I wonder what you think about this one. The dataset is large and the basic method simple, but I can't say I agree with the authors' headline.
The paper looks at survival after cardiac surgery, and the issue highlighted by the authors is deprivation: patients from deprived areas fare worse. But if you look at the numbers it seems that the effects of deprivation are dwarfed by the effects of smoking and diabetes.
It's always good to look at basic data, before any statistical manipulations are done. There is a table sorting the patients into quartiles by deprivation score, and tabulating the number of survivors at 3500 days after surgery:
n in quartile n alive at 3500 days
10 803 536
10 854 554
10 872 568
10 748 532
Which looks a pretty small difference to me. Numerically the difference is reported as 2.4% increased mortality for a one unit increase in Carstairs score (i.e. a hazard ratio of 1.024 in a Cox proportional hazard model). This doesn't mean much if you don't know about Carstairs score, so you need to look for the range of Carstairs scores. Elsewhere the interquartile range for Carstairs is given as -2.2 to +2.3: a 4.1 point difference in score, which equates to a 4.1 * 2.4% i.e. a 9.2% difference in mortality. Some of the deprivation effect is due to more smoking, obesity and diabetes in the higher deprivation categories; after adjusting for this in a multivariate analysis, the deprivation effect drops to 1.7% per unit of Carstairs score.
But the effect of diabetes is stated to be a 31% increase in mortality, and of smoking to be 29% (current smoker) or 25% (ex smoker). So surely the headline of the paper should have been about diabetes and smoking? Or have I misunderstood the numbers badly?
Comments