Cumulative systolic blood pressure (SBP) load may better predict major cardiovascular (CV) episodes compared with traditional blood pressure (BP) measures in patients with type 2 diabetes, new study results suggest. A post hoc analysis of type 2 diabetic patients reinforced the importance of both the magnitude and duration of exposure to elevated SBP in assessing CV risk. “Cumulative SBP load was a superior predictor of major CV events compared with mean SBP, SBP time at target (TITRE), and SBP SD [standard deviation],” the study team stated. “Furthermore, cumulative SBP load and SBP SD were independent predictors of CV events and should be used in conjunction in future CV risk prediction algorithms.” The findings were published Monday online ahead of the Sept. 22 issue of the Journal of the American College of Cardiology. Study approach Led by Nelson Wang, MD, from the George Institute for Global Health UNSW, Sydney, the team began assessing cumulative SBP load’s ability to predict CV events compared to mean SBP, SBP TITRE and visit-to-visit variability of SBP over 24 months. Alongside the post hoc analysis, an ADVANCE-ON (Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation) observational study was conducted by the team. This study was a follow-up to the ADVANCE trial, a two-by-two factorial randomized controlled trial that enrolled 11,140 individuals with type 2 diabetes mellitus at high risk of CV events. Participants were randomly assigned to either a fixed-dose combination of perindopril (4 mg) and indapamide (1.25 mg) or matching placebo and to a gliclazide-based regimen aiming to achieve a hemoglobin A1c level ≤6.5%. Participants could also be randomly assigned to a standard glucose control based on local guidelines of participating countries after a 6-week active run-in period. Once the ADVANCE trial was completed, the ADVANCE-ON study followed up on 8,494 patients from a total of 10,082 patients alive when ADVANCE’s randomized treatment phase was completed. For the post hoc analysis, the team included 9,338 participants who had SBP values on six occasions (3, 4, 6, 12, 18 and 24 months). Baseline population characteristics included 217 participants who had experienced a major CV event within the 2-year period. The mean age of the 9,338 participants was 65 years, and 42% were women. The team found participants with higher cumulative SBP loads were older and had a greater prevalence of traditional CV risk factors. This was noted when excluding a prior history of coronary heart disease and smoking status, which were more common in those with lower cumulative SBP loads. Cumulative SBP load, mean BP, SBP TITRE and visit-to-visit variability in SBP were then calculated based on BP measurements collected on these six occasions. Hazard ratio (HR) for the association between cumulative SBP load with major CV events and death were estimated using Cox models. Main findings Over a median 7.6 years of follow-up, 1,469 major CV events, 1,615 deaths and 660 CV deaths were observed in 9,338 participants. Each 1-SD increase in cumulative SBP load was associated with a 14% increase in major CV events (HR: 1.14; 95% confidence interval [CI]: 1.09-1.20). More findings showed that a 1-SD increase in cumulative SBP load was linked to a 13% increase in all-cause mortality (HR: 1.13; 95% CI: 1.13-1.18), and a 21% increase in CV death (HR: 1.21; 95% CI: 1.13-1.29). For the prediction of CV events and death, cumulative SBP load outperformed mean SBP, time-below-target SBP, and visit-to-visit SBP variability in terms of Akaike information criterion (AIC) and net reclassification indexes. “The present paper reinforces not only the importance of treating the degree of SBP elevation, but also the need for early intervention to minimize the duration of elevated SBP exposure,” the research team commented. “This approach also emphasizes the importance of early BP-lowering interventions, beginning with lifestyle measures and, if needed, pharmacological BP lowering therapies to reduce the cumulative SBP load that each individual experiences over their lifetime,” the team added. Editorial discussion points In an accompanying editorial, Donald M. Lloyd-Jones, MD, ScM, from the Northwestern University Feinberg School of Medicine, Chicago, responded to the study’s suggestion that cumulative SBP load and visit-to-visit SBP variability “should be used in conjunction in future CV risk prediction algorithms.” Lloyd-Jones said the measures needed to be considered through “additional lenses,” asking in whom should the measures be used and whether longer-term cumulative BP values have provided better (or worse) information. He also posed further questions of the study, asking whether cumulative and variability BP values measured in routine clinical practice provided the same information as standardized measures performed in the setting of a clinical study. Further discussion points posed by Lloyd-Jones focused onwhether the new measures added incremental value to existing risk prediction equations. He asked whether clinicians or health systems would take the time to integrate these cumulative measures and present and interpret them correctly to assist risk prediction and preventive decision making. “And finally, can we demonstrate that use of these measures leads to improved decision making and better outcomes?” he continued. “This last bar is one that is rarely even attempted for novel (or even existing) measures or biomarkers. “But certainly, the next guidelines should reconsider all types of BP measures, and other potential predictors, to optimize risk estimation and identification of patients with greatest net benefit from risk-reducing therapies.” Sources: Wang N, Harris K, Hamet P, et al. Cumulative Systolic Blood Pressure Load and Cardiovascular Risk in Patients With Diabetes. J Am Coll Cardiol 2022;80: 1147–1155. Lloyd-Jones DM. Cumulative Blood Pressure Measurement for Cardiovascular Disease Prediction: Promise and Pitfalls. J Am Coll Cardiol 2022; 80:1156–1158 Image Credit: Lara – stock.adobe.com