February Talk: A Student Summary

The talk’s title is “A New Approach to the Generalizability of Randomized Trials” presented by Dr. Anders Huitfeldt.

To extrapolate causal effects from one setting (the study population of a RCT) to another setting (a clinically relevant target population) we need to justify some parameters. For example, we have to see if the conditional effect parameter in the target population is equal to the corresponding parameter in the study population. Known as the “effect homogeneity”. The effect homogeneity parameter occurs not only between the study population and the target population but also between two groups in the RCT’s population. The principle of extrapolating causal effects is that, because we have a randomized trial in the study population, we know what happens in this population if everyone takes the drug and what if they don’t take the drug. In addition, because the drug is not available in the target population we know what happens if they don’t take the drug. Then, we target to use the above information in combination with homogeneity assumption to predict what happens if someone in the target population don’t take the drug. However, the different definition of “effect homogeneity” leads to a different empirical prediction. Traditional approaches for it are: Effect Measure Modification, Forest plots, Cochran’s Q, I2. These approaches contain some shortcomings which can be reduced (eg. No biological interpretation). That is why a method which can be used to determine choice between effect measures is necessary. The COST parameter would be a new class of causal models for the purpose. The COST parameter has many advantages as effect quality measuring because of (1) a clear biological interpretation, (2) the effect of a drug is determined by gene, (3) Baseline risk independence. Finally, there is still controversial among methodologists about using COST parameter as an approach to determining the appropriate choice of scale if effect homogeneity is considered in terms of measures of effect.

January Talk: A Student Summary

The title of the talk is “Understanding Population-based Migraine Through Genome-wide Genetics” by Daniel Chasman from Brigham and Women’s Hospital.

Neurological disorders is becoming a global burden and ranks 2nd for number of years lost to disability. History of diabetes and hypertension, postmenopausal hormone use, physical activities, alcohol consumption, and smoking status are more frequent in people with migraines. Aging is a very important factor in migraine development. In the WGHS data, 3 SNPs investigated the relationship with migraine. Among them, PRDM16 rs22651899 increases the risk and TRPM8 rs10166942 decrease the risk of migraine, while LRP1 rs11172113 was not associated with migraine. After the first implementation of genetic analysis in 2009 with 3 SNPs, the number of SNPs that are included in the analysis increased gradually through each study, and reach out to 44 genome-wide significant loci in a large population study called IHGC 2016 with 59,042 participants. The genetic risk score (GRS) has been calculated to investigate the shared genetic contribution of ischemic stroke and migraine. In observational studies, migraine with aura is a risk factor for ischemic stroke. The causality of the relationship between migraines and coronary artery disease (CAD), MI, angina and atrial fibrillation have been assessed using Mendelian Randomization (MR). The confirmation was drawn from CAD, MI, angina. Some loci with likely vascular function show concordant susceptibility between migraine, dissection but inverse susceptibility with stroke/ CAD. The higher degree of heterogeneity in migraine genetics makes a more complex underlying biology investigation of this form of the disease. In conclusion, there is a long road ahead in Science to determine the matrix of migraine, SNPs, and other diseases.

Announcing December BEMC Talk

Dear Berlin-area Epidemiological Methods Enthusiasts,

You are invited to our next BEMC Talk on Wednesday, December 4th.  

BEMC Talk: Wednesday, December 4th, 2019 @ 4pm

“Causal Decision Analysis of Benefits, Harms and Cost-effectiveness – Estimands, Outcomes, Models and More” – Uwe Siebert, Hall in Tirol, Austria

