Lisinopril population pharmacokinetics in elderly and renal

Transcription

1 Br. J. clin. Pharmac. (1989), 27, Lisinopril population pharmacokinetics in elderly and renal disease patients with hypertension ALISON H. THOMSON', J. G. KELLY2 & B. WHITING' 'Clinical Pharmacokinetics Laboratory, Department of Materia Medica, Stobhill General Hospital, Glasgow G21 3UW and 2Institute of Biopharmaceutics Ltd, Monksland, Athlone, Ireland 1 The population pharmacokinetics of lisinopril were investigated using data collected from two multicentre trials of lisinopril in the treatment of hypertension in elderly patients (n = 40) and patients with renal disease (n = 20). 2 Lisinopril was started at doses of mg daily and increased at 2-4 weekly intervals as required for control of blood pressure. Steady-state concentration-time profiles were measured after at least 2 weeks at a constant dose. 3 All concentration-time data were analysed simultaneously using the program NONMEM and the influence of clinical factors on clearance/f and volume of distribution/ F was tested. 4 Clearance was significantly influenced by creatinine concentration, age, weight and cardiac failure. No clinical features tested were found to influence volume of distribution. 5 The influence of renal function and cardiac failure on lisinopril clearance has been confirmed using a population pharmacokinetic analysis technique. Keywords lisinopril population pharmacokinetics hypertension ACE inhibitor Introduction Inhibitors of angiotensin converting enzyme (ACE) are known to be effective in the treatment of hypertension and congestive cardiac failure and their use in the treatment of these conditions is likely to increase over the next few years. Lisinopril (MK 521) is a new ACE inhibitor which is structurally similar to enalapril but unlike enalapril, lisinopril can be administered orally without the requirement for hepatic conversion to the active form. Lisinopril inhibits plasma converting enzyme and reduces blood pressure in normotensives (Miller et al., 1982), hypertensive patients (van Schaik et al., 1987) and improves haemodynamic parameters in patients with cardiac failure (Dickstein et al., 1987). Early studies of the pharmacokinetics of lisinopril in healthy volunteers indicated that bioavailability is of the order of 29%. The drug is excreted solely by the kidneys, with no evidence of hepatic metabolism (Ulm et al., 1982). It is therefore likely that renal disease will have a significant influence on lisinopril disposition. Higher areas under the curve (AUC) and prolonged terminal half-lives have been observed in patients with renal disease (van Schaik et al;, 1987; Gibson et al., 1986; Kelly et al., 1987), but both van Schaik and Kelly found that significant effects only occurred when the creatinine clearance fell below ml min-'. Elevated serum concentrations have been observed in elderly patients, especially in the presence of cardiac failure, by Gautam et al. (1987), who found lisinopril clearance to be highly correlated with creatinine clearance. In this study, a preliminary analysis of the Correspondence: Dr A. H. Thomson, Clinical Pharmacokinetics Laboratory, Department of Materia Medica, Stobhill General Hospital, Glasgow G21 3UW 57

