Population modeling approach of circadian blood pressure variations using ambulatory monitoring in dippers and non dippers
Dehez, Marion(1)(2)(3), Marylore Chenel(1), Roeline Jochemsen(1), Stéphanie Ragot(2)
(1)Servier Research Group, 6 Place des Pléiades, 92415 Courbevoie cedex, France;(2)Faculté de Médecine Pharmacie, 34 rue du Jardin des Plantes, 86021 Poitiers cedex, France;(3)3EA3809, Faculté de Médecine Pharmacie, 34 rue du Jardin des Plantes, 86021 Poitiers cedex, France
Introduction : In most patients with essential hypertension, blood pressure (BP) decreases by 10% to 30% at night compared with daytime values. Nevertheless, in about 30% of the hypertensive population, patients termed "non dipper" present a blunted night time decrease in BP. These patients are particularly at risk regarding target organ disease and even prognosis. Ambulatory Blood Pressure Measurements (ABPM), a non invasive method carried over 24 hours, allows to detect non dipper patients.
Usually, determining the non dipper status is based on the differences between day and night time mean ABPM values and not using the whole ABPM information. Thus the aim of the present work was to build population 24-hours ABPM models in dipper and non dipper patients in order to estimate model parameters of their 24-hours BP profiles in both populations.
Materials and methods : BP measurements were recorded every 15 minutes over 24 hours after a 4 weeks run-in phase of a large randomized study in 1004 mild to moderate essential hypertensives aged from 30 to 80 years.
The data were split into dipper and non dipper datasets for both systolic and diastolic blood pressure according to the following definition of the dipper status : reduction in average blood pressure at night greater or equal to 10% compared to average daytime values.
2 cosine functions are commonly used to model BP circadian variations, however different cosine and polynomials structural models and various random effects models were tested to describe the circadian rhythm using NONMEM. The 4 datasets were fitted separately using the FOCE method. The model building and selection were performed using usual methods ( objective function, goodness of fits, standard error of estimation).
Results : In dipper patients, 24-hours ABPM means were 86.7± 17 mmHg and 140± 22.1 mmHg for diastolic (N=820) and systolic (N=649) blood pressures, respectively. In non dipper patients 24 hours ABPM means were 87± 15.3 mmHg and 144.3± 21 mmHg for diastolic (N=184) and systolic (N=355) blood pressures respectively.
For systolic as well as diastolic BP, dipper and non dipper profiles were both fitted by a 3 cosine model with interindividual variability in mesor, amplitudes and lag times, using an additive error model. Whereas the population mesor estimates were slightly different within population, the amplitude of the first cosine term and the second cosine term decreased 3 fold and 2 fold respectively in the non dipper population. The third cosine terms and lag times were unchanged.
Conclusion : Although 24-hours ABPM models were the same in both populations, parameters estimates such as the amplitudes of the two first cosine terms were much lower in the non dipper population. This population modeling approach permitted to quantify profile differences between dippers and non dippers. A next step will be the use of a mixture model in order to fit simultaneously both populations and improve the identification of dippers and non dippers.
References :
[1] Beal SL, Sheiner LB. NONMEM users guides. San Francisco : NONMEM Project Group, University of California;1992.
[2] Hempel G, Karlsson MO, De Alwis DP, Toublanc N, McNay J, Schaefer HG. Population pharmacokinetic-pharmacodynamic modeling of moxonidine using 24-hour ambulatory blood pressure measurements.
[3] O’Brien E, Sheridan J, O’Malley K. Dippers and non-dippers. Lancet 1988;2:397.
[4] Okhubo T et al. Relation between nocturnal decline in blood pressure and mortality. The Ohasama study. Am J Hypertens1997;10: 1201-1207.
[5] Ragot S, Herpin D, Siché JP, Poncelet P, Mallion JM. Relationship between short-term and long-term blood pressure variabilities in essential hypertensives. J Hum Hypertens 2001;15:41-48.
[6] Verdecchia P et al. Ambulatory blood pressure. An independent predictor of prognosis in essential hypertension. Hypertension 1994;24: 793-801.