Mikko Kuoppamäki
email: mikko.kuoppamaki@orionpharma.com

Kirsi Korpela

Reijo Marttila

Valtteri Kaasinen

Päivi Hartikainen

Jukka Lyytinen

Seppo Kaakkola

Jutta Hänninen

Eliisa Löyttyniemi

Marita Kailajärvi

Päivi Ruokoniemi

Juha Ellmén

Comparison of pharmacokinetic profile of levodopa throughout the day between levodopa/carbidopa/entacapone and levodopa/carbidopa when administered

Keywords: Pharmacokinetics, Levodopa, Carbidopa, Entacapone, Parkinson's disease

Introduction

The motor symptoms of Parkinson's disease (PD) are mainly due to the loss of dopaminergic innervation of the striatum. Therefore, the most successful treatment strategies are those that replenish striatal dopamine levels or mimic the action of dopamine.

Levodopa is still the most effective treatment for the symptoms of PD. Levodopa is metabolized mainly by two enzymes, dopa decarboxylase (DDC) and catechol O-methyltransferase (COMT). Levodopa is nowadays always combined with a DDC inhibitor (DDCI; carbidopa or benserazide), which improves the delivery of levodopa to the brain. However, blocking DDC shifts the peripheral metabolism of levodopa towards COMT, with O-methylation becoming the prominent metabolic pathway [START_REF] Männistö | New selective COMT inhibitors: useful adjuncts for Parkinson's disease[END_REF]. Therefore, oral levodopa therapy can be further improved by COMT-inhibitors.

Entacapone is a selective, reversible, peripherally acting COMT-inhibitor [START_REF] Keränen | The effect of catechol-O-methyltransferase inhibition by entacapone on the pharmacokinetics and metabolism of levodopa in healthy 48 volunteers[END_REF]. The pharmacokinetic (PK) profiles of entacapone and levodopa are comparable and the time course of COMT inhibition by entacapone also follows the plasma-concentration-time curve (AUC) of entacapone [START_REF] Keränen | The effect of catechol-O-methyltransferase inhibition by entacapone on the pharmacokinetics and metabolism of levodopa in healthy 48 volunteers[END_REF]. Therefore, entacapone is always taken together with each dose of levodopa/DDCI. Tolcapone is another clinically available COMT-inhibitor [START_REF] Dingemanse | Integrated pharmacokinetics and pharmacodynamics of the novel catechol-O-methyltransferase inhibitor tolcapone during first administration to humans[END_REF] that is taken three times daily (t.i.d) regardless of the dosing frequency of levodopa/ DDCI. Oral levodopa therapy with levodopa/DDCI and entacapone or tolcapone is associated with an improved levodopa plasma profile (increased AUC and elimination half-life) and prolonged therapeutic response in patients with PD [START_REF] Müller | Pharmacokinetic behaviour of levodopa and 3-O-methyldopa after repeat administration of levodopa/carbidopa with and without entacapone in patients with Parkinson's disease[END_REF][START_REF] Nutt | Effect of peripheral catechol-O-methyltransferase inhibition on the pharmacokinetics and pharmacodynamics of levodopa in parkinsonian patients[END_REF][START_REF] Davis | Acute effects of COMT inhibition on L-DOPA pharmacokinetics in patients treated with carbidopa and selegiline[END_REF]. This improved pharmacokinetic profile of levodopa has been shown to translate into decreased "offtime" and increased "on-time" in PD patients with wearingoff symptoms [START_REF] Study | Entacapone improves motor fluctuations in levodopa-treated Parkinson's disease patients. Parkinson Study Group[END_REF][START_REF] Rinne | Entacapone enhances the response to levodopa in parkinsonian patients with motor fluctuations[END_REF][START_REF] Kurth | Tolcapone improves motor function and reduces levodopa requirement in patients with Parkinson's disease experiencing motor fluctuations: a multicenter, double-blind, randomized, placebo-controlled trial. Tolcapone Fluctuator Study Group I[END_REF][START_REF] Baas | Catechol-Omethyltransferase inhibition with tolcapone reduces the "wearing off" phenomenon and levodopa requirements in fluctuating parkinsonian patients[END_REF]. Both COMT-inhibitors also improve levodopa's effects in the symptomatic treatment of early PD patients [START_REF] Waters | Tolcapone in stable Parkinson's disease: efficacy and safety of long-term treatment. The Tolcapone Stable Study Group[END_REF][START_REF] Hauser | Double-blind trial of levodopa/carbidopa/entacapone versus levodopa/carbidopa in early Parkinson's disease[END_REF].

The current concept of continuous dopaminergic stimulation (CDS) suggests that a more stable plasma concentration of a given dopaminergic drug will result in a prolonged response to treatment. Additionally, it has been postulated that pulsatile stimulation of striatal post-synaptic dopamine receptors may lead to a series of molecular and physiological changes that are thought to underlie the development of motor complications, such as dyskinesia and wearing-off [START_REF] Olanow | Continuous dopaminereceptor treatment of Parkinson's disease: scientific rationale and clinical implications[END_REF]. In particular, studies with continuous enteral infusion of levodopa indicate that maintaining plasma levodopa concentrations above a minimum antiparkinsonian threshold by avoiding low trough concen-trations may be a key factor in optimizing treatment response and reducing motor complications [START_REF] Nyholm | Levodopa infusion therapy in Parkinson disease: state of the art in 2004[END_REF][START_REF] Stocchi | Intermittent vs continuous levodopa administration in patients with advanced Parkinson disease: a clinical and pharmacokinetic study[END_REF]. Interestingly, these benefits seem to be independent of maximum levodopa concentrations (C max ) and some fluctuation in plasma levels [START_REF] Stocchi | Intermittent vs continuous levodopa administration in patients with advanced Parkinson disease: a clinical and pharmacokinetic study[END_REF].

Whether the improved levodopa plasma profile seen with COMT-inhibitors can reduce motor complications has so far been studied in treatment-naive N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) primates, a widely recognized animal model for PD. Smith et al. [START_REF] Smith | Multiple small doses of levodopa plus entacapone produce continuous dopaminergic stimulation and reduce dyskinesia induction in MPTP-treated drug-naive primates[END_REF] have shown that treatment of MPTP-treated primates with four daily doses of levodopa/carbidopa (LC) and entacapone was equally effective, but produced less dyskinesia compared with those treated with an equivalent daily-dosing regimen of LC alone. Based on the CDS concept and the results reported by Smith et al. [START_REF] Smith | Multiple small doses of levodopa plus entacapone produce continuous dopaminergic stimulation and reduce dyskinesia induction in MPTP-treated drug-naive primates[END_REF], a large, international, double-blind, randomized study is currently on-going in patients with early PD without motor complications who require the initiation of levodopa therapy [START_REF] Olanow | The STRIDE-PD (Stalevo Reduction in Dyskinesia Evaluation) study: a long-term, controlled study to evaluate the effect of initiating Stalevo or carbidopa/levodopa in early PD[END_REF]. The hypothesis of this study is that frequent dosing of levodopa/carbidopa/entacapone (LCE) will delay the onset of dyskinesia compared to treatment with equivalent doses of LC. The two main maintenance-dose levels in this study are LCE 100/25/200 mg or 150/37.5/200 mg, or equivalent doses of LC administered four times daily at 3.5-h intervals.

If the hypothesis of this study holds true, it will be very important to determine which differences in the daily PK profiles of LCE and LC translate into a reduced risk of motor complications during long-term therapy. For this purpose, a study divided into two parts, the first part conducted in healthy volunteers and the other in PD patients, was designed to compare the PK profile of levodopa during treatment with LCE and LC with the above-mentioned treatment regimens. We also studied levodopa plasma profiles in healthy volunteers receiving five daily doses of LCE and LC to see whether more frequent dosing would make any further difference between the two treatments.

Materials and methods

Study design and treatments

The study was conducted in two parts. Part 1 was an openlabel, randomized, active-controlled, two-period, cross-over PK study conducted in healthy volunteers. Subjects were enrolled into one of four dosing groups. Group I received 100 mg levodopa, four times daily every 3.5 h; group II 150 mg levodopa, four times daily every 3.5 h; group III 100 mg levodopa, five times daily every 3.0 h; and group IV 150 mg levodopa, five times daily every 3.0 h. Each parallel group had a cross-over design with their respective LCE and LC strengths. Part 2 was conducted in PD patients and was identical in design to part 1 with groups I and II as described above. The study part conducted in PD patients has been registered at http://www.clinicaltrials.gov/ (study code NCT00693862).

The study medication consisted of LCE 100 or LCE 150 (levodopa/carbidopa/entacapone, 100/25/200 mg or 150/37.5/ 200 mg tablets, respectively; Stalevo, Orion Corporation Orion Pharma, Espoo, Finland), and LC 100 or LC 150 (levodopa/carbidopa, 100/25 mg tablet or one 100/25 mg tablet given together with one 50/12.5 mg tablet, respectively; Sinemet, Merck, Sharp & Dohme, Haarlem, the Netherlands).

In each group (I-IV) of part 1, subjects were randomized to receive either LCE or LC during period 1 and then subsequently crossed over to the other drug in period 2. Study drug was up-titrated during the first treatment period due to the moderate daily levodopa doses used and to avoid possible adverse events (AEs), such as nausea. Between periods 1 and 2, there was no wash-out period to avoid the need for re-titration. Period 1 lasted for 4-7 days and period 2 lasted for 3 days. The length of the titration period was the same for all subjects within each treatment group. In part 2 conducted in PD patients, the appropriate study group for each subject was selected by the investigator according to the subject's daily levodopa dose prior to the randomization. There was a wash-out period of 3-7 days between the treatment periods during which time the subjects continued on their individual daily levodopa treatment.

Both healthy volunteers and patients with PD fasted from 10:00 PM, but water was allowed up to 1 h before the first morning dose and subsequent PK assessment. All study treatment doses were ingested with 200 mL of water and the first morning dose was taken at approximately 08:00 AM. The timing of food intake was standardized to avoid differences between the two periods in each group in this respect. Breakfast, lunch, dinner, and a light evening meal were served 1 h after each dose and a snack was given either 1 h before the third dose (groups I and II in healthy volunteers and PD patients with four daily doses) or 1 h after the third dose (groups III and IV in healthy volunteers with five daily doses).

Each dosing group had a standard 2×2 cross-over design and a block size of two was chosen for the randomization process. Since the study was open, no blinding was applied. The study was performed according to good clinical practice, reviewed by the local ethics committee, and approved by the Finnish national competent authority. All subjects gave their written informed consent.

Study population

Part 1 of the study was conducted in healthy male and female volunteers. Exclusion criteria included any condition requiring regular concomitant medication (except contraceptives or hormone replacement therapy) or other medication that could have affected the outcome of the study. PD patients (male or female) in part 2 had to be on three to five daily doses of levodopa/DDCI ± entacapone with a total daily levodopa dose in the range of 300-600 mg. One or more doses of controlled-release levodopa/ DDCI preparations were allowed providing that they were included in the total of three to five daily doses mentioned above. These requirements regarding prior levodopa treatment were selected to ensure that patients could switch smoothly to their study dosing regimen. Levodopa/DDCI ± entacapone and other antiparkinsonian medications (dopamine agonists, MAO-B inhibitor, amantadine, and/or anticholinergics) were to be kept unchanged for at least 2 weeks prior to the first treatment period.

Blood sampling and determination of levodopa, carbidopa, and entacapone concentrations Venous blood samples for the determination of levodopa and carbidopa levels were collected on PK assessment days prior to the morning dose and subsequently at 0.5-or 1-h intervals up to 16 h (groups I and II) or up to 17 h (groups III and IV in healthy volunteers). An additional blood sample was collected for subjects who received LCE prior to LC to ensure that no detectable levels of entacapone were present before the first dose of LC was administered on the day of the PK assessment for period 2. Plasma samples for levodopa and carbidopa analysis were stored with an antioxidant at -70˚C and samples for entacapone analysis at -20˚C.

