QT time prolongation
Adverse drug events
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Explanations of the substances for patients
We have no additional warnings for the combination of cimetidine and paroxetine. Please also consult the relevant specialist information.
|Paroxetine||1.52 [0.47,8.42] 1||1.52|
The changes in exposure mentioned relate to changes in the plasma concentration-time curve [AUC]. We did not detect any change in exposure to cimetidine. We cannot currently estimate the influence of paroxetine. Paroxetine exposure increases to 152%, when combined with cimetidine (152%). The AUC is between 47% and 842% depending on the CYP2D6
The pharmacokinetic parameters of the average population are used as the starting point for calculating the individual changes in exposure due to the interactions.
Cimetidine has a mean oral bioavailability [ F ] of 65%, which is why the maximum plasma levels [Cmax] tend to change with an interaction. The terminal half-life [ t12 ] is rather short at 1.6333333 hours and constant plasma levels [ Css ] are reached quickly. The protein binding [ Pb ] is very weak at 19% and the volume of distribution [ Vd ] is very large at 91 liters. The metabolism does not take place via the common cytochromes and the active transport takes place partly via BCRP and PGP.
Paroxetine has a low oral bioavailability [ F ] of 40%, which is why the maximum plasma level [Cmax] tends to change strongly with an interaction. The terminal half-life [ t12 ] is 16 hours and constant plasma levels [ Css ] are reached after approximately 64 hours. The protein binding [ Pb ] is moderately strong at 94% and the volume of distribution [ Vd ] is very large at 274 liters, which is why, with a mean hepatic extraction rate of 0.58, both liver blood flow [Q] and a change in protein binding [Pb] are relevant. The metabolism takes place via CYP1A2, CYP2C19, CYP2D6 and CYP3A4, among others and the active transport takes place in particular via PGP.
|Serotonergic Effects a||2||Ø||++|
Recommendation: As a precautionary measure, symptoms of serotonergic overstimulation should be taken into account, especially after increasing the dose and at doses in the upper therapeutic range.
Rating: Paroxetine modulates the serotonergic system to a moderate extent. The risk of a serotonergic syndrome can be classified as low with this medication if the dosage is in the usual range. According to our knowledge, cimetidine does not increase serotonergic activity.
|Kiesel & Durán b||2||+||+|
Recommendation: As a precaution, attention should be paid to anticholinergic symptoms, especially after increasing the dose and at doses in the upper therapeutic range.
Rating: Cimetidine and paroxetine only have a mild effect on the anticholinergic system. The risk of anticholinergic syndrome with this medication is rather low if the dosage is in the usual range.
QT time prolongation
Rating: In combination, cimetidine and paroxetine can potentially trigger ventricular arrhythmias of the torsades de pointes type.
General adverse effects
|Side effects||∑ frequency||cim||par|
|Abnormal ejaculation||20.5 %||n.a.||20.5|
Constipation (9%): paroxetine
Loss of appetite (6.5%): paroxetine
Gastrointestinal hemorrhage: paroxetine
Tremor (7.5%): paroxetine
Dream disorder: paroxetine
Reduced libido (7.5%): paroxetine
Erectile dysfunction (6%): paroxetine
Orgasm disorder (6%): paroxetine
Blurred vision (5%): paroxetine
Gynecomastia (4%): cimetidine
Stevens johnson syndrome: paroxetine
Toxic epidermal necrolysis: paroxetine
Prolonged bleeding time: paroxetine
Anaphylactic reaction: paroxetine
Based on your
Abstract: The relationship between the selective serotonin reuptake inhibitor paroxetine and the sparteine oxidation polymorphism was investigated in a combined single-dose (30 mg) and steady-state (30 mg/day for 2 weeks) study including a panel of nine extensive metabolizers and eight poor metabolizers of sparteine. The median area under the plasma concentration-time curve (AUC) after the first paroxetine dose was about seven times higher in poor metabolizers than in extensive metabolizers (3910 versus 550 nmol.hr/L), whereas at steady state the median AUCss tau interphenotype difference was only twofold (4410 versus 2550 nmol.hr/L). Plasma half-life and steady-state plasma concentration were significantly longer and higher, respectively, in poor metabolizers than in extensive metabolizers (41 versus 16 hours and 151 versus 81 nmol/L). Paroxetine pharmacokinetics were linear in poor metabolizers and nonlinear only in extensive metabolizers. Sparteine metabolic ratio (MR = 12 hour urinary ratio of sparteine/dehydrosparteine), increased during treatment with paroxetine in subjects who were extensive metabolizers, and after 14 days treatment two extensive metabolizers were phenotyped as poor metabolizers and the remaining extensive metabolizers were changed into extremely slow extensive metabolizers with sparteine MRs of 5.7 to 16.5. The inhibition of sparteine metabolism was rapidly reversed after cessation of paroxetine administration. In the poor metabolizers there were no significant changes in MRs during the study. It is concluded that paroxetine and sparteine metabolism cosegregates, but the interphenotype difference in metabolism was less prominent at steady state than after a single dose, presumably because of saturation of the sparteine oxygenase (CYP2D6) in subjects who were extensive metabolizers. Paroxetine is a potent inhibitor of sparteine oxidation by CYP2D6 in vivo.
