The SPRINT Trial was an important trial for the evidence base in hypertension. Previous studies had shown that intensive BP lowering in patients with type 2 diabetes (<120 vs <140 mm Hg) and in patients who previously had a stroke (<130 vs <150 mm Hg) resulted in no significant benefit in major cardiovascular events (except for stroke in diabetics). The natural question arose about whether tight BP control in patients without diabetes or previous stroke mattered more than less intensive control? This became even more important as JNC-8 recommended less stringent goals than previous JNC guidelines.
Unfortunately I have seen physicians I work with and residents become overzealous in extending SPRINT results to other patient groups, especially those which it excluded. Interestingly, when I question them about SPRINT and who was actually studied they either assumed it was all patients with HTN (because they hadn’t actually read the inclusion/exclusion criteria at all) or knew who it was restricted to but assumed that higher risk patients with diabetes and stroke would equally gain benefit (or even more which seems intuitive).
So my 1st point to make is that you should actually read a study and know who was studied (and importantly who wasn’t) before you start using it.
This seems like an intuitive statement but many of my colleagues and trainees simply haven’t closely examined the study. They have heard abbreviated results in conferences or from faculty in clinic and assume that it applies broadly.
So who was in SPRINT? To be included a patient had to be at least 50 yrs of age, have a systolic BP of 130-180 mm Hg, and be at increased risk of cardiovascular disease (clinical or subclinical CVD, CKD with eGFR 20-59 ml/min, Framingham 10-yr risk >15%, or be over 75 yrs of age). Patients with diabetes and prior stroke were excluded. Lets see what they looked like by checking out Table 1.
These patients had pretty good baseline blood pressures and were already on almost 2 anti-hypertensive meds to start. They had fairly good lipid profiles and around 43% were on statins. The majority were nonsmokers and had 20% 10-yr Framingham risk. These patients are somewhat healthier than the patients I see.
Point 2: Compare patients in the study to who you see. Are they sicker or healthier? How would you adjust the results to fit your patients?
Don’t assume the study enrolled the average patient or that your patients will be just like those in the study.
In Part 2 I’ll analyze the intervention and outcome measures of the study.
I am preparing for a talk on the controversy surrounding JNC-8 and came across a post on KevinMD.com by an author of a Cochrane systematic review that aimed to quantify the effects of antihypertensive drug therapy on mortality and morbidity in adults with mild hypertension (systolic blood pressure (BP) 140-159 mmHg and/or diastolic BP 90-99 mmHg) and without cardiovascular disease. This is an important endeavor because the majority of people we consider treating for mild hypertension have no underlying cardiovascular disease.
David Cundiff, MD in his KevinMD.com post made this statement:
The JNC-8 authors simply ignored a systematic review that I co-authored in the Cochrane Database of Systematic Reviews that found no evidence supporting drug treatment for patients of any age with mild hypertension (SBP: 140-159 and/or DBP 90-99) and no previous cardiovascular disease, diabetes, or renal disease (i.e., low risk).
Let’s see if you agree with his assessment of the findings of his systematic review.
As is typical for a Cochrane review the methods are impeccable so we don’t need to critically appraise the review and can review the results. The following images are figures from the review. Examine them and then I will discuss my take on the results.
Coronary Heart Disease results
If you just look at the summary point estimates (black diamonds) you would conclude the treatment of mild hypertension in adults without cardiovascular disease has no effect on mortality, stroke and coronary heart disease but greatly increases withdrawal from the study due to adverse effects. But you are a smarter audience than this. The real crux is in the studies listed and examination of the confidence intervals.
Lets examine stroke closely. 3 studies were included that examined the treatment of mild hypertension on stroke outcomes. Two of the studies had no stroke outcomes at all. The majority of the data came from one study. The point estimate of effect was in fact a reduction of stroke by 49% but the confidence interval included 1.0 so not statistically significant. But the confidence interval ranged from 0.24-1.08- a potential 76% reduction in stroke up to an 8% increase. I would argue that a clinically important effect (stroke reduction) is very possible and had the studies been higher powered we would have seen a statistically significant reduction also. I think to suggest no effect on stroke is misleading. The same can be said for mortality.
