Atomoxetine for depression and other neuropsychiatric symptoms in Parkinson disease.

OBJECTIVES: Depression and antidepressant use, especially selective serotonin reuptake inhibitors (SSRIs), are common in Parkinson disease (PD). The objective of this clinical trial was to assess the efficacy of atomoxetine, a selective norepinephrine reuptake inhibitor (SNRI), for the treatment of clinically significant depressive symptoms and common comorbid neuropsychiatric symptoms in PD. METHODS: A total of 55 subjects with PD and an Inventory of Depressive Symptomatology-Clinician (IDS-C) score > or = 22 were randomized to 8 weeks of atomoxetine or placebo treatment (target dosage = 80 mg/day). Depression response (> 50% decrease in IDS-C score or Clinical Global Impression-Improvement [CGI-I] score of 1 or 2) was assessed using intention-to-treat modeling procedures. Secondary outcomes included global cognition, daytime sleepiness, anxiety, apathy, and motor function. RESULTS: There were no between-groups differences in a priori-defined response rates. Using a more liberal response criterion of > 40% decrease in IDS score from baseline, there was a trend (p = 0.08) favoring atomoxetine. Patients receiving atomoxetine experienced significantly greater improvement in global cognition (p = 0.003) and daytime sleepiness (p = 0.001), and atomoxetine was well-tolerated. CONCLUSIONS: Atomoxetine treatment was not efficacious for the treatment of clinically significant depressive symptoms in PD, but was associated with improvement in global cognitive performance and daytime sleepiness. Larger studies of SNRIs in PD for disorders of mood, cognition, and wakefulness are appropriate. CLASSIFICATION OF EVIDENCE: This interventional study provides Class II evidence that atomoxetine (target dosage = 80 mg/day) is not efficacious in improving clinically significant depression in PD.

Adjustments for center in multicenter studies: an overview.

Increasingly, investigators rely on multicenter or multigroup studies to demonstrate effectiveness and generalizability. Authors too often overlook the analytic challenges in these study designs: the correlation of outcomes and exposures among patients within centers, confounding of associations by center, and effect modification of treatment or exposure across center. Correlation or clustering, resulting from the similarity of outcomes among patients within a center, requires an adjustment to confidence intervals and P values, especially in observational studies and in randomized multicenter studies in which treatment is allocated by center rather than by individual patient. Multicenter designs also warrant testing and adjustment for the potential bias of confounding by center, and for the presence of effect modification or interaction by center. This paper uses examples from the recent biomedical literature to highlight the issues and analytic options.

A mixed effects model for the analysis of ordinal longitudinal pain data subject to informative drop-out.

We extend the model of Pulkstenis et al. that models binary longitudinal data, subject to informative drop-out through remedication, to the ordinal response case. We present a selection model shared-parameter approach that specifies mixed models for both ordinal response and discrete survival time to remedication. In this fashion, the random parameter present in both models completely characterizes the relationship between response and time to remedication inducing their conditional independence. With a log-log link function for both response and study 'survival', as well as specification of a log-gamma distribution for the random effect, we obtain a closed-form expression for the marginal log-likelihood of response and time to remedication that does not require approximation or numerical integration techniques. A data analysis is performed and simulation results presented which support the consistency of parameter and standard error estimates.

Physical activity, functional limitations, and disability in older adults.

OBJECTIVES: To explore initially how low levels of physical activity influence lower body functional limitations in participants of the Longitudinal Study of Aging. Changes in functional limitations are used subsequently to predict transitions in the activities of daily living/instrumental activities of daily living (ADL/IADL) disability, thus investigating a potential pathway for how physical activity may delay the onset of ADL/IADL disability and, thus, prolong independent living. DESIGN: Analysis of a complex sample survey of US civilian, noninstitutionalized population aged 70 years and older in 1984, with repeated interviews in 1986, 1988, and 1990. SETTING AND PARTICIPANTS: Analyses concentrated on 5151 men and women targeted for interview at all four LSOA interviews. MEASUREMENTS: Characteristics used in analyses: gender, age, level of physical activity, comorbid conditions including the presence of hypertension, diabetes, arthritis, and atherosclerotic heart disease, levels of functional limitations, and ADL/IADL disability. RESULTS: Transitional models provide evidence that older adults who have varying levels of disability and who report at least a minimal level of physical activity experience a slower progression in functional limitations (OR = .45, P < .001 for severe vs less severe limitations). This low level of physical activity, through its influence on changes in functional limitations, is shown to slow the progression of ADL/IADL disability. CONCLUSIONS: Results from analyses provide supporting evidence that functional limitations can mediate the effect that physical activity has on ADL/IADL disability. These results contribute further to the increasing data that seem to suggest that physical activity can reduce the progression of disability in older adults.