2 58 A. H. Thomson, J. G. Kelly & B. Whiting population pharmacokinetics of lisinopril (Thomson & Whiting, 1987) was expanded to include all data collected from two multicentre trials: lisinopril in the treatment of hypertension in the elderly and lisinopril in the treatment of hypertension associated with renal disease. Methods Protocols A brief summary of the protocols used in the two multicentre trials is presented below. All patients gave informed consent to participation in the study which was approved by the Research and Ethics Committees associated with each centre. Trial I Lisinopril in mild to moderate systolic/ diastolic hypertension or isolated systolic hypertension in the elderly. Patients aged 65 years or more entered the trial if they had a sitting diastolic blood pressure (BP) of 95 to 120 mm Hg or a systolic BP of > 160 mm Hg after a 2 week washout period. Patients with severe renal, hepatic, cardiac or other disease were excluded. Following the baseline washout, patients with creatinine clearances > 60 ml minm- were started on 10 mg lisinopril daily and patients with creatinine clearances of ml min-1 were started on 5 mg daily. If clinical control (diastolic BP < 90 mm Hg with a reduction of 10 mm Hg or systolic BP < 160 mm Hg with a reduction of 20 mm Hg or more) was not achieved at the end of 4 weeks, the dose was doubled to 20 mg and 10 mg respectively, then further doubled at 8 weeks if necessary. Provision was also made for early dose titration and the addition of a diuretic if clinically indicated. Multiple blood samples were withdrawn for lisinopril analysis after the first dose, trough levels were measured at the end of the 4th, 8th and 12th weeks and a steady state profile (samples at 0, 1, 2, 4, 6, 8 and 12 h) was determined after at least 2 weeks on a constant dose (usually the maximum or final dose). Lisinopril was analysed by radioimmunoassay (Hichens et al., 1981). Trial II Lisinopril in patients with hypertension associated with impaired renal function. This study was very similar to the elderly study, but the patients were classified into three groups as follows: Group 1 - patients with creatinine clearances of ml min-'; Group 2 - patients with creatinine clearances of < 30 ml min-1 and Group 3 - patients on haemodialysis. Patients in Group 1 started with a dose of 10 mg daily and patients in Groups 2 and 3 started with 5 mg daily. The BP entry and 'control' criteria were as above, but the patients were seen weekly for the first 2 weeks then every 2 weeks thereafter. If control was not achieved the dose was doubled at weeks 2, 4 and 6. Provision was again made for early titration or the addition of a diuretic if clinically indicated. Multiple blood samples were obtained for lisinopril analysis after the first dose then trough levels were measured at 1-2 weekly intervals during the study. A full steady-state profile (samples at 0, 1, 2, 4, 6, 8 and 12 h) was obtained after at least 2 weeks therapy at the final dose. Data set Data were available from a total of 140 patients of whom 89 took part in the elderly study and 51 took part in the renal study. Seventy-nine patients were excluded from the data analysis, however, for the following reasons: unreliable compliance (based on undetectable trough concentrations or trough concentrations which did not increase/decrease with dosage alterations); less than 2 weeks constant dosing prior to measurement of the 'steady state' profile; missing dosage history; missing sampling time; no concentrations or only a single concentration; missing biochemistry or demographic data. A further (elderly) patient who had unexpectedly high (tenfold) concentrations despite a relatively low dose (10 mg daily) and apparently normal renal function was also excluded after a preliminary investigation revealed that this patient was an outlier whose concentration data were confounding the analysis. The remaining group of 60 patients consisted of 40 from the elderly study and 20 from the renal study. Obviously some 'elderly' patients had renal impairment and some of the 'renal' group were over 65 years of age. The mean age was 65 years and the mean weight was 72 kg. The distributions of age, weight and serum creatinine are illustrated in Figure 1. Thirteen patients had (compensated) cardiac failure and one patient was receiving haemodialysis. Other drugs were avoided where possible, but some patients had diseases which required chronic treatment and many of the renal disease patients were receiving therapy to control disease other than hypertension. The major diseases and drugs used are detailed in Table 1. Twenty-two patients (37%) received no other drugs during the lisinopril study period. The dose of lisinopril at the time of the 'steady state' profile ranged from 2.5 to 40 mg daily

3 a 30 Lisinopril population pharmacokinetics A I b _ = 101. Cr0*E : R t W Age (years) on I000 Weight (kg) Creatinine (PmoI 1-1) Figure 1 Distributions of (a) age, (b) weight and (c) serum creatinine in patient population. Table 1 List of other drugs and diseases Disease Drugs used Number ofpatients Arthritis/arthrosis Paracetamol/Nonsteroidal antiinflammatory drugs 7 Parkinson's disease Levodopa/carbidopa 1 Hvpothyroidism Thyroxine 2 Diabetes Oral hypoglycaemic Insulin 5 1 Heart failure/ atrial fibrillation Cardiac glycoside 17 Hyperlipidaemia Benzafibrate/clofibrate 4 Ischaemic heart disease Nitrates Frusemide 5 1 Chronic obstructive Theophylline 3 airways disease Terfenadine 1 Budesonide 1 Renal disease Allopurinol 4 Aluminium hydroxide 3 Calcium carbonate 2 Frusemide 2 Dihydrotachysterol 1 Methionine 1 Epilepsy Sodium valproate Phenytoin 1 1 Other drugs Benzodiazepines 2 Dipyridamole 2 Ranitidine 1

