Blanka Koristkova

Differences between prescribed daily doses and defined daily doses of antiepileptics--therapeutic drug monitoring as a marker of the quality of the treatment.

OBJECTIVE Prescribed daily doses (PDDs) of antiepileptics (N03A ATC group) were recorded for drugs used in monotherapy or in combination therapy in the University Hospital in Ostrava, Czechia. Plasma levels were used as an indicator of the quality of treatment. METHOD Request and reply forms for therapeutic drug monitoring (TDM) were used as a source of PDDs and plasma levels. The study included 1,144 in-patients examined in the period 1993 - 2004. The differences in PDD were tested by Mann-Whitney-U-test. ATC/DDD index 2005 was used. Doses given in mono- and polytherapy were compared. RESULTS Median PDDs in samples within the therapeutic range (in mg) in mono-/polytherapy were as follows (DDDs in parenthesis): carbamazepine 600/800 (1,000), clonazepam 2.0/2.0 (8), phenytoin 300/300 (300), ethosuximide -/1000 (1,250), lamotrigine 250/200 (300), phenobarbital -/200 (100), primidone 500/625 (1,250), topiramate -/300 (300), valproic acid 750/1,000 (1,500). Median PDDs in polytherapy with antiepileptics not analyzed for TDM were: gabapentin 900 (1,800), levetiracetam 1,500 (1,500), vigabatrin 1,500 (2,000). CONCLUSIONS PDDs in monotherapy were similar or slightly lower than in combination therapy with an exception for lamotrigine, NS. The differences were significant in carbamazepine, p < 0.0001, and valproic acid, p < 0.001. Patients with plasma levels within the therapeutic range were usually treated with similar or slightly higher doses than the remainder. In polytherapy the PDDs were similar to DDDs in carbamazepine, ethosuximide, phenytoin, and topiramate in samples within the therapeutic range when difference +/- 20 per cent was considered as acceptable PDD of levetiracetam was also similar to actual DDD. In general plasma levels tended to be below the therapeutic range. The differences between PDD and DDD of antiepileptics have to be taken into account especially when utilization of different drugs is compared.

The use of TDM data to assess the validity of defined daily doses of antiepileptics: a comparison between a Czech and Swedish University Hospital.

Prescribed daily doses (PDDs) of antiepileptic drugs (AED) (N03A ATC group) were recorded for drugs used in monotherapy or in combination therapy in the University Hospitals in Ostrava, Czech Republic and Huddinge, Sweden. Plasma concentrations were used as an indicator of the quality of treatment. PDDs were compared with the defined daily doses (DDDs) suggested by WHO in the ATC/DDD index 2005. Request and reply forms for therapeutic drug monitoring (TDM) were used as a source of mean PDDs. The study included 2,824 adult out- and in-patients in Huddinge treated from 1995 to 1999 and 1,268 out-patients treated in Ostrava from 1993 to 2004. The differences in PDD were tested by Students t-test. Mean values of PDD were used when patients were examined more than once. Doses given in mono- and polytherapy were compared. Mean PDDs (in mg) in mono-/polytherapy in Huddinge and Ostrava were as follows (DDDs in parenthesis): carbamazepine 588/842 and 618/770 (1000), clonazepam 3.0/2.5 and 3.4/2.4 (8), phenytoin 278/314 and 291/288 (300), gabapentin -/1533 and -/921 (1800), lamotrigine 228/228 and 216/195 (300), phenobarbital 90/75 and 183/117 (100), vigabatrin -/1794 and -/1259 (2000), valproic acid 1139/1476 and 814/950 (1500). The PDDs of most of the AEDs were lower than the DDDs with the exceptions for valproic acid (Huddinge, in polytherapy only), phenytoin, for which PDDs and DDDs were very close, and phenobarbital for which they were similar in Huddinge but higher in Ostrava. PDDs in monotherapy were only slightly lower than in combination therapy. Patients with plasma concentrations within the therapeutic range were usually treated with slightly higher doses than the remainder. In general, plasma concentrations tended to be in the low therapeutic range. The differences in PDDs between hospitals were significant in the case of valproic acid (P < 0.001), phenobarbital (except monotherapy within), vigabatrin, and gabapentin (P < 0.01), and carbamazepine (in monotherapy P < 0.05, polytherapy P < 0.01). Our data suggest that the DDDs of AEDs should be reconsidered as, in the majority of cases, they appear to be too high.

Therapeutic monitoring of antiepileptic drugs: a comparison between a Czech and a Swedish University Hospital.

