By Michael H. Crawford, MD, Editor
SYNOPSIS: A patient baseline characteristics level analysis of the SPRINT and ACCORD trials resulted in the creation of a simple algorithm for identifying high-risk patients who experienced fewer major cardiac events without increased serious adverse events from intensive blood pressure therapy.
SOURCE: Wang S, Khera R, Das SR, et al. Usefulness of a simple algorithm to identify hypertensive patients who benefit from intensive blood pressure lowering. Am J Cardiol 2018;122:248-254.
Recent large randomized trials have driven a move toward more aggressive blood pressure (BP) control. However, the downsides to such an approach have been downplayed. Investigators from Dallas sought to develop an algorithm that would inform physicians about which patients were most likely to benefit from intensive BP lowering using patient-level data from two large randomized trials: SPRINT and ACCORD. The authors of both trials compared intensive treatment (systolic BP < 120 mmHg) to standard treatment (SBP < 140 mmHg) but enrolled different patient populations. In both trials, investigators enrolled about 10,000 patients, all diabetic in ACCORD and all nondiabetic in SPRINT. All available patient characteristics were included in developing the risk prediction model. The primary outcome was major adverse cardiovascular events (MACE).
In SPRINT, a subset of patients with high MACE was used to develop a decision tree that was tested on the remaining lower MACE risk patients (n = 8,357) and in 2,258 ACCORD patients in the standard glycemic control group. A decision tree model using three variables (age > 74 years, urinary albumin to creatinine ratio > 34, and history of clinical cardiovascular disease) identified 49% of SPRINT patients and 55% of ACCORD patients considered high risk for MACE. Intensive BP lowering reduced MACE in these high-risk patients in SPRINT (hazard ratio [HR], 0.66; 95% confidence interval [CI], 0.52-0.85) and ACCORD (HR, 0.67; 95% CI, 0.50-0.90), but not in the remaining lower-risk patients (SPRINT: HR, 0.83; 95% CI, 0.56-1.25; ACCORD: HR, 1.09; 95% CI, 0.64-1.83). Importantly, intensive BP therapy in the high-risk group did not increase the risk of serious adverse events. The authors concluded that this simple three-factor risk prediction model identified high-risk patients with systolic hypertension in whom the benefits of intensive therapy outweighed the risks.
One of the criticisms of the SPRINT study was the increased incidence of renal insufficiency and orthostatic symptoms in the intensive treatment arm. There was legitimate concern that older patients with stiff blood vessels would experience more harm than benefit. Also, the overall results of ACCORD suggested that there was no difference in MACE between the standard and intensive arms of the study. Thus, some clinicians ignored SPRINT and the new guidelines it spawned.
The hypothesis of the Wang et al study was that perhaps there is a high-risk group among the SPRINT and ACCORD patients who would benefit from more aggressive targets. The investigators analyzed the myriad clinical data in both trials and discovered a simple decision tree model that identified a high-risk group that benefited from intensive therapy in both trials. Also, intensive therapy did not increase the risk of serious adverse events in this same high-risk group.
The differences in four-year MACE were impressive. In SPRINT, 9.5% of the high-risk group experienced a MACE compared to 2.9% of lower-risk patients. In ACCORD, MACE was 11.5% in the high-risk group and 4.3% in the rest. The number needed to treat (NNT) in high-risk SPRINT patients was 39 and 29 in high-risk ACCORD patients. In the lower-risk SPRINT patients, the NNT was 244 but was not calculable for lower-risk ACCORD patients since the HR was > 1.0. The degree of BP-lowering in the high- and lower-risk patients in both trials was equivalent, so a treatment effect difference does not explain the results. Serious adverse events were not higher in the high-risk groups but were among lower-risk patients (HR, 1.16; 95% CI, 1.03-1.3).
This risk predictor is unique because it targets patients with hypertension, not the general public. SPRINT and ACCORD patients already were a higher-risk group among hypertension patients. Despite this, further risk stratification was possible. Also, the new algorithm does not require extensive data. The only unusual aspect of the algorithm is the urine albumin to creatinine ratio, which clinicians usually do not obtain from hypertensive patients without chronic kidney disease. However, it is an inexpensive, easy-to-conduct test.
The major limitation to this study is that it was a retrospective analysis of two trials that only included higher-risk patients. Thus, we do not know if the new algorithm would perform as well in low-risk hypertensive patients. Also, only simple clinical and laboratory data were included in the trial databases. No sophisticated cardiovascular imaging or stress testing was available consistently; consequently, those were not included. It is possible that these more sophisticated and expensive tests would further stratify patients.
At this juncture, I agree with the authors. Despite the limitations of this study, this new algorithm and other insights potentially could inform hypertension management decisions. At the least, the concept that among hypertensive patients there are higher-risk patients who should have lower BP targets seems established. Exactly how to identify these higher-risk patients is evolving.