“Navigating numbers” is a series of Masterclass initiated by a team of Charité researchers who think that our students should be able to get more familiar how numbers shape the field of medicine, i.e. both medical practice and medical research. And I get to organize the next in line.
I am very excited to organise the next Masterclass together with J.O. a bright researcher with a focus on health economics. As the full title of the masterclass is “Papers and Books – series 1 – intended effect of treatments”, some health economics knowledge is a must in this journal club style series of meetings.
But what will we exactly do? This Masterclass will focus on reading some papers as well as a book (very surprising), all with a focus on study design and how to do proper research into “intended effect of treatment” . I borrowed this term from one of my former epidemiology teachers, Jan Vandenbroucke, as it helps to denote only a part of the field of medical research with its own idiosyncrasies, yet not limited by study design.
The Masterclass runs for 8 meetings only, and as such not nearly enough to have the students understand all in and outs of proper study design. But that is also not the goal: we want to show the participants how one should go about when the ultimate question is medicine is asked: “should we treat or not?”
If you want to participate, please check out our flyer
It has been 18 months since I started in Berlin to start at the CSB to take over the lead of the clinical epidemiology research group. Recently, the ISTH early career taskforce have contacted me whether I would be willing to write something about my experiences over the last 18 months as a rookie group leader. The idea is that these experiences, combined with a couple of other papers on similar useful topics for early career researchers, will be published in JTH.
I was a bit reluctant at first, as I believe that how people handle new situations that one encounters as a new group leader is quite dependent on personality and the individual circumstances. But then again, the new situations that i encountered might be more generalizable to other people. So I decided to go ahead and focus more on the description of the new situations I found myself in while trying to keep the personal experiences limited and only for illustrations only.
While writing, I have discerned that there are basically 4 new things about my new situations that I would have loved to realise a bit earlier.
- A new research group is never without context; get to know the academic landscape of your research group as this is where you find people for new collaboration etc
- You either start a new research group from scratch, or your inherit a research group; be aware that both have very different consequences and require different approaches.
- Try to find training and mentoring to help you cope with your new roles that group leaders have; it is not only the role of group leader that you need to get adjusted to. HR manager, accountant, mentor, researcher, project initiator, project manager, consultant are just a couple of roles that I also need to fulfill on a regular basis.
- New projects; it is tempting to put all your power, attention time and money behind a project. but sometimes new projects fail. Perhaps start a couple of small side projects as a contingency?
As said, the stuff I describe in the paper might be very specific for my situation and as such not likely to be applicable for everyone. Nonetheless, I hope that reading the paper might help other young researchers to help them prepare for the transition from post-doc to group leader. I will report back when the paper is finished and available online.
Easter brought another publication, this time with the title
“Statins and risk of poststroke hemorrhagic complications”
I am very pleased with this paper as it demonstrates two important aspects of my job. First, I was able to share my thought on comparing current users vs never users. As has been argued before (e.g. by the group of Hérnan) and also articulated in a letter to the editor I wrote with colleagues from Leiden, such a comparison brings forth an inherent survival bias: you are comparing never users (i.e. those without indication) vs current users (those who have the indication, can handle the side-effects of the medication, and stay alive long enough to be enrolled into the study as users). This matter is of course only relevant if you want to test the effect of statins, not if you are interested in the mere predictive value of being a statin user.
The second thing about this paper is the way we were able to use data from the VISTA collaboration, which is a large amount of data pooled from previous stroke studies (RCT and observational). I believe such ways of sharing data brings forward science. Should all data be shared online for all to use? I do am not sure of that, but the easy access model of the VISTA collaboration (which includes data maintenance and harmonization etc) is certainly appealing.
update 19.5.2016: this project also led to first author JS to be awarded with the young researcher award of the ESOC2016.
— CSB (@BerlinStroke) 10 May 2016
We published a new article just in PLOS Biology today, with the title:
“Where Have All the Rodents Gone? The Effects of Attrition in Experimental Research on Cancer and Stroke”
This is a wonderful collaboration between three fields: stats, epi and lab researchers. Combined we took a look at what is called attrition in the preclinical labs, that is the loss of data in animal experiments. This could be because the animal died before the needed data could be obtained, or just because a measurement failed. This loss of data can be translated to the concept of loss to follow-up in epidemiological cohort studies, and from this field we know that this could lead to substantial loss of statistical power and perhaps even bias.
But it was unknown to what extent this also was a problem in preclinical research, so we did two things. We looked at how often papers indicated there was attrition (with an alarming number of papers that did not provide the data for us to establish whether there was attrition), and we did some simulation what happens if there is attrition in various scenarios. The results paint a clear picture: the loss of power but also the bias is substantial. The degree of these is of course dependent on the scenario of attrition, but the message of the paper is clear: we should be aware of the problems that come with attrition and that reporting on attrition is the first step in minimising this problem.
A nice thing about this paper is that coincides with the start of a new research section in the PLOS galaxy, being “meta-research”, a collection of papers that all focus on how science works, behaves, and can or even should be improved. I can only welcome this, as more projects on this topic are in our pipeline!
Update 6.1.16: WOW what a media attention for this one. Interviews with outlets from UK, US, Germany, Switzerland, Argentina, France, Australia etc, German Radio, the dutch Volkskrant, and a video on focus.de. More via the corresponding altmetrics page . Also interesting is the post by UD, the lead in this project and chief of the CSB, on his own blog “To infinity, and beyond!”
Another publication, this time on the role of the ABI as a predictor for stroke recurrence. This is a meta analysis, which combines data from 11 studies allowing us to see that ABI was moderately associated with recurrent stroke (RR1.7) and vascular events (RR 2.2). Not that much, but it might be just enough to increase some of the risk prediction models available for stroke patients when ABI is incorperated.
This work, the product of the great work of some of the bright students that work at the CSB (JBH and COL), is a good start in our search for a good stroke recurrence risk prediction model. Thiswill be a major topic in our future research in the PROSCIS study which is led by TGL. I am looking forward to the results of that study, as better prediction models are needed in the clinic especially true as more precise data and diagnosis might lead to better subgroup specific risk prediction and treatment.
Hong J Bin, Leonards CO, Endres M, Siegerink B, Liman TG. Ankle-Brachial Index and Recurrent Stroke Risk. Stroke 2015; : STROKEAHA.115.011321.
A quick update on a new article that was published on friday in the NTVG. This article with the title
“Conducting your own research: a revised recipe for a clinical research training project”
– gives a couple of suggestions for young clinicians/researchers on how they should organise their epidemiological research projects. This paper was written to commemorate the retirement of prof JvdB, who wrote the original article back in 1989. I am quite grew quite fond of this article, as it combines insights from 25 years back as well as quite recent insights (e.g. STROBE and cie Schuyt and resulted in a article that will help young research to rethink how they plan and execute their own research project.
There are 5 key suggestions that form the backbone of this article i.e. limit the research question, conduct a pilot study, write the article before you collect the data, streamline the research process and be accountable. As the article is in Dutch only at this moment, I will work on an English version. First drafts of this ms, each discussing each of the 5 recommendations might appear on this website. And how about a German version?
Anyway, it has to be mentioned that if it not was for JvdB, this article would have never come to light. Not only because he wrote the original, but mostly because he is one of the most inspiring teachers of epidemiology.