  • Please register online: https://docs.google.com/forms/d/e/1FAIpQLSe6eep88mkT1x1ym3eULvX0clpS_mpY5bw3DzZ-pvbIblAWIQ/viewform?usp=sf_link
  • Description: “Decision analysis (or decision-analytic modeling) is a systematic approach to decision making under uncertainty that involves combining evidence for different estimands and outcomes from different study types and different sources in order to derive causal conclusions for future clinical, policy or research actions.
    This talk provides an overview on the concepts and methods of causal decision-analytic modeling as a tool for (1) benefit-harm analysis informing clinical guidelines and personalized medical decision making, (2) cost-effectiveness analysis informing reimbursement decision making and (3) value-of-information analysis for future research prioritization.
    Case examples of published decision analyses will be used to illustrate the fields of application, different model types, the importance of using causal model input parameters (particularly from real-world data), the choice of different estimands (e.g., from the ICH E9 framework) and their causal interpretations, approaches to integrate intercurrent events, as well as guidelines for best modeling practices, possible pitfalls in causal modeling, and future developments.
  • Location: Hertwig–Hörsaal (Zweigbibliothek Campus Charité Mitte – Medizinische Bibliothek der Charité), CCM 10117 Berlin
  • Map: https://goo.gl/maps/Ed27GBYXeJkjrYyj8 (Look for our signs! It’s the same entrance as the CCM Medical Library, 1st floor)
  • Register here: https://docs.google.com/forms/d/e/1FAIpQLSefNsbbaTIyo-32yDrIJkrws-BLOY_XGpKT8oHOwAgHyXnIXg/viewform?usp=sf_link
  • Note from Uwe Siebert: Want to hear more about modeling? –> SAVE THE DATE:
    https://smdm.org/meeting/18th-biennial-european-conference

Upcoming Berlin Epi Events:

  • December 18th – BEMC JClub – Paper will be posted online

Interested in other related events? Visit the Institute of Public Health calendar to check out upcoming events & short courses!

Follow BEMC on Twitter and leave questions for our speakers: @BEMColloquium

Announcing November BEMC Talk

Dear Berlin-area Epidemiological Methods Enthusiasts,

You are invited to our next BEMC Talk on Wednesday, November 6th.  

BEMC Talk: Wednesday, November 6th, 2019 @ 4pm

“The causes of the causes in context: confronting the burden of proof in lifecourse and social epidemiology” – Michelle Kelly-Irving, Inserm-Toulouse, Equity research team, LEASP, Faculté de Medecine, Toulouse, France

  • Please register online: https://docs.google.com/forms/d/e/1FAIpQLSeY8N6sQryvMtiJdMIJ5Pdo0grjkqMB6bSf0jrRaPUzlCAg-A/viewform?usp=sf_link
  • Description: “Social determinants are at the root of many potential causal pathways towards health outcomes. Increasingly, the randomized-control trial approach to establishing causality is questioned with the development of other causal approaches. These methods can be especially challenging for research questions involving social determinants and health inequalities within a lifecourse framework. In complex observational settings understanding and defining the context is a key issue affecting the generalizability of findings and transferability of interventions. Theory-driven research may be especially important when dealing with these methodological challenges, and enable lifecourse researchers to interpret their findings. I will present these challenges in terms of research on social-to-biological questions relating to health inequalities, and discuss how interdisciplinarity and triangulation may help to establish the burden of proof.
  • Location: Hertwig–Hörsaal  (Oscar Hertwig-Haus, Anatomie), CCM 10117 Berlin

Upcoming Berlin Epi Events:

  • November 20th – BEMC JClub – Paper will be posted online
  • December 4th – BEMC Talk – Uwe Siebert, Hall in Tirol
  • December 18th – BEMC JClub – Paper will be posted online

Interested in other Institute of Public Health events? Visit our calendar to check out upcoming conferences & short courses!

Follow BEMC on Twitter and leave questions for our speakers: @BEMColloquium

October Annoucment!

There is no BEMC talk in the month of October, but there is still a lot going on in the epi community!

JClub on Oct 16th: Please click on this link to see the chosen journal article. Note: for the first time ever, we will be reading a pre-print and submitting feedback as a group to the authors! Should be a cool experience to influence ongoing research, so don’t miss out!


