Saby George

21.7k total citations · 3 hit papers
170 papers, 5.0k citations indexed

About

Saby George is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Surgery. According to data from OpenAlex, Saby George has authored 170 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 119 papers in Pulmonary and Respiratory Medicine, 98 papers in Oncology and 42 papers in Surgery. Recurrent topics in Saby George's work include Renal cell carcinoma treatment (91 papers), Cancer Immunotherapy and Biomarkers (67 papers) and Bladder and Urothelial Cancer Treatments (39 papers). Saby George is often cited by papers focused on Renal cell carcinoma treatment (91 papers), Cancer Immunotherapy and Biomarkers (67 papers) and Bladder and Urothelial Cancer Treatments (39 papers). Saby George collaborates with scholars based in United States, United Kingdom and France. Saby George's co-authors include Brian I. Rini, Robert J. Motzer, Hans J. Hammers, Elizabeth R. Plimack, David F. McDermott, Ulka N. Vaishampayan, Ian M. Waxman, Toni K. Choueiri, Timothy M. Kuzel and Bruce G. Redman and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Saby George

157 papers receiving 4.9k citations

Hit Papers

Nivolumab for Metastatic Renal Cell Carcinoma: Results of... 2014 2026 2018 2022 2014 2020 2018 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saby George United States 30 3.3k 2.8k 1.4k 966 939 170 5.0k
Allen Lee Cohn United States 38 4.7k 1.4× 2.4k 0.8× 1.5k 1.1× 1.3k 1.3× 875 0.9× 159 6.9k
P. Koralewski Poland 23 4.5k 1.4× 3.5k 1.2× 2.1k 1.5× 1.7k 1.8× 926 1.0× 58 7.1k
Laura S. Wood United States 29 2.3k 0.7× 3.1k 1.1× 2.2k 1.6× 1.4k 1.5× 525 0.6× 99 4.9k
Ihor Vynnychenko Ukraine 21 4.6k 1.4× 4.3k 1.5× 1.4k 1.1× 901 0.9× 1.4k 1.5× 57 7.0k
Neeraj Agarwal United States 34 1.6k 0.5× 3.4k 1.2× 1.9k 1.4× 1.4k 1.4× 1.1k 1.2× 207 4.8k
Nobuaki Matsubara Japan 28 2.3k 0.7× 3.5k 1.2× 878 0.6× 1.1k 1.2× 1.1k 1.2× 233 5.6k
Jonathan Polikoff United States 25 2.5k 0.8× 2.0k 0.7× 694 0.5× 909 0.9× 781 0.8× 70 4.7k
Mark Kozloff United States 36 3.2k 1.0× 1.7k 0.6× 1.3k 1.0× 702 0.7× 612 0.7× 125 4.7k
Jean-Pascal Machiels Belgium 18 2.0k 0.6× 2.4k 0.9× 960 0.7× 848 0.9× 457 0.5× 36 4.5k
Martin H. Voss United States 40 2.6k 0.8× 4.0k 1.4× 3.1k 2.3× 2.0k 2.1× 906 1.0× 219 6.1k

