Donald C. McMillan

41.5k total citations · 8 hit papers
489 papers, 31.8k citations indexed

About

Donald C. McMillan is a scholar working on Oncology, Physiology and Surgery. According to data from OpenAlex, Donald C. McMillan has authored 489 papers receiving a total of 31.8k indexed citations (citations by other indexed papers that have themselves been cited), including 324 papers in Oncology, 121 papers in Physiology and 105 papers in Surgery. Recurrent topics in Donald C. McMillan's work include Inflammatory Biomarkers in Disease Prognosis (202 papers), Nutrition and Health in Aging (100 papers) and Colorectal Cancer Surgical Treatments (95 papers). Donald C. McMillan is often cited by papers focused on Inflammatory Biomarkers in Disease Prognosis (202 papers), Nutrition and Health in Aging (100 papers) and Colorectal Cancer Surgical Treatments (95 papers). Donald C. McMillan collaborates with scholars based in United Kingdom, United States and Japan. Donald C. McMillan's co-authors include Paul G. Horgan, Campbell S.D. Roxburgh, C S McArdle, Stephen Clarke, Kellie A. Charles, Colin S. McArdle, Dinesh Talwar, Wilson J. Angerson, Campbell SD Roxburgh and Connie I. Diakos and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Gastroenterology.

In The Last Decade

Donald C. McMillan

476 papers receiving 31.3k citations

Hit Papers

Cancer-related inflammation and treatment ef... 2003 2026 2010 2018 2014 2013 2012 2009 2017 500 1000 1.5k
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. Cancer-related inflammation and treatment effectiveness
    2014 1.7k citations Donald C. McMillan et al. profile →
  2. The systemic inflammation-based neutrophil–lymphocyte ratio: Experience in patients with cancer
    2013 1.2k citations Graeme J.K. Guthrie, Campbell S.D. Roxburgh et al. Critical Reviews in Oncology/Hematology profile →
  3. The systemic inflammation-based Glasgow Prognostic Score: A decade of experience in patients with cancer
    2012 1.0k citations Donald C. McMillan profile →
  4. Systemic inflammation, nutritional status and survival in patients with cancer
    2009 827 citations Donald C. McMillan profile →
  5. ESPEN expert group recommendations for action against cancer-related malnutrition
    2017 811 citations Jann Arends, Donald C. McMillan et al. Clinical Nutrition profile →
  6. Role of Systemic Inflammatory Response in Predicting Survival in Patients with Primary Operable Cancer
    2009 805 citations Donald C. McMillan et al. profile →
  7. A comparison of inflammation-based prognostic scores in patients with cancer. A Glasgow Inflammation Outcome Study
    2011 644 citations Paul G. Horgan, Donald C. McMillan et al. profile →
  8. Evaluation of cumulative prognostic scores based on the systemic inflammatory response in patients with inoperable non-small-cell lung cancer
    2003 621 citations L M Forrest, Donald C. McMillan et al. British Journal of Cancer profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Donald C. McMillan United Kingdom 90 20.3k 8.2k 6.4k 5.8k 5.4k 489 31.8k
Jeffrey A. Meyerhardt United States 85 16.3k 0.8× 3.3k 0.4× 4.3k 0.7× 5.0k 0.9× 3.9k 0.7× 431 25.8k
Matti Aapro Switzerland 80 10.6k 0.5× 6.5k 0.8× 4.0k 0.6× 3.9k 0.7× 2.1k 0.4× 492 22.4k
Stephen Clarke Australia 65 12.3k 0.6× 3.0k 0.4× 5.4k 0.8× 1.3k 0.2× 3.1k 0.6× 475 21.4k
Michael Trauner Austria 100 12.5k 0.6× 12.0k 1.5× 3.0k 0.5× 2.6k 0.5× 2.0k 0.4× 867 39.1k
Stephen J. Freedland United States 78 6.5k 0.3× 3.9k 0.5× 17.6k 2.8× 1.5k 0.3× 5.7k 1.1× 819 26.2k
Pär Stattin Sweden 74 5.0k 0.2× 2.1k 0.3× 7.0k 1.1× 1.3k 0.2× 3.6k 0.7× 419 16.8k
Piotr Rutkowski Poland 65 8.8k 0.4× 3.2k 0.4× 7.9k 1.2× 660 0.1× 1.3k 0.2× 912 20.3k
Rudolf Kaaks Germany 70 6.2k 0.3× 1.3k 0.2× 2.0k 0.3× 3.3k 0.6× 3.2k 0.6× 308 18.2k
John V. Reynolds Ireland 61 3.5k 0.2× 7.2k 0.9× 4.2k 0.7× 2.4k 0.4× 1.6k 0.3× 502 14.2k
Martin M. Oken United States 47 7.4k 0.4× 2.6k 0.3× 3.8k 0.6× 2.1k 0.4× 944 0.2× 145 18.2k

Countries citing papers authored by Donald C. McMillan

Since Specialization
Citations

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

Fields of papers citing papers by Donald C. McMillan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Donald C. McMillan. 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 Donald C. McMillan. The network helps show where Donald C. McMillan may publish in the future.

