Nicolle M. Gatto

1.5k total citations
40 papers, 996 citations indexed

About

Nicolle M. Gatto is a scholar working on Statistics and Probability, Economics and Econometrics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Nicolle M. Gatto has authored 40 papers receiving a total of 996 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Statistics and Probability, 20 papers in Economics and Econometrics and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Nicolle M. Gatto's work include Health Systems, Economic Evaluations, Quality of Life (20 papers), Advanced Causal Inference Techniques (15 papers) and Statistical Methods in Clinical Trials (12 papers). Nicolle M. Gatto is often cited by papers focused on Health Systems, Economic Evaluations, Quality of Life (20 papers), Advanced Causal Inference Techniques (15 papers) and Statistical Methods in Clinical Trials (12 papers). Nicolle M. Gatto collaborates with scholars based in United States, United Kingdom and Netherlands. Nicolle M. Gatto's co-authors include Ulka B. Campbell, Harold Frucht, Judith S. Jacobson, Alfred I. Neugut, Vijaya Sundararajan, Victor R. Grann, Sharon Schwartz, Robert F. Reynolds, Ashley Jaksa and Seth J. Prins and has published in prestigious journals such as PLoS ONE, Diabetes Care and JNCI Journal of the National Cancer Institute.

In The Last Decade

Nicolle M. Gatto

37 papers receiving 947 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nicolle M. Gatto United States	15	354	251	212	187	183	40	996
Fernando Alarid‐Escudero United States	21	276 0.8×	255 1.0×	249 1.2×	79 0.4×	134 0.7×	75	1.2k
Beth Woods United Kingdom	15	225 0.6×	233 0.9×	370 1.7×	82 0.4×	191 1.0×	59	1.5k
Mark J. Rutherford United Kingdom	23	726 2.1×	384 1.5×	258 1.2×	144 0.8×	225 1.2×	90	2.0k
Ned Calonge United States	20	484 1.4×	218 0.9×	179 0.8×	56 0.3×	125 0.7×	55	1.8k
Jun Yin United States	18	224 0.6×	119 0.5×	60 0.3×	76 0.4×	98 0.5×	77	887
Mark E. Boye United States	18	141 0.4×	157 0.6×	100 0.5×	156 0.8×	169 0.9×	40	851
M. Sanni Ali United Kingdom	19	148 0.4×	61 0.2×	207 1.0×	176 0.9×	188 1.0×	45	1.2k
Bijan A. Niknam United States	16	351 1.0×	72 0.3×	234 1.1×	54 0.3×	131 0.7×	24	900
Julia Thornton Snider United States	18	258 0.7×	124 0.5×	150 0.7×	26 0.1×	74 0.4×	68	998
Linda Yau United States	12	471 1.3×	234 0.9×	59 0.3×	151 0.8×	146 0.8×	19	2.1k

Countries citing papers authored by Nicolle M. Gatto

Since Specialization

Citations

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

Fields of papers citing papers by Nicolle M. Gatto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolle M. Gatto

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolle M. Gatto. A scholar is included among the top collaborators of Nicolle M. Gatto 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 Nicolle M. Gatto. Nicolle M. Gatto 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

Hernandez, Rohini K., Cathy W. Critchlow, Nancy A Dreyer, et al.. (2025). Advancing Principled Pharmacoepidemiologic Research to Support Regulatory and Healthcare Decision Making: The Era of Real‐World Evidence. Clinical Pharmacology & Therapeutics. 117(4). 927–937. 2 indexed citations

Batech, Michael, Ann Madsen, Nicolle M. Gatto, et al.. (2025). Combining Real‐World and Clinical Trial Data Through Privacy‐Preserving Record Linkage: Opportunities and Challenges—A Narrative Review. Health Science Reports. 8(9). e71272–e71272.

Nielson, Carrie M., Tyler D. Alexander, Zhiwei Zhang, et al.. (2024). Linking clinical trial participants to their U.S. real-world data through tokenization: A practical guide. Contemporary Clinical Trials Communications. 41. 101354–101354. 5 indexed citations

Beebe, Elisha, Elizabeth M. Garry, Nicolle M. Gatto, et al.. (2023). A Descriptive Cohort Study of Drug Utilization Patterns Among Patients Hospitalized With Coronavirus Disease 2019 in the United States, January 2021–February 2022. Open Forum Infectious Diseases. 10(7). ofad339–ofad339. 1 indexed citations