Determination of carbidopa and levodopa in human plasma was carried out using HPLC method with EC detection. The sample preparation involved solid-phase extraction of plasma (0.5 mL) on RECIPE Clin Rep cartridges. Samples were stabilized with sodium pyrosulphite. The determination of the analytes was carried out within the calibration range of 2.5 ng/mL (LLOQ, lower limit of quantification) to 500 ng/mL (ULOQ, upper limit of quantification) for carbidopa and 25 ng/mL (LLOQ) to 5,000 ng/mL (ULOQ) for levodopa. During the study, the inter-assay accuracy, indicated by bias, was between -3.6 and 0.0% for carbidopa and 2.7 and 4.2% for levodopa; the precision, indicated by the coefficient of variation, was between 5.5 and 6.6% for carbidopa and 3.7 and 5.1% for levodopa.

Determination of entacapone in human plasma was carried out using the LC-MS/MS method. The sample preparation involved solid-phase extraction of plasma (0.25 mL) on Isolute MFC18 cartridges; D10-entacapone was used as internal standard. The analytical procedure was linear from 10.0 (LLOQ) to 1,000 (ULOQ) ng/mL. During the study (all determinations were done in one batch) the intra-assay inaccuracy was ±3% and the intra-assay imprecision <4%.

Pharmacokinetic analysis

A noncompartmental method was used to calculate the PK parameters of levodopa after each dose. PK parameters of levodopa included minimum observed concentration (C min ), maximum observed concentration (C max ), area under the curve calculated with the linear trapezoidal rule for each dose interval (AUC tau ), time to reach the maximum observed concentration (t max ), and terminal elimination half-life (t 1/2 ) after the last dose. Additionally, the means of the above PK parameters (except t 1/2 and t max ) throughout the day and AUC 0-14 or AUC 0-15 (depending on the group) were also determined. Variability of levodopa plasma concentration during the day (fluctuation) was calculated by C max -C min (and not, for example, by the peak-through-fluctuation formula) because day-time variability was assessed after repeated doses during 1 day of study drug administration, and steady-state conditions were not reached. The PK parameters of interest for carbidopa were AUC tau for each dose interval, as well as AUC 0-14 or AUC 0-15 .

Safety

Twelve-lead electrocardiogram (ECG), vital signs (systolic and diastolic blood pressure and heart rate), physical examination and routine laboratory safety parameters were used to monitor safety in each subject. Data on AEs were collected throughout the study and were classified according to version 9.1 of the Medical Dictionary for Regulatory Activities coding system.

Statistical analysis

The sample-size calculation was based on a previous study with four daily doses of controlled-release LC 100/25 mg and entacapone 200 mg given at 4-h intervals [START_REF] Paija | Entacapone increases levodopa exposure and reduces plasma levodopa variability when used with Sinemet CR[END_REF]. The sample size needed to produce a statistical power of 80% in this study was nine subjects (with a significance level of 5%). As there were no within-subject variance data available, this estimate was considered to be sufficient for a cross-over study. It was, therefore, decided to include 10 subjects in each study group.

The analyses of the primary and secondary variables were based on a comparison of all values after each levodopa dose between the LCE and LC treatments. All analyses were performed separately for each group. These variables were evaluated using analysis of variance for cross-over design, which included repeated measurements within the study periods. The statistical model included treatment, sequence, period, time, sequence × time, period × time, and treatment × time as fixed effects, and subject within sequence, period × subject within sequence, and time × subject within sequence as random effects (Wallenstein-Fisher model [START_REF] Wallenstein | The analysis of the two-period repeated measurements crossover design with application to clinical trials[END_REF]). Values for AUC 0-14 (or AUC 0-15 ) and t 1/2 were also compared using analysis of variance for cross-over design and included treatment, sequence, and period as fixed effects, and subject within sequence as the random effect. These analyses were performed separately for each group.

In all analyses, C min , AUC tau , C max , C max -C min , and AUC 0-14 (or AUC 0-15 ) were analyzed after logarithmic transformation to achieve normality assumption. Analyses of PK variables included all subjects participating in the study and providing calculable data from one or both periods. All tests were two-sided and used a 5% significance level. The 95% confidence intervals were calculated for the ratio of the geometric means within statistical models. No multiplicity corrections were made in the statistical analyses. All analyses were programmed with SAS 9.1.3 for Windows (SAS Institute, Cary, NC, USA).

Results

Study population

In part 1, a total of 53 healthy subjects were screened; of these, 41 subjects (33 women and 8 men) were enrolled and 37 subjects completed the study. The mean age of the 41 enrolled healthy subjects was 23.7 (range: 18-37) years, mean weight was 63 (50-85) kg, and mean body mass index (BMI) was 21.9 (19-27) kg/m 2 . No subject had any medical condition or was taking any concomitant medication that could have interfered with the interpretation of the results. In part 2, a total of 23 PD patients were screened, and 19 patients were enrolled, all completing the study. The mean age of the PD patients was 63.3 (range 57-71) years, mean weight was 81.7 (56-103) kg, and mean BMI was 28.2 (22-34) kg/m 2 . Mean duration of PD was 6.7 (range 0.4-14.1) years, and mean duration of levodopa treatment was 6.2 (0.4-13.3) years. In group I (n=10), two patients had wearing-off symptoms and eight had stable disease. In group II (n=9), six patients had wearing-off symptoms, and three had stable disease.

Pharmacokinetic results

Levodopa

C min in healthy volunteers In all four dosing groups, the geometric means of all C min values from 0-14 h (0-15 h in groups III and IV) were significantly higher (by 78-105%, all P<0.0001) with LCE compared with LC treatment (Fig. 1 and Table 1). The C min values after each LCE dose were also significantly higher (P<0.0001) when compared with C min values after the respective LC dose (Fig. 1 and Table 2). Time × treatment interaction was statistically significant (P< 0.001) in group IV, i.e., the differences in mean C min values between the treatments increased towards the end of the day.

C min in PD patients

In groups I and II, the geometric means of all C min values from 0-14 h were significantly higher (by 89-100%, both P<0.0001) with LCE compared with LC treatment. The C min values after each LCE dose were also significantly higher (P<0.0001) when compared with C min values after the respective LC dose (Fig. 1).

C max in health volunteers

The mean of all C max values from 0-14 h (0-15 h for groups III and IV) was significantly higher (by 17-27%) in all groups (P<0.05) after LCE treatment compared with LC treatment (Tables 1 and3). In group I, the ratio between the treatments changed from the first dose to the later doses of the day, showing significant (P<0.05) treatment × time interaction (Table 4).

C max in PD patients

The mean of all C max values from 0-14 h in group I was 8% higher during LCE treatment compared to LC, the difference being statistically nonsignificant (Table 3, P=0.17). The difference remained nonsignificant also for each dosing interval (Table 4). In group II, the mean of all C max values from 0-14 h was 19% higher during LCE treatment compared to LC (Table 3, P<0.01). However, when the difference was analyzed separately for each dosing interval, it was statistically significant only after the third and fourth dose due to significant treatment × time interaction (Table 4, P<0.05).

AUC tau and AUC 0-14 and AUC 0-15 in healthy volunteers In all groups, AUC 0-14 and AUC 0-15 values were significantly (P<0.001) higher (by 34-46%) following LCE treatment compared with LC treatment (Tables 1 and3). Similarly, AUC tau values for each dosing interval were generally significantly higher (P<0.05) with two exceptions: after the first dose in group III and after the third dose in group IV (Table 2). Values for AUC tau increased towards the end of the day with both LCE and LC (the increase being greater with LCE) resulting in a significant treatment × time interaction (P<0.05) in groups I, III, and IV (Tables 2 and5).

AUC tau and AUC 0-14 and AUC 0-15 in PD patients The AUC 0-14 values in groups I and II were significantly (P< 0.0001) higher (by 32-39%) following LCE compared to LC (Table 3). Similarly, AUC tau values for each dosing interval in both groups were significantly higher following LCE (Table 5). The only exception was the first dosing interval (P=0.06) in group II, in which treatment × time interaction was statistically significant (P<0.01).

Variability of levodopa plasma concentrations, C max -C min , in healthy volunteers

The variability of levodopa plasma concentrations (C max -C min ) during the day was slightly smaller (by 8-16%) during LCE treatment in all four groups (Table 1 and3). However, the difference did not reach statistical difference in any of the groups. C max -C min values of levodopa between the treatments did not reach statistical significance during any of the individual dosing intervals in groups I, II, and III (Tables 2 and6). In group IV, C max -C min of levodopa during LCE was significantly lower (P<0.05) during the fourth dose of the day (Table 2).

Variability of levodopa plasma concentrations, C max -C min , in PD patients In group I, the mean variability (C max -C min ) during the day (0-14 h) was statistically significantly lower (by 18%, P<0.05) during LCE compared to LC (Table 3). For separate dosing intervals, the difference was statistically significant favoring LCE only after the third dose (Table 6, P<0.05). In contrast, there was no difference in the mean variability of levodopa plasma concentrations between the treatments in group II (Tables 3 and6). T 1/2 after the last dose in healthy volunteers Levodopa t 1/2 after the last dose was longer after LCE treatment in all groups. Mean (SD) levodopa t 1/2 in groups I and II were 1.3 (0.20) and 1.4 (0.17) h, respectively, following LC treatment, and 2.0 (0.37) and 1.9 (0.23) h, respectively, following LCE treatment (P <0.001). Similarly, mean levodopa t 1/2 in groups III and IV were 1.6 (0.64) and 2.1 (1.2) h, respectively, following LC treatment, and 2.5 (1.2) and 3.0 (1.4) h, respectively, following LCE treatment (P< 0.05 and P=0.25, respectively).

T 1/2 after the last dose in PD patients Levodopa t 1/2 after the last dose was longer after LCE treatment in both groups. Mean (SD) levodopa t 1/2 in groups I and II were 1.3 (0.20) and 1.4 (0.17) h, respectively, following LC treatment, and 2.0 (0.37) and 1.9 (0.23) h, respectively, following LCE treatment (P<0.001).

T max in healthy volunteers In all four groups, median t max occurred at 0.5-1.0 h and 1.5 h after the first doses of LC and LCE, respectively. After the second dose, the median t max occurred at 1.0-1.5 h with LC and 1.5-2.0 h with LCE.

Median t max was usually observed at 1.5 h for latter doses of both LC and LCE.

T max in PD patients Median t max was 1.5 h after all doses of LCE in both groups. With LC, the median t max was 0.5 h after the first dose and 1.5 h after the next doses.

Carbidopa

In healthy volunteers There was no statistically significant difference between LCE and LC in terms of AUC covering the entire day (AUC 0-14 or AUC 0-15 ) in any of the groups. However, after the first dose of study treatment, AUC tau values were 15-28% lower (P<0.05) with LCE compared with LC in groups I, III, and IV (data not shown).

In PD patients There were no statistically significant differences in carbidopa AUC 0-14 between LCE and LC treatments in groups I and II. All AUC tau values for each dosing interval during 0-14 h were statistically nonsignificant between the treatments. The only exception was

Entacapone concentrations

In healthy volunteers and PD patients In subjects treated with LCE in period 1 (sequence "LCE-LC"), all entacapone concentrations before the first dose of LC on the PK assessment day of period 2 were below the quantification limit of 10 ng/ml.

Safety

In healthy volunteers, the most common AEs reported during the study period were nausea, chromaturia, headache, vomiting, and dizziness. These occurred during LCE and/or LC treatments. The frequency and intensity of nausea and vomiting were higher with higher doses of study drugs.

