Junliang Cai

901 total citations · 1 hit paper
12 papers, 534 citations indexed

About

Junliang Cai is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Surgery. According to data from OpenAlex, Junliang Cai has authored 12 papers receiving a total of 534 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Pulmonary and Respiratory Medicine, 9 papers in Oncology and 4 papers in Surgery. Recurrent topics in Junliang Cai's work include Cancer Immunotherapy and Biomarkers (9 papers), Lung Cancer Treatments and Mutations (9 papers) and Lung Cancer Diagnosis and Treatment (8 papers). Junliang Cai is often cited by papers focused on Cancer Immunotherapy and Biomarkers (9 papers), Lung Cancer Treatments and Mutations (9 papers) and Lung Cancer Diagnosis and Treatment (8 papers). Junliang Cai collaborates with scholars based in United States, China and Japan. Junliang Cai's co-authors include Shun Lü, Jifeng Feng, Yuankai Shi, Ying Cheng, Jianying Zhou, Alexander Luft, Christine Baudelet, Li Zhang, Tony Mok and Caicun Zhou and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Cancer Science.

In The Last Decade

Junliang Cai

12 papers receiving 524 citations

Hit Papers

Nivolumab Versus Docetaxel in a Predominantly Chinese Pat... 2019 2026 2021 2023 2019 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Nivolumab Versus Docetaxel in a Predominantly Chinese Patient Population With Previously Treated Advanced NSCLC: CheckMate 078 Randomized Phase III Clinical Trial
    2019 265 citations Yi‐Long Wu, Shun Lü et al. Journal of Thoracic Oncology profile →

Peers

Junliang Cai
Catherine Wadsworth United States
Gastón Lucas Martinengo Japan
Balazs Medgyasszay Spain
Sufia Safina Russia
Zhenkui Pan China
Vilma Graupner Switzerland
Shawn W. Sun United States
Yoshiro Nakahara Japan
Grant Toland United States
Craig Norton United States
Catherine Wadsworth United States
Junliang Cai
Citations per year, relative to Junliang Cai Junliang Cai (= 1×) peers Catherine Wadsworth

Countries citing papers authored by Junliang Cai

Since Specialization
Citations

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

Fields of papers citing papers by Junliang Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junliang Cai

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

All Works

12 of 12 papers shown
1.
Wang, Changli, Ke‐Neng Chen, Qixun Chen, et al.. (2023). Abstract CT081: Neoadjuvant nivolumab (NIVO) + chemotherapy (chemo) vs chemo in Chinese patients (pts) with resectable NSCLC in CheckMate 816. Cancer Research. 83(8_Supplement). CT081–CT081. 1 indexed citations
2.
Mitsudomi, Tetsuya, Hiroyuki Ito, Morihito Okada, et al.. (2023). Neoadjuvant nivolumab plus chemotherapy in resectable non‐small‐cell lung cancer in Japanese patients from CheckMate 816. Cancer Science. 115(2). 540–554. 12 indexed citations
3.
Spicer, Jonathan, Patrick M. Forde, Mariano Provencio, et al.. (2023). Clinical outcomes with neoadjuvant nivolumab (N) + chemotherapy (C) vs C by definitive surgery in patients (pts) with resectable NSCLC: 3-y results from the phase 3 CheckMate 816 trial.. Journal of Clinical Oncology. 41(16_suppl). 8521–8521. 13 indexed citations
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Spicer, Jonathan, Changli Wang, Fumihiro Tanaka, et al.. (2021). Surgical outcomes from the phase 3 CheckMate 816 trial: Nivolumab (NIVO) + platinum-doublet chemotherapy (chemo) vs chemo alone as neoadjuvant treatment for patients with resectable non-small cell lung cancer (NSCLC).. Journal of Clinical Oncology. 39(15_suppl). 8503–8503. 90 indexed citations
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Zhang, Jason, Junliang Cai, Akintunde Bello, Amit Roy, & Jennifer Sheng. (2019). Model‐Based Population Pharmacokinetic Analysis of Nivolumab in Chinese Patients With Previously Treated Advanced Solid Tumors, Including Non–Small Cell Lung Cancer. The Journal of Clinical Pharmacology. 59(10). 1415–1424. 17 indexed citations
10.
Wu, Yi‐Long, Shun Lü, Ying Cheng, et al.. (2019). Nivolumab Versus Docetaxel in a Predominantly Chinese Patient Population With Previously Treated Advanced NSCLC: CheckMate 078 Randomized Phase III Clinical Trial. Journal of Thoracic Oncology. 14(5). 867–875. 265 indexed citations breakdown →
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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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