The possibilities of the use of N-of-1 and do-it-yourself trials in nutritional research.

BACKGROUND: N-of-1 designs gain popularity in nutritional research because of the improving technological possibilities, practical applicability and promise of increased accuracy and sensitivity, especially in the field of personalized nutrition. This move asks for a search of applicable statistical methods. OBJECTIVE: To demonstrate the differences of three popular statistical methods in analyzing treatment effects of data obtained in N-of-1 designs. METHOD: We compare Individual-participant data meta-analysis, frequentist and Bayesian linear mixed effect models using a simulation experiment. Furthermore, we demonstrate the merits of the Bayesian model including prior information by analyzing data of an empirical study on weight loss. RESULTS: The linear mixed effect models are to be preferred over the meta-analysis method, since the individual effects are estimated more accurately as evidenced by the lower errors, especially with lower sample sizes. Differences between Bayesian and frequentist mixed models were found to be small, indicating that they will lead to the same results without including an informative prior. CONCLUSION: For empirical data, the Bayesian mixed model allows the inclusion of prior knowledge and gives potential for population based and personalized inference.

Effect of Caffeine on Attention and Alertness Measured in a Home-Setting, Using Web-Based Cognition Tests.

BACKGROUND: There is an increasing interest among nutritional researchers to perform lifestyle and nutritional intervention studies in a home setting instead of testing subjects in a clinical unit. The term used in other disciplines is 'ecological validity' stressing a realistic situation. This becomes more and more feasible because devices and self-tests that enable such studies are more commonly available. Here, we present such a study in which we reproduced the effect of caffeine on attention and alertness in an at-home setting. OBJECTIVE: The study was aimed to reproduce the effect of caffeine on attention and alertness using a Web-based study environment of subjects, at home, performing different Web-based cognition tests. METHODS: The study was designed as a randomized, placebo-controlled, double-blind, crossover study. Subjects were provided with coffee sachets (2 with and 2 without caffeine). They were also provided with a written instruction of the test days. Healthy volunteers consumed a cup of coffee after an overnight fast. Each intervention was repeated once. Before and 1 hour after coffee consumption subjects performed Web-based cognitive performance tests at home, which measured alertness and attention, established by 3 computerized tests provided by QuantifiedMind. Each test was performed for 5 minutes. RESULTS: Web-based recruitment was fast and efficient. Within 2 weeks, 102 subjects applied, of whom 70 were eligible. Of the 66 subjects who started the study, 53 completed all 4 test sessions (80%), indicating that they were able to perform the do it yourself tests, at home, correctly. The Go-No Go cognition test performed at home showed the same significant improvement in reaction time with caffeine as found in controlled studies in a metabolic ward (P=.02). For coding and N-back the second block was performed approximately 10% faster. No effect was seen on correctness. CONCLUSIONS: The study showed that the effects of caffeine consumption on a cognition test in an at-home setting revealed similar results as in a controlled setting. The Go-No Go test applied showed improved results after caffeine intake, similar as seen in clinical trials. This type of study is a fast, reliable, economical, and easy way to demonstrate effectiveness of a supplement and is rapidly becoming a viable alternative for the classical randomized control trial to evaluate life style and nutritional interventions. TRIAL REGISTRATION: Clinicaltrials.gov NCT02061982; https://clinicaltrials.gov/ct2/show/NCT02061982 (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT02061982).

Multi-parameter comparison of a standardized mixed meal tolerance test in healthy and type 2 diabetic subjects: the PhenFlex challenge.