Abstract: Paroxetine is well absorbed from the gastrointestinal tract, and appears to undergo first-pass metabolism which is partially saturable. Consistent with its lipophilic amine character, paroxetine is extensively distributed into tissues. Its plasma protein binding at therapeutically relevant concentrations is about 95%. Paroxetine is eliminated by metabolism involving oxidation, methylation, and conjugation. All of these factors lead to wide interindividual variation in the pharmacokinetics of paroxetine. Renal clearance of the compound is negligible. The major metabolites of paroxetine are conjugates which do not compromise its selectivity nor contribute to the clinical response. Ascending single-dose studies reveal that the pharmacokinetics of paroxetine are non-linear to a limited extent in most subjects and to a marked degree in only a few. Also, steady-state pharmacokinetic parameters are not predictable from single-dose data. In many subjects, daily administration of 20-50 mg of paroxetine leads to little or no disproportionality in plasma levels with dose, although in a few subjects this phenomenon is evident. Steady-state plasma concentrations are generally achieved within 7 to 14 days. The terminal half-life is about one day, although there is a wide intersubject variability (e.g. with 30 mg, a range of 7-65 hours was observed in a group of 28 healthy young subjects). In elderly subjects there is wide interindividual variation in steady-state pharmacokinetic parameters, with statistically significantly higher plasma concentrations and slower elimination than in younger subjects, although there is a large degree of overlap in the ranges of corresponding parameters. In severe renal impairment higher plasma levels of paroxetine are achieved than in healthy individuals after single dose. In moderate hepatic impairment the pharmacokinetics after single doses are similar to those of normal subjects. Paroxetine is not a general inducer or inhibitor of hepatic oxidation processes, and has little or no effect on the pharmacokinetics of other drugs examined. Its metabolism and pharmacokinetics are to some degree affected by the induction or inhibition of drug metabolizing enzyme(s). From a pharmacokinetic standpoint, drug interactions involving paroxetine are considered unlikely to be a frequent occurrence. Data available have failed to reveal any correlation between plasma concentrations of paroxetine and its clinical effects (either efficacy or adverse events).
Abstract: Paroxetine is a trans-isomeric phenylpiperidine with antidepressant properties induced by selective inhibition of the neuronal high affinity uptake of serotonin. In comparison with other selective serotonin uptake inhibitors paroxetine is 2 to 23 times more potent. With the exception of a low affinity to muscarinic receptors, which is not relevant for therapeutic effects, it does not interact directly with monoamine neurotransmitter receptors. Paroxetine is applied orally at single daily doses of 20 to 50 mg and well absorbed from the gastrointestinal tract. It undergoes a partially saturated first pass metabolism which reduces the bioavailability at therapeutic doses to about 30-60%. Maximal blood levels are reached 2 to 8 hours after oral administration. In the plasma 95% of the drug are bound to protein. Paroxetine is eliminated after transformation in the liver into pharmacologically inactive metabolites. High affinity to the cytochrome P450 isoenzyme CYP2D6 indicates that interferences occur with other drugs which are metabolized via the same isoenzyme. Although clinical practice has not reported problematic drug interactions so far, comedications with tricyclic antidepressants should be avoided. The most frequent side effects of paroxetine concern nausea and somnolescence. Since cardiotoxicity or other toxic side effects are much less frequent than under tricyclic antidepressants paroxetine seems advantageous in elderly patients. The onset of antidepressant effects requires several weeks as known for all currently available antidepressants. The pharmacokinetic and pharmacodynamic properties of paroxetine taken together indicate that this selective serotonin uptake inhibitor seems advantageous to other antidepressant agents because of its high selectivity and poor toxicity.
