Nicola Orsini

Nicola Orsini

Principal Researcher | Docent
Visiting address: Solnavägen 1 E, 11365 Stockholm
Postal address: K9 Global folkhälsa, K9 GPH Burström, 171 77 Stockholm

About me

  • Researcher and teacher of statistical sciences in the fields of medical and global public health sciences.

    Nicola Orsini, Ph.D. is Principle Researcher, Associate Professor of Medical Statistics, and Head of the Biostatistics Team at the Department of Global
    Public Health, Karolinska Institutet. Dr. Orsini has worked for more than 15 years on development and application of quantitative methods widely used in medical and epidemiological research, including dose-response meta-analysis, sensitivity analysis, time-to-event analysis, quantile analysis, and
    intervention time-series analysis, leading to the publication of more than 200 research articles (H-index=72, i10-index=157).

    His awards include the 2009 Torgny Wännström Prize for the best doctoral thesis in the field of public health from the Swedish Medical Association. In recognition of exceptional research performance demonstrated by multiple highly cited papers, Dr. Orsini has been named by Web of Science (Clarivate Analytics) among the world's most top-cited (top 1%) scientists whose research leads the world in the field of Social Science for seven consecutive years (2017-2023).

    He developed, documented, and freely shared several statistical software components in the Stata language. Dr. Orsini is a fellow of the Royal
    Statistical Society. In 2020 Dr. Orsini has been elected member of the Society of Research Synthesis Methodology. He served in the Executive Board
    of the Strategic Research Program in Epidemiology at Karolinska Institutet between 2015 and 2021.

    2023 Highly Cited Researcher. My research ranks among the top 1% most cited works in the Cross Field. Clarivate Analytics. Web
    of Science.

    2022 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web
    of Science.

    2021 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web
    of Science.

    2020 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web
    of Science.

    2020 Elected Member of the Society of Research Synthesis Methodology.


    2019 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web of
    Science.

    2018 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web of
    Science.

    2017 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web of
    Science.

    2012 Young Scholar Award from the Karolinska Institutet's Strategic Program in Epidemiology. Development of novel procedures in epidemiology:
    A percentiles-based approach to analyse continuous outcomes.

    2010 Young Scholar Award from the Karolinska Institutet's Strategic Program in Epidemiology. Developing user-friendly statistical methods for
    health researchers.

    2009 Torgny Wännström Prize. For the best doctoral thesis in the medical field of public health. Nominations submitted by the medical
    faculties of the universities and the Swedish Medical Society's research mission appoints award winner.

Research

  • He is best known for his work on dose-response meta-analysis based on observational and experimental findings. A book chapter on this topic is with Donna Spiegelman, Professor Emerita of Epidemiologic Methods at Harvard School of Public Health. Handbook of Meta-Analysis, Chapman & Hall/CRC Handbooks of Modern Statistical Methods, 2020). Another book chapter with Professors Susanna C. Larsson (KI) and Georgia Salanti
    (University of Bern) is available in Systematic Reviews in Health Research: Meta-Analysis in Context. The Third Edition. 2022.



    Current doctoral student


    - Robert Theismeier - Simulation methods for design and analysis of prospective meta-analysis of individual participant data




    Previous doctoral and postdoctoral students


    - Alessio Crippa - Development of novel statistical methods for meta-analysis

    - Andrea Bellavia - A percentile approach to time-to-event outcomes

    - Andrea Discacciati - Risk factors for prostate cancer: analysis of primary
    data, pooling, and related methodological aspects

    - XingWu Zhou - Methods for intervention time-series analysis




    Selected publications


    Orsini, N, Moore A, and Wolk A. Interaction Analysis Based on Shapley Values and Extreme Gradient Boosting: A Realistic Simulation and
    Application to a Large Epidemiological Prospective Study. Frontiers in Nutrition 9 (2022).


    Hamza, T., Furukawa, T. A., Orsini, N., Cipriani, A., Iglesias, C. P., & Salanti, G. (2022). A dose–effect network meta-analysis model with
    application in antidepressants using restricted cubic splines. Statistical Methods in Medical Research, 09622802211070256.


    Orsini, N., Larsson, S. C., & Salanti, G. (2022). Dose–Response Meta‐Analysis. Systematic Reviews in Health Research: Meta‐Analysis
    in Context/, 258-269. John Wiley & Sons Ltd.



    Orsini N. Weighted mixed-effects dose-response models for tables of correlated contrasts. Stata Journal. 2021 (2), 320-347.



    Orsini, N., and Spiegelman D. Meta-Analysis of Dose-Response Relationships. Chapter 18. Handbook of Meta-Analysis. Chapman and
    Hall/CRC, 2020. 395-428.