Finally, what about withdrawals due to adverse effects. Only 1 study provided any data. It has an impressive risk ratio of 4.80 (almost 5 fold increased risk of stopping the drugs due to adverse effects). But the absolute risk increase is only 9% (NNH 11). We are not told what these adverse effects are to know if they were clinically worrisome or just nuisances for patients.
So, I don’t agree with Dr. Cundiff’s assessment that there is no evidence supporting treatment. I think the evidence is weak but there is no strong evidence to say we shouldn’t treat mild hypertension. The confidence intervals include clinically important benefits to patients. More studies are needed but will not be forthcoming. Observational data supports treating this group of patients and may have to be relied upon in making clinical recommendations.
Last week the hotly anticipated cholesterol treatment guidelines were released and are an improvement over the previous ATPIII guidelines. The new guidelines abandon LDL targets, focus on statins and not add-on therapies which don’t help, and emphasize stroke prevention in addition to heart disease prevention.
The problem with the new guidelines is that they developed a new risk prediction tool which frankly stinks. And the developers knew it stunk but promoted it anyway!
Lets take a step back and discuss clinical prediction rules (CPR). CPRs are mathematical models that quantify the individual contributions of elements of the history, PE, and basic laboratory tests into a score that aids diagnosis or prognosis estimation. They can accommodate more factors than the human brain can take into account and they always give the same result whereas human judgment is inconsistent (especially in the less clinically experienced). To develop a CPR you 1) construct a list of potential predictors of the outcome of interest, 2)examine a group of patients for the presence of the candidate predictors and their status on the outcome of interest, 3) determine statistically which predictors are powerfully and significantly associated with the outcome, and 4) validate the rule [ideally involves application of rule prospectively in a new population (with different spectrum of disease) by a variety of clinicians in a variety of institutions].
Back to the new risk tool. They decided to develop a new tool because the Framingham Score (previously used in the ATPIII guidelines) was insufficient (developed on exclusively white population). How was it developed? The tool was developed using “community-based cohorts of adults, with adjudicated endpoints for CHD death, nonfatal myocardial infarction, and fatal or nonfatal stroke. Cohorts that included African-American or White participants with at least 12 years of follow-up were included. Data from other race/ethnic groups were insufficient, precluding their inclusion in the final analyses”. The data they used was from “several large, racially and geographically diverse, modern NHLBI-sponsored cohort studies, including the ARIC study, Cardiovascular Health Study, and the CARDIA study, combined with applicable data from the Framingham Original and Offspring Study cohorts”. I think these were reasonable derivation cohorts to use. How did they validate the tool? Importantly they must use external testing because most models work in the cohort from which it was derived. They used “external cohorts consisting of Whites and African Americans from the Multi-Ethnic Study of Atherosclerosis (MESA) and the REasons for Geographic And Racial Differences in Stroke study (REGARDS). The MESA and REGARDS studies were approached for external validation due to their large size, contemporary nature, and comparability of end points. Both studies have less than 10 years of follow up. Validation using “most contemporary cohort” data also was conducted using ARIC visit 4, Framingham original cohort (cycle 22 or 23), and Framingham offspring cohort (cycles 5 or 6) data”. The results of their validity testing showed C statistics ranging from a low of 0.5564 (African -American men) to a high of 0.8182 (African-American women). The C statistic is a measure of discrimination (differentiating those with the outcome of interest from those without the outcome) and ranges from 0.5 (no discrimination- essentially as good as a coin flip) to 1.0 (perfect discrimination). The authors also found that it overpredicted events. See graph below.
So why don’t I want to use the new prediction tool? 3 main reasons:
1) It clearly over predicts outcomes. This would lead to more people being prescribed statins than likely need to be on statins (if you only use the tool to make this decision). One could argue that’s a good thing as statins are fairly low risk and lots of people die from heart disease so overtreating might be the way to err.
2) No study of statins used any prediction rules to enroll patients. They were enrolled based on LDL levels or comorbid diseases. Thus I don’t even need the rule to decide on whether or not to initiate a statin.
3) Its discrimination is not good….see the C-statistic results. For Black men its no better than a coin flip.
Interested in teaching and learning principles and ideas of community involvement, sustainability, equity, technology and engagement. Looking at new ways to innovate and to hack the curriculum. All views my own.