Abstract: Recently, the use of astemizole and terfenadine, both non-sedating H1-antihistamines, caused considerable concern. Several case reports suggested an association of both drugs with an increased risk of torsades de pointes, a special form of ventricular tachycardia. The increased risk of both H1-antihistamines was associated with exposure to supratherapeutic doses; for terfenadine the risk was also associated with concomitant exposure to the cytochrome P-450 inhibitors ketoconazole, erythromycin and cimetidine. To predict the size of the population that runs the risk of developing this potentially fatal adverse reaction in the Netherlands, the prevalence of prescribing supratherapeutic doses and the concomitant exposure to terfenadine and cytochrome P-450 inhibitors was studied. Data were obtained from the PHARMO data base in 1990, a pharmacy-based record linkage system encompassing a catchment population of 300,000 individuals. The results of the study showed that the prescribing of supratherapeutic doses and the concomitant exposure to terfenadine and cytochrome P-450 inhibitors was low. Furthermore, the results of a sensitivity analysis showed that the risk of fatal torsades de pointes has to be as high as 1 in 10,000 to cause one death in the Netherlands in one year.
Abstract: Astemizole (Hismanal), an antihistamine agent, has been reported to be associated with ventricular arrhythmias. In this paper we present a case of QT prolongation and torsades de pointes (TdP) in a 77-year-old woman who had been taking astemizole (10 mg/day) for 6 months because of allergic skin disease. At the time of admission, the serum concentration of astemizole and its metabolites was markedly elevated at 15.85 ng/ml, approximately 3 times the normal level. The patient was also taking cimetidine, a known inhibitor of cytochrome P-450 enzymatic activity, and during her admission was diagnosed as having vasospastic angina. To the best of our knowledge, this is the first report of astemizole-induced QT prolongation and TdP in Japan.
Abstract: We report on a case of serotonin syndrome associated to the use of the paroxetine, a serotonin reuptake inhibitor drug. Serotonin syndrome related to this drug not combined with other drugs had not yet been described in literature.
Abstract: OBJECTIVE: To describe a case of serotonin syndrome due to paroxetine and ethanol. CASE SUMMARY: A 57-year-old white man was brought to the emergency department one day after ingesting paroxetine 3600 mg and a pint of hard liquor. He denied the use of any other drug or herbal products and regular use of alcohol. Upon arrival to the hospital, vital signs were blood pressure 188/103 mm Hg, heart rate 114 beats/min, respiratory rate 28 breaths/min, temperature 36.8 degrees C, and O2 saturation 96% on room air. Findings on physical examination included dilated pupils, facial flushing, diaphoresis, shivering, myoclonic jerks, tremors, and hyperreflexia. A tentative diagnosis of serotonin syndrome was made. Initially, cyproheptadine 8 mg was administered orally with no observable effect. An additional 12 mg was given in 3 doses over 24 hours. Symptoms abated slowly over the next 6 days, during which a thorough evaluation failed to reveal any other potential causes for the patient's condition. Serum paroxetine concentrations at 27.5 and 40 hours after ingestion were 1800 and 1600 ng/mL, respectively (normal 20-200 ng/mL). DISCUSSION: Serotonin syndrome is rarely reported in patients taking only one serotonergic medication. Although serum paroxetine concentrations have not been shown to correlate with efficacy or toxicity, our patient's serum paroxetine concentration was 9 times the upper end of the therapeutic range. Cyproheptadine, which has been suggested as a therapy, did not appear beneficial in this patient. Use of the Naranjo probability scale indicated a probable relationship between the serotonin syndrome and the overdose of paroxetine taken by this patient. CONCLUSIONS: More studies are needed to better assess the role of cyproheptadine and other serotonin antagonists in the management of the serotonin syndrome. Regardless of the use of cyproheptadine or other agents, attention should be paid to fluid status, decontamination, and management of hyperthermia, agitation, and seizures.
