Meat consumption is bad for your health. It gives you cancer, heart attacks, stroke, you name it. Says nutrition science. And they must know. After all, it’s a science. Is it, really?
A few years ago, Jonathan Schoenfeld and John Ioannidis took a standard cookbook and randomly selected 50 frequently occurring ingredients (sugar, coffee, salt, etc.). They then carried out a systematic literature search, asking whether there were epidemiologicial studies that had investigated the cancer risk of these ingredients. And they found what they were looking for. For 80% of the ingredients at least one study existed, for many even several. Of 264 of these studies, 103 found that the ingredient investigated increased the risk of cancer, while 88 reduced the risk! So after all Joe Jackson was right: ‘Everything gives you cancer’! But wait a minute: Milk? Veal? Orange juice? Continue reading
Recently in a train station book shop I stood gaping in astonishment in front of a thematically highly specialized book display. It was the bowels-brain table. The books piled up on it promised enlightenment about how the bowel and in particular its contents influence us – yes – how, they verily steer our emotions. A selection of book titles: “Shit-Wise – How a Healthy Intestinal Flora Keeps us fit”; “Bowels heal brain heal body”; “Happiness begins in the bowels”, or “The second brain – How the bowels influence our mood, our decisions and our feeling of wellbeing”. Newspapers, magazines and the internet can also tell us this. The wrong bowel bacteria make us depressive – but the right ones make us happy … which is why yogurt helps against depression. Continue reading
- Let’s get this out of the way: Reproducibility is a cornerstone of science: Bacon, Boyle, Popper, Rheinberger
- A ‘lexicon’ of reproducibility: Goodman et al.
- What do we mean by ‘reproducible’? Open Science collaboration, Psychology replication
- Reproducible – non reproducible – A false dichotomy: Sizeless science, almost as bad as ‘significant vs non-significant’
- The emptiness of failed replication? How informative is non-replication?
- Hidden moderators – Contextual sensitivity – Tacit knowledge
- “Standardization fallacy”: Low external validity, poor reproducibility
- The stigma of nonreplication (‘incompetence’)- The stigma of the replicator (‘boring science’).
- How likely is strict replication?
- Non-reproducibility must occur at the scientific frontier: Low base rate (prior probability), low hanging fruit already picked: Many false positives – non-reproducibility
- Confirmation – weeding out the false positives of exploration
- Reward the replicators and the replicated – fund replications. Do not stigmatize non-replication, or the replicators.
- Resolving the tension: The Siamese Twins of discovery & replication
- Conclusion: No scientific progress without nonreproducibility: Essential non-reproducibility vs . detrimental non-reproducibility
- Further reading
I failed to reproduce the results of my experiments! Some of us are haunted by this horror vision. The scientific academies, the journals and in the meantime the sponsors themselves are all calling for reproducibility, replicability and robustness of research. A movement for “reproducible science” has developed. Sponsorship programs for the replication of research papers are now in the works.In some branches of science, especially in psychology, but also in fields like cancer research, results are now being systematically replicated… or not, thus we are now in the throws of a “reproducibility crisis”.
Now Daniel Fanelli, a scientist who up to now could be expected to side with those who support the reproducible science movement, has raised a warning voice. In the prestigious Proceedings of the National Academy of Sciences he asked rhetorically: “Is science really facing a reproducibility crisis, and if so, do we need it?” So todayon the eve, perhaps, of a budding oppositional movement, I want to have a look at some of the objections to the “reproducible science” mantra. Is reproducibility of results really the fundament of scientific methods? Continue reading
Tuberculosis kills far more than a million people worldwide per year. The situation is particularly problematic in southern Africa, eastern Europe and Central Asia. There is no truely effective vaccination for tuberculosis (TB). In countries with a high incidence, a live vaccination is carried out with the diluted vaccination strain Bacillus Calmette-Guérin (BCG), but BCG gives very little protection against tuberculosis of the lungs, and in all cases the vaccination is highly variable and unpredictable. For years, a worldwide search has been going on for a better TB vaccination.
Recently, the British Medical Journal has published an investigation in which serious charges have been raised against researchers and their universities: conflicts of interest, animal experiments of questionable quality, selective use of data, deception of grant-givers and ethics commissions, all the way up to endangerment of study participants. There was also a whistle blower… who had to pack his bags. It all happened in Oxford, at one of the most prestigious virological institutes on earth, and the study on humans was carried out on infants of the most destitute layers of the population. Let’s have a closer look at this explosive mix in more detail, for we have much to learn from it about
- the ethical dimension of preclinical research and the dire consequences that low quality in animal experiments and selective reporting can have;
- the important role of systematic reviews of preclinical research, and finally also about
- the selective (or non) availability and scrutiny of preclinical evidence when commissions and authorities decide on clinical studies.
Recently, NIH Scientists B. Ian Hutchins and colleagues have (pre)published “The Relative Citation Ratio (RCR). A new metric that uses citation rates to measure influence at the article level”. [Note added 9.9.2016: A peer reviewed version of the article has now appeared in PLOS Biol]. Just as Stefano Bertuzzi, the Executive Director of the American Society for Cell Biology, I am enthusiastic about the RCR. The RCR appears to be a viable alternative to the widely (ab)used Journal Impact Factor (JIF).
The RCR has been recently discussed in several blogs and editorials (e.g. NIH metric that assesses article impact stirs debate; NIH’s new citation metric: A step forward in quantifying scientific impact? ). At a recent workshop organized by the National Library of Medicine (NLM) I learned that the NIH is planning to widely use the RCR in its own grant assessments as an antidote to JIF, raw article citations, h-factors, and other highly problematic or outright flawed metrics. Continue reading
Using metaanalysis and computer simulation we studied the effects of attrition in experimental research on cancer and stroke. The results were published this week in the new meta-research section of PLOS Biology. Not surprisingly, given the small sample sizes of preclinical experimentation, loss of animals in experiments can dramatically alter results. However, effects of attrition on distortion of results were unknown. We used a simulation study to analyze the effects of random and biased attrition. As expected, random loss of samples decreased statistical power, but biased removal, including that of outliers, dramatically increased probability of false positive results. Next, we performed a meta-analysis of animal reporting and attrition in stroke and cancer. Most papers did not adequately report attrition, and extrapolating from the results of the simulation data, we suggest that their effect sizes were likely overestimated. Continue reading