Co-authorship network of co-authors of Donald C. McMillan

This figure shows the co-authorship network connecting the top 25 collaborators of Donald C. McMillan. A scholar is included among the top collaborators of Donald C. McMillan 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 Donald C. McMillan. Donald C. McMillan 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
1.
Brown, Leo R., Rebekah Patton, I.C. Munro, et al.. (2025). Dissecting the global leadership initiative on malnutrition criteria in advanced cancer: Reduced intake vs. inflammation. Clinical Nutrition ESPEN. 67. 114–121.
2.
McGovern, Josh, Carlos Eduardo Paiva, Ross D. Dolan, et al.. (2025). Prognostic value of the Global Leadership Initiative on Malnutrition criteria including systemic inflammation in patients with advanced cancer. British Journal Of Nutrition. 133(2). 246–252.
3.
Laird, Barry, Richard J. E. Skipworth, Philip Bonomi, et al.. (2025). Anamorelin Efficacy in Non–Small‐Cell Lung Cancer Patients With Cachexia: Insights From ROMANA 1 and ROMANA 2. Journal of Cachexia Sarcopenia and Muscle. 16(1). e13732–e13732. 5 indexed citations
4.
Roxburgh, Campbell S.D., et al.. (2024). A systematic review of the role of systemic inflammation-based prognostic scores in patients with abdominal aortic aneurysm. The Surgeon. 23(1). e1–e8. 2 indexed citations
5.
Ferguson, Michael J., Paul J. McMillan, David Mansouri, et al.. (2024). CT-derived body composition and differential association with age, TNM stage and systemic inflammation in patients with colon cancer. Scientific Reports. 14(1). 15673–15673. 1 indexed citations
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Knight, Katrina, Christopher Bigley, Kathryn A.F. Pennel, et al.. (2024). The Glasgow Microenvironment Score: an exemplar of contemporary biomarker evolution in colorectal cancer. The Journal of Pathology Clinical Research. 10(4). e12385–e12385. 2 indexed citations
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Dolan, Ross D., et al.. (2023). Evaluation of the prognostic value of computed tomography‐derived body composition in patients undergoing endovascular aneurysm repair. Journal of Cachexia Sarcopenia and Muscle. 14(4). 1836–1847. 9 indexed citations
10.
McMillan, Donald C., et al.. (2022). Route to diagnosis of colorectal cancer and association with survival within the context of a bowel screening programme. Public Health. 211. 53–61. 5 indexed citations
11.
Okugawa, Yoshinaga, Yuji Toiyama, Takashi Ichikawa, et al.. (2021). Modified intramuscular adipose tissue content as a feasible surrogate marker for malnutrition in gastrointestinal cancer. Clinical Nutrition. 40(5). 2640–2653. 19 indexed citations
12.
Roseweir, Antonia K., Kathryn A.F. Pennel, Hester C. van Wyk, et al.. (2020). The Glasgow Microenvironment Score associates with prognosis and adjuvant chemotherapy response in colorectal cancer. British Journal of Cancer. 124(4). 786–796. 14 indexed citations
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14.
Wyk, Hester C. van, James J. Going, Paul G. Horgan, & Donald C. McMillan. (2017). The role of perineural invasion in predicting survival in patients with primary operable colorectal cancer: A systematic review. Critical Reviews in Oncology/Hematology. 112. 11–20. 34 indexed citations
15.
Park, James H., Donald C. McMillan, Jean A. Quinn, et al.. (2016). Signal Transduction and Activator of Transcription-3 (STAT3) in Patients with Colorectal Cancer: Associations with the Phenotypic Features of the Tumor and Host. Clinical Cancer Research. 23(7). 1698–1709. 37 indexed citations
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Barber, M D, Donald C. McMillan, Andrew Wallace, et al.. (2004). The response of leptin, interleukin-6 and fat oxidation to feeding in weight-losing patients with pancreatic cancer. British Journal of Cancer. 90(6). 1129–1132. 35 indexed citations
19.
Scott, Hazel R., Donald C. McMillan, L M Forrest, et al.. (2002). The systemic inflammatory response, weight loss, performance status and survival in patients with inoperable non-small cell lung cancer. British Journal of Cancer. 87(3). 264–267. 255 indexed citations
20.
McMillan, Donald C., Anthony F. Graham, Johanna L. Smith, et al.. (1994). Interleukin-6, neutrophilia and the acute phase protein response in colorectal cancer patients.. PubMed. 20(2). 151–4. 12 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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