Abstract: Renal drug interactions can result from competitive inhibition between drugs that undergo extensive renal tubular secretion by transporters such as P-glycoprotein (P-gp). The purpose of this study was to evaluate the effect of itraconazole, a known P-gp inhibitor, on the renal tubular secretion of cimetidine in healthy volunteers who received intravenous cimetidine alone and following 3 days of oral itraconazole (400 mg/day) administration. Glomerular filtration rate (GFR) was measured continuously during each study visit using iothalamate clearance. Iothalamate, cimetidine, and itraconazole concentrations in plasma and urine were determined using high-performance liquid chromatography/ultraviolet (HPLC/UV) methods. Renal tubular secretion (CL(sec)) of cimetidine was calculated as the difference between renal clearance (CL(r)) and GFR (CL(ioth)) on days 1 and 5. Cimetidine pharmacokinetic estimates were obtained for total clearance (CL(T)), volume of distribution (Vd), elimination rate constant (K(el)), area under the plasma concentration-time curve (AUC(0-240 min)), and average plasma concentration (Cp(ave)) before and after itraconazole administration. Plasma itraconazole concentrations following oral dosing ranged from 0.41 to 0.92 microg/mL. The cimetidine AUC(0-240 min) increased by 25% (p < 0.01) following itraconazole administration. The GFR and Vd remained unchanged, but significant reductions in CL(T) (655 vs. 486 mL/min, p < 0.001) and CL(sec) (410 vs. 311 mL/min, p = 0.001) were observed. The increased systemic exposure of cimetidine during coadministration with itraconazole was likely due to inhibition of P-gp-mediated renal tubular secretion. Further evaluation of renal P-gp-modulating drugs such as itraconazole that may alter the renal excretion of coadministered drugs is warranted.
Abstract: Anticholinergic Drug Scale (ADS) scores were previously associated with serum anticholinergic activity (SAA) in a pilot study. To replicate these results, the association between ADS scores and SAA was determined using simple linear regression in subjects from a study of delirium in 201 long-term care facility residents who were not included in the pilot study. Simple and multiple linear regression models were then used to determine whether the ADS could be modified to more effectively predict SAA in all 297 subjects. In the replication analysis, ADS scores were significantly associated with SAA (R2 = .0947, P < .0001). In the modification analysis, each model significantly predicted SAA, including ADS scores (R2 = .0741, P < .0001). The modifications examined did not appear useful in optimizing the ADS. This study replicated findings on the association of the ADS with SAA. Future work will determine whether the ADS is clinically useful for preventing anticholinergic adverse effects.
Abstract: OBJECTIVE: Paroxetine is believed to be a substrate of CYP2D6. However, no information was available indicating drug interaction between paroxetine and inhibitors of CYP2D6. The aim of this study was to examine the effects of terbinafine, a potent inhibitor of CYP2D6, on pharmacokinetics of paroxetine. METHODS: Two 6-day courses of either a daily 150-mg of terbinafine or a placebo, with at least a 4-week washout period, were conducted. Twelve volunteers took a single oral 20-mg dose of paroxetine on day 6 of both courses. Plasma concentrations of paroxetine were monitored up to 48 h after dosing. RESULTS: Compared with the placebo, terbinafine treatment significantly increased the peak plasma concentration (C(max)) of paroxetine, by 1.9-fold (6.4 +/- 2.4 versus 12.1 +/- 2.9 ng/ml, p < 0.001), and the area under the plasma concentration-time curve from zero to 48 h [AUC (0-48)] of paroxetine by 2.5-fold (127 +/- 67 vs 318 +/- 102 ng/ml, p < 0.001). Elimination half-life differed significantly (15.3 +/- 2.4 vs 22.7 +/- 8.8 h, p < 0.05), although the magnitude of alteration (1.4-fold) was smaller than C(max )or AUC. CONCLUSION: The present study demonstrated that the metabolism of paroxetine after a single oral dose was inhibited by terbinafine, suggesting that inhibition of CYP2D6 activity may lead to a change in the pharmacokinetics of paroxetine. However, further study is required to confirm this phenomenon at steady state.