In PD patients, most common AEs during the study periods were tremor, dizziness, headache, nausea, and chromaturia occurring during LC and/or LCE treatments. Nausea was clearly less common compared to healthy volunteers.

Vital signs and ECG data indicated no safety concerns during the study, and there were no consistent differences between LCE and LC treatment in this respect.

Discussion

This study was primarily designed to compare the levodopa concentration profiles throughout the day with the specific daily-dosing regimens of LCE and LC [100 or 150 mg of levodopa four times daily (q.i.d.) at 3.5-h intervals] that are used as the maintenance dose levels in a long-term clinical study comparing LCE and LC in the treatment of early PD [START_REF] Olanow | The STRIDE-PD (Stalevo Reduction in Dyskinesia Evaluation) study: a long-term, controlled study to evaluate the effect of initiating Stalevo or carbidopa/levodopa in early PD[END_REF].

In the present study, t 1/2 of levodopa (measured after the last dose of the day) was longer after LCE administration in all groups compared to LC. Due to prolonged t 1/2 of levodopa, both in healthy volunteers and PD patients, mean trough levels (C min ), maximum observed concentrations (C max ), and AUC values of levodopa were, in general, significantly higher throughout the day during LCE compared to LC administration. This was seen after all dosing regimens regardless of the dose strength, number of doses, or the dosing interval used. The biggest increases in levodopa PK variables after LCE were generally seen in C min and AUC, the mean increases ranging from approximately 1.3-fold (AUC in groups I-II) to 2.0-fold (C min in groups III-IV in healthy volunteers) compared to LC. In turn, C max of levodopa was 1.1-to 1.3-fold higher after LCE compared to LC in all groups. There were no differences in the C max of levodopa between LCE and LC after the first morning dose. This agrees with earlier studies conducted in healthy subjects [START_REF] Keränen | The effect of catechol-O-methyltransferase inhibition by entacapone on the pharmacokinetics and metabolism of levodopa in healthy 48 volunteers[END_REF] and patients with PD [START_REF] Nutt | Effect of peripheral catechol-O-methyltransferase inhibition on the pharmacokinetics and pharmacodynamics of levodopa in parkinsonian patients[END_REF], which have shown that a single administration of LC and entacapone does not increase the C max of levodopa. With different dosing regimens, similar kinds of results (regarding t 1/2 , C min , C max , and AUC of levodopa) have been reported with repeated dosing of entacapone administered together with standard release levodopa/carbidopa [START_REF] Müller | Pharmacokinetic behaviour of levodopa and 3-O-methyldopa after repeat administration of levodopa/carbidopa with and without entacapone in patients with Parkinson's disease[END_REF][START_REF] Nutt | Effect of peripheral catechol-O-methyltransferase inhibition on the pharmacokinetics and pharmacodynamics of levodopa in parkinsonian patients[END_REF] or with controlled-release levodopa/carbidopa [START_REF] Paija | Entacapone increases levodopa exposure and reduces plasma levodopa variability when used with Sinemet CR[END_REF]. It has also been reported that co-administration of tolcapone t.i.d. with four daily doses of levodopa/benserazide has significantly increased C min , C max , and AUC of levodopa by up to 2-to 3-fold compared to levodopa/benserazide alone [START_REF] Baas | Pharmacokineticpharmacodynamic relationship of levodopa with and without tolcapone in patients with Parkinson's disease[END_REF].

As seen from daily plasma level curves (Figs. 2 and3), levodopa concentrations tended to accumulate with both treatments towards the end of the day. These results are well in line with phase III results in patients with PD experiencing wearing-off, showing that increases in on-time with levodopa/ dopa-decarboxylase inhibitor (DDCI) and entacapone therapy were more pronounced towards the end of the day [START_REF] Study | Entacapone improves motor fluctuations in levodopa-treated Parkinson's disease patients. Parkinson Study Group[END_REF]. In contrast to the pharmacokinetic parameters above, no significant differences were generally seen in variability (C max -C min ) of levodopa concentrations during the day between LCE and LC, although there was a slight trend towards lower variability (by 8-16%) with LCE during all dosing regimens.

It is well known that there is a relatively large interindividual variability in levodopa absorption. There are many possible explanations for this, for example, different rates of gastric emptying [START_REF] Kurlan | Erratic gastric emptying of levodopa may cause "random" fluctuations of parkinsonian mobility[END_REF]. However, our study demonstrated that PK of levodopa in PD patients can be predicted reasonably well based on results obtained from healthy volunteers. This was especially true for relative differences between the two levodopa formulations, but also the absolute levodopa plasma levels in groups I and II were close to each other between healthy volunteers and PD patients. This adds to the previous literature reporting that there are generally no differences in PK of levodopa between de novo PD patients, patients with wearing-off symptoms, or patients with late-stage disease [START_REF] Fabbrini | Levodopa pharmacokinetic mechanisms and motor fluctuations in Parkinson's disease[END_REF].

Carbidopa concentration profiles were generally similar between LCE and LC throughout the day in the present study, i.e., entacapone did not affect carbidopa absorption and plasma concentrations in any clinically significant way during repeated dosing. The lack of quantifiable levels of entacapone prior to the first LC dose on the PK assessment day of period 2 in subjects who received LCE in period 1 ruled out carry-over effects from prior LCE treatment. As entacapone has been in clinical use for approximately 10 years already, our focus was not to study COMTinhibition in detail. Therefore, no data on 3-OMD or other metabolites of levodopa or dopamine are reported.

The concept of continuous dopaminergic stimulation (CDS) suggests that a more stable plasma concentration of a given dopaminergic drug will result in a more continuous response to treatment with decreased incidence of motor complications [START_REF] Olanow | Continuous dopaminereceptor treatment of Parkinson's disease: scientific rationale and clinical implications[END_REF]. It has also been claimed that maintaining plasma levodopa concentrations above a minimum antiparkinsonian threshold by avoiding low trough concentrations (C min ) may be a key factor in optimizing treatment response and reducing motor complications [START_REF] Stocchi | Intermittent vs continuous levodopa administration in patients with advanced Parkinson disease: a clinical and pharmacokinetic study[END_REF]. However, in later-stage patients with wearing-off symptoms with or without existing dyskinesia, enhancing dopaminergic therapy with any oral medication will often increase dyskinesia to some extent in addition to expected antiparkinsonian effects. This is true also for enhancement of levodopa therapy with COMT-inhibitors [START_REF] Study | Entacapone improves motor fluctuations in levodopa-treated Parkinson's disease patients. Parkinson Study Group[END_REF][START_REF] Baas | Catechol-Omethyltransferase inhibition with tolcapone reduces the "wearing off" phenomenon and levodopa requirements in fluctuating parkinsonian patients[END_REF][START_REF] Kaakkola | Effect of entacapone, a COMT inhibitor, on clinical disability and levodopa metabolism in parkinsonian patients[END_REF][START_REF] Roberts | Catechol-O-methyltransferase inhibitor tolcapone prolongs levodopa/ carbidopa action in parkinsonian patients[END_REF].

In early (or de novo) PD without wearing-off symptoms and any dyskinesia, the situation may be different. So far there is only experimental evidence showing that, in de novo non-primed MPTP primates, treatment with LC and entacapone (compared to LC alone) induced less dyskinesia despite improving motor symptoms [START_REF] Smith | Multiple small doses of levodopa plus entacapone produce continuous dopaminergic stimulation and reduce dyskinesia induction in MPTP-treated drug-naive primates[END_REF]. If the C min was the most important PK variable of levodopa for reducing the occurrence of motor complications in early PD, then LCE would better fulfil this criterion compared to LC. However, it is not known whether C min levels of levodopa in this study were high enough in this respect even with LCE. On the other hand, if significant difference in the variability of levodopa concentrations (C max -C min ) was the key factor (regardless of the level at which this variability occurs), then the present study might support that there will be no significant difference in inducing motor complications between LCE and LC in early PD. The role of C max levels of a given drug in CDS also remains unclear. However, a recent study (in later-stage patients) suggested that it may be more important to avoid low trough levels of levodopa rather than to avoid higher C max levels [START_REF] Stocchi | Intermittent vs continuous levodopa administration in patients with advanced Parkinson disease: a clinical and pharmacokinetic study[END_REF].

In conclusion, the results of this study demonstrated that 100 or 150 mg of LCE administered four to five times daily at 3.0-to 3.5-h intervals provides a PK profile with higher C min , C max , and AUC of levodopa compared to LC. No unexpected tolerability issues were seen in any of the study groups. The avoidance of low troughs in plasma levodopa levels has been suggested to be one of the most important factors resulting in better symptomatic control of PD symptoms and delay in the development of treatment-associated motor complications. Whether the observed differences in trough levels and/or other PK variables of levodopa in this study translate into the delayed onset of motor complications in patients with early PD remains to be seen. The double-blind, randomized, controlled, multicenter, long-term study [START_REF] Olanow | The STRIDE-PD (Stalevo Reduction in Dyskinesia Evaluation) study: a long-term, controlled study to evaluate the effect of initiating Stalevo or carbidopa/levodopa in early PD[END_REF] comparing LCE and LC q.i.d. in early PD may provide an answer to this important question.

Fig. 1

 1 Fig. 1 Levodopa C min (mean ± SD, ng/ml) after each dose in healthy volunteers and patients with PD (groups I-II)

Fig. 2 Fig. 3

 23 Fig. 2 Levodopa plasma concentration curves throughout the day for 16 h in healthy volunteers and patients with PD (groups I-II)

Table 1

 1 Mean levodopa C min (ng/ml), C max (ng/ml), variability in levodopa concentrations as assessed by C max -C min (ng/ml) and AUC 0-15 (h•µg/ml) during the entire day in healthy volunteers (groups III-IV)

	LCE, mean (SD)	LC, mean (SD)	Ratio LCE/LC a	P value

min Minimum levodopa concentration, C max maximum levodopa concentration, C max -C min fluctuation in levodopa concentration, AUC area under the curve, LCE levodopa/carbidopa/entacapone, LC levodopa/carbidopa, PD Parkinson's disease, SD standard deviation a Ratio for estimates of geometric means b P value was obtained by analyzing all individual values during 0-15 h

Table 2

 2 Pharmacokinetic parameters of levodopa [C min (ng/ml), C max (ng/ml), variability in levodopa concentrations as assessed by C max -C min (ng/ml), AUC 0-15 and AUC tau (h•μg/mL)] after each dose in healthy volunteers (groups III-IV) Minimum levodopa concentration, C max maximum levodopa concentration, C max -C min fluctuation in levodopa concentration, AUC area under the curve, LCE levodopa/carbidopa/entacapone, LC levodopa/carbidopa, SD standard deviation

