Alexander Savchenko

414 total citations
17 papers, 146 citations indexed

About

Alexander Savchenko is a scholar working on Oncology, Immunology and Surgery. According to data from OpenAlex, Alexander Savchenko has authored 17 papers receiving a total of 146 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 6 papers in Immunology and 4 papers in Surgery. Recurrent topics in Alexander Savchenko's work include Cancer Immunotherapy and Biomarkers (7 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and CAR-T cell therapy research (2 papers). Alexander Savchenko is often cited by papers focused on Cancer Immunotherapy and Biomarkers (7 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and CAR-T cell therapy research (2 papers). Alexander Savchenko collaborates with scholars based in United States, Italy and Austria. Alexander Savchenko's co-authors include S. Yu. Zavalishina, Norbert Kraut, Michael P. Sanderson, Hans Clevers, Markus Moehler, Barbara Drobits, Dirk Kessler, Hussein A. Tawbi, Marco H. Hofmann and Jens Quant and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Alexander Savchenko

14 papers receiving 139 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexander Savchenko United States 6 60 54 42 39 36 17 146
Tarek Abdel‐Aziz United Kingdom 9 133 2.2× 45 0.8× 33 0.8× 26 0.7× 104 2.9× 27 226
Archana Balan United States 6 25 0.4× 53 1.0× 54 1.3× 24 0.6× 26 0.7× 12 139
Shiva Balachander Australia 5 59 1.0× 48 0.9× 81 1.9× 26 0.7× 37 1.0× 7 155
Jan‐Willem B. de Groot Netherlands 8 35 0.6× 111 2.1× 19 0.5× 45 1.2× 68 1.9× 12 183
Samuel Backman Sweden 9 74 1.2× 36 0.7× 70 1.7× 43 1.1× 95 2.6× 11 177
Carla Vaz Ferreira Brazil 8 60 1.0× 65 1.2× 46 1.1× 77 2.0× 215 6.0× 11 280
Zhihui Li China 10 90 1.5× 32 0.6× 21 0.5× 41 1.1× 144 4.0× 33 230
Jörn Meinel Germany 6 54 0.9× 71 1.3× 23 0.5× 15 0.4× 16 0.4× 11 148
Mathieu Larivière Canada 7 45 0.8× 30 0.6× 41 1.0× 87 2.2× 33 0.9× 9 160
Eduard-Alexandru Bonci Romania 8 42 0.7× 47 0.9× 63 1.5× 36 0.9× 30 0.8× 28 172

Countries citing papers authored by Alexander Savchenko

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Savchenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexander Savchenko

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

All Works

17 of 17 papers shown
1.
Solomon, Benjamin, Daniel S.W. Tan, Gilberto de Castro, et al.. (2025). The Impact of the Tumor Microenvironment on the Effect of IL-1β Blockade in NSCLC: Biomarker Analyses from CANOPY-1 and CANOPY-N Trials. Cancer Research Communications. 5(4). 632–646. 1 indexed citations
2.
Lee, Jay M., Jean-Louis Pujol, Jun Zhang, et al.. (2025). CANOPY-N: A Phase 2 Study of Canakinumab or Pembrolizumab, Alone or in Combination, as Neoadjuvant Therapy in Patients With Resectable, Stage IB–IIIA NSCLC. JTO Clinical and Research Reports. 6(8). 100859–100859.
3.
Klempner, Samuel J., Matteo Fassan, Hisato Kawakami, et al.. (2024). PD-L1 immunohistochemistry in gastric cancer: Comparison of combined positive score and tumor area positivity across 28-8, 22C3, and SP263 assays.. Journal of Clinical Oncology. 42(16_suppl). 2625–2625. 1 indexed citations
4.
Klempner, Samuel J., Matteo Fassan, Hisato Kawakami, et al.. (2024). PD-L1 Immunohistochemistry in Gastric Cancer: Comparison of Combined Positive Score and Tumor Area Positivity Across 28-8, 22C3, and SP263 Assays. JCO Precision Oncology. 8(8). e2400230–e2400230. 12 indexed citations
5.
Tawbi, Hussein A., Caroline Robert, Jan C. Brase, et al.. (2022). Spartalizumab or placebo in combination with dabrafenib and trametinib in patients with BRAF V600-mutant melanoma: exploratory biomarker analyses from a randomized phase 3 trial (COMBI-i). Journal for ImmunoTherapy of Cancer. 10(6). e004226–e004226. 19 indexed citations
6.
Бузмаков, А. В., Dmitry I. Ignatov, Anna Kalenkova, et al.. (2021). Automatic Grading of Knee Osteoarthritis from Plain Radiographs Using Densely Connected Convolutional Networks. Europe PMC (PubMed Central). 1357. 149–161. 2 indexed citations
7.
8.
Jayaraman, Pushpa, Vanessa Rodrik-Outmezguine, John M. Millholland, et al.. (2020). Abstract 5640: Targeting tumor-promoting inflammation (TPI) via the IL-1βpathway for cancer immunotherapy. Cancer Research. 80(16_Supplement). 5640–5640. 3 indexed citations
9.
Jayaraman, Pushpa, John M. Millholland, Neil A. O’Brien, et al.. (2019). Abstract C103: Targeting IL-1β pathway for cancer immunotherapy. Molecular Cancer Therapeutics. 18(12_Supplement). C103–C103. 3 indexed citations
10.
Zinzalla, Vittoria, Barbara Drobits, Alexander Savchenko, et al.. (2019). Abstract DDT01-01: BI 905677: A first-in-class LRP5/6 antagonist targeting Wnt-driven proliferation and immune escape. DDT01–1. 2 indexed citations
11.
Zinzalla, Vittoria, Barbara Drobits, Alexander Savchenko, et al.. (2019). Abstract DDT01-01: BI 905677: A first-in-class LRP5/6 antagonist targeting Wnt-driven proliferation and immune escape. Cancer Research. 79(13_Supplement). DDT01–1. 5 indexed citations
12.
Reschke, Markus, Ulrich Reiser, Dirk Scharn, et al.. (2017). Abstract 2330: BI5: a novel SMAC mimetic that triggers tumor cell death and potentiates PD-1 mediated cancer therapy. Cancer Research. 77(13_Supplement). 2330–2330.
13.
Savchenko, Alexander, et al.. (2016). Breast cancer and Epstein–Barr virus infection. European Journal of Cancer. 61. S38–S38.
14.
Sanderson, Michael P., Joshua F. Apgar, Pilar Garin‐Chesa, et al.. (2015). BI 885578, a Novel IGF1R/INSR Tyrosine Kinase Inhibitor with Pharmacokinetic Properties That Dissociate Antitumor Efficacy and Perturbation of Glucose Homeostasis. Molecular Cancer Therapeutics. 14(12). 2762–2772. 16 indexed citations
15.
Savchenko, Alexander, et al.. (2009). METHODOLOGY OF BLOOD RHEOLOGY ASSESSMENT IN VARIOUS CLINICAL SITUATIONS. SHILAP Revista de lepidopterología. 13 indexed citations
16.
Ежов, М. В., et al.. (1997). 2.P.115 Apolipoprotein(a) phenotypes as a predictor of occlusions in coronary arteries. Atherosclerosis. 134(1-2). 140–140. 1 indexed citations
17.
Savchenko, Alexander, et al.. (1980). [Cancer of the adrenal cortex].. PubMed. 108–9. 52 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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