Effects of alcohol consumption on the treatment of depression among elderly patients.

The authors examined the effects of alcohol use on the short-term and 3-4-month treatment outcomes of patients with late-life depression. Patients (N=2,666) were assessed for symptoms of depression, alcohol use, and disability during an initial inpatient hospitalization and then 3-4 months postdischarge. Contrary to our hypothesis that alcohol consumption imparted a significant additive detriment to treatment outcome in patients already suffering from major depression, the results suggest that treatment was effective even in those with concomitant use of alcohol. Moreover, there appeared to be an added benefit when even modest alcohol consumption was decreased among elderly patients suffering from depression.

Heuristic comparison of sertraline with nortriptyline for the treatment of depression in frail elderly patients.

Studies have demonstrated that the selective serotonin reuptake inhibitor antidepressants have similar efficacy to other agents, such as tricyclic antidepressants. However, data are limited for direct comparisons with other antidepressants. The authors conducted a contemporaneous comparison of nursing home residents treated with open-label sertraline in doses up to 100 mg/day with nursing home residents treated in a double-blind randomized study of low vs. regular doses of nortriptyline. There were 97 patients enrolled in the study (28 treated with sertraline), with an average treatment duration of 55 days. There were no differences in the tolerability of sertraline vs. nortriptyline. However, in this group of frail older adults, sertraline was not as effective as nortriptyline for the treatment of depression.

Mixed effects logistic regression models for longitudinal ordinal functional response data with multiple-cause drop-out from the longitudinal study of aging.

In the context of analyzing ordinal functional limitation responses from the Longitudinal Study of Aging, we investigate the association between current functional limitation and previous year's limitation and its modification by physical activity and multiple causes of drop-out. We accommodate the longitudinal nature of the multiple causes of informative drop-out (death and unknown loss-to-follow-up) with a mixed effects logistic model. Under the proposed model with a random intercept and slope, the ordinal functional outcome and multiple discrete time survival profiles share a common random effect structure. This shared parameter selection model assumes that the multiple causes of drop-out are conditionally independent of the functional limitation outcome given the underlying random effect representing an individual's trajectory of general health status across time. Although it is not possible to fully assess the adequacy of this assumption, we assess the robustness of the approach by varying the assumptions underlying the proposed model, such as the random effects distribution and the drop-out component. It appears that between-subject differences in initial functional limitation are strongly associated with future functional limitation and that this association is stronger for those who do not have physical activity regardless of the random effects and informative drop-out specifications. In contrast, the association between current functional limitation and previous trajectory of functional status within an individual is weaker and more sensitive to changes in the random effects and drop-out assumptions.

Outcomes of a cardiovascular nutrition counseling program in African-Americans with elevated blood pressure or cholesterol level.

OBJECTIVE: To evaluate a cardiovascular nutrition education package designed for African-American adults with a wide range of literacy skills. DESIGN: Comparison of a self-help group and a full-instruction group; each group received nutrition counseling and clinical monitoring every 4 months. SUBJECTS: Three hundred thirty African-American adults, aged 40 to 70 years, with elevated cholesterol level or high blood pressure were randomly assigned to the self-help or full-instruction group; 255 completed the 12-month follow-up. INTERVENTIONS: Counseling to reduce intake of dietary fat, cholesterol, and sodium was based on Cardiovascular Dietary Education System (CARDES) materials, which included food-picture cards, a nutrition guide (self-help and full-instruction group), a video and audiotape series, and 4 classes (full-instruction group only). MAIN OUTCOME MEASURES: Changes in lipid levels and blood pressure after 12 months. STATISTICAL ANALYSES PERFORMED: Primary analyses consisted of repeated-measures analysis of variance to examine effects of time and randomization group on outcomes. RESULTS: Total cholesterol and low-density lipoprotein cholesterol level decreased by 7% to 8% in the self-help and full-instruction groups of men and women (P < .01). The ratio of total cholesterol to high-density lipoprotein cholesterol (HDL-C) decreased in both groups of women and in the men in the full-instruction group (P < .01). In full-instruction and self-help participants with elevated blood pressure at baseline, systolic blood pressure decreased by 7 to 11 mm Hg and diastolic blood pressure decreased by 4 to 7 mm Hg (P < .01). Outcomes did not differ by literacy scores but were positively related to the reported initial frequency of using CARDES materials. APPLICATIONS/CONCLUSIONS: These results suggest that periodic nutrition counseling based on CARDES materials used for home study can enhance management of lipid levels and blood pressure in African-American outpatients.

