Stephen Zappala

734 total citations
21 papers, 239 citations indexed

About

Stephen Zappala is a scholar working on Pulmonary and Respiratory Medicine, Statistics and Probability and Surgery. According to data from OpenAlex, Stephen Zappala has authored 21 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Pulmonary and Respiratory Medicine, 4 papers in Statistics and Probability and 3 papers in Surgery. Recurrent topics in Stephen Zappala's work include Prostate Cancer Treatment and Research (14 papers), Prostate Cancer Diagnosis and Treatment (12 papers) and Statistical Methods in Clinical Trials (4 papers). Stephen Zappala is often cited by papers focused on Prostate Cancer Treatment and Research (14 papers), Prostate Cancer Diagnosis and Treatment (12 papers) and Statistical Methods in Clinical Trials (4 papers). Stephen Zappala collaborates with scholars based in United States, Sweden and Italy. Stephen Zappala's co-authors include Yan Dong, Vincent Linder, David Okrongly, Dipen J. Parekh, Peter T. Scardino, Jeffrey Voigt, Alan J. Wein, E. Darracott Vaughan, Badrinath R. Konety and Kenneth Kernen and has published in prestigious journals such as Journal of Clinical Oncology, The Journal of Urology and Urology.

In The Last Decade

Stephen Zappala

18 papers receiving 231 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Zappala United States 10 191 53 37 34 31 21 239
Kenneth L. Zeitzer United States 10 255 1.3× 42 0.8× 30 0.8× 20 0.6× 34 1.1× 22 297
Marguerite du Plessis United States 7 199 1.0× 65 1.2× 80 2.2× 11 0.3× 46 1.5× 22 290
Jacques Irani France 8 216 1.1× 67 1.3× 75 2.0× 9 0.3× 62 2.0× 12 338
R.G.H.M. Cremers Netherlands 8 142 0.7× 37 0.7× 28 0.8× 6 0.2× 35 1.1× 16 222
U. W. Tunn Germany 7 254 1.3× 35 0.7× 39 1.1× 12 0.4× 47 1.5× 11 305
Alexander G. Balogh Canada 7 189 1.0× 36 0.7× 25 0.7× 23 0.7× 15 0.5× 10 223
C. Sturgeon United Kingdom 3 166 0.9× 44 0.8× 48 1.3× 20 0.6× 58 1.9× 3 295
Á. Gómez-Ferrer Spain 11 318 1.7× 32 0.6× 95 2.6× 12 0.4× 27 0.9× 67 406
Heikki Seikkula Finland 8 104 0.5× 28 0.5× 33 0.9× 5 0.1× 79 2.5× 30 204
Mary Achim United States 12 271 1.4× 42 0.8× 76 2.1× 16 0.5× 16 0.5× 23 323

Countries citing papers authored by Stephen Zappala

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Zappala

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Zappala

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Zappala. A scholar is included among the top collaborators of Stephen Zappala 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 Stephen Zappala. Stephen Zappala 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.
Vertosick, Emily, Stephen Zappala, Sanoj Punnen, et al.. (2021). Individual Patient Data Meta-analysis of Discrimination of the Four Kallikrein Panel Associated With the Inclusion of Prostate Volume. Urology. 157. 102–106. 1 indexed citations
2.
Bhattu, Amit S., Stephen Zappala, Dipen J. Parekh, & Sanoj Punnen. (2020). A 4Kscore Cut-off of 7.5% for Prostate Biopsy Decisions Provides High Sensitivity and Negative Predictive Value for Significant Prostate Cancer. Urology. 148. 53–58. 10 indexed citations
3.
Marzouk, Karim, Behfar Ehdaie, Emily Vertosick, Stephen Zappala, & Andrew J. Vickers. (2019). Developing an effective strategy to improve the detection of significant prostate cancer by combining the 4Kscore and multiparametric MRI. Urologic Oncology Seminars and Original Investigations. 37(10). 672–677. 13 indexed citations
4.
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Vickers, Andrew J., Emily Vertosick, Daniel D. Sjoberg, et al.. (2018). Value of Intact Prostate Specific Antigen and Human Kallikrein 2 in the 4 Kallikrein Predictive Model: An Individual Patient Data Meta-Analysis. The Journal of Urology. 199(6). 1470–1474. 10 indexed citations
6.
Zappala, Stephen, Yan Dong, Vincent Linder, et al.. (2017). The 4Kscore blood test accurately identifies men with aggressive prostate cancer prior to prostate biopsy with or without DRE information. International Journal of Clinical Practice. 71(6). e12943–e12943. 22 indexed citations
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Punnen, Sanoj, Bruno Nahar, Nachiketh Soodana‐Prakash, et al.. (2016). The 4Kscore Predicts the Grade and Stage of Prostate Cancer in the Radical Prostatectomy Specimen: Results from a Multi-institutional Prospective Trial. European Urology Focus. 3(1). 94–99. 9 indexed citations
10.
Vickers, Andrew J., Emily Vertosick, Daniel D. Sjoberg, et al.. (2016). Properties of the 4-Kallikrein Panel Outside the Diagnostic Gray Zone: Meta-Analysis of Patients with Positive Digital Rectal Examination or Prostate Specific Antigen 10 ng/ml and Above. The Journal of Urology. 197(3 Part 1). 607–613. 10 indexed citations
11.
Nahar, Bruno, Sanoj Punnen, Daniel D. Sjoberg, Stephen Zappala, & Dipen J. Parekh. (2016). The 4Kscore to predict the grade and stage of prostate cancer in the radical prostatectomy specimen: Results from a multi-institutional prospective trial.. Journal of Clinical Oncology. 34(2_suppl). 69–69.
12.
Albala, David, Vladimir Mouraviev, Kimberly Rieger‐Christ, et al.. (2016). A live cell microfluidics device utilizing phenotypic biomarkers for prostate cancer.. Journal of Clinical Oncology. 34(2_suppl). 338–338. 1 indexed citations
13.
Albala, David, Vladimir Mouraviev, Kimberly Rieger‐Christ, et al.. (2016). MP07-17 CLINICAL VALIDATION OF A LIVE-CELL PHENOTYPIC BIOMARKER - BASED DIAGNOSTIC ASSAY FOR THE PREDICTION OF ADVERSE PATHOLOGY IN PROSTATE CANCER. The Journal of Urology. 195(4S). 1 indexed citations
14.
Punnen, Sanoj, Stephen Zappala, Joan Palou, et al.. (2015). 433 Among men with low-grade prostate cancer on prostate biopsy, the 4Kscore predicts the presence of more aggressive prostate cancer. European Urology Supplements. 14(2). e433–e433. 2 indexed citations
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Konety, Badrinath R., et al.. (2015). The 4Kscore® Test Reduces Prostate Biopsy Rates in Community and Academic Urology Practices.. PubMed. 17(4). 231–40. 42 indexed citations
17.
Voigt, Jeffrey, Stephen Zappala, E. Darracott Vaughan, & Alan J. Wein. (2013). The Kallikrein Panel for prostate cancer screening: Its economic impact. The Prostate. 74(3). 250–259. 29 indexed citations
18.
Zappala, Stephen, et al.. (2003). [Early diagnosis of gastric cancer].. PubMed. 61(3). 276–81.
19.
Pittiruti, Mauro, et al.. (1998). Tension-free hernioplasty: technical remarks and personal experience.. PubMed. 68(3). 343–5; discussion 345. 1 indexed citations
20.
Zappala, Stephen, et al.. (1992). Management of intraoperative penile erections with diluted epinephrine solution. Urology. 40(1). 76–77. 13 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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