	Dosing group and regimen		LCE, mean (SD)	LC, mean (SD)	Ratio LCE/LC a	P value
	C min (ng/ml)	Group III: 100 mg × 5,	Mean	901 (386)	445 (201)	2.05	<0.0001 b
		3-h interval, LCE n=8, LC n=9	C min (dose 1) C min (dose 2)	525 (164) 909 (387)	257 (68.9) 442 (175)	2.06 2.05	<0.0001 <0.0001
			C min (dose 3)	931 (320)	538 (194)	1.75	<0.0001
			C min (dose 4)	1,050 (350)	497 (162)	2.09	<0.0001
			C min (dose 5) c	1,090 (446)	493 (259)	2.33	<0.0001
		Group IV: 100 mg × 5,	Mean	1,580 (654)	798 (224)	1.84	<0.001 b
		3-h interval, LCE n=7, LC n=8	C min (dose 1) C min (dose 2)	766 (150) 1,300 (200)	484 (97.8) 836 (209)	1.46 1.56	<0.001 <0.0001
			C min (dose 3)	1,470 (300)	844 (144)	1.69	<0.0001
			C min (dose 4)	1,980 (556)	938 (209)	2.12	<0.0001
			C min (dose 5) c	2,360 (429)	890 (117)	2.57	<0.0001
	C max (ng/ml)	Group III: 100 mg × 5,	Mean	1,760 (509)	1,550 (535)	1.17	<0.05 b
		3-h interval, LCE n=8, LC n=9	C max (dose 1) C max (dose 2)	1,250 (279) 2,110 (395)	1,500 (732) 1,560 (399)	0.93 1.37	0.56 0.012
			C max (dose 3)	1,680 (266)	1,290 (506)	1.41	<0.01
			C max (dose 4)	2,020 (735)	1,800 (538)	1.12	0.36
			C max (dose 5)	1,730 (270)	1,610 (427)	1.11	0.37
		Group IV: 150 mg × 5,	Mean	2,770 (915)	2,210 (773)	1.27	<0.05 b
		3-h interval, LCE n=7, LC n=8	C max (dose 1) C max (dose 2)	2,250 (560) 3,100 (1,190)	1,760 (568) 2,580 (777)	1.32 1.22	0.10 0.23
			C max (dose 3)	2,070 (295)	2,110 (807)	1.04	0.83
			C max (dose 4)	3,110 (915)	2,590 (645)	1.18	0.33
			C max (dose 5)	3,310 (785)	2,040 (855)	1.70	<0.01
	C max -C min (ng/ml)	Group III: 100 mg × 5,	Mean	888 (408)	1,110 (556)	0.84	0.24
		3-h interval, LCE n=8, LC n=9	C max -C min (dose 1) C max -C min (dose 2)	747 (337) 1,240 (342)	1,250 (745) 1,120 (469)	0.62 1.18	0.09 0.57
			C max -C min (dose 3)	823 (282)	754 (434)	1.33	0.31
			C max -C min (dose 4)	969 (512)	1,300 (429)	0.73	0.27
			C max -C min (dose 5)	642 (347)	1,110 (589)	0.60	0.08
		Group IV: 150 mg × 5,	Mean	1,270 (894)	1,420 (808)	0.85	0.45
		3-h interval, LCE n=7, LC n=8	C max -C min (dose 1) C max -C min (dose 2)	1,590 (501) 2,010 (1150)	1,270 (642) 1,740 (911)	1.37 1.15	0.38 0.71
			C max -C min (dose 3)	627 (314)	1,260 (900)	0.63	0.22
			C max -C min (dose 4)	1,110 (1,030)	1,650 (702)	0.46	<0.05
			C max -C min (dose 5)	949 (593)	1,150 (882)	0.98	0.97
	AUC (h•μg/ml)	Group III: 100 mg × 5,	AUC 0-15	17,300 (3,780)	12,400 (2,350)	1.42	<0.0001
		3-h interval, LCE n=8, LCE n=9	AUC tau (dose 1) AUC tau (dose 2)	2,000 (477) 3,490 (646)	1,910 (646) 2,320 (457)	1.12 1.53	0.15 <0.0001
			AUC tau (dose 3)	3,730 (971)	2,430 (826)	1.61	<0.0001
			AUC tau (dose 4)	4,040 (1,300)	2,960 (803)	1.37	<0.001
			AUC tau (dose 5)	4,000 (888)	2,740 (264)	1.46	<0.0001
		Group IV: 150 mg × 5,	AUC 0-15	28,300 (4,340)	19,400 (2,380)	1.46	<0.001
		3-h interval, LCE n=7, LCE n=8	AUC tau (dose 1) AUC tau (dose 2)	3,770 (610) 5,110 (1,220)	2,990 (613) 3,730 (545)	1.29 1.36	<0.05 <0.05
			AUC tau (dose 3)	4,690 (377)	4,010 (998)	1.15	0.23
			AUC tau (dose 4)	6,730 (1,270)	4,560 (658)	1.47	<0.001
			AUC tau (dose 5)	7,790 (1,790)	4,220 (1080)	1.88	<0.0001
	C min

a Ratio for estimates of geometric means b P value was obtained by analyzing all individual values during 0-14 h c Concentration measured at 15 h

Table 3

 3 Mean levodopa C max (ng/ml), variability in levodopa concentrations as assessed by C max -C min (ng/ml) and AUC 0-14 (h•µg/ml) during the entire day in healthy volunteers and patients with PD (groups I-II)

	Dosing group and regimen		LCE, mean (SD)	LC, mean (SD)	Ratio LCE/LC a	P value
	Healthy volunteers	Group I: 100 mg × 4,	C max	1,520 (515)	1,260 (413)	1.17	<0.01 b
		3.5-h interval, LCE n=9, LC n=10	C max -C min AUC 0-14	949 (546) 12,300 (2,190)	949 (423) 9,100 (945)	0.89 1.34	0.24 b <0.0001
		Group II: 150 mg × 4,	C max	2,370 (769)	1,960 (654)	1.21	<0.05 b
		3.5-h interval, LCE n=10, LC n=10	C max -C min AUC 0-14	1,420 (787) 20,300 (767)	1,460 (684) 15,300 (2,700)	0.92 1.32	0.51 b <0.001
	Patients with PD	Group I: 100 mg × 4,	C max	1,410 (313)	1,280 (209)	1.08	0.17 b
		3.5-h interval, LCE n=10, LC n=10	C max -C min AUC 0-14	824 (210) 12,000 (2,920)	978 (156) 8,840 (1,870)	0.82 1.32	<0.05 b <0.0001
		Group II: 150 mg × 4,	C max	2,380 (825)	2,010 (644)	1.19	<0.01 b
		3.5-h interval, LCE n=9, LC n=9	C max -C min AUC 0-14	1,350 (634) 19,900 (6,950)	1,490 (580) 14,100 (4,880)	0.92 1.39	0.48 b <0.0001
	C Dosing group and regimen		LCE, mean (SD)	LC, mean (SD)	Ratio LCE/LC a	P value
	Healthy volunteers	Group I: 100 mg × 4,	Mean C max	1,520 (515)	1,260 (413)	1.17	<0.01 b
		3.5-h interval, LCE n=9, LC n=10	C max (dose 1) C max (dose 2)	1,120 (406) 1,930 (556)	1,180 (356) 1,340 (595)	0.92 1.49	0.41 <0.001
			C max (dose 3)	1,560 (431)	1,270 (327)	1.20	0.10
			C max (dose 4)	1,450 (338)	1,240 (366)	1.16	0.17
		Group II: 150 mg × 4,	Mean C max	2,370 (769)	1,960 (654)	1.21	<0.05 b
		3.5-h interval, LCE n=10, LC n=10	C max (dose 1) C max (dose 2)	1,760 (356) 3,050 (764)	1,840 (839) 2,330 (574)	1.02 1.32	0.82 <0.05
			C max (dose 3)	2,360 (617)	1,840 (498)	1.29	<0.05
			C max (dose 4)	2,300 (730)	1,850 (614)	1.23	0.07
	Patients with PD	Group I: 100 mg × 4,	Mean C max	1,410 (313)	1,280 (209)	1.08	0.17 b
		3.5-h interval, LCE n=10, LC n=10	C max (dose 1) C max (dose 2)	1,130 (247) 1,400 (275)	1,160 (327) 1,270 (360)	1.00 1.12	0.97 0.22
			C max (dose 3)	1,480 (613)	1,360 (268)	1.03	0.72
			C max (dose 4)	1,640 (484)	1,340 (258)	1.20	0.05
		Group II: 150 mg × 4,	Mean C max	2,380 (825)	2,010 (644)	1.19	<0.01 b
		3.5-h interval, LCE n=9, LC n=9	C max (dose 1) C max (dose 2)	1,920 (870) 2,450 (837)	1,850 (1,040) 2,400 (469)	1.07 0.98	0.51 0.81
			C max (dose 3)	2,500 (1,030)	1,810 (708)	1.40	<0.01
			C max (dose 4)	2,650 (756)	1,980 (767)	1.38	<0.01
	C

min Minimum levodopa concentration, C max maximum levodopa concentration, C max -C min fluctuation in levodopa concentration, AUC area under the curve, LCE levodopa/carbidopa/entacapone, LC levodopa/carbidopa, SD standard deviation, PD Parkinson's disease a Ratio for estimates of geometric means b P value was obtained by analyzing all individual values during 0-14 h Table 4 Levodopa C max (ng/ml) during the entire day and after each dose in healthy volunteers and patients with PD (groups I-II) max Maximum levodopa concentration, LCE levodopa/carbidopa/entacapone, LC levodopa/carbidopa, SD standard deviation, PD Parkinson's disease a Ratio for estimates of geometric means b P value was obtained by analyzing all individual values during 0-14 h

Table 5

 5 Levodopa AUC 0-14 and AUC tau (h•μg/mL) after each dose in healthy volunteers and patients with PD (groups I-II)

	Dosing group and regimen		LCE, mean (SD)	LC, mean (SD)	Ratio LCE/LC a	P value
	Healthy volunteers	Group I: 100 mg × 4,	AUC 0-14	12,300 (2,190)	9,100 (945)	1.34	<0.0001
		3.5-h interval, LCE n=9, LC n=10	AUC tau (dose 1) AUC tau (dose 2)	2,200 (703) 3,140 (523)	1,930 (588) 2,320 (605)	1.12 1.37	<0.05 <0.0001
			AUC tau (dose 3)	3,200 (732)	2,320 (377)	1.35	<0.0001
			AUC tau (dose 4)	3,590 (1,040)	2,550 (644)	1.36	<0.0001
		Group II: 150 mg × 4,	AUC 0-14	20,300 (767)	15,300 (2,700)	1.32	<0.001
		3.5-h interval, LCE n=10, LC n=10	AUC tau (dose 1) AUC tau (dose 2)	3,420 (767) 5,330 (251)	2,860 (734) 4,050 (748)	1.20 1.31	<0.05 <0.01
			AUC tau (dose 3)	5,100 (322)	3,760 (718)	1.34	<0.01
			AUC tau (dose 4)	5,480 (811)	4,060 (882)	1.30	<0.01
	Patients with PD	Group I: 100 mg × 4,	AUC 0-14	12,000 (2,920)	8,840 (1,870)	1.32	<0.0001
		3.5-h interval, LCE n=10, LC n=10	AUC tau (dose 1) AUC tau (dose 2)	2,060 (471) 2,940 (768)	1,810 (400) 2,270 (623)	1.14 1.30	<0.05 <0.0001
			AUC tau (dose 3)	3,190 (1,040)	2,320 (462)	1.34	<0.0001
			AUC tau (dose 4)	3,810 (1,110)	2,440 (504)	1.53	<0.0001
		Group II: 150 mg × 4,	AUC 0-14	19,900 (6,950)	14,100 (4,880)	1.39	<0.0001
		3.5-h interval, LCE n=9, LC n=9	AUC tau (dose 1) AUC tau (dose 2)	3,360 (1,420) 4,950 (1,680)	2,870 (1,110) 3,750 (1,140)	1.15 1.31	0.06 <0.001
			AUC tau (dose 3)	5,380 (2,200)	3,360 (1,190)	1.58	<0.0001
			AUC tau (dose 4)	6,230 (1,960)	4,070 (1,700)	1.57	<0.0001

LCE Levodopa/carbidopa/entacapone, LC levodopa/carbidopa, SD standard deviation, PD Parkinson's disease a Ratio for estimates of geometric means

Table 6

 6 Variability in levodopa concentrations throughout the day and during each dosing interval as assessed by C max -C min (ng/ml) in healthy volunteers and patients with PD (groups I-II) C min Fluctuation in levodopa concentration, LCE levodopa/carbidopa/entacapone, LC levodopa/carbidopa, SD standard deviation, PD Parkinson's disease a Ratio for estimates of geometric means b P value was obtained by analyzing all individual values during 0-14 h AUC tau after the first dose in group II, which was significantly lower with LCE compared to LC (P<0.01, data not shown).

