PURPOSE:

To undertake a multi-country study to investigate the risk of acute hyperglycaemia with antipsychotic use.

METHODS:

Using a distributed network model with a common minimal data set, we performed a prescription sequence symmetry analysis (PSSA) to investigate the risk of acute hyperglycaemia associated with antipsychotic initiation. Incident insulin prescriptions were used as a proxy indicator of acute hyperglycaemia. Participating countries and population datasets included Australia (300,000 persons), Japan I (300,000 persons), Japan II (200,000 persons), Korea (53 million persons) Taiwan (1 million persons), Sweden (9 million persons), USA-Public (87 million persons) and USA-Private (47 million persons).

RESULTS:

Olanzapine showed a trend towards increased risk in most databases, with a significant association observed in the USA-Public database (Adjusted sequence ratio (ASR) = 1.14; 95% Confidence Interval (CI) 1.10-1.17) and Sweden (ASR = 1.53; 95% CI 1.13-2.06). Null or negative associations were observed for haloperidol, quetiapine and risperidone.

CONCLUSION:

Acute hyperglycaemia appears to be associated with olanzapine use, however, this effect was only observed in two large databases. Despite different patterns of utilization of both antipsychotics and insulin, PSSA analysis results for individual antipsychotic medicines were qualitatively similar across most countries. PSSA, used in conjunction with existing methods, may provide a simple and timely method further supporting multi-national drug safety monitoring. Copyright © 2013 John Wiley & Sons, Ltd.

Biosimilars have been available on the European market since 2006 and experience with their use is increasing. The next wave of biopharmaceuticals that are about to lose patent protection consists of more-complicated products, including many monoclonal antibodies. Guidance has been released on the particulars of a biosimilarity exercise involving these products. Considerable challenges are posed by anticancer products and there is ongoing controversy regarding which basis to establish biosimilarity for such products. An especially challenging product is bevacizumab (Avastin®). Based on data available for the innovator product (bevacizumab) we will discuss strengths and weaknesses of preclinical and clinical models and explore the application of novel endpoints to the biosimilar comparability exercise.

STUDY OBJECTIVE:

To identify predictors of hospital admissions associated with adverse drug events (ADEs) and to determine the preventability of ADEs in patients admitted to two hospitals.

DESIGN:

Prospective observational study.

SETTING:

Medical admission units at two British National Health Service hospitals in the United Kingdom.

PATIENTS:

3904 adults age 16 years or older who were admitted to the two hospitals between June 2006 and November 2007.

MEASUREMENTS AND MAIN RESULTS:

Clinical pharmacists identified hospital admissions associated with drug-related problems by using medical record review, supplemented by patient interview for those identified as having an ADE. The contribution of ADEs to hospital admission and the causality, severity, and preventability of the events were independently assessed by a multidisciplinary clinical team. Multivariate logistic regression was used to identify predictors of hospital admissions associated with ADEs, and a maximum-likelihood multinomial model was used to examine predictors of the preventability of ADEs. Of the 3904 patients included in the analysis, 439 (11.2%) were judged by the review panel to have experienced ADEs. Of these, 209 patients (47.6%) experienced preventable ADEs. Four independent variables were found to have significant relationships with ADE admissions and preventability of ADEs: patient age, length of time since starting new drug, total number of prescription drugs, and hospital site. Drug classes most commonly associated with preventable ADEs were antiplatelet drugs, anticoagulants, diuretics (loop and thiazide diuretics), angiotensin-converting enzyme inhibitors, and antiepileptic drugs.

CONCLUSION:

Adverse drug events are an important cause of hospital admission. Better systems for health care practitioners to identify patients at high risk of preventable hospital admissions associated with ADEs (e.g., age > 65 years old, receiving more than five drugs, and starting new high-risk drugs) should be implemented in order to minimize the risks to patients and the burden on the health care system.

BACKGROUND::

Classifying medication adherence is important for efficiently targeting adherence improvement interventions. The purpose of this study was to evaluate the use of a novel method, group-based trajectory models, for classifying patients by their long-term adherence. RESEARCH

DESIGN:

: We identified patients who initiated a statin between June 1, 2006 and May 30, 2007 in prescription claims from CVS Caremark and evaluated adherence over the subsequent 15 months. We compared several adherence summary measures, including proportion of days covered (PDC) and trajectory models with 2-6 groups, with the observed adherence pattern, defined by monthly indicators of full adherence (defined as having ≥24 d covered of 30). We also compared the accuracy of adherence prediction based on patient characteristics when adherence was defined by either a trajectory model or PDC.

