The overstatement of the DOPS trial (http://www.bmj.com/content/345/bmj.e6409) results have bothered me this week. So much so that even though I am on vacation I wanted to write something about it. Thankfully comments linked to the article show that at least a few readers were smart enough to detect the limitations of this study. What has bothered me is the ridiculous headline on theheart.org about this trial (http://www.theheart.org/article/1458789.do)
HRT cuts CVD by 50%, latest “unique” data show
First off all data is unique so that’s stupid…..CVD cut by 50%. When something seems too good to be true and goes against what we already know take it with a grain of salt. Almost nothing in medicine is 50% effective, especially as primary prevention. But I digress.
The authors of the trial point out their study was different that the previous large HRT study – the Womens’ Health Initiative (WHI). So why do these studies contradict each other?
Whenever you see a study finding always consider 4 things that can explain what you see and its your job to figure out which one it is: truth, chance, bias, and confounding. So let’s look at the DOPS study with this framework
Truth: maybe DOPS is right and the Cochrane review with 24,283 total patients is wrong. Possible but unlikely. DOPS enrolled 1006 patients and has very low event rates (much lower than other studies in this area).
Chance: The composite outcome (which I’ll comment on in a minute) did have a p value <0.05 but none of its components were statistically significant. Each study we do can be a false positive study (or a false negative). So its possible the study is a false positive and if repeated would not give the same results. Small studies are more likely to have false positives and false negatives.
Bias: Biases are systematic errors made in a study.There are a couple in this study: no blinding (this leads to overestimation of effects) and poorly concealed allocation (again leads to overestimation of effects).
Confounding: Women in the control group were about 6 months older than treated patients but this was controlled for in the analysis phase. What else was different about these women that could have affected the outcome?
So far my summary of this study would be that it is small with potential for overestimation of effects due to lack of blinding and poorly concealed allocation.
But there’s more:
- This study ended years ago and is now just getting published. Why? Were the authors playing with the data? The study was industry funded and the authors have industry ties. Hmmm.
- The composite outcome they used is bizarre and not the typical composite used in cardiovascular trials . They used death, admission to the hospital for myocardial infarction or heart failure. This isn’t a good composite because patients wouldn’t consider each component equally important and the biology of each component is very different. Thus you must look at individual components and none are statistically significant by themselves.
- The WHI is the largest HRT trial done to date. Women in the WHI were older and fatter than the DOPS participants and thus are at higher risk. So why would women at higher risk for an outcome gain less benefit that those at lower risk for the outcome? Things usually don’t work that way. A big difference though in these 2 trials is that DOPS women started HRT earlier than WHI women. So maybe timing is important.
Thus, I think this trial at best suggests a hypothesis to test: starting HRT within the first couple of years compared to starting later is more beneficial. DOPS doesn’t prove this. The body of evidence contradicting this trial is stronger than DOPS. Thus I don’t think I will change what I tell my female patients.