Plasma concentrations obtained during routine therapeutic monitoring of antiepileptic drugs (AED) (N03A ATC group) were compared in patients treated with one or several AED in the University Hospitals in Ostrava, Czech Republic and Huddinge, Sweden. Request and reply forms for therapeutic drug monitoring (TDM) were used as a source of mean plasma concentrations (PC). The study included 2,824 adult out- and inpatients in Huddinge treated from 1995 to 1999 and 1,268 outpatients treated in Ostrava from 1993 to 2004. PC of valproic acid in Huddinge and all AED except clonazepam in Ostrava were analyzed with gas-liquid chromatography. Plasma concentrations of clonazepam in Ostrava and all AED except valproic acid in Huddinge were analyzed by HPLC. The differences in PC were tested by Students t-test. χ2 method was used for the differences in the distribution of PC relative to the therapeutic window. The mean plasma concentrations generally reached the apparent therapeutic ranges but were below the range in the cases of phenytoin monotherapy in both hospitals, and clonazepam, phenobarbital and phenytoin in polytherapy in Ostrava. In monotherapy 33% of the analyses showed sub-therapeutic concentrations in Huddinge, compared to 38% in Ostrava. Eight percent of the analyses showed potentially toxic concentrations in Huddinge, but only 3% in Ostrava. The highest number of sub-therapeutic concentrations was detected for phenytoin in both hospitals: 59% in Huddinge, 78% in Ostrava. In polytherapy only slight differences between the hospitals were found. PC/dose ratios were significantly lower in polytherapy than in monotherapy for carbamazepine and valproic acid in both hospitals. In contrast a higher PC/dose ratio was found in polytherapy for phenytoin in both cohorts and for lamotrigine in Ostrava. Drug treatment of epilepsy in our two hospitals is surprisingly similar in terms of achieved plasma concentrations, in spite of socioeconomic and cultural differences between our two countries. This may be explained by the long experience with TDM in both hospitals, which has the inherent capacity to promote evidence based drug therapy.

Significant discrepancy in cyclosporin A post-dose concentrations when analyzed with specific RIA and HPLC method.

C(2) or AUC sparse sampling methods are widely recommended for therapeutic monitoring of cyclosporin A (CsA). One additional reason for promoting the C(2) sampling time in place of commonly used C(0) is that the C(2) level may actually provide more accurate measurement of parent drug concentration by immunoassays, as lower portion of metabolites has been formed 2 hours post-dose than at the steady-state trough time point. HPLC and RIA whole blood levels of CsA and its main metabolites AM1, AM9 and AM4N were compared during 12 hours profile after chronic administration. 40 stable renal transplant male patients (age 49 +/- 6 years, body weight 76 +/- 7 kg) were treated with CsA (Sandimmun Neoral, Novartis s.r.o, Prague, Czech Republic) in doses 198 +/- 56 mg twice daily. Samples were collected in steady state (after 2 weeks of regular treatment regimen) as follows: pre-dose, 0.5, 1, 1.5, 2, 3, 5, 8 and 12 hours after dose. CsA concentrations were determined both specific RIA assay (Cyclo-Trac SP Whole, Dia Sorin) and HPLC method, where concentrations of metabolites AM1, AM9 and AM4N were simultaneously analyzed. The AUC(0-12) was calculated by the linear trapezoidal rule. The percentage prediction error defined as [(RIA value-HPLC value)/HPLC value] x 100 was used for estimation of differences. C(max), t(max), and C(avg) were compared using Students t-test. RIA produced significantly higher CsA levels than HPLC method in the period of 0.5 - 5 hours after application. The greatest differences (43 - 56%) occurred between 1 and 3 hours after dose. AUC(0-12), C(max) a C(avg) calculated from RIA results were consequently significantly higher. Only t(max) remained unchanged. The ratio of metabolites/parent drug after CsA intake is decreasing but their absolute concentrations are significantly increasing. Mean levels at C(0)/C(2) were CsA-RIA 82/612, CsA-HPLC 89/425, AM1 121/179, AM9 4.1/81.4, AM4N 9.5/21.0 ng/ml. TDM using C(2) and AUC sparse sampling may cause misleading interpretation using both methods alternately for the same patient.