	Dosing group and regimen		LCE, mean (SD) LC, mean (SD) Ratio LCE/LC a P value
	Healthy volunteers Group I: 100 mg × 4,	Mean C max -C min	949 (546)	949 (423)	0.89	0.24 b
		3.5-h interval, LCE n=9, LC n=10	C max -C min (dose 1) 780 (415) C max -C min (dose 2) 1,460 (565)	984 (343) 1,050 (570)	0.71 1.43	0.08 0.07
			C max -C min (dose 3) 886 (539)	884 (373)	0.85	0.39
			C max -C min (dose 4) 671 (324)	867 (412)	0.74	0.14
		Group II: 150 mg × 4,	Mean C max -C min	1,420 (787)	1,460 (684)	0.92	0.51 b
		3.5-h interval, LCE n=10, LC n=10	C max -C min (dose 1) 1,050 (373) C max -C min (dose 2) 2,290 (625)	1,500 (866) 1,870 (622)	0.76 1.26	0.14 0.23
			C max -C min (dose 3) 1,370 (568)	1,240 (510)	1.08	0.70
			C max -C min (dose 4) 952 (774)	1,220 (565)	0.71	0.09
	Patients with PD	Group I: 100 mg × 4,	Mean C max -C min	824 (210)	978 (156)	0.82	<0.05 b
		3.5-h interval, LCE n=10, LC n=10	C max -C min (dose 1) 770 (161) C max -C min (dose 2) 875 (299)	951 (326) 999 (341)	0.84 0.84	0.21 0.21
			C max -C min (dose 3) 870 (508)	1,030 (229)	0.75	<0.05
			C max -C min (dose 4) 782 (335)	929 (285)	0.83	0.17
		Group II: 150 mg × 4,	Mean C max -C min	1,350 (634)	1,490 (580)	0.92	0.48 b
		3.5-h interval, LCE n=9, LC n=9	C max -C min (dose 1) 1,280 (735) C max -C min (dose 2) 1,590 (595)	1,530 (989) 1,990 (421)	0.78 0.73	0.25 0.15
			C max -C min (dose 3) 1,340 (973)	1,160 (779)	1.19	0.44
			C max -C min (dose 4) 1,170 (783)	1,260 (781)	1.08	0.75
	C max -

Acknowledgements The authors gratefully acknowledge levodopa/ carbidopa bioanalytical work of AAIParma Deutschland, Neu-Ulm Germany, supervised by Carmen Dilger. The validation of the entacapone method and analysis of clinical samples was performed at SGS Life Science Services, 90 avenue des Hauts de la Chaume, 86281 Saint-Benoît Cedex, France, using an analytical method validated under the supervision of Murielle Brault. The authors would like to thank Iina Elo, MSc, for her assistance in the preparation of this manuscript, and Rachel Hood, MSc, for her editorial assistance with the figures and tables. Editorial assistance was funded by Orion Corporation Orion Pharma and Novartis Pharmaceuticals AG. The study was sponsored by Orion Corporation Orion Pharma.

Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.


J Simon

Heidi T Taipale

Helena Soini

Kaisu H Pitkälä

J S Bell

: H T Taipale

Prognostic value of the quality indicator "concurrent use of three or more psychotropic drugs" among residents of long-term-care facilities

To the Editor: We commend Lesén et al. [1] for their excellent research investigating whether the quality indicator "concurrent use of three or more psychotropic drugs" captures use of potentially inappropriate psychotropic drugs (PIPs). Lesén et al. used explicit (or criterion-based) indicators proposed by the Swedish National Board of Health and Welfare to determine PIPs [2]. Explicit indicators can be used in conjunction with large data sets. However, possible limitations of explicit indicators, as acknowledged by Lesén et al., include their limited transferability, lack of consideration given to comorbid disease, and limited or unknown ability to predict poor health outcomes [3,4]. There is no evidence that potentially inappropriate drug use defined using Beers Criteria, the most widely cited explicit indicators, is associated with mortality or hospitalization among nursinghome residents [5]. Evidence with respect to the association between quality of life and costs among communitydwelling older people is inconclusive. With this in mind, we sought to complement the research of Lesén et al. by analyzing whether the quality indicator predicts 5-year allcause mortality among residents of long-term-care facilities.

Cross-sectional data were obtained from all 53 long-term care wards in Helsinki, Finland, over a 2-week period in September 2003 [6]. Of 1,444 eligible residents, 1,087 residents or their proxies provided consent to participate. All medication and diagnostic data were extracted from residents' medication charts by trained nurses. Medication, diagnostic, and mortality data were available for 1,004 residents. All regularly used drugs were classified according to the Anatomical Therapeutic Chemical Classification System (drugs used "when required" were excluded). Psychotropic drugs included antidepressants, antipsychotics, anxiolytics, and sedative-hypnotics. Five-year mortality data were obtained from central registers. Cox proportional hazards analysis was used to model the prognostic significance of the quality indicator. Three models were estimated: the unadjusted risk of mortality; the risk of mortality adjusted for age, gender, and Charlson's comorbidity index (CCI); and the risk of mortality adjusted for age, gender, CCI, nutritional status (assessed using the Mini-Nutritional Assessment), and mobility (assessed as a dichotomous variable). The project was approved by the Helsinki University Hospital Research Ethics Committee.

The mean age of the 1,004 residents was 81.3 [standard deviation (SD 10.9)]. Of these, 75% were women, 58% had a primary school education or less, and 46% were widowed. The mean number of regularly used drugs was 7.1 (SD 3.4), and 31% of residents used nine or more drugs. Among the residents, 76% used one or more psychotropic drug, 49% used two or more psychotropic drugs, and 22% used three or more psychotropic drugs. At the 5-year follow-up, 80% of residents who used 0-2 psychotropic drugs were deceased compared with 78% of residents who used three or more psychotropic drugs. Concurrent use of three or more psychotropic drugs was not associated with an increased risk of mortality (Table 1).

Our analyses revealed the quality indicator was not associated with increased mortality. This was despite having high statistical power and adjusting using covariates previously associated with mortality. Our cohort comprised residents who were primarily frail, immobile, diagnosed with dementia, and at high risk of mortality. This population was different to most others in which the risk of mortality associated with atypical antipsychotics has been observed [7]. Our research may not be generalizable to all populations of older people. Hartikainen et al. reported that concurrent use of two or more psychotropic drugs by primarily community-dwelling older people with dementia was associated with an increased risk of 5-year mortality when adjusted for age and gender [8]. The value of the quality indicator may depend on the specific population to which it is applied. When considered together with the findings of Lesén et al., our

Table 1

 1 data highlight the need for urgent research into which quality indicators have prognostic value for poor health outcomes. Risk of 5-year, allcause mortality associated with the quality indicator "concurrent use of three or more psychotropic drugs" HR hazard ratio, CI confidence interval, CCI Charlson's comorbidity index, MNA Mini-Nutritional Assessment

		Model 1		Model 2		Model 3
		HR	95% CI	HR	95% CI	HR	95% CI
	Indicator	0.92	(0.78-1.09)	1.09	(0.92-1.29)	1.16	(0.97-1.38)
	Age			1.04	(1.03-1.05)	1.04	(1.03-1.05)
	Male gender			1.24	(1.04-1.49)	1.29	(1.08-1.54)
	CCI			1.06	(1.02-1.11)	1.06	(1.01-1.11)
	MNA					1.49	(1.29-1.72)
	Mobility					0.76	(0.62-0.93)
			References
			1. Lesén E, Petzold M, Andersson K, Carlsten A (2009) To what
			extent does the indicator "concurrent use of three or more
			psychotropic drugs" capture use of potentially inappropriate
			psychotropics among the elderly? Eur J Clin Pharmacol 65:635-
			642
			2. National Board of Health and Welfare (2003) Indicators for
			evaluation of the quality in drug use among the elderly: proposal
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Nils Milman
email: nils.mil@dadlnet.dk

Agnes N Pedersen

Blood haemoglobin concentrations are higher in smokers and heavy alcohol consumers than in non-smokers and abstainers-should we adjust the reference range?

Keywords: Alcohol, Body mass index, Epidemiological study, Ferritin, Hemoglobins, Men, Reference range, Smoking, Women

The blood haemoglobin concentration is one of the most frequently used laboratory parameters in clinical practice. There is evidence that haemoglobin levels are influenced by tobacco smoking. The objective of this study was to evaluate the impact of smoking and alcohol consumption on haemoglobin concentrations in apparently healthy subjects living at sea level. A retrospective, epidemiological cohort study was performed in 1984. Participants were 1,503 men and 1,437 non-pregnant women evenly distributed in age cohorts of 30, 40, 50, and 60 years. Information of smoking habits and alcohol consumption were obtained by a questionnaire. Haemoglobin was measured in the fasting state on Coulter-S. Men displayed no difference in mean haemoglobin levels in the four age groups. In women, mean haemoglobin increased gradually with age (p=0.001). Fifty-nine percent of men and 50% of women were daily smokers. Female smokers displayed a significant positive correlation between number of cigarettes/day and haemoglobin concentrations (r=0.12, p=0.002). Heavy smokers (more than ten cigarettes/day)

had significantly higher mean haemoglobin (1.4% higher in men, on average 3.5% higher in women) than non-smokers (p<0.01). Smokers demonstrated a significant correlation between cigarettes/day and drinks/week in men (r=0.24, p<0.001) and women (r=0.16, p<0.001). Non-smokers displayed a significant positive correlation between drinks/ week and haemoglobin concentrations in men (r=0.14, p= 0.001) and women (r=0.08, p=0.05). In non-smokers, alcohol consumption >14 drinks/week and more than seven drinks/week for men and women, respectively, increased mean haemoglobin by 1.3% in men and by average 1.9% in women compared with those consuming ≤14 and less than or equal to seven drinks/week. Smokers displayed similar results. Body mass index per se had no direct influence on haemoglobin levels but had indirect positive influence in men through its correlation with tobacco smoking and alcohol consumption. Tobacco smoking has an increasing effect on haemoglobin concentrations in both genders, which is proportional to the amount of tobacco smoked. The effect appears to be more pronounced in women. Likewise, high alcohol consumption has an increasing effect on haemoglobin in both genders, being most pronounced in women. However, in clinical biochemistry, the relatively small changes in haemoglobin do not justify the use of separate reference ranges in smokers and alcohol consumers.

status and in the discrimination between healthiness and disease [START_REF] Skjelbakken | Haemoglobin predicts total mortality in a general young and middle-aged male population. The Tromsø Study[END_REF][START_REF] Milman | Haemoglobin concentrations in 358 apparently healthy 80-year-old Danish men and women. Should the reference interval be adjusted for age?[END_REF]. In epidemiological studies, low and high haemoglobin levels, even within the reference range, are predictors of mortality [START_REF] Skjelbakken | Haemoglobin predicts total mortality in a general young and middle-aged male population. The Tromsø Study[END_REF][START_REF] Milman | Haemoglobin concentrations in 358 apparently healthy 80-year-old Danish men and women. Should the reference interval be adjusted for age?[END_REF]. The establishment of appropriate reference ranges in healthy populations is therefore of paramount importance [START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF].

