Cor H. van der Leest

579 total citations
16 papers, 289 citations indexed

About

Cor H. van der Leest is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Immunology. According to data from OpenAlex, Cor H. van der Leest has authored 16 papers receiving a total of 289 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 10 papers in Pulmonary and Respiratory Medicine and 4 papers in Immunology. Recurrent topics in Cor H. van der Leest's work include Cancer Immunotherapy and Biomarkers (10 papers), Lung Cancer Treatments and Mutations (10 papers) and Pancreatic and Hepatic Oncology Research (3 papers). Cor H. van der Leest is often cited by papers focused on Cancer Immunotherapy and Biomarkers (10 papers), Lung Cancer Treatments and Mutations (10 papers) and Pancreatic and Hepatic Oncology Research (3 papers). Cor H. van der Leest collaborates with scholars based in Netherlands, Switzerland and Chile. Cor H. van der Leest's co-authors include Joachim G.J.V. Aerts, Ron H.J. Mathijssen, Stijn L.W. Koolen, Esther Oomen‐de Hoop, Edwin A. Basak, Astrid A.M. van der Veldt, Reno Debets, Sander Bins, Daan P. Hurkmans and Samira El Bouazzaoui and has published in prestigious journals such as Clinical Cancer Research, British Journal of Cancer and Annals of Oncology.

In The Last Decade

Cor H. van der Leest

13 papers receiving 288 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cor H. van der Leest Netherlands 7 206 110 93 44 26 16 289
Camille L. Gérard Switzerland 10 196 1.0× 85 0.8× 80 0.9× 97 2.2× 12 0.5× 33 300
Blessie Elizabeth Nelson United States 10 126 0.6× 47 0.4× 62 0.7× 63 1.4× 44 1.7× 33 249
Miao Huang China 9 184 0.9× 159 1.4× 50 0.5× 61 1.4× 44 1.7× 17 298
Sara Delfanti Italy 10 116 0.6× 95 0.9× 43 0.5× 58 1.3× 34 1.3× 32 254
Francesca Sparano Italy 9 219 1.1× 103 0.9× 78 0.8× 113 2.6× 65 2.5× 19 369
Shaochuan Liu China 9 237 1.2× 89 0.8× 121 1.3× 106 2.4× 54 2.1× 15 362
Huiping Qiang China 9 288 1.4× 194 1.8× 40 0.4× 61 1.4× 33 1.3× 20 362
E. Goode United Kingdom 7 177 0.9× 106 1.0× 86 0.9× 108 2.5× 34 1.3× 12 325
M. Dómine Gómez Spain 9 210 1.0× 128 1.2× 52 0.6× 73 1.7× 22 0.8× 36 277
Weiheng Hu China 8 268 1.3× 154 1.4× 52 0.6× 59 1.3× 36 1.4× 35 334

Countries citing papers authored by Cor H. van der Leest

Since Specialization
Citations

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

Fields of papers citing papers by Cor H. van der Leest

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cor H. van der Leest. 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 Cor H. van der Leest. The network helps show where Cor H. van der Leest may publish in the future.