Validation of Sparse Sampling Strategies to Estimate Cyclosporine A Area Under the Concentration-Time Curve Using Either a Specific Radioimmunoassay or High-Performance Liquid Chromography Method

Introduction: Area under the concentration-time curve (AUC) has been advocated as a better parameter to monitor cyclosporine A than trough concentrations. Up to now, more than 100 equations to estimate AUC using a limited sampling strategy have been published, but not all have been validated. Material and Methods: Eight equations for AUC0-12h and two for AUC0-8h were validated. Concentrations of cyclosporine A were analyzed by high-performance liquid chromatography (HPLC) and a specific radioimmunoassay (RIA) method. Forty male renal transplant patients were included in the study. Blood samples were taken predose and at 0.5, 1, 1.5, 2, 3, 5, 8, and 12 hours after the morning dose when the patient was in steady state. The percentage prediction error (%pe) was used for an assessment of the performance of the equations. Mean %pe less than ±15% and absolute %pe less than 30% in 95% of predictions were considered to be acceptable. Other possibilities such as %pe less than 25%, 20%, and 15% were also tested. Results: Eight equations for AUC0-12h met the requirements using both assays, six in the HPLC set only and four in the RIA set only. The highest precision was obtained with AUC0-12h = 123.792 + 1.165*C1h + 3.021*C3h + 7.33*C8h proposed by de Mattos et al. The mean %pe was 1% ± 8% (-16 to 19) for HPLC (values given as mean ± standard deviation [range]) and -1 ± 5 (-17 to 10) for RIA. Mean absolute %pe was 7 ± 5 (0.0 to 19) for HPLC and 4 ± 4 (0.0 to 17) for RIA. For clinical use, the most suitable equation was AUC0-12h = 363.078 + 8.77*C1h + 3.07*C3h proposed by Wacke et al, which produced the second lowest %pe and used two sampling points in the period of 1 to 3 hours after dose. The mean %pe was -7 ± 10 (-25 to 25) for HPLC and 2.3 ± 6 (-10 to 17) for RIA. Mean absolute %pe was 10 ± 7 (0.4 to 25) for HPLC and 5 ± 4 (0.0 to 17) for RIA. The equation: AUC0-8h = 55.37 + 2.89*C0h + 1.08*C1h0.9*C2h + 2.23*C3h proposed by Foradori et al met the criteria with 95% of prediction with absolute %pe less than 15% in the HPLC set and 10% in the RIA set. Conclusion: The validation of equations is of major importance for prediction precision, whereas the analytical method for limited sampling strategy proposals had no influence. Because of the wide interassay variability, it is also important to know which analytical method was used for AUC calculation when interpreting the results.

Cyclosporine A area-under-time-concentration-curve in rheumatologic patients after the first dose. Which of the sparse sampling strategies will predict the best?

OBJECTIVE The aim of the present study was to validate the limited sampling strategies (LSS:s) for prediction of AUC of cyclosporine A (CsA) after the first dose in rheumatologic patients. METHODS 22 patients suffering from rheumathoid arthritis, systemic lupus erythematodus, ankylosing spondylitis dermato(poly)myositis or seronegative spondylarthritis were treated with Neoral® (female/male: 11/3, mean ± SD: age 49 ± 14 y, body weight 75 ± 12 kg, height 166 ± 7 cm, dose 71 ± 25 mg, dose per kg 1.0 ± 0.3 mg/kg), or Consupren® (7/1, 78 ± 36, 175 ± 8, 82 ± 22, 1.1 ± 0.3). Two patients whose C12h were missing were excluded from the AUC0-12 calculation. Whole blood levels of CsA were analyzed with HPLC. Blood samples were collected at 0, 0.5, 1, 1.5, 2, 3, 4, 6, 8, and 12 hours after taking the first dose. Altogether 115 LSS:s obtained from the literature were validated. A linear trapezoidal rule was used as a reference method. Mean percentage prediction error (%PE) < ± 15% and maximal one value of absolute %PE > 30% were considered to be acceptable. The root mean squared error (RMSE) was evaluated for equations that passed the criteria. RESULTS The best performance with all values of the absolute %PE < 30% was found in three LSS:s for AUC0-12 and two for AUC0-8: AUC0-12 = 123.792 + 1.165 × C1h + 3.021 × C3h + 7.33 × C8h; 97.6 + 1.27 × C1h + 3.14 × C3h + 4.06 × C6h; or 124.3 + 1.34 × C1h - 0.16 × C2h + 3.27 × C3h + 3.96 × C6h; AUC0-8 = -19.8 + 1.99 × C2h + 2.38 × C4h + 3.15 × C6h or -22.4 + 2.51 × C2h + 5.49 × C6h. Validation criteria were further fulfilled in AUC0-12 = 24 + 3.66 × C0h + 2.11 × C1.5h + 4.54 × C4h or 0.2 + 2 × C2h + 10.2 × C6h; AUC0-8 = 55.37 + 2.89 × C0h + 1.08 × C1 + 0.9 × C2h + 2.23 × C3h; and AUC0-4 = -41 + 1.17 × C1h + 1.85 × C2h. Only one equation proposed for AUC0-6 did not pass the validation criteria. CONCLUSIONS Equations validated for prediction of AUC0-12, AUC0-8 and AUC0-4 might be used for LSS:s of CsA independently of the length of treatment, indication, dosage or galenic formulation.