In previous papers we have described iron status and the distribution of haemoglobin concentrations in apparently healthy Danes [START_REF] Milman | Iron stores in 1433, 30-to 60-yearold Danish males. Evaluation by serum ferritin and haemoglobin[END_REF][START_REF] Milman | Iron stores in 1359, 30-to 60year-old Danish women: evaluation by serum ferritin and hemoglobin[END_REF] but not considered the potential influence of smoking. However, in our recent paper on 80-year-old subjects [START_REF] Milman | Haemoglobin concentrations in 358 apparently healthy 80-year-old Danish men and women. Should the reference interval be adjusted for age?[END_REF], it appeared that tobacco smoking had a significant influence on haemoglobin levels, i.e. smokers displayed higher levels than non-smokers. Search of the literature disclosed several papers reporting an association between smoking and haemoglobin [START_REF] Milman | Haemoglobin concentrations in 358 apparently healthy 80-year-old Danish men and women. Should the reference interval be adjusted for age?[END_REF][START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF][START_REF] Tsang | Hematological indices in an older population sample: derivation of healthy reference values[END_REF][START_REF] Skjelbakken | Changes in haemoglobin levels according to changes in body mass index and smoking habits, a 20-year follow-up of a male cohort: the Tromsø Study 1974-1995[END_REF][START_REF] Van Tiel | Quitting smoking may restore hematological characteristics within five years[END_REF], although the studies were not specifically designed to evaluate this topic. The widespread and variable habit of smoking makes it a potential confounder in the establishment of normal reference ranges for haemoglobin. The objectives of the present study were to clarify the influence of smoking habits, alcohol consumption and, in addition, body mass index on haemoglobin concentrations and to define reference ranges for non-smokers in a cohort of apparently healthy Danes.

Materials and methods

Subjects

The selection of the participants has been described in detail elsewhere [START_REF] Milman | Iron stores in 1433, 30-to 60-yearold Danish males. Evaluation by serum ferritin and haemoglobin[END_REF][START_REF] Milman | Iron stores in 1359, 30-to 60year-old Danish women: evaluation by serum ferritin and hemoglobin[END_REF]. During 1982During -1984, a , a World Health Organization-initiated study, Monitoring of Trends and Determinants in Cardiovascular Disease (DAN-MONICA1) was performed at the Center for Population Studies in Glostrup, Denmark. The participants were residents in Greater Copenhagen and lived at sea level. A randomised sample of 2,404 men (124 of non-Danish origin) and 2,403 women (103 of non-Danish origin) in age cohorts of 30, 40, 50, and 60 years was derived from the Census Registry and were invited by letter to a health examination. A total of 1,843 men (77%) accepted the invitation and were examined in November 1982 through January 1984; among these, 1,503 men examined in February 1983 through January 1984 participated in the iron status survey (70 of non-Danish origin). A total of 1,765 women (74%) accepted the invitation, and 1,455 women examined in February 1983 through January 1984 participated in the iron status survey. After exclusion of pregnant women (n= 18), the final series comprised 1,437 non-pregnant women (78 of non-Danish origin).

Concerning demographic characteristics, the population sample was representative for the entire Danish population, except that farming and fishing occupations were slightly underrepresented.

Methods

All participants had a clinical examination and gave a detailed medical history including blood donation activity and menopausal status. Tobacco smoking was assessed in a questionnaire containing questions about the frequency of smoking and the quantity of tobacco being smoked. "Heavy smokers" were defined as those whose smoke more than ten cigarettes/day. Alcohol consumption was likewise assessed in a questionnaire and transformed into drinks per week. A drink contains ~12 g ethanol. "Heavy drinkers" were defined as those who consume >14 drinks/ week for men and more than seven drinks/week for women according to the Nordic recommendations [9]. Body mass index (BMI) was calculated as body weight in kilogram divided by body height in square meters.

Blood samples were drawn in the fasting state between 0800 and 1100 hours. Venipuncture was performed with the participants seated in a recumbent position and using a minimum of compression on the upper arm. Haemoglobin (Hb) was measured on Coulter-S. In order to convert from Hb in mmol/L to Hb in g/L, the value multiply by 0.06205. Serum ferritin was measured by an immunoradiometric assay (Phadebas Ferritin PRIST ® , Pharmacia Diagnostics, Uppsala, Sweden) [START_REF] Milman | Serum ferritin in healthy Danes: relation to bone marrow haemosiderin iron[END_REF]. According to the results obtained in our previous studies [START_REF] Milman | Haemoglobin concentrations in 358 apparently healthy 80-year-old Danish men and women. Should the reference interval be adjusted for age?[END_REF][START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF] we considered serum ferritin values >20 μg/l to be consistent with the absence of iron deficiency anaemia.

Statistics

Haemoglobin values and serum ferritin log 10 values displayed normal distributions. Differences between groups were assessed by Pearson's chi-square test, analysis of variance (ANOVA) and Student's two-tailed t test for unpaired observations. Correlations were assessed by Pearson's coefficient of correlation (r). Reference ranges were calculated as 95% confidence intervals (CI)=mean± (1.96SD).

Results

Tobacco smoking

The number of participants in the various age cohorts and smoking groups are shown in Table 1. Among men, 59% (n=892) were daily smokers, and the smoking pattern was fairly similar within the age groups. Among women, 50% (n=716) were daily smokers, and there were significant differences between the smoking pattern in the age groups, those being 30 years of age having the highest and those being 60 years of age the lowest frequency of smoking (p<0.001).

Among daily smokers (n=1,608), 710 men (80%) and 670 women (94%) smoked cigarettes. Among men, 203/ 710 (29%) and among women 250/670 (37%) smoked less than or equal to ten cigarettes/day (p=0.0001).

Alcohol consumption

Only 49 men and 169 women neither smoked nor drank alcohol. Among men, 1,388 (93%) consumed alcohol (missing information in 2), mean 14 drinks/week, median nine drinks/week (observed range, 1-170); 317 (23%) consumed >20 drinks/week. Among women, 1,122 (78%) consumed alcohol (missing information in 1), mean six drinks/week, median three drinks/week (observed range, 1-70); 44 (4%) consumed >20 drinks/week. In daily smokers, there was a significant correlation between the number of drinks/week and number of cigarettes/day both in men (r= 0.24, p<0.001) and in women (r=0.16, p<0.001).

Smoking and haemoglobin

Haemoglobin concentrations in the entire series are shown in Table 2. In men, there was no significant difference between the age groups (p = 0.08). In women, mean haemoglobin displayed a gradual, significant increase with age (p=0.001); mean value in the entire series of women (n=1,437) was 8.58±0.65 (SD) mmol/L, with 95% CI 7.31-9.85 mmol/L. Table 2 also shows the influence of smoking on haemoglobin concentrations. In both genders, smokers had significantly higher mean haemoglobin than non-smokers. In men, the difference in mean haemoglobin was 0.11 mmol/L (1.8 g/L), and in women, it ranged from 0.12 mmol/L (1.9 g/L) in 30-year-old to 0.31 mmol/L (5.0 g/L) in 50-year-old women.

The influence of smoking on haemoglobin was evaluated in subjects with serum ferritin >20 μg/L (n=2652), i.e. without iron deficiency as shown in Table 3. Male smokers had significantly higher mean haemoglobin than non-smokers, being 0.12 mmol/L (1.9 g/L) higher. Thirtyyear-old female smokers had similar haemoglobin as nonsmokers, whereas 40-, 50-, and 60-year-old smokers had significantly higher mean haemoglobin than non-smokers, being 0.19-0.27 mmol/L (3.1-4.4 g/L) higher. We found exactly the same pattern in subjects with serum ferritin ≤20 μg/L (n=288; data not shown).

There was a weak but significant positive correlation in daily smokers between haemoglobin and the number of cigarettes/day in women (r=0.12, p=0.002) but not in men (r=0.06, p=0.10). Table 4 shows the association in daily smokers between haemoglobin and the number of cigarettes/ day. In all groups, heavy smokers had higher mean haemoglobin levels than "light" smokers (less than or equal to ten cigarettes/day), but the difference was significant only in 30-and 50-year-old women. Men smoking more than ten cigarettes/day had a 1.4% increase in haemoglobin compared to non-smokers, whereas the increase in women was on the average 3.5% (2.7%, 3.8%, 4.7%, and 2.7% in 30-, 40-, 50-, and 60 year-old women, respectively).

Table 5 shows the frequency of low haemoglobin values <130 g/L (8.07 mmol/L) and of <120 g/L (7.45 mmol/L) as defined by the World Health Organization's cutoff values for anaemia in men and women, respectively [START_REF]Iron deficiency anaemia. Assessment, prevention and control[END_REF]. In men, the frequency of low haemoglobin was similar (2.1%) in smokers and non-smokers. However, among women, nonsmokers had a consistently higher frequency of low haemoglobin values (4.4-6.7% according to age) than smokers (0.8-3.6% according to age). In the entire series, the frequency of low haemoglobin was significantly higher in female non-smokers (5.4%) than in smokers (2.5%) (p<0.001).

Alcohol and haemoglobin

We evaluated the effect of alcohol separately in nonsmokers and in daily smokers. In non-smokers, there was a significant positive correlation between the number of drinks/week and haemoglobin levels both in men (r=0.14, p=0.001) and in women (r=0.08, p=0.05). The effect of alcohol was only present in subjects consuming >14 drinks/ week. It appears from Table 6 that male non-smokers consuming >14 drinks/week have 1.3% higher mean haemoglobin than non-smokers consuming ≤14 drinks/ week (p=0.04). In smoking men taking >14 drinks/week, mean haemoglobin was 1.5% higher than in men taking ≤14 drinks/week. Similar results were found in female non-smokers, where heavy drinkers had on the average 1.9% (3.7%, 1.6%, 0% and 2.4% according to age group) higher mean haemoglobin than light drinkers, while heavy-drinking female smokers had on the average 2.3% (3.3%, 2.0%, 1.7%, and 2.3% according to age group) higher mean haemoglobin than light-drinking female smokers.

In daily smokers, there were likewise a significant positive correlation between the number of drinks/week and haemoglobin levels both in men (r=0.11, p=0.001) and in women (r=0.12, p=0.001).

Smoking and alcohol vs serum ferritin

There was no consistent association between smoking and serum ferritin. Male smokers had significantly lower ferritin than non-smokers (p=0.002), while female smokers had higher ferritin than non-smokers, although the difference was significant only in 40-year-old women (p=0.01).

However, there was a consistent positive correlation between ferritin and alcohol consumption both in men (r= 0.20, p<0001) and in women (r=0.15, p<0.001).

BMI vs haemoglobin, smoking and alcohol

Men had a mean BMI of 27±4 (SD) and women of 25±5 (p<0.0001). In non-smoking men having ≤14 drinks/week (n=162), there was no significant correlation between BMI and haemoglobin (r=0.11, p=0.2). Likewise, in nonsmoking women having less than or equal to seven drinks/week (n=60), there was no correlation between BMI and haemoglobin (r=-0.006, p=1.0).

Men (n=1,503) displayed a weak correlation between BMI and haemoglobin (r=0.14, p=0.01). Women displayed no correlations in the four age groups (data not shown).

In men, there was a significant correlation between BMI and the daily number of smoked cigarettes (r=0.16, p= 0.01) as well as the weekly number of drinks (r=0.08, p= 0.01). Such correlations were not found in women either for cigarettes (r=0.04, p=0.4) or for drinks (r=-0.003, p=0.9). number of cigarettes/day in women. This correlation was not significant in men, perhaps due to other confounding factors including alcohol consumption and BMI. In heavy smokers, the increase in haemoglobin was higher in women, i.e. ~0.39 mmol/L (6.3 g/L) than 0.19 mmol/L (3.1 g/L) in men compared to non-smokers.

In addition, we found that the amount of alcohol per se had a significant influence on haemoglobin levels in both genders, when it exceeded 14 drinks/week, i.e. ~170 g ethanol/week in men, and seven drinks/week, i.e. ~85 g ethanol/week, in women. The impact of alcohol on haemoglobin was more pronounced in women than in men. In both smokers and non-smokers, the quantitative alcohol consumption displayed a positive correlation with haemoglobin. Furthermore, there was a positive correlation between alcohol consumption and serum ferritin levels. This could be due to an enhancing effect on dietary iron absorption [START_REF] Charlton | The effect of alcohol on iron absorption[END_REF], which tends to improve iron status and lower the risk of iron deficiency. In addition, alcohol has a harmful effect on the hepatocytes and may induce an inappropriate release of intracellular ferritin to the plasma [START_REF] Tavill | Alcohol and iron[END_REF].