4 60 A. H. Thomson, J. G. Kelly & B. Whiting a 0 S a 40r- lkb _ Dos Dose (mg). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~..... _ U2 250"' 300 " Concentration (ng ml-') Figure 2 Distributions of (a) lisinopril dose and (b) steady state peak concentration. (median 10 mg daily) and the peak concentration achieved ranged from 6.4 to 343 ng ml[1. Distributions of dose and peak concentrations are shown in Figure 2. A total of 381 concentration measurements was used in the data analysis (an average of six per subject). Data analysis All concentration-time data from all subjects were fitted simultaneously using the non-linear regression program NONMEM (Beal & Sheiner, 1979). Steady state one-compartment open models with first-order and zero-order absorption were fitted to the data. The parameters of these structural models were: clearance/bioavailability (CL/F), volume of distribution/ bioavailability (V/F) and either absorption rate constant (ka) or duration of zero-order input (Ti). The influence of age, body surface area, creatinine concentration, weight, alkaline phosphatase, cardiac failure, cardiac glycoside, sex and estimated creatinine clearance (Jelliffe et al., 1972) were tested on clearance, and age, body surface area, creatinine concentration and weight were tested on volume of distribution according to the following two general models: Pk = x Fac x FaC on XFacn (1) Pk=01 xfac1o2xfac203x... x Facn en (2) where Pk represents the relevant structural model parameter, (CL/F, VIF), Facn represents the clinical characteristic under investigation and each 0 represents a proportionality constant or power parameter relating the clinical characteristic to the Pk. Hierarchical models were compared by the chi-squared test (P < 0.01) of the difference between the log likelihood values obtained from fitting the full or reduced models (Sheiner et al., 1977). Non-hierarchical models were assessed by direct comparison of the log likelihood values and by visual examination of residual plots for abnormal trends. Intersubject variability in the pharmacokinetic parameters was assumed to correspond to a log-additive model, i.e. ln (Pk) = ln (Pk) + Pkij (3) where nqpkij represents the random fluctuations in the j-th individual at time t, of the log of the individual parameters (Pkj) from the population mean parameters (Pk). The.jPki are assumed to be independent and normally distributed with mean zero and variance wpk. A log-additive error model was also used to describe the residual error (e) between the predicted and observed concentrations, i.e. (4) where -jj are normally distributed with mean zero and variance ac2. This assumes that the error between Cij and Cij increases in proportion to the measured concentration. Results In (Cij) = In (eij) + f-ij The two input functions were compared using the simplest model (CL/F = 01, V = 02). First order input appeared to be the more appropriate function based on the log likelihood value (Table 2) and the observation that the standard errors of the estimates were unobtainable when the zero-order input model was used. A number of clinical characteristics were tested for their influence on lisinopril clearance: the most important factors were the serum creatinine concentration and estimated creatinine clearance. Both linear and non-linear clearance models were investigated: a better fit was obtained with the non-linear model for creatinine and a linear model for creatinine clearance. The combination of creatinine concentration and

5 Table 2 List of models tested and log likelihood difference Lisinopril population pharmacokinetics 61 (i) Clearance models Model c.f. LLD P 1. CL= CL = 01 x Cr < CL = X CrCL < CL = 01 x wt x Cr < CL = 01 X wt -04 X Cr < CL= 01 x wt04 x CrO5 4 0 NS 7. CL = 01 x wt x Cr64 x AgeO < CL= 01 x BSA x Cr04 x AgeO NA 9. CL= O1 x wt x CrO4 x AgeO5 x AlkO NS 10. CL = [01 x wt x Cr04 x AgeOs] x 06 (fem) 7-41 NS 11. CL = [01 x wt x Cr04 x AgeOs] x 06 (chf) 7 24 < CL = [01 x wt x Cre4 x Age5s] x 06 (cag) 7 15 < (ii) Volume models Model c.f. LLD P 13. V= V= 02 X wt 13 1 NA 15. V= 02 x BSA 13 1 NA 16. V= 02 Xwt NS 17. V= 02 X Cr NS 18. V= 02 x Age NS (iii) Absorption models Model c.f. LLD P 19. ka = Ti = NA Key: CL = clearance (I h-1), Cr = creatinine concentration (p.mol r1)/o, Age = age/65, alk alkaline phosphatase (iu [-1)/123, BSA = body surface area (m2)/1.7, chf = cardiac failure, cag = cardiac glycoside, crcl = estimated creatinine'clearance, fem = female, ka = absorption rate constant, NA = not appropriate, NS = not significant, Ti = duration of zero-order input, V = volume of distribution, wt = weight (kg). weight was superior to estimated creatinine clearance (Table 2). Other factors such as sex, body surface area, alkaline phosphatase concentration, cardiac failure, cardiac glycoside therapy and age were also tested, but only age and cardiac failure or cardiac glycoside therapy produced significant improvements in the model fit. These results are summarised in Table 2 (i). Volume of distribution was modelled as a linear function of weight or body surface area but neither had an identifiable effect (Table 2(ii)). Similarly, power models incorporating weight, creatinine or age offered no advantage over the simpler model. Estimates of the parameters of the most appropriate model (models 11, 13 and 19) are presented in Table 3 together with their inter-subject and residual variabilities (expressed as coefficients of variation). The coefficient of variation of clearance/f was reduced from 82% with the simplest model (model 1) to 65% with the addition of creatinine concentration, and 52% with the full model. However, the coefficient of variation of volume of distribution remained high (over 100%) with all models. The intersubject variability associated with ka improved with the more complex clearance models from 213% (model 1) to 73% (model 11). Residual variability was around 20-35% when first order input was used, but it was 49% with zero-order absorption, suggesting model misspecification. Using the parameter estimates from models 11, 13 and 19, a general equation for estimating clearance/f can be defined, i.e., CL/F = 0.25 x wt (kg) x (creatinine/70)-089 x (age/65) -041 CL/F = CL/F x 0.65 (if patient has cardiac failure) (5) By substituting values of weight, creatinine concentration and age into this equation, the likely influence of these factors can be examined

