“The 3Rs are dead; long live the 3Rs.” So might a herald cry from the battlements of an evidence-based hill. Sharon Straus and Brian Haynes have captured beautifully the need to move beyond just publishing your paper to making evidence available that is ‘reliable, relevant, and readable’.

Why these three Rs? more…

Have you ever been involved with a debate with a partner or colleague, travelling from one place to another, and when the course they took has got you to the destination safely, they turn to you and say “So, [add endearment here], you see my way was right.”? If you have, I doubt that you took the opportunity to explain that they may be suffering from a methodological reasoning problem, of which the conterfactual argument and the possibility of differential verification bias may be important to consider. more…

The separation of ‘risk’ factors and ‘prognostic’ factors at first seems the sort of obsessive fine detail that gives epidemiologists and statisticians a bad name. Sadly, the difference is actually worth understanding for any clinician that’s going to try to cut through an observational study and understand what it might be truthfully telling us. (This isn’t the true of the difference between a Peto odds ratio meta-analysis and a DerSimion & Laird random effects meta-analysis. That is a pointlessly academic difference.) Fortunately, the difference between risk and prognostic factors is straight forward. ‘Risk’ factors are those which as associated with causing a condition (like smoking for lung cancer, being premature for chronic lung disease, or soft light and wine for falling in love). more…

Sometimes we are in situations where we think that something causes problems, and we can’t do a trial randomising one group to get something which we think causes problems! How do we then go about finding out - how to we avoid the problems of ‘confounding’ - and what is that anyway? For example, think about necrotising enterocolitis. Which babies develop NEC? more…

If you were offered a choice of medication to treat an ailment you were suffering from, and you’d asked about how effective they were (and there’s a huge chunk of the population that wouldn’t, and would be happy to just do as they are told), then what information would you like? more…

The five steps of evidence based practice are commonly summarised as ‘Ask, Acquire, Appraise, Apply and Assess’. The first one of these - just asking a question - can prove terribly time consuming and difficult, but with a bit of dissection can be made much easier. The first step when deconstructing the anatomy of inquiry is to ask ‘What sort of question is being asked?’. If it’s about a clinical topic (not directions to the Pharmacy), then the questions can be grossly categorised as ‘foreground’ and ‘background’. Foreground questions are specific and pointed, and can be fitted into a ‘PICO’ frame [1]:Patient-problem, Intervention, Comparision, Outcome. An example might be ‘in bronchilitis [problem], is ipratropium [intervention] or salbutamol [comparison] better for improving respiratory distress? [outcome]‘ more…

In the window of the Wellcome Collection in London artists work to interpret and explain science: it’s an impressive experience to the irregular visitor. When faced with the presenting problems of a child & family, we are faced with trying to do the reverse. We have the sometimes inaccurate recollections of history, the variable responses of clinical examination and our own bias-riddled minds to bash, through the ‘art of diagnosis’ into a suitable explanation for the predicament and onwards into a management strategy. Can this really be evidence based?

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It’s uncommon for us, as paediatricians, to be asked about how cost-effective our treatments are. Glancing at the media shows health stories about the new wonder drugs in adult cancer, or in Alzheimer’s disease, and how they are being restricted by a heartless and miserly health system. Where do these statements about ‘cost-effectiveness’ come from?

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In examining a diagnostic test, we make the assumption that the characteristics of the test - its sensitivity and specificity (or likelihood ratios, the way I prefer to think) - will stay constant across different populations, although the positive and negative predictive values will change * . This is sort of true, and sort of false.

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It’s a great sport of journalists and commentators to look back at predictions of the future from decades past, and see just how badly they have gone astray. We do this as clinicians too, but with a sense of guilt … looking back to an unexpected relapse of a low-risk tumour, or a fulminant hepatitis that presented with mild nausea, and ask ‘Why didn’t we predict that?”. more…