Actually, the effect of alcohol on haemoglobin appeared to be of the same order of magnitude as the effect of tobacco. However, the number of cigarettes/day displayed a positive correlation with the number of drinks/week, demonstrating that tobacco and alcohol go hand in hand as lifestyle factor companions. This makes it difficult to separate the effect of tobacco from the effect alcohol. Approximately 90% of men and 80% of women consumed alcohol, including the vast majority of smokers.

Other studies have reported the influence of smoking on haemoglobin levels. Tsang et al. [START_REF] Tsang | Hematological indices in an older population sample: derivation of healthy reference values[END_REF] examined 3,654 Australian subjects 49-97 years of age and stated that smoking and alcohol influenced the reference range but did not report any specific details. In a Dutch cohort study of 16,254 subjects 20-70 years of age, Van Tiel et al. [START_REF] Van Tiel | Quitting smoking may restore hematological characteristics within five years[END_REF] found higher haemoglobin in smokers than in non-smokers of both genders. Skjelbakken et al. [START_REF] Skjelbakken | Changes in haemoglobin levels according to changes in body mass index and smoking habits, a 20-year follow-up of a male cohort: the Tromsø Study 1974-1995[END_REF] examined a cohort of 4,159 Norwegian men 20-49 years of age at baseline and 20 years later. They observed no difference in mean haemoglobin levels after 20 years in any strata of age, which is in accordance with our results showing similar haemoglobin levels in men from 30 to 60 years of age. During the 20-year period, 20% of the men had quitted smoking. Smoking cessation lowered their mean haemoglobin by 0.10 mmol/L (1.6 g/L) compared to those who never smoked. Furthermore, among consistent smokers, there was a positive dose-response relationship between change in cigarettes smoked per day and change in haemoglobin. Nordin et al. [START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF] established haematological reference intervals in the Nordic Reference Interval Project comprising 1,826 subjects (866 men) 18-90 years of age, of whom 14% were regular smokers. Haemoglobin decreased with age in men; this was probably due to the large age variation with inclusion of elderly men. In previous studies [START_REF] Milman | Haemoglobin concentrations in 358 apparently healthy 80-year-old Danish men and women. Should the reference interval be adjusted for age?[END_REF], we have also demonstrated a decrease in haemoglobin in men above 60 years of age. Haemoglobin increased with age in women [START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF], which is consistent with our findings. Smoking increased the mean haemoglobin in women by 0.25 mmol/L (4.0 g/L), but there was no increase in men [START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF]. There was no effect of alcohol on haemoglobin levels [START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF]. The distribution of haemoglobin in smoking vs nonsmoking women fulfilled the criteria for partitioning. However, for practical reasons, in the final calculation of the reference values, only gender and age were considered when applying the rules for partitioning [START_REF] Nordin | A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries[END_REF]. Milman et al. [START_REF] Milman | Haemoglobin concentrations in 358 apparently healthy 80-year-old Danish men and women. Should the reference interval be adjusted for age?[END_REF] examined 358 Danes 80 years of age, of whom ~30% were daily smokers. Male smokers had higher median haemoglobin than non-smokers (8.59 vs 8.56 mmol/L); likewise, female smokers had higher median haemoglobin than non-smokers (8.38 vs 8.07 mmol/L).

It appear from both the present and previous series [2, 7] that female smokers display a higher percent increase in mean haemoglobin than male smokers. This could indicate a higher sensitivity to the CO-induced hypoxaemic stimulus and consequently a greater erythropoietic response. However, we were not able to adjust for contributing factors in women, e.g. the concentration of carboxyhaemoglobin, the exact number of cigarettes/day and whether the smoke was inhaled or not.

Tobacco smoking increases the blood levels of CO [START_REF] Scherer | Carboxyhemoglobin and thiocyanate as biomarkers of exposure to carbon monoxide and hydrogen cyanide in tobacco smoke[END_REF], which binds to haemoglobin to form carboxyhaemoglobin, which is unable to bind oxygen. The blood concentration of carboxyhaemoglobin increases in proportion with the amount of smoked tobacco and whether the smoke is inhaled. The higher the carboxyhaemoglobin levels, the lower the oxygen transporting capacity of the haemoglobin mass, a scenario corresponding to functional anaemia, which can reduce exercise tolerance and maximal aerobic capacity [START_REF] Mcdonough | Smoking-induced elevations in blood carboxyhaemoglobin levels. Effect on maximal oxygen uptake[END_REF]. Rats being exposed to CO display an increase in both the blood reticulocyte count and the haemoglobin concentration; when exposure is stopped, haematological parameters return to pre-exposure levels [START_REF] Ramsey | The hematological effects of chronic, low level exposures to carbon monoxide in rats[END_REF].

Presumably, the reduced oxyhaemoglobin levels in smokers stimulate the production of erythropoietin, which increases the haemoglobin concentrations. In our series, men smoking >10 cigarettes/day had a 1.4% increase in haemoglobin compared to non-smokers, whereas in women, the increase was on the average 3.5%, which is in accordance with the carboxyhaemoglobin levels of 3-6% reported in smokers [START_REF] Scherer | Carboxyhemoglobin and thiocyanate as biomarkers of exposure to carbon monoxide and hydrogen cyanide in tobacco smoke[END_REF][START_REF] Cronenberger | Population pharmacokinetic analysis of carboxyhaemoglobin concentrations in adult cigarette smokers[END_REF]. "Normalization" of haemoglobin after smoking cessation has likewise been reported in humans [START_REF] Skjelbakken | Changes in haemoglobin levels according to changes in body mass index and smoking habits, a 20-year follow-up of a male cohort: the Tromsø Study 1974-1995[END_REF][START_REF] Van Tiel | Quitting smoking may restore hematological characteristics within five years[END_REF].

However, besides carboxyhaemoglobin, we should also consider that other yet unidentified compounds in the complex chemistry of tobacco smoke may have direct or indirect influence on erythropoiesis.

Apparently, the influence of BMI on haemoglobin levels was small. In non-smokers/non-drinkers, there was no association between BMI and haemoglobin in either of the genders. Therefore, the weak association between BMI and haemoglobin observed in the entire male series appears to be indirect, i.e. elicited by the association between BMI and smoking and drinking. This association was not found in women.

In the clinical setting, we already operate with differential reference ranges for haemoglobin according to age and gender. Should we also adjust the reference range according to smoking and alcohol consumption? If we use a reference range derived from a mixed population of smokers and nonsmokers, a fraction of non-smokers will erroneously be classified as being anaemic and a fraction of smokers will erroneously be classified as not having anaemia. For example, in our series, the frequency of low haemoglobin values <120 g/L was more than twice as high in female non-smokers (5.4%) than in smokers (2.5%). The number of subjects who will be misclassified depends on the ratio between smokers/ non-smokers in the background population. A high ratio will increase the number of misclassified non-smokers and a low ratio will increase the number of misclassified smokers. Ideally, smokers and non-smokers should have separate reference ranges for haemoglobin, although this would be of some inconvenience in the daily clinical routine.

In conclusion, tobacco smoking has an increasing effect on haemoglobin concentrations, which is proportional to the amount of tobacco smoked, and appears to be more pronounced in women. Likewise, high alcohol consumption has an increasing effect on haemoglobin in both genders, being most pronounced in women. However, in many patients, it is difficult or impossible to obtain reliable estimates of both tobacco and alcohol intake. Therefore, in clinical biochemistry and laboratory medicine, the relatively small changes in haemoglobin do not justify the use of separate reference ranges for in smokers and alcohol consumers.

Table 1

 1 Smoking habits of the participants in the study

	Number of subjects	Smoking

a Pearson's chi-square test

Table 2

 2 Haemoglobin concentrations according smoking habits in the entire series (n=2,940)

	Smoking	Haemoglobin (mmol/L)

Table 3

 3 Haemoglobin concentrations according smoking habits in subjects with serum ferritin >20 μg/L (n=2,652)

	Smoking, n	Haemoglobin, mmol/L

Table 4

 4 Association between number of cigarettes and haemoglobin in daily cigarette smokers

		Cigarettes no./day	Subjects n	Haemoglobin (mmol/L) a	p value b
	Men
	Age (years)
	30-60	≤10	203	9.60±0.66
		>10	507	9.64±0.74	0.6
	Women
	Age (years)
	30	≤10	72	8.28±0.59
		>10	147	8.61±0.56	<0.001
	40	≤10	57	8.57±0.46
		>10	107	8.68±0.71	0.3
	50	≤10	60	8.60±0.57
		>10	120	8.89±0.72	<0.001
	60	≤10	61	8.73±0.62
		>10	46	8.89±0.55	0.2

a Mean±SD b Student's t test

Acknowledgements

The study was supported by Sygekassernes Helsefond (grant H 11-23-89), Forskningsfonden for Medicinsk Forskning i København, Faerøerne og Grønland (grant 46-83), Bloddonorernes Forskningsfond and Danish National Board of Health. The authors are indebted to the Department of Clinical Biochemistry, Bispebjerg Hospital, Copenhagen, Denmark, for analyses of haemoglobin and serum ferritin.

Discussion

Although the number of smokers is steadily declining in Denmark, smoking is still widespread among the population. According to a Danish survey in 2003, 30% of men and 24% of women are daily smokers, and the fraction of hardcore heavy smokers has increased (http://www.sst.dk).

Our results demonstrate that smoking has a significant impact on haemoglobin concentrations, irrespective of gender and age. Smokers had consistently higher haemoglobin levels than non-smokers, and the increase in haemoglobin displayed a positive correlation with the


Valentine Brousse
email: valentine.brousse@nck.aphp.fr

Lucie Hertz-Pannier

Yann Consigny

Jean-Louis Bresson

Robert Girot

Elsa Mirre

Gérard Lenoir

Mariane De Montalembert

Does regular blood transfusion prevent progression of cerebrovascular lesions in children with sickle cell disease?

Keywords: Sickle cell disease, Stroke, Transfusion, Brain imaging

A retrospective study was conducted to assess changes in cerebrovascular lesions, as assessed by magnetic resonance (MR) imaging and angiography in 18 children with sickle cell disease (SCD) receiving optimised chronic transfusions for primary stroke prevention (abnormal transcranial Doppler flow, nine patients, median follow-up 14.3 months (range, 7.9-48.9)) or secondary stroke pre-vention (nine patients, median follow-up 59.6 months (range, 11.0-127.9)). An experienced neuroradiologist blinded to patient data reviewed the 41 MR scans (median/patient, three (2-4)). Standard scores were used to evaluate parenchymal and vascular abnormalities at baseline and last follow-up. Within-patient score changes evaluated using Wilcoxon's paired rank test indicated lesion progression in the secondary-prevention group (p=0.027). Optimised transfusion therapy does not prevent progression of cerebral vasculopathy in SCD children with a history of stroke.

returned to normal after regular transfusions for at least 30 months, stopping the transfusions was associated with recurrence of abnormal blood-flow velocities and with stroke [START_REF] Adams | Discontinuing prophylactic transfusions used to prevent stroke in sickle cell disease[END_REF]. Despite the convincing evidence that transfusion is beneficial in children at high risk for neurological complications, no data are available on long-term magnetic resonance imaging or angiography (MRA) in children with SCD who receive regular transfusions. Longitudinal studies involving serial TCD studies suggest that transfusion therapy may markedly reduce both blood-flow velocity in the middle cerebral arteries and red-cell sickling [START_REF] Venketasubramanian | Middle cerebral artery velocity changes during transfusion in sickle cell anemia[END_REF]. However, conventional angiography studies have shown mild progression of vascular lesions over time, despite an initial decrease in vessel irregularity [START_REF] Russell | Effect of transfusion therapy on arteriographic abnormalities and on recurrence of stroke in sickle cell disease[END_REF], suggesting that transfusions may fail to stabilise or improve the vascular lesions.