IPH lecture on Oct 23rd: Professor John Gill is going to give a talk on “Understanding and communicating risk of rare but serious health complications – an example from living kidney donation” – click on this link to find out more and register for the event.


Our next regularly scheduled BEMC talk will be in November.

See you soon!

September Talk: A Student Summary

“An introduction to precisely and ggdag: Tools for modern methods in R” – a summary by Ana Sofia Oliveira Gonçalves

On the 4th September 2019, Malcolm Barrett held a lecture on the topic of “An introduction to precisely and ggdag: Tools for modern methods in R”. Malcolm Barrett is a PhD student in Epidemiology at the University of Southern California. He has experience in epidemiology and has worked with R studio.

During his lecture, he introduced two R packages that he has developed: “precisely” and “ggdag”. He then wrapped up his talk by sharing best practices in creating software for epidemiology analysis.

Malcolm first introduced the package “precisely”. Precisely is an R package which calculates sample size based on precision rather than power. It allows researchers to calculate sample sizes for common epidemiology measures, like risk differences, risk ratios and odds ratios. It can be used with R or just as a calculator on the web. It goes hand-in-hand with the recent discussion regarding statistical significance. During the discussion, he commented that the move away from p-values will still take some time. The motivation behind developing this package came from reading an article from Rothman and Greenland on planning study size based on precision. In this package, researchers need to set a desired precision, proportions of exposed to unexposed, group ratio and coverage. It also allows the calculation of precision given the sample size. The package shiny helps to run webapps, thus, people who do not work with R can still use precisely. He highlighted the common wrong interpretations of confidence intervals. 

Malcolm proceeded to introduce his package “ggdag”. Ggdag is a package used to create causal diagrams in R. Dagitty does not always create beautiful plots and ggplot2 is the best data visualization tool at the moment. Hence, ggdag aims to integrate dagitty and ggplot2 (and ggraph which is actually part of ggplot2). Dagitty has powerful, robust algorithms and ggplot2 has unlimited flexibility. Ggdag also provides information (graphically) regarding the variables that need to be adjusted/controlled for.

Later on, he gave some insights on designing software for epidemiology. He mentioned that the developed software should be 1) very flexible, in order to automate tedious parts of analysis and be very loud about the difficult part, 2) expressive (modular code is better than monolithic functions), 3) able to fit into the ecosystem. He finished his lecture describing the package he is currently creating, which will be a tool to help clone datasets. 

Announcing September BEMC Talk

Dear Berlin-area Epidemiological Methods Enthusiasts,

You are invited to our next BEMC Talk on Wednesday, September 4th. Please note the location — CVK, Forum 3, Hörsaal 3, 13353 – Campus Virchow Clinic. 

BEMC Talk: Wednesday, September 4th, 2019 @ 4pm

“An introduction to precisely and ggdag: Tools for modern methods in R” – Malcolm Barrett, California

  • Please register online:
  • Description: “Modern epidemiology gives us insight into study planning and causal inference, but the success of these approaches require friendly and accessible software. I will discuss two R packages for modern methods in study design and causal inference: precisely and ggdag. precisely is a study planning tool to calculate sample size based on precision rather than power. Calculating sample size based on precision focuses on the width of the confidence interval instead of statistical significance. precisely is a fast and flexible R implementation of the work by Rothman and Greenland on this subject, including a Shiny web app for calculating sample size. ggdag is a toolkit for working with causal directed acyclic graphs (DAGs), a central tool in causal inference. DAGs help identify many types of bias, such as confounding, selection bias, and measurement error, as well as tell us how to correct for it. ggdag makes it easy to create, analyze, and plot DAGs in ggplot2.
  • **Location change: CVK, Forum 3, Hörsaal 3, 13353 – Campus Virchow Clinic

Upcoming Berlin Epi Events:

  • September 18th – BEMC JClub – Paper posted online
  • October 2nd – BEMC JClub – Paper will be posted online
  • Wednesday, October 23rd – IPH Lecture Partner event– John Gill from Vancouver
    • Charite Mitte Campus, COO starting at 4pm
  • November 6th – BEMC Talk – “The causes of the causes in context: confronting the burden of proof in lifecourse and social epidemiology” – Michelle Kelly-Irving, Toulouse
  • November 20th – BEMC JClub – Paper will be posted online
  • December 4th – BEMC Talk – Uwe Siebert, Hall in Tirol
  • December 18th – BEMC JClub – Paper will be posted online

Interested in other Institute of Public Health events? Visit our calendar to check out upcoming conferences & short courses!

