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). ‘Prognostic’ factors are those which, in people who have the condition, influence the outcome (like resectability of tumour for lung cancer, duration of intubation for CLD, or an unhealthy joint interest in home furnishings for staying in love). Risk factors are determined by looking at things that influence new cases (‘incident’ ones), wheras prognostic factors can only be determined by following up people who already have the disease. The two things are frequently similar (e.g. 24/40 are often intubated for longer and have more CLD)., but may be strikingly different (e.g. those who fall in love with candlelight are not much more likely to stay together than those whose relationship began with florescent overheads). When you’re reading, it’s worth keeping this in mind to untangle those factors which might make a difference in stopping something happening, and those which you may use to modify the intensity of your treatments.

Acknowledgement:

Dr Steven Oliver, HYMS, for the love-related inspiration for this blog posting

Postscript:

Gold star for the first reader to spot the link between the image and the post.