6 62 A. H. Thomson, J. G. Kelly & B. Whiting Table 3 Parameter estimates (s.e.) and variability from NONMEM. Analysis of lisinopril data (i) Parameter estimates (0.029) (3.9) (0.006) (0.108) (0.172) (0.112) (ii) Variability estimates Clearance Volume ka Interindividual variability (0.059) 1.61 (0.52) (0.198) Residual variability (0.0184) The interindividual variability estimates correspond to coefficients of variation as follows: clearance 52%, volume 127%, ka 73% and residual variability 28%. 2E a LL 2t 1' 5 a) 0 C 1(c 0. a)._a b 30r U- '6 20 C (a 10 0CL._4 ri ( I - W... -.A- I... JIL.. I]....L.LL.LL.L.J Creatinine concentration (,umol/l) 3C I l Il IIlI,... AL l l l ll v Weight (kg) U- ' 20 c a) m._0 *Q10 CL c I... I * v en Age (years) Figure 3 Profile of clearance/f estimates based on average population parameter estimates for patients with (---) and without (-) cardiac failure. (a) Patients aged 65 years weighing 70 kg with varying creatinine concentrations. (b) Patients aged 65 years with creatinine 70,umol l-l and varying weights. (c) Patients weighing 70 kg with creatinine 70 gj.mol [-' and varying ages. J

7 Lisinopril population pharmacokinetics 63 Table 4 Adverse effects Patient Creatinine Dose C,,,ax number (ixmol 1-1) (mg) (ng ml-) Adverse effect rash * postural hypotension hyperkalaemia hyperkalaemia increased serum creatinine/potassium * dizziness angioneurotic oedema gastrointestinal disturbance/taste alteration dizziness/drowsiness increased creatinine/urate rash * dose reduced and no adverse effects at time of profile visually. Figure 3 shows the pattern of clearance associated with declining renal function, increasing age and increasing weight in two groups of patients: those with and without cardiac failure. Adverse effects were more common in patients with renal dysfunction, but there was no obvious relationship with lisinopril concentration. Maximum concentrations of ng ml-' were tolerated by some patients without side effects. A list of adverse effects in individual patients together with maximum steady state concentration is shown in Table 4. Discussion The pharmacokinetics of lisinopril have been investigated in a population of patients with hypertension and the analysis has confirmed the relationship between lisinopril disposition and renal function (based on creatinine concentration). Other factors which influence renal function are weight and age: it is therefore not surprising that these factors also have an effect on lisinopril clearance. However, there was no identifiable difference between lisinopril clearance in males and females. The relationship between creatinine concentration and lisinopril clearance is non-linear, which again mimics the relationship between creatinine concentration and renal function (Jelliffe et al., 1972). However, use of the patient's individual creatinine, age and weight measurements were superior to using creatinine clearance values estimated from a nomogram. Other workers have observed that a significant increase in area under the curve only occurs if the creatinine clearance is less than 30 ml min-1 (Kelly etal., 1987; van Schaik et al., 1987). There were, however, no patients with creatinine clearances between 25 and 50 ml min-' in Kelly's study, there were only six patients with 'moderate' renal failure (defined as a creatinine clearance of between 30 and 80 ml min-) in the study by van Schaik et al. (1987) and only two of these patients had creatinine clearances below 45 ml min-'. It is therefore unlikely that these studies had sufficient data to identify the influence of creatinine clearance in the range 25 and 50 ml min-'. Cardiac failure had a significant effect on lisinopril disposition, although all patients were apparently adequately treated and symptom free at the time of the study. Clearance was reduced by a factor of 0.65 which is remarkably similar to the reduction in clearance observed by Gautam et al. (1987) who estimated lisinopril clearance to be 12.2 ml min-' in elderly patients with chronic cardiac failure stabilised on diuretics compared to 20.8 ml min-' in healthy elderly subjects. All of the patients with cardiac failure were receiving a cardiac glycoside and it could be postulated that a drug interaction may have affected the clearance. However, when all patients receiving a cardiac glycoside were tested, the log likelihood difference was less than for cardiac failure. This suggests that the disease, not the drug, was responsible for the effect. Although actual body weight was used in the analysis, ideal body weight or lean body mass may act as more appropriate indicators of drug clearance. However, in a preliminary analysis of a reduced data set, we found that there was no improvement in the fit when ideal body weight was used (Thomson & Whiting, 1987). This may reflect the relatively few (4) obese patients included in the analysis and extrapolation of the