BACKGROUND: A key feature of metabolic health is the ability to adapt upon dietary perturbations. Recently, it was shown that metabolic challenge tests in combination with the new generation biomarkers allow the simultaneous quantification of major metabolic health processes. Currently, applied challenge tests are largely non-standardized. A systematic review defined an optimal nutritional challenge test, the "PhenFlex test" (PFT). This study aimed to prove that PFT modulates all relevant processes governing metabolic health thereby allowing to distinguish subjects with different metabolic health status. Therefore, 20 healthy and 20 type 2 diabetic (T2D) male subjects were challenged both by PFT and oral glucose tolerance test (OGTT). During the 8-h response time course, 132 parameters were quantified that report on 26 metabolic processes distributed over 7 organs (gut, liver, adipose, pancreas, vasculature, muscle, kidney) and systemic stress. RESULTS: In healthy subjects, 110 of the 132 parameters showed a time course response. Patients with T2D showed 18 parameters to be significantly different after overnight fasting compared to healthy subjects, while 58 parameters were different in the post-challenge time course after the PFT. This demonstrates the added value of PFT in distinguishing subjects with different health status. The OGTT and PFT response was highly comparable for glucose metabolism as identical amounts of glucose were present in both challenge tests. Yet the PFT reports on additional processes, including vasculature, systemic stress, and metabolic flexibility. CONCLUSION: The PFT enables the quantification of all relevant metabolic processes involved in maintaining or regaining homeostasis of metabolic health. Studying both healthy subjects and subjects with impaired metabolic health showed that the PFT revealed new processes laying underneath health. This study provides the first evidence towards adopting the PFT as gold standard in nutrition research.

Assessment of Determinants of Emission Potentially Affecting the Concentration of Airborne Nano-Objects and Their Agglomerates and Aggregates.

Background: Nano-specific inhalation exposure models could potentially be effective tools to assess and control worker exposure to nano-objects, and their aggregates and agglomerates (NOAA). However, due to the lack of reliable and consistent collected NOAA exposure data, the scientific basis for validation of the existing NOAA exposure models is missing or limited. The main objective of this study was to gain more insight into the effect of various determinants underlying the potential on the concentration of airborne NOAA close to the source with the purpose of providing a scientific basis for existing and future exposure inhalation models. Method: Four experimental studies were conducted to investigate the effect of 11 determinants of emission on the concentration airborne NOAA close to the source during dumping of ~100% nanopowders. Determinants under study were: nanomaterial, particle size, dump mass, height, rate, ventilation rate, mixing speed, containment, particle surface coating, moisture content of the powder, and receiving surface. The experiments were conducted in an experimental room (19.5 m3) with well-controlled environmental and ventilation conditions. Particle number concentration and size distribution were measured using real-time measurement devices. Results: Dumping of nanopowders resulted in a higher number concentration and larger particles than dumping their reference microsized powder (P < 0.05). Statistically significant more and larger particles were also found during dumping of SiO2 nanopowder compared to TiO2/Al2O3 nanopowders. Particle surface coating did not affect the number concentration but on average larger particles were found during dumping of coated nanopowders. An increase of the powder's moisture content resulted in less and smaller particles in the air. Furthermore, the results indicate that particle number concentration increases with increasing dump height, rate, and mass and decreases when ventilation is turned on. Discussion: These results give an indication of the direction and magnitude of the effect of the studied determinants on concentrations close to the source and provide a scientific basis for (further) development of existing and future NOAA inhalation exposure models.

Predictors of Diet-Induced Weight Loss in Overweight Adults with Type 2 Diabetes.

AIMS: A very low calorie diet improves the metabolic regulation of obesity related type 2 diabetes, but not for all patients, which leads to frustration in patients and professionals alike. The aim of this study was to develop a prediction model of diet-induced weight loss in type 2 diabetes. METHODS: 192 patients with type 2 diabetes and BMI>27 kg/m2 from the outpatient diabetes clinic of the Erasmus Medical Center underwent an 8-week very low calorie diet. Baseline demographic, psychological and physiological parameters were measured and the C-index was calculated of the model with the largest explained variance of relative weight loss using backward linear regression analysis. The model was internally validated using bootstrapping techniques. RESULTS: Weight loss after the diet was 7.8±4.6 kg (95%CI 7.2-8.5; p<0.001) and was independently associated with the baseline variables fasting glucose (B = -0.33 (95%CI -0.49, -0.18), p = 0.001), anxiety (HADS; B = -0.22 (95%CI -0.34, -0.11), p = 0.001), numb feeling in extremities (B = 1.86 (95%CI 0.85, 2.87), p = 0.002), insulin dose (B = 0.01 (95%CI 0.00, 0.02), p = 0.014) and waist-to-hip ratio (B = 6.79 (95%CI 2.10, 11.78), p = 0.003). This model explained 25% of the variance in weight loss. The C-index of this model to predict successful (≥5%) weight loss was 0.74 (95%CI 0.67-0.82), with a sensitivity of 0.93 (95% CI 0.89-0.97) and specificity of 0.29 (95% CI 0.16-0.42). When only the obese T2D patients (BMI≥30 kg/m2; n = 181) were considered, age also contributed to the model (B = 0.06 (95%CI 0.02, 0.11), p = 0.008), whereas waist-to-hip ratio did not. CONCLUSIONS: Diet-induced weight loss in overweight adults with T2D was predicted by five baseline parameters, which were predominantly diabetes related. However, failure seems difficult to predict. We propose to test this prediction model in future prospective diet intervention studies in patients with type 2 diabetes.