Abstract: A recent in vitro study has shown that paroxetine is a substrate of P-glycoprotein. However, there was no in vivo information indicating the involvement of P-glycoprotein on the pharmacokinetics of paroxetine. The aim of this study was to examine the effects of itraconazole, a P-glycoprotein inhibitor, on the pharmacokinetics of paroxetine. Two 6 day courses of either 200 mg itraconazole daily or placebo with at least a 4 week washout period were conducted. Thirteen volunteers took a single oral 20 mg dose of paroxetine on day 6 of both courses. Plasma concentrations of paroxetine were monitored up to 48 hours after the dosing. Compared with placebo, itraconazole treatment significantly increased the peak plasma concentration (Cmax) of paroxetine by 1.3 fold (6.7 +/- 2.5 versus 9.0 +/- 3.3 ng/mL, P < 0.05) and the area under the plasma concentration-time curve from zero to 48 hours [AUC (0-48)] of paroxetine by 1.5 fold (137 +/- 73 versus 199 +/- 91 ng*h/mL, P < 0.01). Although elimination half-life differed significantly (16.1 +/- 3.4 versus 18.8 +/- 5.9 hours, P < 0.05), the alteration was small (1.1 fold). The present study demonstrated that the bioavailability of paroxetine was increased by itraconazole, suggesting a possible involvement of P-glycoprotein in the pharmacokinetics of paroxetine.
Abstract: Human immunodeficiency virus-infected patients have an increased risk for depression. Despite the high potential for drug-drug interactions, limited data on the combined use of antidepressants and antiretrovirals are available. Theoretically, ritonavir-boosted protease inhibitors may inhibit CYP2D6-mediated metabolism of paroxetine. We wanted to determine the effect of fosamprenavir-ritonavir on paroxetine pharmacokinetics and vice versa and to evaluate the safety of the combination. Group A started with 20 mg paroxetine every day for 10 days; after a wash-out period of 16 days, subjects received paroxetine (20 mg every day) plus fosamprenavir-ritonavir (700/100 mg twice a day) from days 28 to 37. Group B received the regimens in reverse order. On days 10 and 37, pharmacokinetic curves were recorded. Twenty-six healthy subjects (18 females, 8 males) were included. Median (range) age and weight were 44.4 (18.2 to 64.3) years and 68.8 (51.0 to 89.4) kg. Three subjects were excluded (two because of adverse events; one for nonadherence). Addition of fosamprenavir-ritonavir to paroxetine resulted in a significant decrease in paroxetine exposure: the geometric mean ratios (90% confidence intervals) of paroxetine plus fosamprenavir-ritonavir to paroxetine alone were 0.45 (0.41 to 0.49) for the area under the concentration-time curve from 0 to 24 h (AUC(0-24)), 0.49 (0.45 to 0.53) for the maximum concentration of the drug in plasma (C(max)), and 0.75 (0.71 to 0.80) for the apparent elimination half-life (t(1/2)). The free fraction of paroxetine showed a median (interquartile range) increase of 30% (18 to 42%) after the addition of fosamprenavir-ritonavir. The AUC(0-12), C(max), C(min), and t(1/2) of amprenavir and ritonavir were similar to those of historical controls. No serious adverse events occurred. Fosamprenavir-ritonavir reduced total paroxetine exposure by 55%. This is partly explained by protein displacement of paroxetine. We think that this interaction is clinically relevant and that titration to a higher dose of paroxetine may be necessary to accomplish the needed antidepressant effect.
