Michael DeRosa

1.5k total citations
29 papers, 559 citations indexed

About

Michael DeRosa is a scholar working on Economics and Econometrics, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Michael DeRosa has authored 29 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Economics and Econometrics, 10 papers in Pulmonary and Respiratory Medicine and 9 papers in Oncology. Recurrent topics in Michael DeRosa's work include Cancer Immunotherapy and Biomarkers (9 papers), Health Systems, Economic Evaluations, Quality of Life (9 papers) and Economic and Financial Impacts of Cancer (7 papers). Michael DeRosa is often cited by papers focused on Cancer Immunotherapy and Biomarkers (9 papers), Health Systems, Economic Evaluations, Quality of Life (9 papers) and Economic and Financial Impacts of Cancer (7 papers). Michael DeRosa collaborates with scholars based in United States, United Kingdom and Germany. Michael DeRosa's co-authors include Fiona Taylor, Homa Dastani, Bryan Bennett, Richard J. Gralla, Martin Reck, Marcia E. Cornford, Michael A. Farrell, John Curran, Diana Lenard Secor and John R. Penrod and has published in prestigious journals such as Journal of Personality and Social Psychology, Journal of Clinical Oncology and The Lancet Oncology.

In The Last Decade

Michael DeRosa

24 papers receiving 551 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael DeRosa United States	9	270	209	100	87	84	29	559
Candace L. Haddox United States	12	286 1.1×	178 0.9×	42 0.4×	212 2.4×	105 1.3×	32	931
Ronald L. Davis United States	15	201 0.7×	79 0.4×	151 1.5×	130 1.5×	17 0.2×	45	737
Michael Eleff United States	9	73 0.3×	56 0.3×	74 0.7×	87 1.0×	28 0.3×	14	474
Shantanu N. Razdan United States	15	249 0.9×	49 0.2×	96 1.0×	86 1.0×	29 0.3×	25	945
Catherine Loustalot France	17	306 1.1×	79 0.4×	23 0.2×	103 1.2×	15 0.2×	30	728
Justin J. Buthorn United States	10	104 0.4×	50 0.2×	33 0.3×	75 0.9×	10 0.1×	18	530
Jacob A. Reiss United States	19	87 0.3×	115 0.6×	11 0.1×	273 3.1×	21 0.3×	43	1.0k
Kohei Hashimoto Japan	15	164 0.6×	208 1.0×	203 2.0×	249 2.9×	5 0.1×	90	991
Tracy Dudding Australia	16	98 0.4×	55 0.3×	10 0.1×	239 2.7×	28 0.3×	24	752
Sonalee Agarwal United States	13	150 0.6×	47 0.2×	36 0.4×	113 1.3×	53 0.6×	23	599

Countries citing papers authored by Michael DeRosa

Since Specialization

Citations

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

Fields of papers citing papers by Michael DeRosa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael DeRosa

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

All Works

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20 of 20 papers shown

Gold, Linda Stein, Michael Sebastian, Brandon Becker, et al.. (2025). Deucravacitinib, an Oral, Selective, Allosteric Tyrosine Kinase 2 (TYK2) Inhibitor, in Patients with Moderate to Severe Scalp Psoriasis: Time to Meaningful Improvement in Patient-Reported Outcomes in a Phase 3b/4, Multicenter, Randomized, Double-blinded, Placebo-Controlled Study (PSORIATYK SCALP). SKIN The Journal of Cutaneous Medicine. 9(2). s533–s533.

Bedke, Jens, Rachel H. Giles, Thomas Powles, et al.. (2024). Health-related quality of life (HRQoL) profile and clinical outcomes in first-line (1L) advanced renal cell carcinoma (aRCC): A modelling analysis based on CheckMate 9ER (CM9ER) trial.. Journal of Clinical Oncology. 42(4_suppl). 384–384.

Shaw, James W., Bryan Bennett, Andrew Trigg, et al.. (2021). A Comparison of Generic and Condition-Specific Preference-Based Measures Using Data From Nivolumab Trials: EQ-5D-3L, Mapping to the EQ-5D-5L, and European Organisation for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions. Value in Health. 24(11). 1651–1659. 12 indexed citations

Trigg, Andrew, Michael DeRosa, Prianka Singh, et al.. (2020). PCN295 Health State Utility Values By Time to Death in Recurrent or Metastatic Squamous-Cell Carcinoma of the Head and Neck. Value in Health. 23. S474–S474.