Evaluation of Decision Rules in a Tiered Assessment of Inhalation Exposure to Nanomaterials.

Tiered or stepwise approaches to assess occupational exposure to nano-objects, and their agglomerates and aggregates have been proposed, which require decision rules (DRs) to move to a next tier, or terminate the assessment. In a desk study the performance of a number of DRs based on the evaluation of results from direct reading instruments was investigated by both statistical simulations and the application of the DRs to real workplace data sets. A statistical model that accounts for autocorrelation patterns in time-series, i.e. autoregressive integrated moving average (ARIMA), was used as 'gold' standard. The simulations showed that none of the proposed DRs covered the entire range of simulated scenarios with respect to the ARIMA model parameters, however, a combined DR showed a slightly better agreement. Application of the DRs to real workplace datasets (n = 117) revealed sensitivity up to 0.72, whereas the lowest observed specificity was 0.95. The selection of the most appropriate DR is very much dependent on the consequences of the decision, i.e. ruling in or ruling out of scenarios for further evaluation. Since a basic assessment may also comprise of other type of measurements and information, an evaluation logic was proposed which embeds the DRs, but furthermore supports decision making in view of a tiered-approach exposure assessment.

A microsimulation model for the development and progression of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a chronic lung disease that is thought to affect over one million people in Great Britain. The main factor contributing to the development of COPD is tobacco smoke. This paper presents a microsimulation model for the development of COPD, incorporating population dynamics and trends in smoking. The model simulates a population longitudinally throughout their lifetimes, providing projections of future COPD prevalence and evaluation of the effects of changes in risk factor prevalence such as smoking. Sensitivity analysis provides information on the most influential model parameters. The model-predicted prevalence of COPD in 2040 was 17% in males over the age of 35 years (13% amongst non-smokers and 22% amongst smokers), and a modest decline over the next 25 years due to recent trends in smoking rates. The simulation model provides us with valuable information on current and future trends in COPD in Great Britain. It was developed primarily to enable easy extension to evaluate the effects of occupational and environmental exposures on lung function and the prevalence of COPD and to allow evaluation of interventions, such as introducing health surveillance or policy changes. As longitudinal studies for investigating COPD are difficult due to the lengthy follow-up time required and the potentially large number of drop-outs, we anticipate that the model will provide a valuable tool for health impact assessment. An extended model for occupational exposures is under development and will be presented in a subsequent paper.

Effectiveness of a Multidimensional Randomized Control Intervention to Reduce Quartz Exposure Among Construction Workers.