Abstract: BACKGROUND: Adverse effects of anticholinergic medications may contribute to events such as falls, delirium, and cognitive impairment in older patients. To further assess this risk, we developed the Anticholinergic Risk Scale (ARS), a ranked categorical list of commonly prescribed medications with anticholinergic potential. The objective of this study was to determine if the ARS score could be used to predict the risk of anticholinergic adverse effects in a geriatric evaluation and management (GEM) cohort and in a primary care cohort. METHODS: Medical records of 132 GEM patients were reviewed retrospectively for medications included on the ARS and their resultant possible anticholinergic adverse effects. Prospectively, we enrolled 117 patients, 65 years or older, in primary care clinics; performed medication reconciliation; and asked about anticholinergic adverse effects. The relationship between the ARS score and the risk of anticholinergic adverse effects was assessed using Poisson regression analysis. RESULTS: Higher ARS scores were associated with increased risk of anticholinergic adverse effects in the GEM cohort (crude relative risk [RR], 1.5; 95% confidence interval [CI], 1.3-1.8) and in the primary care cohort (crude RR, 1.9; 95% CI, 1.5-2.4). After adjustment for age and the number of medications, higher ARS scores increased the risk of anticholinergic adverse effects in the GEM cohort (adjusted RR, 1.3; 95% CI, 1.1-1.6; c statistic, 0.74) and in the primary care cohort (adjusted RR, 1.9; 95% CI, 1.5-2.5; c statistic, 0.77). CONCLUSION: Higher ARS scores are associated with statistically significantly increased risk of anticholinergic adverse effects in older patients.
Abstract: The objective of this study was to measure the anticholinergic activity (AA) of medications commonly used by older adults. A radioreceptor assay was used to investigate the AA of 107 medications. Six clinically relevant concentrations were assessed for each medication. Rodent forebrain and striatum homogenate was used with tritiated quinuclidinyl benzilate. Drug-free serum was added to medication and atropine standard-curve samples. For medications that showed detectable AA, average steady-state peak plasma and serum concentrations (C(max)) in older adults were used to estimate relationships between in vitro dose and AA. All results are reported in pmol/mL of atropine equivalents. At typical doses administered to older adults, amitriptyline, atropine, clozapine, dicyclomine, doxepin, L-hyoscyamine, thioridazine, and tolterodine demonstrated AA exceeding 15 pmol/mL. Chlorpromazine, diphenhydramine, nortriptyline, olanzapine, oxybutynin, and paroxetine had AA values of 5 to 15 pmol/mL. Citalopram, escitalopram, fluoxetine, lithium, mirtazapine, quetiapine, ranitidine, and temazepam had values less than 5 pmol/mL. Amoxicillin, celecoxib, cephalexin, diazepam, digoxin, diphenoxylate, donepezil, duloxetine, fentanyl, furosemide, hydrocodone, lansoprazole, levofloxacin, metformin, phenytoin, propoxyphene, and topiramate demonstrated AA only at the highest concentrations tested (patients with above-average C(max) values, who receive higher doses, or are frail may show AA). The remainder of the medications investigated did not demonstrate any AA at the concentrations examined. Psychotropic medications were particularly likely to demonstrate AA. Each of the drug classifications investigated (e.g., antipsychotic, cardiovascular) had at least one medication that demonstrated AA at therapeutic doses. Clinicians can use this information when choosing between equally efficacious medications, as well as in assessing overall anticholinergic burden.
Abstract: OBJECTIVES: To examine the longitudinal relationship between cumulative exposure to anticholinergic medications and memory and executive function in older men. DESIGN: Prospective cohort study. SETTING: A Department of Veterans Affairs primary care clinic. PARTICIPANTS: Five hundred forty-four community-dwelling men aged 65 and older with diagnosed hypertension. MEASUREMENTS: The outcomes were measured using the Hopkins Verbal Recall Test (HVRT) for short-term memory and the instrumental activity of daily living (IADL) scale for executive function at baseline and during follow-up. Anticholinergic medication use was ascertained using participants' primary care visit records and quantified as total anticholinergic burden using a clinician-rated anticholinergic score. RESULTS: Cumulative exposure to anticholinergic medications over the preceding 12 months was associated with poorer performance on the HVRT and IADLs. On average, a 1-unit increase in the total anticholinergic burden per 3 months was associated with a 0.32-point (95% confidence interval (CI)= 0.05-0.58) and 0.10-point (95% CI=0.04-0.17) decrease in the HVRT and IADLs, respectively, independent of other potential risk factors for cognitive impairment, including age, education, cognitive and physical function, comorbidities, and severity of hypertension. The association was attenuated but remained statistically significant with memory (0.29, 95% CI=0.01-0.56) and executive function (0.08, 95% CI=0.02-0.15) after further adjustment for concomitant non-anticholinergic medications. CONCLUSION: Cumulative anticholinergic exposure across multiple medications over 1 year may negatively affect verbal memory and executive function in older men. Prescription of drugs with anticholinergic effects in older persons deserves continued attention to avoid deleterious adverse effects.