Countries citing papers authored by Saby George

Since Specialization
Citations

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

Fields of papers citing papers by Saby George

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saby George

This figure shows the co-authorship network connecting the top 25 collaborators of Saby George. A scholar is included among the top collaborators of Saby George 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 Saby George. Saby George 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
2.
4.
Motzer, Robert J., Camillo Porta, Masatoshi Eto, et al.. (2024). Biomarker analyses in patients with advanced renal cell carcinoma (aRCC) from the phase 3 CLEAR trial.. Journal of Clinical Oncology. 42(16_suppl). 4504–4504. 7 indexed citations
5.
Powles, Thomas, Mauricio Burotto, Bernard Escudier, et al.. (2024). Nivolumab plus cabozantinib versus sunitinib for first-line treatment of advanced renal cell carcinoma: extended follow-up from the phase III randomised CheckMate 9ER trial. ESMO Open. 9(5). 102994–102994. 31 indexed citations
6.
Atkins, Michael B., Pooja Ghatalia, Jaime R. Merchan, et al.. (2024). Belzutifan in patients with advanced clear cell renal cellcarcinoma (ccRCC): Subgroup analysis of the phase 2 LITESPARK-013 study.. Journal of Clinical Oncology. 42(16_suppl). 4534–4534. 1 indexed citations
7.
Shariftabrizi, Ahmad, Shalin Kothari, Saby George, et al.. (2023). Optimization of Radium-223 Treatment of Castration-resistant Prostate Cancer Based on the Burden of Skeletal Metastasis and Clinical Parameters. The Oncologist. 28(3). 246–251. 2 indexed citations
8.
Roy, Arya Mariam & Saby George. (2023). Emerging resistance vs. losing response to immune check point inhibitors in renal cell carcinoma: two differing phenomena. Cancer Drug Resistance. 6(3). 642–55. 7 indexed citations
9.
Petrylak, Daniel P., Bernhard J. Eigl, Saby George, et al.. (2023). Phase I Dose-Escalation Study of the Safety and Pharmacokinetics of AGS15E Monotherapy in Patients with Metastatic Urothelial Carcinoma. Clinical Cancer Research. 30(1). 63–73. 2 indexed citations
11.
Rini, Brian I., Sabina Signoretti, Toni K. Choueiri, et al.. (2022). Long-term outcomes with nivolumab plus ipilimumab versus sunitinib in first-line treatment of patients with advanced sarcomatoid renal cell carcinoma. Journal for ImmunoTherapy of Cancer. 10(12). e005445–e005445. 42 indexed citations
12.
Yamauchi, Takayoshi, Toshifumi Hoki, Takaaki Oba, et al.. (2021). T-cell CX3CR1 expression as a dynamic blood-based biomarker of response to immune checkpoint inhibitors. Nature Communications. 12(1). 1402–1402. 102 indexed citations
13.
Higano, Celestia S., Sabina Dizdarevic, Santhanam Sundar, et al.. (2021). 593P Pain efficacy with radium-223 (Ra-223) in the REASSURE global, prospective, observational study of men with metastatic castration-resistant prostate cancer (mCRPC). Annals of Oncology. 32. S640–S641. 2 indexed citations
14.
Martini, Jean-François, Elizabeth R. Plimack, Toni K. Choueiri, et al.. (2020). Angiogenic and Immune-Related Biomarkers and Outcomes Following Axitinib/Pembrolizumab Treatment in Patients with Advanced Renal Cell Carcinoma. Clinical Cancer Research. 26(21). 5598–5608. 16 indexed citations
15.
McGregor, Bradley A., Michael S. Gordon, Ronan Flippot, et al.. (2020). Safety and efficacy of CDX-014, an antibody-drug conjugate directed against T cell immunoglobulin mucin-1 in advanced renal cell carcinoma. Investigational New Drugs. 38(6). 1807–1814. 24 indexed citations
17.
Пили, Роберто, David I. Quinn, Hans J. Hammers, et al.. (2017). Immunomodulation by Entinostat in Renal Cell Carcinoma Patients Receiving High-Dose Interleukin 2: A Multicenter, Single-Arm, Phase I/II Trial (NCI-CTEP#7870). Clinical Cancer Research. 23(23). 7199–7208. 76 indexed citations
18.
George, Saby, et al.. (2015). Anti-Androgen Therapies for Prostate Cancer: A Focused Review. 11(2). 9 indexed citations
19.
Motzer, Robert J., Brian I. Rini, David F. McDermott, et al.. (2014). Nivolumab for Metastatic Renal Cell Carcinoma: Results of a Randomized Phase II Trial. Journal of Clinical Oncology. 33(13). 1430–1437. 865 indexed citations breakdown →
20.
George, Saby, Shetal N. Shah, & Ronald M. Bukowski. (2010). Stable Disease in Renal Cell Carcinoma After Using Signal Transduction Inhibitors. Reviews on Recent Clinical Trials. 5(2). 117–122. 2 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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