Toshimi Takano

8.0k total citations · 1 hit paper
172 papers, 3.0k citations indexed

About

Toshimi Takano is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Toshimi Takano has authored 172 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 139 papers in Oncology, 86 papers in Pulmonary and Respiratory Medicine and 49 papers in Cancer Research. Recurrent topics in Toshimi Takano's work include HER2/EGFR in Cancer Research (56 papers), Cancer Treatment and Pharmacology (45 papers) and Advanced Breast Cancer Therapies (33 papers). Toshimi Takano is often cited by papers focused on HER2/EGFR in Cancer Research (56 papers), Cancer Treatment and Pharmacology (45 papers) and Advanced Breast Cancer Therapies (33 papers). Toshimi Takano collaborates with scholars based in Japan, United States and Spain. Toshimi Takano's co-authors include Yuichiro Ohe, Koji Tsuta, Ikuo Sekine, Hideo Kunitoh, Tomohide Tamura, Noboru Yamamoto, Hiroshi Nokihara, Seiichiro Yamamoto, Yoshihiro Matsuno and Hiromi Sakamoto and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and Cancer Cell.

In The Last Decade

Toshimi Takano

163 papers receiving 2.9k citations

Hit Papers

Epidermal Growth Factor R... 2005 2026 2012 2019 2005 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Toshimi Takano Japan 25 2.1k 1.7k 628 616 256 172 3.0k
Koichi Minato Japan 29 2.1k 1.0× 1.6k 0.9× 781 1.2× 364 0.6× 140 0.5× 171 3.1k
Conor Steuer United States 27 1.4k 0.7× 1.4k 0.8× 797 1.3× 512 0.8× 234 0.9× 121 2.8k
Thomas Brodowicz Austria 28 2.4k 1.1× 2.0k 1.2× 585 0.9× 468 0.8× 350 1.4× 126 3.4k
R. Delva France 21 1.3k 0.6× 1.3k 0.8× 657 1.0× 538 0.9× 218 0.9× 99 2.5k
G. Deplanque France 23 1.3k 0.6× 812 0.5× 633 1.0× 542 0.9× 221 0.9× 77 2.3k
Motoki Yano Japan 34 1.2k 0.6× 2.0k 1.2× 1.1k 1.8× 538 0.9× 209 0.8× 170 3.7k
Hervé Curé France 20 1.3k 0.6× 827 0.5× 279 0.4× 510 0.8× 297 1.2× 52 2.3k
Michele Aieta Italy 24 1.2k 0.6× 997 0.6× 638 1.0× 600 1.0× 166 0.6× 116 2.3k
Simon Thézenas France 29 1.7k 0.8× 786 0.5× 830 1.3× 723 1.2× 363 1.4× 117 3.0k
Young Hak Kim Japan 30 1.9k 0.9× 1.7k 1.0× 644 1.0× 279 0.5× 109 0.4× 127 2.8k

Countries citing papers authored by Toshimi Takano

Since Specialization
Citations

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

Fields of papers citing papers by Toshimi Takano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Toshimi Takano