Abstract: BACKGROUND: Cognitive decline is common in Parkinson's disease (PD). Although some of the aetiological factors are known, it is not yet known whether drugs with anticholinergic activity (AA) contribute to this cognitive decline. Such knowledge would provide opportunities to prevent acceleration of cognitive decline in PD. OBJECTIVE: To study whether the use of agents with anticholinergic properties is an independent risk factor for cognitive decline in patients with PD. METHODS: A community-based cohort of patients with PD (n=235) were included and assessed at baseline. They were reassessed 4 and 8 years later. Cognition was assessed using the Mini-Mental State Examination (MMSE). A detailed assessment of the AA of all drugs prescribed was made, and AA was classified according to a standardised scale. Relationships between cognitive decline and AA load and duration of treatment were assessed using bivariate and multivariate statistical analyses. RESULTS: More than 40% used drugs with AA at baseline. During the 8-year follow-up, the cognitive decline was higher in those who had been taking AA drugs (median decline on MMSE 6.5 points) compared with those who had not taken such drugs (median decline 1 point; p=0.025). In linear regression analyses adjusting for age, baseline cognition and depression, significant associations with decline on MMSE were found for total AA load (standardised beta=0.229, p=0.04) as well as the duration of using AA drugs (standardised beta 0.231, p=0.032). CONCLUSION: Our findings suggest that there is an association between anticholinergic drug use and cognitive decline in PD. This may provide an important opportunity for clinicians to avoid increasing progression of cognitive decline by avoiding drugs with AA. Increased awareness by clinicians is required about the classes of drugs that have anticholinergic properties.
Abstract: We identify here for the first time the low-affinity cytochrome P450 (P450) isoforms that metabolize paroxetine, using cDNA-expressed human P450s measuring substrate depletion and paroxetine-catechol (product) formation by liquid chromatography-tandem mass spectrometry. CYP1A2, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 were identified as paroxetine-catechol-forming P450 isoforms, and CYP2C19 and CYP2D6 were identified as metabolizing P450 isoforms by substrate depletion. Michaelis-Menten constants K(m) and V(max) were determined by product formation and substrate depletion. Using selective inhibitory studies and a relative activity factor approach for pooled and single-donor human liver microsomes, we confirmed involvement of the identified P450 isoforms for paroxetine-catechol formation at 1 and 20 muM paroxetine. In addition, we used the population-based simulator Simcyp to estimate the importance of the identified paroxetine-metabolizing P450 isoforms for human metabolism, taking mechanism-based inhibition into account. The amount of active hepatic CYP2D6 and CYP3A4 (not inactivated by mechanism-based inhibition) was also estimated by Simcyp. For extensive and poor metabolizers of CYP2D6, Simcyp-estimated pharmacokinetic profiles were in good agreement with those reported in published in vivo studies. Considering the kinetic parameters, inhibition results, relative activity factor calculations, and Simcyp simulations, CYP2D6 (high affinity) and CYP3A4 (low affinity) are most likely to be the major contributors to paroxetine metabolism in humans. For some individuals CYP1A2 could be of importance for paroxetine metabolism, whereas the importance of CYP2C19 and CYP3A5 is probably limited.
Abstract: BACKGROUND/AIMS: The nature and extent of adverse cognitive effects due to the prescription of anticholinergic drugs in older people with and without dementia is unclear. METHODS: We calculated the anticholinergic load (ACL) of medications taken by participants of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing, a cohort of 211 Alzheimer's disease (AD) patients, 133 mild cognitive impairment (MCI) patients and 768 healthy controls (HC) all aged over 60 years. The association between ACL and cognitive function was examined for each diagnostic group (HC, MCI, AD). RESULTS: A high ACL within the HC group was associated with significantly slower response speeds for the Stroop color and incongruent trials. No other significant relationships between ACL and cognition were noted. CONCLUSION: In this large cohort, prescribed anticholinergic drugs appeared to have modest effects upon psychomotor speed and executive function, but not on other areas of cognition in healthy older adults.
