Norikazu Masuda

29.7k total citations · 10 hit papers
389 papers, 14.0k citations indexed

About

Norikazu Masuda is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Norikazu Masuda has authored 389 papers receiving a total of 14.0k indexed citations (citations by other indexed papers that have themselves been cited), including 316 papers in Oncology, 162 papers in Pulmonary and Respiratory Medicine and 145 papers in Cancer Research. Recurrent topics in Norikazu Masuda's work include HER2/EGFR in Cancer Research (149 papers), Cancer Treatment and Pharmacology (138 papers) and Breast Cancer Treatment Studies (130 papers). Norikazu Masuda is often cited by papers focused on HER2/EGFR in Cancer Research (149 papers), Cancer Treatment and Pharmacology (138 papers) and Breast Cancer Treatment Studies (130 papers). Norikazu Masuda collaborates with scholars based in Japan, United States and South Korea. Norikazu Masuda's co-authors include Seock‐Ah Im, Hiroji Iwata, Pierfranco Conté, Binghe Xu, Mark E. Robson, Suzette Delaloge, Anne Armstrong, Elżbieta Senkus, Nadine Tung and Susan M. Domchek and has published in prestigious journals such as New England Journal of Medicine, Nucleic Acids Research and Journal of Clinical Oncology.

In The Last Decade

Norikazu Masuda

364 papers receiving 13.7k citations

Hit Papers

Olaparib for Metastatic B... 1999 2026 2008 2017 2017 2016 2017 2018 2015 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Norikazu Masuda Japan 45 9.9k 7.0k 4.4k 3.0k 1.7k 389 14.0k
Joohyuk Sohn South Korea 44 7.9k 0.8× 5.6k 0.8× 3.3k 0.7× 1.8k 0.6× 811 0.5× 303 10.9k
Joyce O’Shaughnessy United States 53 10.3k 1.0× 3.9k 0.6× 4.4k 1.0× 3.0k 1.0× 1.4k 0.8× 347 14.0k
Luc Dirix Belgium 65 9.4k 0.9× 3.4k 0.5× 4.6k 1.0× 4.4k 1.5× 1.2k 0.7× 311 14.6k
Sabino De Placido Italy 64 7.8k 0.8× 4.5k 0.6× 3.7k 0.8× 4.4k 1.5× 1.2k 0.7× 381 14.0k
Suzanne Kamel‐Reid Canada 55 4.3k 0.4× 3.6k 0.5× 3.0k 0.7× 4.4k 1.5× 1.2k 0.7× 285 12.1k
Emilio Bajetta Italy 55 10.4k 1.0× 5.8k 0.8× 3.7k 0.8× 3.9k 1.3× 1.6k 0.9× 325 16.6k
Antonio Llombart‐Cussac Spain 43 6.8k 0.7× 3.9k 0.6× 3.5k 0.8× 1.4k 0.5× 1.6k 0.9× 317 9.4k
Vivek Subbiah United States 54 6.0k 0.6× 4.6k 0.7× 3.1k 0.7× 3.7k 1.3× 706 0.4× 599 12.2k
Keyue Ding Canada 45 8.1k 0.8× 8.4k 1.2× 2.6k 0.6× 3.4k 1.1× 641 0.4× 218 14.5k
Neal I. Lindeman United States 49 11.6k 1.2× 13.2k 1.9× 5.8k 1.3× 8.1k 2.7× 1.1k 0.6× 172 22.4k

Countries citing papers authored by Norikazu Masuda

Since Specialization
Citations

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

Fields of papers citing papers by Norikazu Masuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Norikazu Masuda

This figure shows the co-authorship network connecting the top 25 collaborators of Norikazu Masuda. A scholar is included among the top collaborators of Norikazu Masuda 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 Norikazu Masuda. Norikazu Masuda 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
4.
Cescon, David W., Peter Schmid, Hope S. Rugo, et al.. (2023). Health-related quality of life with pembrolizumab plus chemotherapy vs placebo plus chemotherapy for advanced triple-negative breast cancer: KEYNOTE-355. JNCI Journal of the National Cancer Institute. 116(5). 717–727. 7 indexed citations
5.
Takahashi, Masato, Tomofumi Osako, Hiroyuki Yasojima, et al.. (2023). Overall survival in Japanese patients with ER+/HER2− advanced breast cancer treated with first-line palbociclib plus letrozole. Breast Cancer. 31(1). 53–62. 2 indexed citations
6.
Cortés, Javier, Hope S. Rugo, David W. Cescon, et al.. (2022). Pembrolizumab plus Chemotherapy in Advanced Triple-Negative Breast Cancer. New England Journal of Medicine. 387(3). 217–226. 594 indexed citations breakdown →
7.
Neven, Patrick, Stephen Johnston, Masakazu Toi, et al.. (2021). MONARCH 2: Subgroup Analysis of Patients Receiving Abemaciclib Plus Fulvestrant as First-Line and Second-Line Therapy for HR+, HER2−-Advanced Breast Cancer. Clinical Cancer Research. 27(21). 5801–5809. 7 indexed citations
8.
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
10.
Masuda, Norikazu, Hirofumi Mukai, Kenichi Inoue, et al.. (2019). Neutropenia management with palbociclib in Japanese patients with advanced breast cancer. Breast Cancer. 26(5). 637–650. 10 indexed citations
11.
Sugie, Tomoharu, Eiji Suzuki, Akira Yamauchi, et al.. (2018). Combined effects of neoadjuvant letrozole and zoledronic acid on γδT cells in postmenopausal women with early-stage breast cancer. The Breast. 38. 114–119. 9 indexed citations
12.
Takada, Masahiro, Masahiro Sugimoto, Norikazu Masuda, et al.. (2018). Prediction of postoperative disease-free survival and brain metastasis for HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab using a machine learning algorithm. Breast Cancer Research and Treatment. 172(3). 611–618. 18 indexed citations
13.
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
14.
Sledge, George W., Masakazu Toi, Patrick Neven, et al.. (2017). MONARCH 2: Abemaciclib in Combination With Fulvestrant in Women With HR+/HER2− Advanced Breast Cancer Who Had Progressed While Receiving Endocrine Therapy. Journal of Clinical Oncology. 35(25). 2875–2884. 1103 indexed citations breakdown →
17.
Cortés, Javier, Sandra M. Swain, Iveta Kudaba, et al.. (2013). Absence of pharmacokinetic drug–drug interaction of pertuzumab with trastuzumab and docetaxel. Anti-Cancer Drugs. 24(10). 1084–1092. 19 indexed citations
18.
Aogi, Kenjiro, Toshiaki Saeki, Seigo Nakamura, et al.. (2012). A multicenter, phase II study of epirubicin/cyclophosphamide followed by docetaxel and concurrent trastuzumab as primary systemic therapy for HER-2 positive advanced breast cancer (the HER2NAT study). International Journal of Clinical Oncology. 18(4). 598–606. 5 indexed citations
19.
Miyoshi, Yasuo, Masafumi Kurosumi, Junichi Kurebayashi, et al.. (2009). Predictive factors for anthracycline-based chemotherapy for human breast cancer. Breast Cancer. 17(2). 103–109. 13 indexed citations
20.
Miyoshi, Yasuo, Masafumi Kurosumi, Junichi Kurebayashi, et al.. (2007). Low nuclear grade but not cell proliferation predictive of pathological complete response to docetaxel in human breast cancers. Journal of Cancer Research and Clinical Oncology. 134(5). 561–567. 10 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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