This post addresses only the data in this paper concerning dementia, Alzheimer’s Disease (AD) and vascular dementia—the dementia outcomes.
To my mind, the most important threat to the validity of a conclusion that these medications CAUSE an increase in the likelihood of developing dementia, vascular dementia, and/or Alzheimer’s Disease (AD) is bias that arises because of more complete, or earlier, detection of cognitive impairment/dementia in men who receive a prescription for one of the medications because they seek care and are diagnosed with BPH and/or androgenic alopecia. The authors call this “surveillance” bias but it could equally be called detection bias. The authors mention the possibility that surveillance bias may have affected their results but seem to dismiss it as an explanation for the observed associations.
I believe dismissing surveillance bias as an explanation for the findings about dementia is a big mistake. Neither multivariate analysis nor propensity score matching using any set of covariates will eliminate this bias if it exists.
A DAG would not help if this critical factor affecting a causal interpretation of the observed association is ignored or dismissed.
Putting aside the almost intractable problem of surveillance bias, the variables included in the multivariate analysis should be selected because they are confounders or potential confounders–that is, they affect both the outcome and the chances that the medication was prescribed. Their selection should be based on a deep understanding of the literature about risk factors for the dementia outcomes. In my opinion, the authors should have explained in detail why the variables selected for adjustment and for the propensity score were chosen. Variables that are confounders or potential confounders that were considered for the adjustment but not used should have been identified. The authors should have included citations to relevant prior epidemiologic research to justify their choice of variables.
The variables used appear to be, with the exception of “eating disorder,” well-established risk factors for vascular disease or markers of vascular disease: beta-blockers (as a marker of hypertension or CAD), type 2 diabetes, obesity, hypertension, lipid disorder. Other than genetics and age, the established risk factors for AD are cerebrovascular disease, Type 2 diabetes, hypertension, obesity and dyslipidemia (Mayeux and Stern 2012).
It is difficult to distinguish vascular dementia from AD reliably using computer-stored administrative data. Also, as seen in this study, many people with a diagnosis of dementia do not have a specific diagnosis of either vascular dementia or AD. Thus, in the unexposed men in the cited study, 53,0275 had “dementia,” 15,085 had AD, and 10,504 had vascular dementia. Given the overlap in risk factors between vascular disease, cerebrovascular disease, and AD, the risk factors used in the multivariate analysis (and the propensity score matched analysis) EXCEPT eating disorders seem reasonable. The inclusion of eating disorders in the adjustment considering the dementia outcomes, in my opinion, bewildering (and probably unnecessary given its low frequency).
A DAG would perhaps have clarified the authors’ thinking about the choice of variables included in the multivariate analysis and in the propensity score matching exercise. But only if the adjustment / propensity match was more than just a “kitchen sink” adjustment for all the variables in the dataset that are risk factors for vascular disease and/or AD. In my opinion, even a “kitchen sink” adjustment (put in everything that increases the risk of vascular disease and/or AD not worrying about pathways) should have included a diagnosis of cerebrovascular disease/stroke and coronary artery disease since both are strong (causal) risk factors for vascular dementia, AD, and dementia that is not specified as vascular dementia or AD.
Note also that exercise (more) and diet may be risk factors for AD (Mayeux and Stern 2012) and perhaps also for vascular dementia and dementia not specified as vascular or AD. Information on these variables is almost never available in datasets like the one used in this analysis and is potentially a source of residual confounding. Unmeasured variables as a potential source of uncontrolled confounding should have been given more emphasis in this publication.
The OP asks:
Are the resulting estimates for the primary exposure (BPH medication use) at all convincing?”
Given the unexcluded possibility of surveillance bias, the small overall magnitude of the effect size estimates, the existence of known potential confounders not included in the adjustment, and the possibility of unmeasured confounders, my vote concerning the dementia outcomes is a resounding “NO.”
Literature Cited
Mayeux R, Stern Y. Epidemiology of Alzheimer Disease. Cold Spring Harb Perspect Med. 2012;2:a006239.