    Bottai M, Orsini N. qmodel: A command for fitting parametric quantile models. The Stata Journal. 2019 (2), 261-293.



    Crippa A, Discacciati A, Bottai M, Spiegelman D, and Orsini N One-stage dose–response meta-analysis for aggregated data. Statistical Methods in
    Medical Research. 2019. 28 (5), 1579-1596.



    Crippa A, Thomas I, Orsini N. A pointwise approach to dose-response meta-analysis of aggregated data. International Journal of Statistics in
    Medical Research. 2018. 7 (2), 25-32.



    Discacciati A, Crippa A, Orsini N. Goodness of fit tools for dose-response meta-analysis of binary outcomes. Research Synthesis Methods. 2017 Jun
  • 8(2):149.


    Crippa A, Khudyakov P, Wang M, Orsini N, Spiegelman D. A new measure of between-studies heterogeneity in meta-analysis. Statistics in Medicine.
    2016
  • 35(21):3661–75.


    Bellavia A, Bottai M, Orsini N. Evaluating additive interaction using survival percentiles. Epidemiology. 2016 May
  • 27(3):360-4.



    Crippa A, and Orsini N. Multivariate dose–response meta-analysis: the dosresmeta R Package. Journal of Statistical Software 2016
  • 72(1):1–15.



    Discacciati A, Bellavia A, Orsini N, Greenland S. On the interpretation of risk and rate advancement periods. International Journal of
    Epidemiology. 2015. Dec 15. pii: dyv320.



    Bellavia A, Discacciati A, Bottai M, Wolk A, Orsini N. Using Laplace regression to model and predict percentiles of age at death, when age is
    the primary time-scale. American Journal of Epidemiology. 2015. Aug 1
  • 182(3):271-7.


    Bellavia A, Bottai M, Orsini N. Adjusted survival curves with multivariable Laplace regression. Epidemiology 2015. Volume 26 - Issue 2. pp: 137-288, e14-e30.


    Bottai M, Orsini N, Geraci M. A Gradient Search Maximization Algorithm for the Asymmetric Laplace Likelihood. Journal of Statistical Computation
    and Simulation. 2015. Volume 85, Issue 10.



    Discacciati A, Orsini N, Greenland S. Approximate Bayesian logistic regression via penalized likelihood by data augmentation. Stata Journal.
    Volume 15 Number 3: pp. 712-736.



    Bottai M, Orsini N, A command for Laplace regression. Stata Journal. 2013. Vol. 13, Nr.2, pp. 302-314.


    Orsini N, Bellocco R, Sjölander A. Doubly robust estimation in Generalized Linear Models. Stata Journal. 2013. Vol. 13, Nr.1. pp.
    185-205.



    Orsini N, Wolk A, Bottai M. Evaluating Percentiles of Survival. Epidemiology. 2012 Sep
  • 23(5):770-1.


    Orsini N, Ruifeng L, Wolk A, Khudyakov P, Spiegelman D. Meta-analysis for linear and non-linear dose-response relationships: examples, an
    evaluation of approximations, and software. American Journal of Epidemiology. 2012 Jan 1
  • 175(1):66-73.


    Orsini N, Bottai M. Logistic quantile regression in Stata. Stata Journal. 2011. Volume 11 Number 3: pp. 327-344.



    Orsini N, Greenland S. A procedure to tabulate and plot results after flexible modeling of a quantitative covariate. Stata Journal. 2011. 11,
    Number 1, pp. 1–29.



    Larsson SC, Orsini N, Wolk A. Vitamin B6 and the Risk of Colorectal Cancer: A Meta-Analysis of Prospective Studies. 2010. JAMA. Mar
    17
  • 303(11):1077-83.


    Orsini N, Bellocco R, Greenland S. Generalized least squares for trend estimation of summarized dose-response data. Stata Journal. 2006, 6:
    40-57.

Teaching

  • Master Program in Public Health


    - Course Director "Biostatistics I" (5 weeks)

    - Course Director "Biostatistics II" (5 weeks)




    Doctoral Program in Epidemiology


    - Course Director of "Fundamentals of Stata language" (1 week)

    - Course Director of "Fundamentals of using Python in Health Related Research" (1 week)

    - Course Director of "Biostatistics II: Logistic regression for Epidemiologists" (1 week)

Articles

All other publications

Grants

Employments

  • Principal Researcher, Department of Global Public Health, Karolinska Institutet, 2022-

Degrees and Education

  • Docent, Karolinska Institutet, 2011
  • Degree Of Doctor Of Philosophy, Institute of Environmental Medicine, Karolinska Institutet, 2008
  • Licentiate Degree, Institute of Environmental Medicine, Karolinska Institutet, 2006

Supervisor

  • Ehrlinder Hanne, Förmaksflimmer: Risker och vinster med antikoagulation hos äldre

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