A systematic review and empirical analysis of the relation between dose and duration of drug action

Spontaneous recovery from neuromuscular block after a single dose of a muscle relaxant in pediatric patients: A systematic review using a network meta-analytic and meta-regression approach

BACKGROUND

Age-related differences in the pharmacokinetics and pharmacodynamics of neuromuscular blocking agents (NMBAs) and the short duration of many surgical procedures put pediatric patients at risk of postoperative residual curarization (PORC). To date, the duration of neuromuscular blocking agent effect in children has not been analyzed in a quantitative review. The current meta-analysis aimed to compare spontaneous recovery following administration of various types and doses of neuromuscular blocking agents and to quantify the effect of prognostic variables associated with the recovery time in pediatric patients.

METHOD

We searched for randomized controlled trials (RCTs) and controlled clinical trials (CCTs) that compared the time to 25% T1 (t25), from 25% to 75% T1 (RI25-75), and to ≥90% train-of-four (tTOF90) neuromuscular recovery between common neuromuscular blocking agent treatments administered as a single bolus to healthy pediatric participants. We compared spontaneous t25, RI25-75, and tTOF90 between (1) neuromuscular blocking agent treatments and (2) age groups receiving a given neuromuscular blocking agent intervention and anesthesia technique. Bayesian random-effects network and pairwise meta-analyses along with meta-regression were used to evaluate the results.

RESULTS

We used data from 71 randomized controlled trials/controlled clinical trials including 4319 participants. Network meta-analysis allowed for the juxtaposition and ranking of spontaneous t25, RI25-75, and tTOF90 following common neuromuscular blocking agent interventions. For all neuromuscular blocking agents a log-linear relationship between dose and duration of action was found. With the neuromuscular blocking agent treatments studied, the average tTOF90 (mean[CrI95]) in children (>2-11 y) was 41.96 [14.35, 69.50] and 17.06 [5.99, 28.30] min shorter than in neonates (<28 d) and infants (28 d-12 M), respectively. We found a negative log-linear correlation between age and duration of neuromuscular blocking agent effect. The difference in the tTOF90 (mean[CrI95]) between children and other age groups increased by 21.66 [8.82, 34.53] min with the use of aminosteroid neuromuscular blocking agents and by 24.73 [7.92, 41.43] min with the addition of sevoflurane/isoflurane for anesthesia maintenance.

CONCLUSIONS

The times to neuromuscular recovery are highly variable. These can decrease significantly with age and are prolonged when volatile anesthetics are administered. This variability, combined with the short duration of many pediatric surgical procedures, makes quantitative neuromuscular monitoring mandatory even after a single dose of neuromuscular blocking agent.

Methods for meta-analysis of pharmacodynamic dose-response data with application to multi-arm studies of alogliptin

Standard methods for meta-analysis of dose-response data in epidemiology assume a model with a single scalar parameter, such as log-linear relationships between exposure and outcome; such models are implicitly unbounded. In contrast, in pharmacology, multi-parameter models, such as the widely used E_max model, are used to describe relationships that are bounded above and below. We propose methods for estimating the parameters of a dose-response model by meta-analysis of summary data from the results of randomized controlled trials of a drug, in which each trial uses multiple doses of the drug of interest (possibly including dose 0 or placebo). We assume that, for each randomized arm of each trial, the mean and standard error of a continuous response measure and the corresponding allocated dose are available. We consider weighted least squares fitting of the model to the mean and dose pairs from all arms of all studies, and a two-stage procedure in which scalar inverse-variance meta-analysis is performed at each dose, and the dose-response model is fitted to the results by weighted least squares. We then compare these with two further methods inspired by network meta-analysis that fit the model to the contrasts between doses. We illustrate the methods by estimating the parameters of the E_max model to a collection of multi-arm, multiple-dose, randomized controlled trials of alogliptin, a drug for the management of diabetes mellitus, and further examine the properties of the four methods with sensitivity analyses and a simulation study. We find that all four methods produce broadly comparable point estimates for the parameters of most interest, but a single-stage method based on contrasts between doses produces the most appropriate confidence intervals. Although simpler methods may have pragmatic advantages, such as the use of standard software for scalar meta-analysis, more sophisticated methods are nevertheless preferable for their advantages in estimation.

