolfgang Hueber, Bruce E. Sands et al. Gut profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Steve Lewitzky United States	10	887	600	285	282	281	14	1.8k
D. Sayer Australia	18	978 1.1×	219 0.4×	309 1.1×	245 0.9×	329 1.2×	52	2.6k
Mariam Molokhia United Kingdom	20	658 0.7×	280 0.5×	156 0.5×	256 0.9×	225 0.8×	32	1.8k
Arthur Kavanaugh United States	20	520 0.6×	331 0.6×	279 1.0×	285 1.0×	783 2.8×	44	1.9k
Stephan Bek Germany	9	1.0k 1.2×	519 0.9×	267 0.9×	509 1.8×	340 1.2×	11	1.8k
Marc Vandemeulebroecke Switzerland	13	868 1.0×	475 0.8×	244 0.9×	218 0.8×	264 0.9×	36	1.9k
Yoichi Kakuta Japan	20	391 0.4×	651 1.1×	367 1.3×	383 1.4×	125 0.4×	120	1.6k
Carrie Brodmerkel United States	28	1.9k 2.1×	409 0.7×	434 1.5×	479 1.7×	867 3.1×	58	3.4k
Jon Florholmen Norway	27	771 0.9×	886 1.5×	551 1.9×	378 1.3×	49 0.2×	60	2.0k
Patrizia Ricci Italy	25	616 0.7×	134 0.2×	232 0.8×	478 1.7×	61 0.2×	53	1.8k
J.M. Carrascosa Spain	30	2.1k 2.3×	99 0.2×	317 1.1×	227 0.8×	455 1.6×	211	3.0k

Countries citing papers authored by Steve Lewitzky

Since Specialization

Citations

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

Fields of papers citing papers by Steve Lewitzky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Steve Lewitzky

This figure shows the co-authorship network connecting the top 25 collaborators of Steve Lewitzky. A scholar is included among the top collaborators of Steve Lewitzky 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 Steve Lewitzky. Steve Lewitzky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

1.

Burmester, Gerd R, Patrick Durez, Mark C. Genovese, et al.. (2015). Association ofHLA-DRB1alleles with clinical responses to the anti-interleukin-17A monoclonal antibody secukinumab in active rheumatoid arthritis. Lara D. Veeken. 55(1). 49–55. 37 indexed citations

2.

Hueber, Wolfgang, Bruce E. Sands, Steve Lewitzky, et al.. (2012). Secukinumab, a human anti-IL-17A monoclonal antibody, for moderate to severe Crohn's disease: unexpected results of a randomised, double-blind placebo-controlled trial. Gut. 61(12). 1693–1700. 1156 indexed citations breakdown →

3.

Yelensky, Roman, Steve Lewitzky, Elizabeth C. LeRoy, et al.. (2011). A pharmacogenetic study of ADRB2 polymorphisms and indacaterol response in COPD patients. The Pharmacogenomics Journal. 12(6). 484–488. 11 indexed citations

4.

Singer, Jonathan B., Steve Lewitzky, Elisabeth Leroy, et al.. (2010). A genome-wide study identifies HLA alleles associated with lumiracoxib-related liver injury. Nature Genetics. 42(8). 711–714. 273 indexed citations

5.

Paulding, Charles, Jonathan B. Singer, Steve Lewitzky, et al.. (2010). OC-036 A genome-wide study identifies HLA alleles associated with lumiracoxib-related liver injury. Gut. 59(Suppl 1). A15.2–A15. 1 indexed citations

6.

McCarthy, Jeanette, Steve Lewitzky, Cynthia Reeves, et al.. (2003). Polymorphisms of the HDL Receptor Gene Associated with HDL Cholesterol Levels in Diabetic Kindred from Three Populations. Human Heredity. 55(4). 163–170. 26 indexed citations

7.

McCarthy, Jeanette, Steve Lewitzky, Alan Permutt, et al.. (2001). SR-B1 variants associated with HDL cholesterol levels in three populations. Lund University Publications (Lund University). 2 indexed citations

8.

Xu, Xin, Zhian Fang, Binyan Wang, et al.. (2001). A Genomewide Search for Quantitative-Trait Loci Underlying Asthma. The American Journal of Human Genetics. 69(6). 1271–1277. 63 indexed citations

9.

Suarez, Brian K., Jennifer Y. Lin, Jeffrey D. Thomas, et al.. (2001). A Genome Scan for Type 2 Diabetes Susceptibility Loci in a Genetically Isolated Population. Diabetes. 50(3). 681–685. 110 indexed citations

10.

Parker, Alex, Joanne M. Meyer, Steve Lewitzky, et al.. (2001). A Gene Conferring Susceptibility to Type 2 Diabetes in Conjunction With Obesity Is Located on Chromosome 18p11. Diabetes. 50(3). 675–680. 74 indexed citations

11.

Elliott, Michael R., Roderick J. A. Little, & Steve Lewitzky. (2000). Subsampling Callbacks to Improve Survey Efficiency. Journal of the American Statistical Association. 95(451). 730–738. 20 indexed citations

12.

Elliott, Michael R., Roderick J. A. Little, & Steve Lewitzky. (2000). Subsampling Callbacks to Improve Survey Efficiency. Journal of the American Statistical Association. 95(451). 730–730. 2 indexed citations

13.

Little, R. J. A., Steve Lewitzky, Steven G. Heeringa, James M. Lepkowski, & Ronald C. Kessler. (1997). Assessment of Weighting Methodology for the National Comorbidity Survey. American Journal of Epidemiology. 146(5). 439–449. 65 indexed citations

14.

Cronin, Francis J., et al.. (1995). The calculation and application of composite telecommunications service price indexes. Information Economics and Policy. 7(1). 1–26. 3 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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