Design issues in crossover trials involving patients with Parkinson’s disease

Background and objectivesCrossover designs are frequently used to assess treatments for patients with Parkinson’s disease. Typically, two-period two-treatment trials include a washout period between the 2 periods and assume that the washout period is sufficiently long to eliminate carryover effects. A complementary strategy might be to jointly model carryover and treatment effects, though this has rarely been done in Parkinson’s disease crossover studies. The primary objective of this research is to demonstrate a modeling approach that assesses treatment and carryover effects in one unified mixed model analysis and to examine how it performs in a simulation study and a real data analysis example, as compared to other data analytic approaches used in Parkinson’s disease crossover studies.MethodsWe examined how three different methods of analysis (standard crossover t-test, mixed model with a carryover term included in model statement, and mixed model with no carryover term) performed in a simulation study and illustrated the methods in a real data example in Parkinson’s disease.ResultsThe simulation study based on the presence of a carryover effect indicated that mixed models with a carryover term and an unstructured correlation matrix provided unbiased estimates of treatment effect and appropriate type I error. The methods are illustrated in a real data example involving Parkinson’s disease. Our literature review revealed that a majority of crossover studies included a washout period but did not assess whether the washout was sufficiently long to eliminate the possibility of carryover.DiscussionWe recommend using a mixed model with a carryover term and an unstructured correlation matrix to obtain unbiased estimates of treatment effect

Automated telephone communication systems for preventive healthcare and management of long-term conditions

Background Automated telephone communication systems (ATCS) can deliver voice messages and collect health-related information from patients using either their telephone’s touch-tone keypad or voice recognition software. ATCS can supplement or replace telephone contact between health professionals and patients. There are four different types of ATCS: unidirectional (one-way, non-interactive voice communication), interactive voice response (IVR) systems, ATCS with additional functions such as access to an expert to request advice (ATCS Plus) and multimodal ATCS, where the calls are delivered as part of a multicomponent intervention. Objectives To assess the effects of ATCS for preventing disease and managing long-term conditions on behavioural change, clinical, process, cognitive, patient-centred and adverse outcomes. Search methods We searched 10 electronic databases (the Cochrane Central Register of Controlled Trials; MEDLINE; Embase; PsycINFO; CINAHL; Global Health; WHOLIS; LILACS; Web of Science; and ASSIA); three grey literature sources (Dissertation Abstracts, Index to Theses, Australasian Digital Theses); and two trial registries (www.controlled-trials.com; www.clinicaltrials.gov) for papers published between 1980 and June 2015. Selection criteria Randomised, cluster- and quasi-randomised trials, interrupted time series and controlled before-and-after studies comparing ATCS interventions, with any control or another ATCS type were eligible for inclusion. Studies in all settings, for all consumers/carers, in any preventive healthcare or long term condition management role were eligible. Data collection and analysis We used standard Cochrane methods to select and extract data and to appraise eligible studies. Main results We included 132 trials (N = 4,669,689). Studies spanned across several clinical areas, assessing many comparisons based on evaluation of different ATCS types and variable comparison groups. Forty-one studies evaluated ATCS for delivering preventive healthcare, 84 for managing long-term conditions, and seven studies for appointment reminders. We downgraded our certainty in the evidence primarily because of the risk of bias for many outcomes. We judged the risk of bias arising from allocation processes to be low for just over half the studies and unclear for the remainder. We considered most studies to be at unclear risk of performance or detection bias due to blinding, while only 16% of studies were at low risk. We generally judged the risk of bias due to missing data and selective outcome reporting to be unclear. For preventive healthcare, ATCS (ATCS Plus, IVR, unidirectional) probably increase immunisation uptake in children (risk ratio (RR) 1.25, 95% confidence interval (CI) 1.18 to 1.32; 5 studies, N = 10,454; moderate certainty) and to a lesser extent in adolescents (RR 1.06, 95% CI 1.02 to 1.11; 2 studies, N = 5725; moderate certainty). The effects of ATCS in adults are unclear (RR 2.18, 95% CI 0.53 to 9.02; 2 studies, N = 1743; very low certainty). For screening, multimodal ATCS increase uptake of screening for breast cancer (RR 2.17, 95% CI 1.55 to 3.04; 2 studies, N = 462; high certainty) and colorectal cancer (CRC) (RR 2.19, 95% CI 1.88 to 2.55; 3 studies, N = 1013; high certainty) versus usual care. It may also increase osteoporosis screening. ATCS Plus interventions probably slightly increase cervical cancer screening (moderate certainty), but effects on osteoporosis screening are uncertain. IVR systems probably increase CRC screening at 6 months (RR 1.36, 95% CI 1.25 to 1.48; 2 studies, N = 16,915; moderate certainty) but not at 9 to 12 months, with probably little or no effect of IVR (RR 1.05, 95% CI 0.99, 1.11; 2 studies, 2599 participants; moderate certainty) or unidirectional ATCS on breast cancer screening. Appointment reminders delivered through IVR or unidirectional ATCS may improve attendance rates compared with no calls (low certainty). For long-term management, medication or laboratory test adherence provided the most general evidence across conditions (25 studies, data not combined). Multimodal ATCS versus usual care showed conflicting effects (positive and uncertain) on medication adherence. ATCS Plus probably slightly (versus control; moderate certainty) or probably (versus usual care; moderate certainty) improves medication adherence but may have little effect on adherence to tests (versus control). IVR probably slightly improves medication adherence versus control (moderate certainty). Compared with usual care, IVR probably improves test adherence and slightly increases medication adherence up to six months but has little or no effect at longer time points (moderate certainty). Unidirectional ATCS, compared with control, may have little effect or slightly improve medication adherence (low certainty). The evidence suggested little or no consistent effect of any ATCS type on clinical outcomes (blood pressure control, blood lipids, asthma control, therapeutic coverage) related to adherence, but only a small number of studies contributed clinical outcome data. The above results focus on areas with the most general findings across conditions. In condition-specific areas, the effects of ATCS varied, including by the type of ATCS intervention in use. Multimodal ATCS probably decrease both cancer pain and chronic pain as well as depression (moderate certainty), but other ATCS types were less effective. Depending on the type of intervention, ATCS may have small effects on outcomes for physical activity, weight management, alcohol consumption, and diabetes mellitus. ATCS have little or no effect on outcomes related to heart failure, hypertension, mental health or smoking cessation, and there is insufficient evidence to determine their effects for preventing alcohol/ substance misuse or managing illicit drug addiction, asthma, chronic obstructive pulmonary disease, HIV/AIDS, hypercholesterolaemia, obstructive sleep apnoea, spinal cord dysfunction or psychological stress in carers. Only four trials (3%) reported adverse events, and it was unclear whether these were related to the intervention