Follow BEMC on Twitter and leave questions for our speakers: @BEMColloquium

Announcing September BEMC Talk

Dear Berlin-area Epidemiological Methods Enthusiasts,

We hope you had a great summer break!
We look forward to seeing you again at our September BEMC Talk in a few short weeks…
BEMC Talk: Wednesday, Sept. 4th, 2019 @ 4pm ·

“An introduction to precisely and ggdag: Tools for modern methods in R” -Malcolm Barrett (US)
**IMPORTANT: Location change: Forum 3, Hörsaal 3, Campus Virchow Klinikum (CVK) in Berlin-Wedding, 13353** ·
Please register here

Description: “Modern epidemiology gives us insight into study planning and causal inference, but the success of these approaches require friendly and accessible software. Malcolm will discuss two R packages he has developed as tools for implementing modern methods in study design and causal inference: precisely and ggdag. precisely is a study planning tool to calculate sample size based on precision rather than power. Calculating sample size based on precision focuses on the width of the confidence interval instead of statistical significance. precisely is a fast and flexible R implementation of the work by Rothman and Greenland on this subject, including a Shiny web app for calculating sample size. ggdag is a toolkit for working with causal directed acyclic graphs (DAGs), a central tool in causal inference. DAGs help identify many types of bias, like confounding, selection bias, and measurement error, as well as tell us how to correct for it. ggdag makes it easy to create, analyze, and plot DAGs in ggplot2.”

Other upcoming Berlin-area epi-related events:
Sept. 18th BEMC JClub article posted here ·
Early Oct no BEMC Talk!
Join us for the IPH lecture on Oct. 23rd · “Understanding and communicating risk of rare but serious health complications – an example from living kidney donation” – John Gill (Vancouver) ·
Oct. 16th, BEMC JClub article posted here ·
February 20-22nd, 2020: REWARD/EQUATOR Conference in Berlin (co-hosted by BIH-QUEST). Details & abstract submission here: https://www.reward-equator-conference-2020.com/

July Talk: Student summary

“Thick” and “Thin” Branches in Epidemiology – a Student Summary from Ana Sofia Oliveira Goncalves

On the 3rd of July 2019, Suzanne Cannegieter held a lecture on ““Epidemiology as a Toolbox to Benefit the Patient”. She graduated as a MD, did a PhD focused on anticoagulant therapy in patients with artificial heart valves, and then completed a Masters in Epidemiology. Throughout her career, she has done numerous studies focused on venous thrombosis. During her lecture, she used venous thrombosis examples to clarify her toolbox, this toolbox can be applied on other diseases as well. She started by highlighting the difference between “thick” and “thin” branch research using a tree as a metaphor. In thick branch research, discoveries are scientific relevant but with little clinical effect. Many other discoveries can come from thick branch research as it leads to further unanswered questions. On the other hand, thin branch research is clinically relevant but holds little scientific influence. Compared to thick branch research, thin branch research is more relevant for patients. She used venous thrombosis as an example for the main study design types: case-control studies, matched case-control studies, self-controlled case series and RCTs. She pointed out that for “thicker” studies, case-controls are the most appropriate study designs, while for “thinner” studies, RCTs are the best option. During the discussion, participants questioned Suzanne whether research can both be “thick” and “thin”, to which her answer was positive. She thinks that it is ideal to be a specialist in a specific disease and a generalist in terms of methods. She also mentioned that scientific research follows trends and some study designs are used less often compared to others.