Treatment with paliperidone in children with behavior disorders previously treated with risperidone: an open-label trial

Initial severity and efficacy of risperidone in autism: Results from the RUPP trial

Background

Risperidone is a common psychopharmacological treatment for irritability in autism spectrum disorder (ASD). It is not well-established how effective risperidone is across the initial symptom severity range. This study aims to examine the influence of baseline severity on the efficacy of risperidone in the treatment of ASD.

Methods

Participants were from the NIMH funded RUPP multisite, randomized, double-blind trial that compared risperidone to placebo to treat autistic disorder with severe tantrums, aggression, or self-injury. Participants were aged 5 to 17, and randomly assigned to risperidone (n = 49) or placebo (n = 52). Baseline and change scores were computed with the Aberrant Behavior Checklist (ABC) parent assessed scales with irritability as the primary outcome, as well as the clinician assessed ABC Irritability subscale, and Clinical Global Impression Scale.

Results

The relationship between baseline severity and change scores for the risperdone and placebo groups was examined with eight competing three-level mixed-effects models for repeated measure models. Significant (P < 0.01) interactions between treatment and baseline severity were observed for parent ABC ratings of irritability and lethargy only. Greater magnitudes of the differences between risperidone and placebo were observed from moderate to very severe baseline severity on irritability and lethargy. Initial severity values over approximately 30 had a strong effect on symptom change [irritability: effect size (ES) = 1.9, number needed to treat (NNT) = 2, lethargy ES = 0.9, NNT = 5].

Conclusions

Parents may expect benefits of risperidone on irritability and lethargy with moderate to severe symptoms of ASD.

Trial registration

Registry name: ClinicalTrials.gov, trial identifier: NCT00005014, URL: http://www.clinicaltrials.gov/ct2/show/NCT00005014?term=NCT00005014&rank=1, registered on March 31, 2000.

Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets

The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and artefactual trends. To address these problems, we mapped drugs to their ingredients and used natural language processing to classify and correlate drug events. Our analysis exposed key idiosyncrasies in FAERS, for example reports of thalidomide causing a deadly ADR when used against myeloma, a likely result of the disease itself; multiplications of the same report, unjustifiably increasing its importance; correlation of reported ADRs with public events, regulatory announcements, and with publications. Comparing the pharmacological, pharmacokinetic, and clinical ADR profiles of methylphenidate, aripiprazole, and risperidone, and of kinase drugs targeting the VEGF receptor, demonstrates how underlying molecular mechanisms can emerge from ADR co-analysis. The precautions and methods we describe may enable investigators to avoid confounding chemistry-based associations and reporting biases in FAERS, and illustrate how comparative analysis of ADRs can reveal underlying mechanisms.

DOI:http://dx.doi.org/10.7554/eLife.25818.001

New treatments are tested in clinical trials before they are licensed for use in patients, but until the drugs are available for prescribing it’s not always possible to identify every side effect. When the drugs enter the clinic, they might be prescribed to patients with multiple medical conditions, or combined with other treatments. The drugs may also be taken for longer periods of time than tested in trials. It is therefore common for new adverse reactions to emerge after a drug is in widespread use.

The FDA Adverse Event Reporting System (FAERS) is a surveillance system used in the United States for reporting drug side effects after new treatments have been licensed. Healthcare professionals and patients can submit reports to the database, logging the adverse drug reactions that they have experienced.

FAERS currently contains over 8.5 million entries, and is growing all the time. However, Maciejewski et al. show that the database has several shortcomings that are reducing its usefulness. For instance, on average any given drug will have 16 different names in the system; this makes it challenging to group all of the reported side effects so that trends and patterns can be correctly seen.

To address this first problem, Maciejewski et al. grouped together drugs according to their active ingredients, rather than their name. This made it much easier to account for subsequent, and more crucial conflating factors such as multiple reports for the same adverse event and patient, or cases where adverse reactions were confused with the diseases that the drugs are trying to treat. For example, diabetes was listed as a side effect for drugs used to treat diabetes.

Building on this cleaned-up dataset, Maciejewski et al. monitored how adverse event signals evolve over time and uncovered biases that were hard to see otherwise. For example, side-effects were reported more often when drugs were in the news. More strikingly, this bias affected not only the drug in question, but also other drugs that acted in the same way or on the same molecular target.

The computational method developed by Maciejewski et al. allows the data in FAERS to be combined and corrected, making easier to evaluate the safety of different medicines. The link between adverse side effects and the molecular targets of the drug, via the ingredient’s chemical structure, furthermore makes it possible to analyze such clinical data reliably by using chemical and genetic information. In the future, this method could also help to identify previously unknown side effects and the biological mechanisms behind them. This could help researchers to develop new drugs with improved side effect profiles.

DOI:http://dx.doi.org/10.7554/eLife.25818.002

The pharmacological treatment of aggression in children and adolescents with conduct disorder. Do callous-unemotional traits modulate the efficacy of medication?

BACKGROUND

Children and adolescents with conduct disorder (CD) show repetitive and persistent patterns of aggressive behaviour and the more severe forms are often associated with callous-unemotional (CU) traits.

OBJECTIVES

To systematically review and, where data are adequate, conduct meta-analyses on the efficacy of medication on aggression in children and adolescent with CD considering the impact of CU traits.

RESULTS

Few studies have investigated patients with CD as primary diagnosis, and few of these have discriminated between different types of aggression or reported measures of CU traits. Methylphenidate and risperidone showed the largest effects on aggression in randomized controlled trials; other antipsychotics showed clinical efficacy on CD but this evidence is mainly revealed by open label trials. There is some low quality evidence to support a small effect of mood stabilizers and other agents. There were only two papers describing the effects of CU traits thus providing inconclusive results.

CONCLUSION

Considering heterogeneity of the disorder, more proof-of-concept clinical studies are needed to define effects of medication and role of CU traits.