Association of body mass index with the development of methacholine airway hyperresponsiveness in men: the Normative Aging Study

Background: The rising prevalence of asthma in developed nations may be associated with the rising prevalence of obesity in these same nations. The relationship between body mass index (BMI) and the development of an objective marker for asthma, methacholine airway hyperresponsiveness (AHR), was investigated in adult men. Methods: Sixty one men who had no AHR at initial methacholine challenge testing but who developed AHR about 4 years later and 244 matched controls participated in the study. The effects of initial BMI and change in BMI on development of AHR were examined in conditional logistic regression models. Results: Initial BMI was found to have a non-linear relationship with development of AHR. Compared with men with initial BMI in the middle quintile, men with BMI in the lowest quintile (BMI=19.8–24.3 kg/m(2)) and those with BMI in the highest quintile (BMI >29.4 kg/m(2)) were more likely to develop AHR: OR=7.0 (95% CI 1.8 to 27.7) and OR=10.0 (95% CI 2.6 to 37.9), respectively. These results remained significant after controlling for age, smoking, IgE level, and initial FEV(1). In addition, there was a positive linear relationship between change in BMI over the period of observation and the subsequent development of AHR. Conclusions: In this cohort of adult men, both a low BMI and a high BMI were associated with the development of AHR. For men with a low initial BMI the increased risk for development of AHR appears to be partly mediated by a gain in weight. The effect of BMI on AHR may suggest mechanisms in the observed associations between obesity and asthma

Randomised controlled trial of an automated, interactive telephone intervention (TLC Diabetes) to improve type 2 diabetes management: baseline findings and six-month outcomes

Background: Effective self-management of diabetes is essential for the reduction of diabetes-related complications, as global rates of diabetes escalate. Methods: Randomised controlled trial. Adults with type 2 diabetes (n = 120), with HbA1c greater than or equal to 7.5 %, were randomly allocated (4 × 4 block randomised block design) to receive an automated, interactive telephone-delivered management intervention or usual routine care. Baseline sociodemographic, behavioural and medical history data were collected by self-administered questionnaires and biological data were obtained during hospital appointments. Health-related quality of life (HRQL) was measured using the SF-36. Results: The mean age of participants was 57.4 (SD 8.3), 63 % of whom were male. There were no differences in demographic, socioeconomic and behavioural variables between the study arms at baseline. Over the six-month period from baseline, participants receiving the Australian TLC (Telephone-Linked Care) Diabetes program showed a 0.8 % decrease in geometric mean HbA1c from 8.7 % to 7.9 %, compared with a 0.2 % HbA1c reduction (8.9 % to 8.7 %) in the usual care arm (p = 0.002). There was also a significant improvement in mental HRQL, with a mean increase of 1.9 in the intervention arm, while the usual care arm decreased by 0.8 (p = 0.007). No significant improvements in physical HRQL were observed. Conclusions: These analyses indicate the efficacy of the Australian TLC Diabetes program with clinically significant post-intervention improvements in both glycaemic control and mental HRQL. These observed improvements, if supported and maintained by an ongoing program such as this, could significantly reduce diabetes-related complications in the longer term. Given the accessibility and feasibility of this kind of program, it has strong potential for providing effective, ongoing support to many individuals with diabetes in the future