M. Treur

412 total citations
32 papers, 318 citations indexed

About

M. Treur is a scholar working on Hematology, Economics and Econometrics and Oncology. According to data from OpenAlex, M. Treur has authored 32 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Hematology, 8 papers in Economics and Econometrics and 7 papers in Oncology. Recurrent topics in M. Treur's work include Multiple Myeloma Research and Treatments (7 papers), Cancer Treatment and Pharmacology (6 papers) and Health Systems, Economic Evaluations, Quality of Life (6 papers). M. Treur is often cited by papers focused on Multiple Myeloma Research and Treatments (7 papers), Cancer Treatment and Pharmacology (6 papers) and Health Systems, Economic Evaluations, Quality of Life (6 papers). M. Treur collaborates with scholars based in United Kingdom, Germany and Belgium. M. Treur's co-authors include M. Charokopou, Krystallia Pantiri, Floortje van Nooten, Malcolm Stoker, Bart Heeg, Marc Botteman, Ben van Hout, Ashish V. Joshi, Frank de Charro and Hans‐Jürgen Möller and has published in prestigious journals such as Blood, Gastroenterology and PLoS ONE.

In The Last Decade

M. Treur

29 papers receiving 307 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Treur United Kingdom 11 71 64 64 49 39 32 318
Klaus Krueger Germany 9 64 0.9× 112 1.8× 12 0.2× 28 0.6× 14 0.4× 21 565
Kelly McQuarrie United States 13 34 0.5× 43 0.7× 46 0.7× 9 0.2× 65 1.7× 33 634
Adeel Nasir United States 4 35 0.5× 46 0.7× 9 0.1× 11 0.2× 40 1.0× 6 428
Jesse Fishman United States 10 23 0.3× 39 0.6× 14 0.2× 43 0.9× 119 3.1× 50 405
Roni Sharon Israel 12 70 1.0× 75 1.2× 15 0.2× 18 0.4× 81 2.1× 49 335
Valeria Fadda Italy 9 8 0.1× 23 0.4× 35 0.5× 14 0.3× 60 1.5× 44 264
Shilpa Jain India 8 18 0.3× 32 0.5× 7 0.1× 27 0.6× 13 0.3× 28 262
Miranda Pans Belgium 10 43 0.6× 24 0.4× 47 0.7× 30 0.6× 244 6.3× 10 493
Ann Brownfield United Kingdom 10 15 0.2× 100 1.6× 9 0.1× 6 0.1× 47 1.2× 12 460
Rosemarie Neuner United States 10 47 0.7× 41 0.6× 13 0.2× 6 0.1× 26 0.7× 13 412

Countries citing papers authored by M. Treur

Since Specialization
Citations

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

Fields of papers citing papers by M. Treur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Treur

This figure shows the co-authorship network connecting the top 25 collaborators of M. Treur. A scholar is included among the top collaborators of M. Treur 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 M. Treur. M. Treur 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.
Hájek, Roman, Jiří Jarkovský, Vladimír Maisnar, et al.. (2018). Real-world Outcomes of Multiple Myeloma: Retrospective Analysis of the Czech Registry of Monoclonal Gammopathies. Clinical Lymphoma Myeloma & Leukemia. 18(6). e219–e240. 18 indexed citations
5.
Hájek, Roman, Jiří Jarkovský, Walter Bouwmeester, et al.. (2016). Exploration of Survival Stratification of Patients with Multiple Myeloma after First Relapse Using Real World Data. Blood. 128(22). 2417–2417. 1 indexed citations
8.
Sapin, Christophe, et al.. (2015). Pharmacoeconomic Evaluation of Aripiprazole Once-Monthly Versus Paliperidone Palmitate in the UK: Findings From Qualify. Value in Health. 18(7). A410–A411. 2 indexed citations
11.
Heeg, Bart, Michel van Agthoven, Johan Liwing, et al.. (2014). Treatment Sequencing Survival Model for Patients with Multiple Myeloma Ineligible for Stem Cell Transplantation (SCT). Value in Health. 17(7). A617–A618. 2 indexed citations
12.
Chuang, Ling‐Hsiang, M. Treur, Bart Heeg, Ben van Hout, & Anna Filonenko. (2013). The use and impact of value of information analysis in decision-making. Value in Health. 16(3). A30–A30. 1 indexed citations
17.
Treur, M., Enrique Baca, Julio Bobes, et al.. (2012). The cost-effectiveness of paliperidone extended release in Spain. Journal of Medical Economics. 15(sup1). 26–34. 16 indexed citations
18.
Heisen, Marieke, et al.. (2012). Fingolimod reduces direct medical costs compared to natalizumab in patients with relapsing–remitting multiple sclerosis in The Netherlands. Journal of Medical Economics. 15(6). 1149–1158. 8 indexed citations
19.
Heeg, Bart, Michel van Agthoven, Johan Liwing, et al.. (2010). Optimal Treatment Sequencing In Multiple Myeloma: An Exploratory Modeling Approach. Blood. 116(21). 3046–3046. 4 indexed citations
20.
Treur, M., Bart Heeg, Hans‐Jürgen Möller, A Schmeding, & Ben van Hout. (2009). A pharmaco-economic analysis of patients with schizophrenia switching to generic risperidone involving a possible compliance loss. BMC Health Services Research. 9(1). 32–32. 26 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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