Michal Pac1,2, Alessandro Di Deo1, Oscar Della Pasqua1
1Clinical Pharmacology & Therapeutics Group University College London, 2Department of Nephrology, Kidney Transplantation and Arterial Hypertension Children’s Memorial Health Institute
Introduction: Primary hypertension (PH) affects 4-5% of children and adolescents [1]. The exposure to elevated blood pressure (BP) increases the risk of developing, subclinical target organ damage (TOD) including left ventricular hypertrophy (LVH) and increase in carotid intima-media thickness (cIMT) [2]. Patients with PH in childhood or increased BP trajectories over time are at higher risk of subclinical TOD in early adulthood [3]. Pharmacological treatment for PH should be initiated when the lifestyle modifications (LFM) fail to lower BP and/or at the presence of TOD [4]. It is generally accepted that PH standard therapy lowers BP and decreases TOD in most patients. However, 33% of patients treated for PH progress with TOD, whilst LVH persists in 67% of those with LVH at the time of diagnosis, despite the treatment [5]. Little is known about the baseline phenotype associated with worsening of TOD. Objectives: The present study aimed to identify clinical and demographic baseline characteristics that are associated with higher likelihood of increasing left ventricular mass index (LVMi) since time of diagnosis and to find prognostic marker of LVMi increase. Methods: Here we apply an approach similar to the work by Oosterholt et al. for the evaluation of treatable traits in moderate-severe asthma [6]. Data from a retrospective, single centre, observational study in patients admitted to the Deptartment of Nephrology, Kidney Transplantation and Arterial Hypertension of Children’s Memorial Health Institute were available for this investigation. Standard clinical data including demographic, laboratory [plasma uric acid (UA), fasting plasma glucose and lipid profile], ambulatory blood pressure monitoring (ABPM) parameters, and TOD measurements (LVMi and cIMT assessed by ultrasonography) were collected during the first visit and at follow-up visits. Prior to model development, an exploratory analysis was performed using Kaplan-Meier estimator to examine the baseline characteristics impact on LVMi increase. The exploratory step aimed to describe LVMi changes over time, and to identify influential factors and assess correlations between variables of interest. Subsequently, different functions (i.e., exponential, Weibull, Gompertz) were evaluated within a time-to-event (TTE) model to characterise time-to-first occurrence of a LVMi increase of at least of 5 g/m2.7 according to the de Simone formula [7]. An observation window of 16 months was defined considering the event distribution. Model development and evaluation were implemented in NONMEM v.7.5 using the Laplacian estimation method. Model diagnostics (i.e., visual predictive checks, goodness-of-fit, decrease in log-likelihood) were used for model selection and evaluation. Comparison of hierarchical models was based on the likelihood ratio test and standard error of the parameter estimates. Eventually, covariate model building was implemented using a forward inclusion-backward elimination procedure. Results: The analysis population included 193 patients (77.7% males) aged 6-17.6 years old with weight range: 22-121 kg, LVMi range: 18.5-76.1 g/m2.7 and cIMT range: 0.32-0.63 mm. 63 patients were diagnosed with white coat hypertension, 17 with pre-hypertension, 23 with grade 1 hypertension, and 90 with grade 2 hypertension based on the ABPM. 25 events were observed during the 16-month observation window. A Gompertz model was chosen as best describing the time-to-first LVMi increase in the overall population and across subgroups stratified by treatment type and baseline covariates. No significant differences in survival curves between patients on antihypertensive (anti-HT) drugs and patients solely on LFM were identified. In contrast, BMI, 24-hour systolic BP, UA, and lipid profile appeared to be significant covariates on the baseline hazard, which corresponded to an annualised incidence of 4.85% per year (6.49% events in 16 months). The most clinically relevant was BMI. The instantaneous risk of LVMi increase by 5 g/m2.7 increases by 9.99% for every unit increase in BMI relative to the median of 24.1 kg/m2. Conclusion: Differences in clinical characteristics at the time of diagnosis of PH affect the risk of LVMi increase and progression in TOD. Baseline BMI was found to be prognostic marker of LVMi increase. This initial result suggests that changes in LFM as well as adjuvant therapies aimed at decreasing body weight should be considered in addition to anti-HT therapy.
[1] S Song P, Zhang Y, Yu J, Zha M, Zhu Y, Rahimi K, et al. Global prevalence of hypertension in children: a systematic review and meta-analysis. JAMA Pediatr. 2019;173(11):1154. [2] Forouzanfar MH, Liu P, Roth GA, Ng M, Biryukov S, Marczak L, et al. Global burden of hypertension and systolic blood pressure of at least 110 to 115 mm Hg, 1990-2015. JAMA. 2017;317(2):165–82 [3] Azegami T, Uchida K, Tokumura M, Mori M. Blood pressure tracking from childhood to adulthood. Front Pediatr. 2021;9:785356. [4] Lurbe E, Agabiti-Rosei E, Cruickshank JK, et al. 2016 European Society of Hypertension guidelines for the management of high blood pressure in children and adolescents. J Hypertens. 2016;34(10):1887–1920. [5] Litwin M, Niemirska A, Sladowska-Kozlowska J, Wierzbicka A, Janas R, Wawer ZT, Wisniewski A, Feber J. Regression of target organ damage in children and adolescents with primary hypertension. Pediatr Nephrol. 2010;25(12):2489-99. [6] Oosterholt S, Pavord ID, Brusselle G, Yorgancioglu A, Pitrez PM, Pg A, Teli C, Della Pasqua O. Modelling ASthma TrEatment Responses (MASTER): Effect of individual patient characteristics on the risk of exacerbation in moderate or severe asthma: A time-to-event analysis of randomized clinical trials. Br J Clin Pharmacol. 2023; 89(11):3273-3290. [7] De Simone G, Devereux RB, Daniels SR, Koren MJ, Meyer RA, Laragh JH. Effect of growth on variability of left ventricular mass: assessment of allometric signals in adults and children and their capacity to predict cardiovascular risk. J Am Coll Cardiol. 2015;25:1056–1062.
Reference: PAGE 33 (2025) Abstr 11607 [www.page-meeting.org/?abstract=11607]
Poster: Drug/Disease Modelling - Paediatrics