There is little evidence with respect to the effectiveness of intervention programs that focus on the reduction of occupational quartz exposure in the construction industry. This article evaluates the effectiveness of a multidimensional intervention which was aimed at reducing occupational quartz exposure among construction workers by increasing the use of technical control measures. Eight companies participating in the cluster randomized controlled trial were randomly allocated to the intervention (four companies) or control condition (four companies). The multidimensional intervention included engineering, organizational, and behavioural elements at both organizational and individual level. Full-shift personal quartz exposure measurements and detailed observations were conducted before and after the intervention among bricklayers, carpenters, concrete drillers, demolishers, and tuck pointers (n = 282). About 59% of these workers measured at baseline were reassessed during follow-up. Bayesian hierarchical models were used to evaluate the intervention effect on exposure levels. Concrete drillers in the intervention group used technical control measures, particularly water suppression, for a significantly greater proportion of the time spent on abrasive tasks during follow-up compared to baseline (93 versus 62%; P < 0.05). A similar effect, although not statistically significant, was observed among demolishers. A substantial overall reduction in quartz exposure (73 versus 40% in the intervention and control group respectively; P < 0.001) was observed for concrete drillers, demolishers, and tuck pointers. The decrease in exposure in the intervention group compared to controls was significantly larger for demolishers and tuck pointers, but not for concrete drillers. The observed effect could at least partly be explained by the introduced interventions; the statistically significant increased use of control measures among concrete drillers explains the observed effect to some extent in this job category only. Sensitivity analyses indicated that the observed decrease in exposure may also partly be attributable to changes in work location and abrasiveness of the tasks performed. Despite the difficulties in assessing the exact magnitude of the intervention, this study showed that the structured intervention approach at least partly contributed to a substantial reduction in quartz exposure among high exposed construction workers.

Improving clinical trial efficiency by biomarker-guided patient selection.

BACKGROUND: In many therapeutic areas, individual patient markers have been identified that are associated with differential treatment response. These markers include both baseline characteristics, as well as short-term changes following treatment. Using such predictive markers to select subjects for inclusion in randomized clinical trials could potentially result in more targeted studies and reduce the number of subjects to recruit. METHODS: This study compared three trial designs on the sample size needed to establish treatment efficacy across a range of realistic scenarios. A conventional parallel group design served as the point of reference, while the alternative designs selected subjects on either a baseline characteristic or an early improvement after a short active run-in phase. Data were generated using a model that characterized the effect of treatment on survival as a combination of a primary effect, an interaction with a baseline marker and/or an early marker improvement. A representative scenario derived from empirical data was also evaluated. RESULTS: Simulations showed that an active run-in design could substantially reduce the number of subjects to recruit when improvement during active run-in was a reliable predictor of differential treatment response. In this case, the baseline selection design was also more efficient than the parallel group design, but less efficient than the active run-in design with an equally restricted population. For most scenarios, however, the advantage of the baseline selection design was limited. CONCLUSIONS: An active run-in design could substantially reduce the number of subjects to recruit in a randomized clinical trial. However, just as with the baseline selection design, generalizability of results may be limited and implementation could be difficult.

fMRI guided rTMS evidence for reduced left prefrontal involvement after task practice.

INTRODUCTION: Cognitive tasks that do not change the required response for a stimulus over time ('consistent mapping') show dramatically improved performance after relative short periods of practice. This improvement is associated with reduced brain activity in a large network of brain regions, including left prefrontal and parietal cortex. The present study used fMRI-guided repetitive transcranial magnetic stimulation (rTMS), which has been shown to reduce processing efficacy, to examine if the reduced activity in these regions also reflects reduced involvement, or possibly increased efficiency. METHODS: First, subjects performed runs of a Sternberg task in the scanner with novel or practiced target-sets. This data was used to identify individual sites for left prefrontal and parietal peak brain activity, as well as to examine the change in activity related to practice. Outside of the scanner, real and sham rTMS was applied at left prefrontal and parietal cortex to examine their involvement novel and practiced conditions. RESULTS: Prefrontal as well as parietal rTMS significantly reduced target accuracy for novel targets. Prefrontal, but not parietal, rTMS interference was significantly lower for practiced than novel target-sets. rTMS did not affect non-target accuracy, or reaction time in any condition. DISCUSSION: These results show that task practice in a consistent environment reduces involvement of the prefrontal cortex. Our findings suggest that prefrontal cortex is predominantly involved in target maintenance and comparison, as rTMS interference was only detectable for targets. Findings support process switching hypotheses that propose that practice creates the possibility to select a response without the need to compare with target items. Our results also support the notion that practice allows for redistribution of limited maintenance resources.

