“BTL provides the best critique and comparison of observational vs. interventional (e.g., randomized clinical trials) research studies that I’ve ever read. Even evidence-based medicine experts will find something eye-opening in this book.”
Posting a book review on this blog is a first for me. I am making an exception because this compact volume, Between the Lines: Finding the Truth in Medical Literature, by Marya Zilberberg, MD, MPH, provides an expert’s explanation of many critical issues related to health literacy, evidence-based medicine, and changing models of medical research—all issues that are covered in this blog.
At the highest level, Between the Lines tackles the complex issue of uncertainty in medicine. Dr. Zilberberg presents a framework for assessing the strength of medical evidence in a way that anyone with some basic knowledge of statistics can follow. She uses clear examples that explain, for instance, why a medical test with a 5% rate of false positives could yield a 98% chance of a false positive if the known prevalence of the disease is very low. If these numbers sound irrational, then it’s time you either study Bayesian statistics or read Between the Lines.
In fact, Bayesian statistics are what united Dr. Zilberberg and me. We met via Twitter and our first engaged conversation occurred when she commented on David H. Freedman’s article in The Atlantic: Lies, Damned Lies, and Medical Science. David’s article provoked quite a lot of discussion about the state of evidence-based medicine (EBM), at least based on the type of research we currently consider our ‘gold standard’. His article profiled Dr. John Iaonnidis, who is now chief of the Stanford Prevention Research Center at Stanford Medical School. 
When Dr. Zilberberg started explaining the effects of heterogeneity in her blog, I knew I had found someone who had the ability to address important statistical topics in a way that could be understood by a broad universe of readers.
In addition, the book is an excellent resource for non-medical professionals who do have some training in statistics. For me—someone who has experience in econometric modeling and has long been an advocate of Bayesian statistics— but has no formal training in epidemiology, I found the book to be a terrific resource for translating mathematical statistics terminology into medical statistics terminology. All I need now is a self-study guide and comprehension test and I think I’ll feel confident in my understanding of concepts in epidemiology. This shouldn’t be a surprise given that Dr. Zilberberg teaches epidemiology.
I highly recommend this concise volume to anyone involved in peer-review or any aspect of medical communications. I’d even go as far as to say it should be required reading for these groups. And for clinicians and those who determine evidence-based guidelines? Well, I know I’d feel a lot more confident in our healthcare system if I thought that most clinicians could answer the 12 questions that Dr. Zilberberg recommends patients ask before accepting to undergo a medical test or procedure (see Chapter 12).
Finally, I’m confident that Between the Lines will be an important addition to core readings for two groups I highly admire: 1) medical librarians and 2) the Society for Participatory Medicine (http://participatorymedicine.org/).
To obtain a copy of the book, which was published May, 2012, visit the Between the Lines website.
 See: http://alumni.stanford.edu/get/page/magazine/article/?article_id=53345 for a recent article about Dr. Iaonnidis’s work.