NorPEN webinar and annual meeting

Due to the corona pandemic the 13th annual NorPEN meeting in Stockholm has been postponed until 2021. A webinar for the NorPEN community was held instead in November 2020, the recording is available below.

NorPen Webinar 

November 11th 2020 a webinar including the following presentations were held. The presentation by Jessica and a recording of the webinar is available further down on this page.

An overview of G methods by Jessica Young*

Presentations from 4 junior researchers conducting studies on pharmacoepidemiology in Nordic data:

  • Tyra Lagerberg, PhD student 
    Karolinska Institutet, Stockholm, Sweden
    Selective serotonin reuptake inhibitors and adverse behavioural outcomes
  • Anders Husby, Post-doctoral Researcher
    Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
    Inhaled corticosteroids and COVID-19 morbidity: nationwide cohort study
  • Lars Jøran Kjerpeseth, Post-doctoral Researcher
    Norwegian Institute of Public Health, Oslo, Norway
    Risk of major congenital malformations with metformin compared with insulin in pregnancy    
  • Aleksi Hamina, Post-doctoral Researcher
    University of Oslo, Oslo, Norway
    University of Eastern Finland, Kuopio, Finland Niuva Hospital, Kuopio,  Finland
    Opioid utilization trends among older adults across the Nordic countries -- preliminary results

Documents

NorPen Webinar 2020-11-11

*The presentation was an introduction to G methods and teaser for the full NorPEN2021 pre-conference course on G-methods in relation to pharmacoepidemiology. 

G-methods is a class of methods for estimating the causal effects of time-varying treatment strategies in longitudinal studies where time-varying confounders may be affected by past treatment. G-methods specifically aim to estimate Robins’s g-formula, a function of only measured study variables.  Under assumptions that include no unmeasured confounding, the g-formula indexed by a particular time-varying treatment strategy equals the (counterfactual) outcome mean in the study population had all individuals adhered to that strategy. The g-formula is usually a high-dimensional function when the dimension of measured confounders is high and/or there are many follow-up times. Different g-methods (e.g. inverse probability weighting, parametric g-computation, targeted maximum likelihood estimation) constitute different estimation methods for this function of the longitudinal data.  In this presentation, we will introduce counterfactual causal reasoning that motivates the g-formula as a target of statistical analysis and give a high-level overview of some different estimation methods.

Jessica Young, PhD

Jessica Young, PhD

Assistant Professor and Biostatistician

Department of Population Medicine, Harvard Medical School

https://www.populationmedicine.org/JYoung

Her research focuses on the development and application of statistical methods for estimating policy and clinically relevant causal effects of time-varying treatment strategies on health outcomes in the face of complex time-varying confounding and selection bias, competing events and treatments that are challenging to measure. 

NorPEN 13th Annual Meeting

Due to the corona pandemic the 13th annual NorPEN meeting in Stockholm has been postponed until 2021!

Pre-conference course: Wednesday November 10th 2021

Conference: Thursday and Friday November 11-12th 2021

Save the dates! More information will come during 2021.

In case of questions regarding the 13th annual meeting please send an email to norpen-2020@meds.ki.se

CC
Content reviewer:
Karin Gembert
05-10-2022