Optimizing trial design in pharmacogenetics research: comparing a fixed parallel group, group sequential, and adaptive selection design on sample size requirements.

Two-stage clinical trial designs may be efficient in pharmacogenetics research when there is some but inconclusive evidence of effect modification by a genomic marker. Two-stage designs allow to stop early for efficacy or futility and can offer the additional opportunity to enrich the study population to a specific patient subgroup after an interim analysis. This study compared sample size requirements for fixed parallel group, group sequential, and adaptive selection designs with equal overall power and control of the family-wise type I error rate. The designs were evaluated across scenarios that defined the effect sizes in the marker positive and marker negative subgroups and the prevalence of marker positive patients in the overall study population. Effect sizes were chosen to reflect realistic planning scenarios, where at least some effect is present in the marker negative subgroup. In addition, scenarios were considered in which the assumed 'true' subgroup effects (i.e., the postulated effects) differed from those hypothesized at the planning stage. As expected, both two-stage designs generally required fewer patients than a fixed parallel group design, and the advantage increased as the difference between subgroups increased. The adaptive selection design added little further reduction in sample size, as compared with the group sequential design, when the postulated effect sizes were equal to those hypothesized at the planning stage. However, when the postulated effects deviated strongly in favor of enrichment, the comparative advantage of the adaptive selection design increased, which precisely reflects the adaptive nature of the design.

Comparing HAMD(17) and HAMD subscales on their ability to differentiate active treatment from placebo in randomized controlled trials.

BACKGROUND: The 17-item Hamilton depression rating scale (HAMD(17)) is the standard efficacy outcome in antidepressant clinical trials. It is criticized for multidimensionality and poorly discriminating treatment from placebo. HAMD subscales may overcome these limitations and reduce the sample size of clinical trials. This study compared the discriminative performance of the HAMD(17) and three established HAMD subscales (Bech, Maier-Philipp, Gibbons) across a range of antidepressants with different mechanisms of action. METHODS: We analyzed data from 24 clinical trials including 3692 patients randomized to tricyclic or tetracyclic antidepressants (TCAs or TeCAs), selective serotonin reuptake inhibitors (SSRIs) or placebo. Data were analyzed using a mixed model for repeated measurements (MMRM). Standardized effect sizes for the HAMD(17) and subscales were derived for every time-point, and their effect on sample size was evaluated. RESULTS: For TCAs and TeCAs vs. placebo, the HAMD(17) consistently provided the highest standardized effects. The sample size to establish efficacy at week six was >25 percent smaller than for any of the subscales. However, for SSRIs vs. placebo, the HAMD(17) provided slightly smaller standardized effects and was the least efficient outcome. There were no relevant differences between the subscales. LIMITATIONS: Data were derived exclusively from mirtazapine trials. Conclusions are restricted to clinical trial settings. CONCLUSIONS: Comparative performance of the HAMD(17) and various subscales strongly depends on type of antidepressant. Results support using HAMD(17) as primary endpoint in clinical trials, but it will be beneficial to pro-actively include subscales as additional endpoints to successfully establish treatment effects of new antidepressants.

Increasing trial efficiency by early reallocation of placebo nonresponders in sequential parallel comparison designs: application to antidepressant trials.

