Avvisi di avvertenza
Estensione di tempo QT
Effetti avversi del farmaco
Varianti ✨Per la valutazione computazionalmente intensiva delle varianti, scegli l'abbonamento standard a pagamento.
Aree di applicazione
Spiegazioni per i pazienti
Avvisi di avvertenza
Non abbiamo ulteriori avvertenze per la combinazione di montelukast e cimetidina. Si prega di consultare anche le informazioni specialistiche pertinenti.
|Montelukast||1.06 [1.06,10.68] 1||1.06|
I cambiamenti nell'esposizione menzionati si riferiscono ai cambiamenti nella curva concentrazione plasmatica-tempo [AUC]. L'esposizione alla montelukast aumenta al 106%, se combinato con cimetidina (106%). Non abbiamo rilevato alcun cambiamento nell'esposizione alla cimetidina. Al momento non possiamo stimare l'influenza della montelukast.
I parametri farmacocinetici della popolazione media sono utilizzati come punto di partenza per il calcolo delle singole variazioni di esposizione dovute alle interazioni.
La montelukast ha una biodisponibilità orale media [ F ] del 64%, motivo per cui i livelli plasmatici massimi [Cmax] tendono a cambiare con un'interazione. L'emivita terminale [ t12 ] è piuttosto breve a 4.1 ore e i livelli plasmatici costanti [ Css ] vengono raggiunti rapidamente. Il legame proteico [ Pb ] è molto forte al 99.7% e il volume di distribuzione [ Vd ] è piccolo a 10 litri, Il metabolismo avviene tramite CYP2C8, CYP2C9 e CYP3A4, tra gli altri e il trasporto attivo avviene in particolare tramite OATP1B1.
La cimetidina ha una biodisponibilità orale media [ F ] del 65%, motivo per cui i livelli plasmatici massimi [Cmax] tendono a cambiare con un'interazione. L'emivita terminale [ t12 ] è piuttosto breve a 1.6333333 ore e i livelli plasmatici costanti [ Css ] vengono raggiunti rapidamente. Il legame proteico [ Pb ] è molto debole al 19% e il volume di distribuzione [ Vd ] è molto grande a 91 litri. Il metabolismo non avviene tramite i comuni citocromi e il trasporto attivo avviene in parte tramite BCRP e PGP.
|Effetti serotoninergici a||0||Ø||Ø|
Valutazione: Secondo le nostre conoscenze, né la montelukast né la cimetidina aumentano l'attività serotoninergica.
|Kiesel & Durán b||1||Ø||+|
Raccomandazione: A scopo precauzionale, occorre prestare attenzione ai sintomi anticolinergici, soprattutto dopo aver aumentato la dose ea dosi nel range terapeutico superiore.
Valutazione: La cimetidina ha solo un lieve effetto sul sistema anticolinergico. Il rischio di sindrome anticolinergica con questo farmaco è piuttosto basso se il dosaggio è nel range usuale. Secondo i nostri risultati, la montelukast non aumenta l'attività anticolinergica.
Estensione di tempo QT
Raccomandazione: Assicurati che i fattori di rischio influenzabili siano ridotti al minimo. Disturbi elettrolitici come bassi livelli di calcio, potassio e magnesio devono essere compensati. Deve essere utilizzata la dose minima efficace di cimetidina.
Valutazione: La cimetidina può potenzialmente prolungare il tempo dell'intervallo QT e in presenza di fattori di rischio, possono essere preferite le aritmie di tipo torsioni di punta. Non conosciamo alcun potenziale di prolungamento dell'intervallo QT per la montelukast.
Effetti collaterali generali
|Effetti collaterali||∑ frequenza||mon||cim|
|Dolore addominale||2.0 %||2.0||n.a.|
|Mal di testa||1.0 %||+||n.a.|
|Secrezione nasale||1.0 %||+||n.a.|
|Infezione delle vie respiratorie superiori||1.0 %||+||n.a.|
Comportamento aggressivo: montelukast
Sulla base delle vostre
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: 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: 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: According to published in vitro studies, cytochrome P450 3A4 catalyzes montelukast 21-hydroxylation (M5 formation), whereas CYP2C9 catalyzes 36-hydroxylation (M6), the primary step in the main metabolic pathway of montelukast. However, montelukast is a selective competitive CYP2C8 inhibitor, and our recent in vivo studies suggest that CYP2C8 is involved in its metabolism. We therefore reevaluated the contributions of different cytochrome P450 (P450) enzymes, particularly that of CYP2C8, to the hepatic microsomal metabolism of montelukast using clinically relevant substrate concentrations in vitro. The effects of P450 isoform inhibitors on montelukast metabolism were examined using pooled human liver microsomes, and montelukast oxidations by human recombinant CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 were investigated. The results verified the central role of CYP3A4 in M5 formation. The CYP2C8 inhibitors gemfibrozil 1-O-β glucuronide and trimethoprim inhibited the depletion of 0.02 μM montelukast and formation of M6 from 0.05 μM montelukast more potently than did the CYP2C9 inhibitor sulfaphenazole. Likewise, recombinant CYP2C8 catalyzed montelukast depletion and M6 formation at a 6 times higher intrinsic clearance than did CYP2C9, whereas other P450 isoforms produced no M6. On the basis of depletion of 0.02 μM montelukast, CYP2C8 was estimated to account for 72% of the oxidative metabolism of montelukast in vivo, with a 16% contribution for CYP3A4 and 12% for CYP2C9. Moreover, CYP2C8 catalyzed the further metabolism of M6 more actively than did any other P450. In conclusion, CYP2C8 plays a major role in the main metabolic pathway of montelukast at clinically relevant montelukast concentrations in vitro.
Abstract: Montelukast, a leukotriene receptor antagonist commonly prescribed for treatment of asthma, is primarily metabolized by cytochrome P450 (CYP)2C8, and has been suggested as a probe substrate for investigating CYP2C8 activity in vivo. We evaluated the quantitative role of hepatic uptake transport in its pharmacokinetics and drug-drug interactions (DDIs). Montelukast was characterized with significant active uptake in human hepatocytes, and showed affinity towards organic anion transporting polypeptides (OATPs) in transfected cell systems. Single-dose rifampicin, an OATP inhibitor, decreased montelukast clearance in rats and monkeys. Clinical DDIs of montelukast were evaluated using physiologically based pharmacokinetic modeling; and simulation of the interactions with gemfibrozil-CYP2C8 and OATP1B1/1B3 inhibitor, clarithromycin-CYP3A and OATP1B1/1B3 inhibitor, and itraconazole-CYP3A inhibitor, implicated OATPs-CYP2C8-CYP2C8 interplay as the primary determinant of montelukast pharmacokinetics. In conclusion, hepatic uptake plays a key role in the pharmacokinetics of montelukast, which should be taken into account when interpreting clinical interactions.
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.