This figure shows the co-authorship network connecting the top 25 collaborators of Toshimi Takano. A scholar is included among the top collaborators of Toshimi Takano 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 Toshimi Takano. Toshimi Takano 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
3.
Nakayama, Izuma, Kazuo Kobayashi, Naoki Shibata, et al.. (2024). Analysis of Adverse Events Associated with Trastuzumab Deruxtecan in Patients with Gastric and Breast Cancer: A Retrospective Study. Biological and Pharmaceutical Bulletin. 47(2). 411–416. 1 indexed citations
5.
Shimomura, Akihiko, Toshimi Takano, Shunji Takahashi, et al.. (2022). Effect of Trastuzumab Deruxtecan on QT/QTc Interval and Pharmacokinetics in HER2‐Positive or HER2‐Low Metastatic/Unresectable Breast Cancer. Clinical Pharmacology & Therapeutics. 113(1). 160–169. 11 indexed citations
6.
Jérusalem, Guy, Yeon Hee Park, Sara A. Hurvitz, et al.. (2022). Trastuzumab Deruxtecan in HER2-Positive Metastatic Breast Cancer Patients with Brain Metastases: A DESTINY-Breast01 Subgroup Analysis. Cancer Discovery. 12(12). 2754–2762. 60 indexed citations
7.
Yamashiro, Hiroyasu, Hiroji Iwata, Norikazu Masuda, et al.. (2020). Outcomes of trastuzumab therapy in HER2-positive early breast cancer patients: extended follow-up of JBCRG-cohort study 01. Breast Cancer. 27(4). 631–641. 5 indexed citations
9.
Saitoh, Satoshi, Fumitaka Suzuki, Keiichi Kinowaki, et al.. (2020). Undifferentiated carcinoma of the liver demonstrated by contrast-enhanced ultrasonography. Clinical Journal of Gastroenterology. 13(6). 1225–1232. 3 indexed citations
10.
Iwasa, Tsutomu, Junji Tsurutani, Satomi Watanabe, et al.. (2019). Multicentre, phase II study of eribulin in combination with S-1 in patients with advanced breast cancer. BMC Cancer. 19(1). 962–962. 2 indexed citations
11.
Takahashi, Momoko, Yukinori Ozaki, Jun Masuda, et al.. (2019). Atypical femoral fracture in patients with bone metastasis receiving denosumab therapy: a retrospective study and systematic review. BMC Cancer. 19(1). 980–980. 45 indexed citations
12.
Kuwayama, Takashi, Seigo Nakamura, Naoki Hayashi, et al.. (2018). Randomized Multicenter Phase II Trial of Neoadjuvant Therapy Comparing Weekly Nab-paclitaxel Followed by FEC With Docetaxel Followed by FEC in HER2− Early-stage Breast Cancer. Clinical Breast Cancer. 18(6). 474–480. 22 indexed citations
13.
Hayashida, Tetsu, Aiko Nagayama, Tomoko Seki, et al.. (2018). Effectiveness of Antiemetic Regimens for Highly Emetogenic Chemotherapy-Induced Nausea and Vomiting: A Systematic Review and Network Meta-Analysis. The Oncologist. 24(6). e347–e357. 31 indexed citations
15.
Akamatsu, Hiroaki, Hideyuki Harada, Shoji Tokunaga, et al.. (2018). A Phase II Study of Gefitinib With Concurrent Thoracic Radiotherapy in Patients With Unresectable, Stage III Non–small-cell Lung Cancer Harboring EGFR Mutations (WJOG6911L). Clinical Lung Cancer. 20(1). e25–e27. 18 indexed citations
16.
Inoshita, Naoko, Yuji Miura, Ryosuke Oki, et al.. (2018). The loss of BAP1 protein expression predicts poor prognosis in patients with nonmetastatic clear cell renal cell carcinoma with inferior vena cava tumor thrombosis. Urologic Oncology Seminars and Original Investigations. 36(8). 365.e9–365.e14. 7 indexed citations
17.
Watanabe, Junichiro, Yoshinori Ito, Toshiaki Saeki, et al.. (2017). Safety Evaluation of Trastuzumab Emtansine in Japanese Patients with HER2-Positive Advanced Breast Cancer. In Vivo. 31(3). 493–500. 18 indexed citations
18.
Takashima, Tsutomu, Hirofumi Mukai, Fumikata Hara, et al.. (2015). Taxanes versus S-1 as the first-line chemotherapy for metastatic breast cancer (SELECT BC): an open-label, non-inferiority, randomised phase 3 trial. The Lancet Oncology. 17(1). 90–98. 66 indexed citations
20.
Okano, Tetsuya, Tadashi Kondo, Kiyonaga Fujii, et al.. (2007). Proteomic Signature Corresponding to the Response to Gefitinib (Iressa, ZD1839), an Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor in Lung Adenocarcinoma. Clinical Cancer Research. 13(3). 799–805. 49 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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