Jaksa, Ashley, et al.. (2023). Availability of comparative real-world evidence research in Medicare patients: implications for Centers for Medicare and Medicaid Services drug price negotiations. Journal of Comparative Effectiveness Research. 12(11). e230125–e230125. 1 indexed citations

Gatto, Nicolle M., et al.. (2023). A Structured Process to Identify Fit‐for‐Purpose Study Design and Data to Generate Valid and Transparent Real‐World Evidence for Regulatory Uses. Clinical Pharmacology & Therapeutics. 113(6). 1235–1239. 11 indexed citations

Campbell, Ulka B., et al.. (2023). SURF: A Screening Tool (for Sponsors) to Evaluate Whether Using Real‐World Data to Support an Effectiveness Claim in an FDA Application Has Regulatory Feasibility. Clinical Pharmacology & Therapeutics. 114(5). 981–993. 5 indexed citations

Garry, Elizabeth M., Andrew R. Weckstein, Kenneth Quinto, et al.. (2022). Categorization of COVID‐19 severity to determine mortality risk. Pharmacoepidemiology and Drug Safety. 31(7). 721–728. 13 indexed citations

Gatto, Nicolle M., Shirley Wang, William Murk, et al.. (2022). Visualizations throughout pharmacoepidemiology study planning, implementation, and reporting. Pharmacoepidemiology and Drug Safety. 31(11). 1140–1152. 8 indexed citations

10.

Jaksa, Ashley, Seamus Kent, Stephen Duffield, et al.. (2022). Using primary care data to assess comparative effectiveness and safety of apixaban and rivaroxaban in patients with nonvalvular atrial fibrillation in the UK: an observational cohort study. BMJ Open. 12(10). e064662–e064662. 11 indexed citations

11.

Jaksa, Ashley, Anthony Louder, Laura Díaz‐Martín, et al.. (2022). A Comparison of 7 Oncology External Control Arm Case Studies: Critiques From Regulatory and Health Technology Assessment Agencies. Value in Health. 25(12). 1967–1976. 28 indexed citations

12.

Franklin, Jessica M., Kueiyu Joshua Lin, Nicolle M. Gatto, et al.. (2021). Real‐World Evidence for Assessing Pharmaceutical Treatments in the Context of COVID‐19. Clinical Pharmacology & Therapeutics. 109(4). 816–828. 27 indexed citations

13.

Gatto, Nicolle M., Michael B. Bracken, William Duggan, et al.. (2019). Pulmonary and cardiovascular safety of inhaled insulin in routine practice: The Exubera Large Simple Trial (VOLUME). Contemporary Clinical Trials Communications. 18. 100427–100427. 10 indexed citations

14.

Schwartz, Sharon, Nicolle M. Gatto, & Ulka B. Campbell. (2017). Heeding the call for less casual causal inferences: the utility of realized (quantitative) causal effects. Annals of Epidemiology. 27(6). 402–405. 6 indexed citations

15.

Ali, M. Sanni, Rolf H. H. Groenwold, Svetlana V. Belitser, et al.. (2016). Methodological comparison of marginal structural model, time‐varying Cox regression, and propensity score methods: the example of antidepressant use and the risk of hip fracture. Pharmacoepidemiology and Drug Safety. 25(S1). 114–121. 27 indexed citations

16.

Schwartz, Sharon, Nicolle M. Gatto, & Ulka B. Campbell. (2016). Causal identification: a charge of epidemiology in danger of marginalization. Annals of Epidemiology. 26(10). 669–673. 34 indexed citations

17.

Schwartz, Sharon, Seth J. Prins, Ulka B. Campbell, & Nicolle M. Gatto. (2015). Is the “well-defined intervention assumption” politically conservative?. Social Science & Medicine. 166. 254–257. 42 indexed citations

18.

Gatto, Nicolle M., Ulka B. Campbell, & Sharon Schwartz. (2013). An Organizational Schema for Epidemiologic Causal Effects. Epidemiology. 25(1). 88–97. 9 indexed citations

19.

Reynolds, Robert F., et al.. (2011). Is the Large Simple Trial Design Used for Comparative, Post-Approval Safety Research?. Drug Safety. 34(10). 799–820. 8 indexed citations

20.

Gatto, Nicolle M., Harold Frucht, Vijaya Sundararajan, et al.. (2003). Risk of Perforation After Colonoscopy and Sigmoidoscopy: A Population-Based Study. JNCI Journal of the National Cancer Institute. 95(3). 230–236. 393 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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