BACKGROUND: The sequential parallel comparison (SPC) design was proposed to improve the efficiency of psychiatric clinical trials by reducing the impact of placebo response. It consists of two consecutive placebo-controlled comparisons of which the second is only entered by placebo nonresponders from the first. Previous studies suggest that in antidepressant trials, nonresponse to placebo can already be predicted after 2 weeks of follow-up. This would allow to reduce the first phase of the SPC design to further increase its efficiency. PURPOSE: To compare the sample size requirements of an 8-week randomized controlled trial (RCT(8)) and alternative SPC designs with equal or longer total follow-up duration (SPC(2+6), SPC(4+4), and SPC(6+6)). METHODS: Scenarios for response and dropout rates were defined. Sample sizes to achieve 80% power were determined for the various designs. Three treatment functions assumed either a smaller, equal, or larger effect at the early stage of the trial as compared with that at the end. Two dropout models described either predominantly early or linearly increasing dropout, and dropout was considered as nonresponse. The relative efficiency of the different designs was evaluated across these scenarios and for a specific scenario based on empirical antidepressant trial data. RESULTS: The different SPC designs (i.e., SPC(2+6), SPC(4+4), and SPC(6+6)) were generally more efficient than the RCT(8) design when the treatment effect at the early stage of the trial was equal or larger than the effect at the end. In this case, the advantage of the SPC designs increased in the presence of dropout. The SPC(2+6) design was usually more efficient than the SPC(4+4) design and was relatively less affected by dropout when it occurred predominantly early. For the scenario that was based on antidepressant trial data, the SPC(2+6) and SPC(4+4) designs required 51% and 53% fewer patients than the RCT(8) design. LIMITATIONS: A limited variety of scenarios was evaluated. Parameter values resembled those observed in antidepressant trials. CONCLUSIONS: This study suggests that SPC designs are highly efficient alternatives to a conventional RCT in indications where placebo response is high and substantial treatment effects are established after a relatively short follow-up period (i.e., after the first SPC design phase). We conclude that SPC designs can reduce sample size requirements and increase success rates of antidepressant trials.

Classifying responders and non-responders; does it help when there is evidence of differentially responding patient groups?

INTRODUCTION: Continuous trial outcomes are often dichotomized into 'response' and 'non-response' categories prior to statistical analysis. This facilitates the interpretation of results, but generally reduces statistical power. Exceptions may occur when response in the study population is heterogeneous, and outcomes are bimodally distributed. We explore whether bimodality is present in antidepressant trial data and whether dichotomizing then indeed results in more powerful statistical tests. METHODS: The distributions of relative changes from baseline (rCFB) on the Hamilton depression rating scale (HAM-D) were estimated using pooled data from nine antidepressant trials. T-tests on rCFB scores and chi-square tests on dichotomized outcomes were compared to assess the consequences of dichotomization, using both the commonly applied cutoff (i.e. rCFB > 50%) and an estimated cutoff that provided optimal separation of the mixture of two normal distributions that best fitted the pooled placebo outcomes. The power of both tests was also evaluated for simulated scenario's that varied the degree of bimodality and the treatment effect and sample size. RESULTS: Placebo and treatment groups showed evidence of bimodality. The estimated cutoff closely matched the commonly applied cutoff. Nevertheless, t-tests generally yielded smaller p-values than chi-square tests. Simulations showed that dichotomization only provides superior power when bimodality was considerably more marked than observed in the empirical data. CONCLUSION: Antidepressant trial outcomes showed bimodality, suggesting differential response among patient groups. This heterogeneity in outcome distributions should be reported more often, since a comparison of means does not adequately summarize the differences between treatment groups. However, simply dichotomizing outcomes is not an appropriate alternative as it reduces statistical power.

Dynamic subcortical blood flow during male sexual activity with ecological validity: a perfusion fMRI study.

This study used arterial spin labeling (ASL) fMRI to measure brain perfusion in a group of healthy men under conditions that closely resembled customary sexual behavior. Serial perfusion measures for 30 min during two self-limited periods of partnered penis stimulation, and during post-stimulatory periods, revealed novel sexual activity-related cerebral blood flow (rCBF) changes, mainly in subcortical parts of the brain. Ventral pallidum rCBF was highest during the onset of penile erection, and lowest after the termination of penis stimulation. The perceived level of sexual arousal showed the strongest positive association with rCBF in the right basal forebrain. In addition, our results demonstrate that distinct subregions of the hypothalamus and cingulate cortex subserve opposite functions during human male sexual behavior. The lateral hypothalamus and anterior part of the middle cingulate cortex showed increased rCBF correlated with penile erection. By contrast, the anteroventral hypothalamus and subgenual anterior cingulate cortex exhibited rCBF changes correlated with penile detumescence after penile stimulation. Continuous rapid and high-resolution brain perfusion imaging during normal sexual activity has provided novel insights into the central mechanisms that control male sexual arousal.