Sun, Xiaowu, et al.. (2020). PNS213 Dimensional Structure of Dermatology Life Quality Index in Patients with Atopic Dermatitis: Bifactor Model Approach. Value in Health. 23. S676–S677. 1 indexed citations

Shaw, James W., et al.. (2020). PCN317 ASSOCIATIONS BETWEEN THE EQ-5D-3L AND QLU-C10D DESCRIPTIVE SYSTEMS: USE OF CORRELATION NETWORKS TO EXPLORE PREFERENCE DIFFERENCES IN SOLID TUMOR TRIALS. Value in Health. 23. S80–S80. 1 indexed citations

Bennett, Bryan, et al.. (2019). SP1 COMPARISON OF GENERIC AND CONDITION-SPECIFIC PREFERENCE MEASURES TO DERIVE HEALTH UTILITIES: A RETROSPECTIVE ANALYSIS OF NIVOLUMAB TRIALS IN SOLID TUMOURS. Value in Health. 22. S922–S922. 1 indexed citations

Reck, Martin, Julie R. Brahmer, Bryan Bennett, et al.. (2018). Evaluation of health-related quality of life and symptoms in patients with advanced non-squamous non-small cell lung cancer treated with nivolumab or docetaxel in CheckMate 057. European Journal of Cancer. 102. 23–30. 53 indexed citations

Reck, Martin, Fiona Taylor, John R. Penrod, et al.. (2017). Impact of Nivolumab versus Docetaxel on Health-Related Quality of Life and Symptoms in Patients with Advanced Squamous Non–Small Cell Lung Cancer: Results from the CheckMate 017 Study. Journal of Thoracic Oncology. 13(2). 194–204. 79 indexed citations

10.

DeRosa, Michael, et al.. (2017). Association of Health-Related Quality of Life (HRQOL) and Healthcare Resource Utilization (HCRU) in Checkmate 141, A Phase 3 Study of Nivolumab Versus Investigator’s Choice (IC) in Patients with Recurrent or Metastatic (R/M) Platinum-Refractory Squamous Cell Carcinoma of The Head and Neck (SCCHN). Value in Health. 20(9). A447–A447. 2 indexed citations

11.

Cocks, Kim, et al.. (2017). A Quality-Adjusted Time without Symptoms of Disease And Toxicity (Q-TWIST) Analysis Comparing Nivolumab and Therapy Of Investigator’s Choice (IC) in Patients with Recurrent or Metastatic (R/M) Platinum-Refractory Squamous Cell Carcinoma of the Head and Neck (SCCHN) (Checkmate 141). Value in Health. 20(9). A450–A450. 1 indexed citations

12.

Crawford, Bruce, Narayanan Prepageran, Bee See Goh, et al.. (2016). Impact of Pediatric Acute Otitis Media on Child and Parental Quality of Life and Associated Productivity Loss in Malaysia: A Prospective Observational Study. Drugs - Real World Outcomes. 4(1). 21–31. 16 indexed citations

13.

Gralla, Richard J., David R. Spigel, Bryan Bennett, et al.. (2016). PD1.01 (also presented as P2.46): LCSS as a Marker of Treatment Benefit With Nivolumab vs Docetaxel in Pts With Advanced Non-Squamous NSCLC From Checkmate 057. Journal of Thoracic Oncology. 11(10). S171–S171. 1 indexed citations

14.

Reck, Martin, Julie R. Brahmer, Bryan Bennett, et al.. (2016). Overall health status (HS) in patients (pts) with advanced (adv) non-squamous (NSQ) NSCLC treated with nivolumab (nivo) or docetaxel (doc) in CheckMate 057. Annals of Oncology. 27. vi421–vi421. 6 indexed citations

15.

Taylor, Fiona, et al.. (2016). Overall Survival, Health-Related Quality of Life, and Healthcare Resource Use: Independent Analyses from Checkmate 025, A Phase Iii Study of Nivolumab Versus Everolimus in Patients with Advanced or Metastatic Clear-Cell Renal Cell Carcinoma. Value in Health. 19(3). A167–A167. 2 indexed citations

16.

Reck, Martin, Cheryl D. Coon, Fiona Taylor, et al.. (2015). 460P Evaluation of overall health status in patients with advanced squamous non-small cell lung cancer treated with nivolumab or docetaxel in CheckMate 017. Annals of Oncology. 26. ix125–ix125. 5 indexed citations

17.

Tiplady, B., et al.. (2015). Equivalence of Paper and Electronic Administration of Patient Reported Outcomes: a Comparison in Psoriatic Arthritis. Value in Health. 18(7). A342–A342. 3 indexed citations

18.

Rendas‐Baum, Regina, et al.. (2010). PND26 VALIDATING USE OF THE MIGRAINE-SPECIFIC QUALITY OF LIFE QUESTIONNAIRE VERSION 2.1 (MSQ) ACROSS MIGRAINE DISORDERS. Value in Health. 13(3). A142–A142. 2 indexed citations

19.

Malloy, Thomas E., et al.. (2005). Individual Differences and Cross-Situational Consistency of Dyadic Social Behavior.. Journal of Personality and Social Psychology. 89(4). 643–654. 29 indexed citations

20.

Farrell, Michael A., Michael DeRosa, John Curran, et al.. (1992). Neuropathologic findings in cortical resections (including hemispherectomies) performed for the treatment of intractable childhood epilepsy. Acta Neuropathologica. 83(3). 246–259. 152 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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