Abstract: INTRODUCTION: Many psychotropic drugs can delay cardiac repolarization and thereby prolong the rate-corrected QT interval (QTc). A prolonged QTc often arouses concern in clinical practice, as it can be followed, in rare cases, by the life-threatening polymorphic ventricular tachyarrhythmia called torsade de pointes (TdP). METHOD: We searched PubMed for pertinent literature on the risk of QTc prolongation and/or TdP associated with commonly used psychotropic drugs. RESULTS: Thioridazine and ziprasidone confer the highest risk of QTc prolongation and/or TdP. There is also a clinically significant risk associated with haloperidol given intravenously in high doses. TdP has been reported in a few cases in association with the use of newer antipsychotic drugs (mainly quetiapine and amisulpride), most of the tri- and tetracyclic antidepressants, and the selective monoamine reuptake inhibitors citalopram, fluoxetine, paroxetine, and venlafaxine. As a rule, however, QTc prolongation and/or TdP occur only in the presence of multiple additional risk factors, such as age over 65 years, pre-existing cardiovascular disease, bradycardia, female sex, hypokalemia, hypomagnesemia, a supratherapeutic or toxic serum concentration, or the simultaneous administration of other drugs that delay repolarization or interfere with drug metabolism. CONCLUSION: Before prescribing a psychotropic drug, the physician should carefully assess its risks and benefits to avoid this type of adverse reaction, particularly when additional risk factors are present. The ECG and electrolytes should be regularly monitored in patients taking psychotropic drugs.
Abstract: OBJECTIVE: To report QT prolongation potential in selective serotonin reuptake inhibitors (SSRIs) in order to advise clinicians on safe use of SSRIs other than citalopram in light of citalopram warnings. DATA SOURCES: Primary literature and case reports were identified through a systematic search. Data from drug manufacturers, package inserts, and the ArizonaCERT database were also utilized. STUDY SELECTION AND DATA EXTRACTION: English-language studies and case reports were included. DATA SYNTHESIS: Studies demonstrate possible dose-related clinically significant QT prolongation with escitalopram. Fluoxetine, fluvoxamine, and sertraline at traditional doses demonstrate a lack of clinically significant increases in QTc in the majority of studies. Further, paroxetine monotherapy shows a lack of clinically significant QTc prolongation in all studies. However, case reports or reporting tools still link these SSRIs with QTc prolongation. Fluoxetine, escitalopram, and sertraline used in post-acute coronary syndrome patients did not demonstrate risk of QTc prolongation. CONCLUSION: For clinicians who choose not to use citalopram due to recent Food and Drug Administration (FDA) recommendations, other antidepressants within this class may be considered. When citalopram is not utilized based on risk factors for TdP, use of escitalopram is not likely the safest alternative. Based on current literature, fluoxetine, fluvoxamine, and sertraline appear to have similar, low risk for QT prolongation, and paroxetine appears to have the lowest risk. However, there are significant limitations in interpreting the studies, including varying definitions of significant QT prolongation. Therefore, choice of an alternative SSRI should be based on individual risk factors for arrhythmias and other patient-specific factors.
Abstract: Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.
Abstract: The aim of this work was to predict the extent of Cytochrome P450 2D6 (CYP2D6)-mediated drug-drug interactions (DDIs) in different CYP2D6 genotypes using physiologically-based pharmacokinetic (PBPK) modeling. Following the development of a new duloxetine model and optimization of a paroxetine model, the effect of genetic polymorphisms on CYP2D6-mediated intrinsic clearances of dextromethorphan, duloxetine, and paroxetine was estimated from rich pharmacokinetic profiles in activity score (AS)1 and AS2 subjects. We obtained good predictions for the dextromethorphan-duloxetine interaction (Ratio of predicted over observed area under the curve (AUC) ratio (R) 1.38-1.43). Similarly, the effect of genotype was well predicted, with an increase of area under the curve ratio of 28% in AS2 subjects when compared with AS1 (observed, 33%). Despite an approximately twofold underprediction of the dextromethorphan-paroxetine interaction, an Rof 0.71 was obtained for the effect of genotype on the area under the curve ratio. Therefore, PBPK modeling can be successfully used to predict gene-drug-drug interactions (GDDIs). Based on these promising results, a workflow is suggested for the generic evaluation of GDDIs and DDIs that can be applied in other situations.