Melissa D. Curtis

543 total citations
8 papers, 427 citations indexed

About

Melissa D. Curtis is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Melissa D. Curtis has authored 8 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Oncology, 2 papers in Pulmonary and Respiratory Medicine and 2 papers in Artificial Intelligence. Recurrent topics in Melissa D. Curtis's work include Cancer Immunotherapy and Biomarkers (3 papers), Pancreatic and Hepatic Oncology Research (2 papers) and Economic and Financial Impacts of Cancer (2 papers). Melissa D. Curtis is often cited by papers focused on Cancer Immunotherapy and Biomarkers (3 papers), Pancreatic and Hepatic Oncology Research (2 papers) and Economic and Financial Impacts of Cancer (2 papers). Melissa D. Curtis collaborates with scholars based in United States. Melissa D. Curtis's co-authors include Amy P. Abernethy, Aracelis Z. Torres, Melisa Tucker, William B. Capra, James Harnett, Marc L. Berger, Paul You, Michael D. Taylor, Gillis Carrigan and Sandra D. Griffith and has published in prestigious journals such as Journal of Clinical Oncology, Clinical Pharmacology & Therapeutics and The Oncologist.

In The Last Decade

Melissa D. Curtis

8 papers receiving 421 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Melissa D. Curtis United States	6	258	217	78	68	49	8	427
Paul You United States	6	241 0.9×	191 0.9×	94 1.2×	55 0.8×	44 0.9×	8	412
Melisa Tucker United States	9	357 1.4×	301 1.4×	123 1.6×	86 1.3×	70 1.4×	13	566
Navdeep Pal United States	11	189 0.7×	127 0.6×	90 1.2×	63 0.9×	55 1.1×	26	689
Brandon Arnieri United States	6	175 0.7×	140 0.6×	93 1.2×	112 1.6×	117 2.4×	10	498
Nathan C. Nussbaum United States	11	397 1.5×	332 1.5×	154 2.0×	73 1.1×	34 0.7×	22	635
Aracelis Z. Torres United States	14	510 2.0×	388 1.8×	162 2.1×	108 1.6×	87 1.8×	34	826
Ray Lin United States	11	280 1.1×	272 1.3×	50 0.6×	19 0.3×	73 1.5×	27	613
Abhishek Kumar United States	12	186 0.7×	202 0.9×	40 0.5×	76 1.1×	16 0.3×	37	405
Tiago M. de Carvalho Netherlands	10	301 1.2×	275 1.3×	25 0.3×	64 0.9×	25 0.5×	14	537
A.L. Vataire France	13	157 0.6×	170 0.8×	158 2.0×	114 1.7×	33 0.7×	34	478

Countries citing papers authored by Melissa D. Curtis

Since Specialization

Citations

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

Fields of papers citing papers by Melissa D. Curtis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Melissa D. Curtis. 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 Melissa D. Curtis. The network helps show where Melissa D. Curtis may publish in the future.

Co-authorship network of co-authors of Melissa D. Curtis

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

All Works

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8 of 8 papers shown

Curtis, Melissa D., Shrujal S. Baxi, William B. Capra, et al.. (2022). Augmenting control arms with real-world data for cancer trials: Hybrid control arm methods and considerations. Contemporary Clinical Trials Communications. 30. 101000–101000. 10 indexed citations

Tucker, Melisa, et al.. (2021). Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record‐Derived Real‐World Data. Clinical Pharmacology & Therapeutics. 111(1). 168–178. 19 indexed citations

Bennette, Caroline S., Nathan C. Nussbaum, Melissa D. Curtis, & Neal J. Meropol. (2019). Using real-world cohorts to assess the generalizability and relevance of randomized clinical trials (RCTs).. Journal of Clinical Oncology. 37(15_suppl). 6540–6540. 1 indexed citations

Khozin, Sean, Kenneth R. Carson, Jizu Zhi, et al.. (2018). Real-World Outcomes of Patients with Metastatic Non-Small Cell Lung Cancer Treated with Programmed Cell Death Protein 1 Inhibitors in the Year Following U.S. Regulatory Approval. The Oncologist. 24(5). 648–656. 58 indexed citations

Khozin, Sean, Amy P. Abernethy, Nathan C. Nussbaum, et al.. (2018). Characteristics of Real-World Metastatic Non-Small Cell Lung Cancer Patients Treated with Nivolumab and Pembrolizumab During the Year Following Approval. The Oncologist. 23(3). 328–336. 86 indexed citations

Curtis, Melissa D., Sandra D. Griffith, Melisa Tucker, et al.. (2018). Development and Validation of a High‐Quality Composite Real‐World Mortality Endpoint. Health Services Research. 53(6). 4460–4476. 166 indexed citations

Khozin, Sean, Amy Pickar Abernethy, Nathan C. Nussbaum, et al.. (2017). Rates of PD-L1 expression testing in U.S. community-based oncology practices (USCPs) for patients with metastatic non-small cell lung cancer (mNSCLC) receiving nivolumab (N) or pembrolizumab (P).. Journal of Clinical Oncology. 35(15_suppl). 11596–11596. 5 indexed citations

Berger, Marc L., et al.. (2016). Opportunities and Challenges in Leveraging Electronic Health Record Data in Oncology. Future Oncology. 12(10). 1261–1274. 82 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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