Our objective was to assess changes in MRI and MRA evidence of cerebrovascular disease over time in children with SCD receiving optimised chronic transfusion therapy.

Materials and methods

Patients

We reviewed the records of all consecutive children with homozygous SCD who received chronic transfusion therapy for primary or secondary stroke prevention at the Necker Enfants Malades Hospital, Paris, France, from June 1994 to June 2006. We identified 18 patients, nine boys and nine girls. Among them, nine were started on primary prevention after TCD screening showed abnormal bloodflow velocities (time-averaged mean of the maximum velocity≥200 cm per second) and nine were put on secondary prevention after sustaining a first stroke. These last patients had experienced a cerebrovascular accident before the implementation of annual TCD screening as standard care and have subsequently the longest follow-up. Chronic transfusion therapy was initiated within 1 month after the stroke or abnormal TCD screen. Patients received either transfusions or exchange transfusions according to the haemoglobin level at admission. We recorded the following data: age at the first stroke or abnormal TCD screen, time of transfusion therapy initiation and results of monthly complete blood cell counts and haemoglobin S (HbS) determinations.

Brain imaging MRI and MRA were performed at 1-to 2-year intervals in all patients. Because these investigations were part of standard care and the study design was retrospective, informed consent from the patients and families was not required.

Before 1998, there was no standard protocol, but MR evaluation included at least T1-and T2-weighted sequences and 3D time-of-flight MRA images. After 1998, MR evaluation routinely included 5-mm-thick T1-and T2-weighted images and 4-mm-thick FLAIR images, as well as 3D time-of-flight 1.2-mm-thick MRA images. All images were reviewed twice by an experienced neuroradiologist (LH-P), who was unaware of patient identity, history and date of imaging. Image quality was scored from 1 to 3 (1, unacceptable movement artefact or missing sequence; 2, minor movement artefact and 3, high-quality images). We excluded the six investigations that received a score of 1. Scoring systems adapted from Steen [START_REF] Steen | Brain imaging findings in pediatric patients with sickle cell disease[END_REF] were used to evaluate parenchymal abnormalities (lacunae, leucoencephalopathy, cerebral atrophy and encephalomalacia) and vascular abnormalities (arterial tortuosity, stenosis, occlusion and moyamoya); scores could range from 0 to 16 (Table 1).

Statistical analysis

Quantitative variables were expressed as median (range). MRI scores, MRA scores and total MR scores at baseline and at last follow-up were compared in each patient using Wilcoxon paired rank tests.

Results

Median age at first stroke (n = 9) was 7.6 years (3.0-10.8) and median age at first abnormal TCD was 6.5 years (4.0-12.8). Median follow-up was 59.6 months (11.0-127.9) in the stroke group and 14.3 months (7.9-48.9) in the abnormal-TCD group. Mean pre-transfusion HbS percentage was 30.8 ± 4.7 in the stroke group and 33.3 ± 9.8 in the abnormal-TCD group. Corresponding mean post-transfusion HbS percentages were 21.4 ± 2.9 and 22.9 ± 6.5, respectively.

The 18 patients had 41 MR evaluations included in the analysis (Table 2). The median number of MR evaluations per patient was 3 (2-4). In the stroke group, the median total score (MRI+MRA) was 10 [2-22] at baseline and 12 at last follow-up (p=0.027). Thus, progression of the MR abnormalities occurred despite adequate transfusion therapy in patients with a history of a single stroke episode. In the abnormal-TCD group, the median total score was 0 (0-7) at baseline and 0 (0-10) at last follow-up.

Discussion

Cerebrovascular lesions as assessed by MR worsened in children with SCD who had a history of stroke, despite chronic transfusion therapy that kept the HbS percentage within the range usually considered protective [START_REF] Pegelow | Risk of recurrent stroke in patients with sickle cell disease treated with erythrocyte transfusions[END_REF]. In the abnormal-TCD group, MR evaluation showed no change, but the follow-up was too short to draw conclusions from this finding. Although age was comparable in the two groups, the total MR score at baseline was lower in the abnormal-TCD group, in keeping with the hypothesis that increased cerebral blood-flow velocity antedates the development of MR abnormalities.

The worsening MR findings in the stroke subgroup were clinically silent in eight of the nine patients; the remaining patient experienced a second stroke episode. Stroke recurrence has been reported previously in children receiving monthly transfusions for SCD [START_REF] Pegelow | Risk of recurrent stroke in patients with sickle cell disease treated with erythrocyte transfusions[END_REF][START_REF] Scothorn | Risk of recurrent stroke in children with sickle cell disease receiving blood transfusion therapy for at least five years after initial stroke[END_REF] however, in these previous studies, HbS levels were greater than 30% in most of the patients and were most likely to be high among patients who experienced recurrent stroke or transient ischemic attacks. The rate of recurrent stroke was 1.9 per 100 patient-years in a retrospective study where most patients had less than 30% HbS [START_REF] Scothorn | Risk of recurrent stroke in children with sickle cell disease receiving blood transfusion therapy for at least five years after initial stroke[END_REF]. It was only 1.15 per 100 patient-years in our study, suggesting that 30% may be a good HbS target level. However, despite the optimal transfusion regimen used in our study, cerebrovascular lesions worsened in the patients who had a history of stroke. Although the long-term consequences of this finding are unclear, children with progressive cerebrovascular disease may experience cognitive impairments and an increased risk of moya-moya disease.

The reasons for the inability of regular transfusions to halt the progression of cerebrovascular disease in children with SCD and a history of stroke deserve discussion. Factors that may be relevant include the genetic makeup and lesion severity at treatment onset. Conceivably, specific genetic influences may result in progressive vascular lesions that fail to respond to transfusion therapy. In keeping with this possibility, a small minority of children in the STOP study had persistent increases in cerebral blood-flow velocities despite transfusion therapy [START_REF] Adams | Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial Doppler ultrasonography[END_REF]. Another possibility is that the vascular lesions may become refractory to treatment once they have crossed a severity threshold. The absence of disease progression in the abnormal-TCD group may be related to the short follow-up.

Our study has limitations inherent to the retrospective design. Advances in imaging techniques in recent years have increased the ability to detect lesions [START_REF] Steen | Brain imaging findings in pediatric patients with sickle cell disease[END_REF]. In our study, however, the same imaging protocol was used from 1998 to 2006, so that a role for technical changes in the worsening of MR findings is unlikely. In addition, the quality score filter strongly reduced the risk of spurious interpretation of low quality images. Both reproducibility and accuracy of imaging criteria are critical issues. We are unaware of other longitudinal studies using the Steen et al. scoring system. In this study, all scans were reviewed twice by an experienced (>15 years) pediatric neuroradiologist blinded to any clinical data. After complete analysis of randomly ordered scans of all mixed patients, the longitudinal sequence of each patient was reviewed allowing a retrospective determination of the accuracy of the previous readings. This internal check proved a high degree of reproducibility as only in two cases did discrepancies lead to a third determination. In the original Steen et al. study, the inter observer variability was deemed low and all discrepant cases could be solved by consensus. We used a validated score 1 for within-patient comparisons over time. However, the score items do not reflect a single pathophysiological process. For this reason, and because the number of patients was limited, a separate analysis of microvessel and macrovessel damage was not feasible. Such an analysis would help to identify the mechanisms that lead to cerebrovascular disease progression.

In conclusion, our findings do not challenge the usefulness of chronic transfusion in children with SCD and a history of stroke or abnormal TCD. They establish that, in patients with a history of stroke, SCD-related cerebrovascular damage continues to progress despite chronic transfusion keeping HbS levels below 30%. The long-term consequences of cerebrovascular disease progression are unclear. Little is known about changes in brain parenchyma damage after haematopoietic stem cell transplantation for severe SCD [START_REF] Woodard | Brain parenchymal damage after haematopoietic stem cell transplantation for severe sickle cell disease[END_REF]. Therefore, we do not know whether early transplantation would be more effective in preserving a normal neurodevelopmental pattern than chronic transfusion in at-risk SCD children. Knowledge of the mechanisms involved in SCD-related brain damage would help to determine the best treatment strategy for preventing this devastating complication.

Table 1

 1 Method for scoring abnormalities found by magnetic resonance imaging and angiography, adapted from Steen et al.[START_REF] Steen | Brain imaging findings in pediatric patients with sickle cell disease[END_REF]

	Lacunae	Leuco-	Atrophy	Encephalomalacia
		encephalopathy
	0: absence 0: absence	0: absence	0: absence
	1: <1 cm	1: ≤3 cm	1: ≤1 unilateral	1: ≤1 unilateral
	unilateral	unilateral	territory	territory
	2: >1 cm	2: >3 cm	2 >1 unilateral	2 >1 unilateral
	unilateral	unilateral	territory	territory
	3: <1 cm	3: ≤3 cm	3 ≤1 bilateral	3 ≤1 bilateral
	bilateral	bilateral	territory	territory
	Tortuosity Stenosis/occlusion		Moya moya
		of right and left
		MCA, ACA, ICA
	0: absence 0: absence		0: absence
	1: unilateral 1: <50%		1: unilateral
	2: bilateral 2: ≥50%		2: bilateral
		3: 100%
	MCA middle cerebral artery, ACA anterior cerebral artery, ICA internal
	carotid artery

Table 2

 2 Clinical data and scores of patients

	Patient	Date of	Inclusion	Date transfusion	Date of first	Quality	Initial	Date of	Quality	Final
		birth	criteria	program started	MR	score	score	last MR	score	score
	1	15/02/00	Stroke	1/09/05	15/09/05	3	10	15/08/06	2	10
	2	26/06/86	Stroke	1/01/1994	15/02/94	3	14	17/01/03	3	23
	3	31/08/90	Stroke	1/07/96	15/06/98	3	13	6/06/06	3	12
	4	23/06/88	Stroke	1/05/95	1/03/96	2	9	1/03/03	3	10
	5	14/06/00	Stroke	1/11/03	1/01/05	3	4	11/07/06	3	5
	6 a	13/08/92	Stroke	1/02/96	1/08/96	2	9	6/04/06	3	23
	7	16/01/91	Stroke	1/02/01	26/01/01	3	22	4/01/06	3	26
	8	30/03/90	Stroke	1/10/98	1/01/99	3	19	30/05/06	3	25
	9	18/09/97	Stroke	1/02/02	16/07/02	2	2	1/12/04	3	3
	10	4/07/97	TCD	1/05/05	8/05/05	3	0	18/07/06	3	0
	11	23/12/98	TCD	1/12/04	1/01/05	3	1	11/17/2006	3	1
	12	23/09/93	TCD	1/01/04	1/02/04	3	6	28/06/06	3	8
	13	19/08/01	TCD	1/06/05	1/09/05	3	0	1/05/06	3	0
	14	16/11/99	TCD	1/08/05	15/08/05	3	7	11/08/06	3	10
	15	5/02/99	TCD	1/01/05	1/08/05	3	0	7/08/06	3	0
	16	6/05/97	TCD	1/06/05	24/06/05	3	0	3/08/06	3	0
	17	11/11/97	TCD	1/11/02	1/08/02	2	0	30/08/06	2	0
	18	20/09/91	TCD	1/04/04	19/07/04	2	0	12/07/06	3	1

a Patient 6 experienced recurrence of overt stroke despite chronic exchange transfusion program

Ann Hematol (2009) 88:785-788

assistance was received in support of this study.