Co-authorship network of co-authors of Cor H. van der Leest

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

All Works

16 of 16 papers shown
1.
Heine, Rob ter, Bas Peters, Nienke A. G. Lankheet, et al.. (2025). The Toxicity Profile of Pemetrexed in Non-Small Cell Lung Cancer Patients With Moderate Renal Impairment: A Retrospective Cohort Study. Clinical Lung Cancer. 26(4). 324–330.e3.
2.
3.
Hofman, Michael S., Juliette Degens, Daphne W. Dumoulin, et al.. (2024). 1335P The relationship between nivolumab pharmacokinetics and cancer cachexia biomarkers in patients with metastatic non-small cell lung cancer (NSCLC). Annals of Oncology. 35. S847–S847. 1 indexed citations
4.
Westgeest, Hans M., et al.. (2024). Bronchiolitis after Combination Immunotherapy With Ipilimumab and Nivolumab in a Melanoma Patient. Journal of Immunotherapy. 47(7). 263–265.
5.
Heine, Rob ter, Michel M. van den Heuvel, Berber Piet, et al.. (2023). A Systematic Evaluation of Cost-Saving Dosing Regimens for Therapeutic Antibodies and Antibody-Drug Conjugates for the Treatment of Lung Cancer. Targeted Oncology. 18(3). 441–450. 8 indexed citations
6.
Basak, Edwin A., Karlijn de Joode, Marco W.J. Schreurs, et al.. (2022). The course of C-peptide levels in patients developing diabetes during anti-PD-1 therapy. Biomedicine & Pharmacotherapy. 156. 113839–113839. 4 indexed citations
7.
Lievense, Lysanne A., et al.. (2022). Clinical Outcomes of Patients With Metastatic NSCLC After Discontinuation of Immunotherapy Because of Immune-Related Adverse Effects. JTO Clinical and Research Reports. 4(1). 100441–100441. 6 indexed citations
8.
Veerman, G., Daan P. Hurkmans, Marthe S. Paats, et al.. (2022). Influence of esomeprazole on the bioavailability of afatinib: A pharmacokinetic cross-over study in patients with non-small cell lung cancer. Biomedicine & Pharmacotherapy. 155. 113695–113695. 1 indexed citations
9.
Hurkmans, Daan P., Karlijn de Joode, Edwin A. Basak, et al.. (2021). Prospective real-world study on the pharmacokinetics of pembrolizumab in patients with solid tumors. Journal for ImmunoTherapy of Cancer. 9(6). e002344–e002344. 15 indexed citations
10.
Veerman, G., Koen G. A. M. Hussaarts, Esther Oomen‐de Hoop, et al.. (2020). Influence of Cow’s Milk and Esomeprazole on the Absorption of Erlotinib: A Randomized, Crossover Pharmacokinetic Study in Lung Cancer Patients. Clinical Pharmacokinetics. 60(1). 69–77. 11 indexed citations
11.
Hurkmans, Daan P., Edwin A. Basak, Esther Oomen‐de Hoop, et al.. (2020). Granzyme B is correlated with clinical outcome after PD-1 blockade in patients with stage IV non-small-cell lung cancer. Journal for ImmunoTherapy of Cancer. 8(1). e000586–e000586. 51 indexed citations
12.
Hurkmans, Daan P., Edwin A. Basak, Marco W.J. Schreurs, et al.. (2019). A prospective cohort study on the pharmacokinetics of nivolumab in metastatic non-small cell lung cancer, melanoma, and renal cell cancer patients. Journal for ImmunoTherapy of Cancer. 7(1). 192–192. 66 indexed citations
13.
Veerman, G., Koen G. A. M. Hussaarts, Esther Oomen‐de Hoop, et al.. (2019). Influence of cow’s milk on the absorption and exposure of erlotinib in NSCLC patients. Annals of Oncology. 30. v632–v632. 1 indexed citations
14.
Hurkmans, Daan P., Edwin A. Basak, Marco W.J. Schreurs, et al.. (2019). A prospective cohort study on the pharmacokinetics of nivolumab in metastatic non-small cell lung cancer, melanoma, and renal cell cancer patients. Annals of Oncology. 30. v518–v518. 2 indexed citations
15.
Bins, Sander, Edwin A. Basak, Samira El Bouazzaoui, et al.. (2018). Association between single-nucleotide polymorphisms and adverse events in nivolumab-treated non-small cell lung cancer patients. British Journal of Cancer. 118(10). 1296–1301. 52 indexed citations
16.
Aerts, Joachim G.J.V., Pauline L. de Goeje, Robin Cornelissen, et al.. (2017). Autologous Dendritic Cells Pulsed with Allogeneic Tumor Cell Lysate in Mesothelioma: From Mouse to Human. Clinical Cancer Research. 24(4). 766–776. 71 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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