8 64 A. H. Thomson, J. G. Kelly & B. Whiting linear weight-clearance relationship above 90 kg would be unwise. It is unlikely that obesity per se would lead to an increase in clearance. Similarly, although a non-linear relationship was identified between clearance/f and age, extrapolation to patients younger than 40 years would be unwise because there were only two (renal disease) patients under 40 and the apparent increase in clearance may be confounded by differences in bioavailability (or compliance). Even when clinical factors are taken into account, the variability of lisinopril clearance/f is still very large (52%), suggesting that other clinical factors (not investigated in this analysis) may be important. Alternatively, it may reflect large fluctuations in bioavailability or compliance, because in a longterm study such as this, it is very difficult to ensure that compliance remains consistent throughout. Multiple trough levels were taken during the course of the study and patients were excluded if excessive variability or 'zero' concentrations were observed, but in many cases trough data were missing and it was then impossible to distinguish between 'expected' and 'unexpected' variability. It is likely therefore that compliance was a major confounding factor in the analysis. Alternatively, the variability may have been related to other drugs which many of the patients were taking, but there were insufficient data to identify the influence of potential drug interactions. The variability in volume of distribution could not be established from this study reflecting the lack of information about this parameter in this steadystate data set. In a more restricted, single-dose study of lisinopril pharmacokinetics in 19 young normotensive males by Ajayi et al. (1985), the mean estimate of clearance/f was 15 1 h'1. If an age of 40 years, a weight 70 kg and a creatinine concentration of 70,umol 1-l are substituted into the population equation obtained in this analysis (without cardiac failure), the estimate of clearance/f is h-1 which is similar to the results obtained by Ajayi et al. (1985). It has been observed with other ACE inhibitors that a prolonged terminal phase occurs after a single dose or on discontinuation of therapy after multiple dosing. Till et al. (1984) suggested that this may represent binding of a fixed amount of drug to ACE and that it does not influence drug accumulation. Francis et al. (1987) investigated this phenomenon in more detail with another ACE inhibitor, cilazapril, and concluded that this binding would be achieved by approximately 313 nmol of drug (or 0.13 mg). In the present study, it was assumed that this binding would have little, if any, influence on the steady state pharmacokinetics of lisinopril, and was therefore ignored. Indeed, if lisinopril plasma ACE binding is similar to that of cilazapril, the total binding would also be accounted for by about 0.13 mg - an insignificant amount compared with steady state doses of 2.5 to 40 mg daily. It is therefore unlikely that the influence of ACE binding would seriously confound interpretation of the results obtained here. In conclusion, pharmacokinetic data from a study of the use of lisinopril in patients with hypertension has been analysed using a population approach. This method identified clinical factors which significantly influenced the disposition of the drug, but emphasised the need for adequate and appropriate data collection especially in small subgroups of patients. With the small numbers concerned, the influence of features such as obesity and other drug therapy could not be identified, but the analysis clearly revealed the relationship between lisinopril disposition and renal function. Moreover, it was clear that even compensated heart failure reduced lisinopril clearance by about 35%. The clinical significance of these findings in terms of dosage adjustment in disease is difficult to determine because a 'therapeutic range' for lisinopril has not yet been established. The incidence of side effects was greater in patients with renal disease who also had higher levels, but a simple relationship between the serum concentration and these effects was not apparent. High concentrations were sometimes tolerated without adverse effects and relatively low levels were associated with adverse effects in some patients. We are grateful to Dr David Glover, Merck, Sharpe and Dohme, Hoddesdon, Hertfordshire, England and Dr Hector Gomez, Merck, Sharpe and Dohme, Rahway, New Jersey, USA for providing the data and for financial assistance. References Ajayi, A. A., Campbell, B. C., Kelman, A. W., Howie, C., Meredith, P. A. & Reid, J. L. (1985). Pharmacodynamics and population pharmacokinetics of enalapril and lisinopril. Int. J. clin. Pharm. Res., 5, Beal, S. L. & Sheiner, L. B. (1979). NONMEM (User's Guide) Parts I and VI. Technical Report, Division of Clinical Pharmacology, University of California, San Francisco. Dickstein, K., Aarsland, T., Tjelta, K., Cirillo, V. J.

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