RESULTS::

In 264,789 statin initiators, the 6-group trajectory model summarized long-term adherence best (C=0.938), whereas PDC summarized less well (C=0.881). The accuracy of adherence predictions was similar whether adherence was classified by PDC or by trajectory model.

CONCLUSIONS::

Trajectory models summarized adherence patterns better than traditional approaches and were similarly predicted by covariates. Group-based trajectory models may facilitate targeting of interventions and may be useful to adjust for confounding by health-seeking behavior.

It is well known that abdominal obesity, dyslipidemia, and insulin resistance are highly prevalent in patients receiving maintenance treatment with antipsychotics, but there is limited knowledge about the association between cardiovascular risk factors and treatment with antipsychotic drugs. In this naturalistic study we investigated a sample of 809 antipsychotic-treated patients from Swedish psychosis outpatient teams. Cardiovascular risk factors (eg, metabolic syndrome, homeostasis model assessment of insulin resistance, and low-density lipoprotein values) were measured, and their associations to current antipsychotic pharmacotherapy were studied. Ten antipsychotic drugs were compared in a stepwise logistic regression model. For the patients, the presence of the components of metabolic syndrome ranged from 35% for hyperglycemia to 64% for elevated waist circumference. Hypertriglyceridemia was associated with clozapine (odds ratio [OR] = 1.81, 95% confidence interval [CI] 1.08-3.04), reduced high-density lipoprotein with both clozapine and olanzapine (OR = 1.73, 95% CI 1.01-2.97; and OR = 2.03, 95% CI 1.32-3.13), hypertension with perphenazine (OR = 2.00, 95% CI 1.21-3.59), and hyperglycemia inversely with ziprasidone (OR = 0.21, 95% CI 0.05-0.89) and positively with haloperidol (OR = 2.02, 95% CI 1.18-3.48). There were no significant relationships between any of the antipsychotic drugs and increased waist circumference, homeostasis model assessment of insulin resistance, or low-density lipoprotein levels. In conclusion, treatment with antipsychotic drugs is differentially associated with cardiovascular risk factors, even after adjusting for waist circumference, sex, age, and smoking.

Strategic and legislative efforts to catalyse pharmaceutical innovation may be hampered by a lack of consensus over what characterizes an innovative drug. To help clarify this issue, we conducted an extensive survey on transformative drug development, involving ∼180 expert physicians based at 30 leading US academic medical centres, covering 15 medical specialties. In an iterative Delphi process, the survey participants narrowed a list of all new drugs approved in their fields in the past 25 years and reached consensus over those that they considered to be most transformative, which are presented in this article. Participants were also asked how various factors affected their opinion; they most often invoked the effectiveness and superiority of the drugs over existing alternatives when identifying transformative drug innovation.

AIMS/

HYPOTHESIS:

This study aimed to systematically review what has been reported on the incidence and prevalence of type 2 diabetes in children and adolescents, to scrutinise the methodological issues observed in the included studies and to prepare recommendations for future research and surveillances.

METHODS:

PubMed, the Cochrane Database of Systematic Reviews, Scopus, EMBASE and Web of Science were searched from inception to February 2013. Population-based studies on incidence and prevalence of type 2 diabetes in children and adolescents were summarised and methodologically evaluated. Owing to substantial methodological heterogeneity and considerable differences in study populations a quantitative meta-analysis was not performed.

RESULTS:

Among 145 potentially relevant studies, 37 population-based studies met the inclusion criteria. Variations in the incidence and prevalence rates of type 2 diabetes in children and adolescents were mainly related to age of the study population, calendar time, geographical regions and ethnicity, resulting in a range of 0-330 per 100,000 person-years for incidence rates, and 0-5,300 per 100,000 population for prevalence rates. Furthermore, a substantial variation in the methodological characteristics was observed for response rates (60-96%), ascertainment rates (53-99%), diagnostic tests and criteria used to diagnose type 2 diabetes.

CONCLUSIONS

/

INTERPRETATION:

Worldwide incidence and prevalence of type 2 diabetes in children and adolescents vary substantially among countries, age categories and ethnic groups and this can be explained by variations in population characteristics and methodological dissimilarities between studies.