Advancing stem cell therapy from bench to bedside: lessons from drug therapies

The inadequacy of existing therapeutic tools together with the paucity of organ donors have always led medical researchers to innovate the current treatment methods or to discover new ways to cure disease. Emergence of cell-based therapies has provided a new framework through which it has given the human world a new hope. Though relatively a new concept, the pace of advancement clearly reveals the significant role that stem cells will ultimately play in the near future. However, there are numerous uncertainties that are prevailing against the present setting of clinical trials related to stem cells: like the best route of cell administration, appropriate dosage, duration and several other applications. A better knowledge of these factors can substantially improve the effectiveness of disease cure or organ repair using this latest therapeutic tool. From a certain perspective, it could be argued that by considering certain proven clinical concepts and experience from synthetic drug system, we could improve the overall efficacy of cell-based therapies. In the past, studies on synthetic drug therapies and their clinical trials have shown that all the aforementioned factors have critical ascendancy over its therapeutic outcomes. Therefore, based on the knowledge gained from synthetic drug delivery systems, we hypothesize that by employing many of the clinical approaches from synthetic drug therapies to this new regenerative therapeutic tool, the efficacy of stem cell-based therapies can also be improved.

Time of effect duration and administration interval for sitagliptin in patients with kidney failure

A measure correlating the time course of the effect with the time course of concentrations could be helpful in drug dosing. We propose a new equation with explicit solutions for calculating the effect duration. A specific effect fraction is selected (fr) and the time of fractional effect duration (TED.fr) can be derived as a function of the elimination half-life by combining linear elimination kinetics with sigmoid effect dynamics. This new measure is applied to the example of sitagliptin, whose elimination half-life increases from 10.1 to 28.4 h in patients with kidney failure. Under normal multiple-dose conditions, the 24-h sitagliptin administration interval corresponds to a 0.90 time of fractional effect duration (TED.90). A dose reduction to one-fourth or 25 mg every 24 h is proposed for patients with kidney failure; this results in a TED.90 of 45 h, i.e. 21 h longer than the proposed 24-h administration interval (+88 %). The proportional dosing alternative of 100 mg every 96 h would result in a TED.90 of 64 h, which is 32 h less than the 96-h administration interval (-33 %). With a half dose of 50 mg and a doubled administration interval of 48 h, the TED.90 is 51 h in kidney failure, only 3 h longer than the latter administration interval (+6 %). We conclude that our general equation can be applied to rapidly calculate the specific time of effect duration for the different dose schedules.

Using pharmacokinetic principles to optimize pain therapy

Cyclo-oxygenase (COX) inhibitors are widely used to relieve musculoskeletal pain. These agents block the production of prostaglandins (PGs) at sites of inflammation by inhibiting the activity of two COX enzymes necessary for PG production and normal organ homeostasis. Inhibition of PG production at sites unrelated to pain is associated with adverse drug reactions (ADRs). The degree of analgesic efficacy, as well as the incidence and the localization of ADRs, are critically influenced by the pharmacokinetics (absorption, distribution and elimination) of these drugs. Ideally, sufficient and permanent inhibition of COX enzymes should be achieved in target tissues, with minimal ADRs. To minimize underdosing or overdosing, which result in therapeutic failure or ADRs, the COX inhibitor with the most appropriate pharmacokinetic properties should be selected on the basis of a thorough pharmacokinetic-pharmacodynamic analysis. In this Review, the pharmacokinetics of the prevailing COX inhibitors will be discussed and enigmatic aspects of these intensively used drugs will be considered.