A comparison of mixed effects logistic regression models for binary response data with two nested levels of clustering.

We compare mixed effects logistic regression models for binary response data with two nested levels of clustering. The comparison of these models occurs in the context of developmental toxicity data sets, for which multiple types of outcomes (first level) are measured on each rat pup (second level) nested within a litter (third level). Because the nested nature of such data is occasionally accommodated by ignoring one level of clustering, we consider three models: (i) a three-level model adjusting for clustering due to both pup and litter (M1); (ii) a two-level model adjusting for just pup (M2); and (iii) another two-level model adjusting for just litter (M3). The three types of effects of interest are: (i) differences among malformation types (first-level effects); (ii) differences among groups of pups (for example, sex of pup, second-level effects); and (iii) differences among groups of litters (for example, dose, third-level effects). Simulations and data analyses suggest that the M3 model leads to more bias than the M1 or M2 models for all three types of effects. In terms of coverage of confidence intervals for fixed effects log odds ratio parameters, the M1 model achieves nominal coverage, whereas the M2 model reduces coverage for the third-level effects and the M3 model obtains poor coverage for both first- and second-level effects. These reductions in coverage for certain model-parameter combinations worsen as baseline risk increases. The data analyses support these simulation-based conclusions to some extent.

Empirical Bayes estimation of random effects parameters in mixed effects logistic regression models.

We extend an approach for estimating random effects parameters under a random intercept and slope logistic regression model to include standard errors, thereby including confidence intervals. The procedure entails numerical integration to yield posterior empirical Bayes (EB) estimates of random effects parameters and their corresponding posterior standard errors. We incorporate an adjustment of the standard error due to Kass and Steffey (KS; 1989, Journal of the American Statistical Association 84, 717-726) to account for the variability in estimating the variance component of the random effects distribution. In assessing health care providers with respect to adult pneumonia mortality, comparisons are made with the penalized quasi-likelihood (PQL) approximation approach of Breslow and Clayton (1993, Journal of the American Statistical Association 88, 9-25) and a Bayesian approach. To make comparisons with an EB method previously reported in the literature, we apply these approaches to crossover trials data previously analyzed with the estimating equations EB approach of Waclawiw and Liang (1994, Statistics in Medicine 13, 541-551). We also perform simulations to compare the proposed KS and PQL approaches. These two approaches lead to EB estimates of random effects parameters with similar asymptotic bias. However, for many clusters with small cluster size, the proposed KS approach does better than the PQL procedures in terms of coverage of nominal 95% confidence intervals for random effects estimates. For large cluster sizes and a few clusters, the PQL approach performs better than the KS adjustment. These simulation results agree somewhat with those of the data analyses.

Mixed effects models with bivariate and univariate association parameters for longitudinal bivariate binary response data.

When two binary responses are measured for each study subject across time, it may be of interest to model how the bivariate associations and marginal univariate risks involving the two responses change across time. To achieve such a goal, marginal models with bivariate log odds ratio and univariate logit components are extended to include random effects for all components. Specifically, separate normal random effects are specified on the log odds ratio scale for bivariate responses and on the logit scale for univariate responses. Assuming conditional independence given the random effects facilitates the modeling of bivariate associations across time with missing at random incomplete data. We fit the model to a dataset for which such structures are feasible: a longitudinal randomized trial of a cardiovascular educational program where the responses of interest are change in hypertension and hypercholestemia status. The proposed model is compared to a naive bivariate model that assumes independence between time points and univariate mixed effects logit models.

An empirical comparison of several clustered data approaches under confounding due to cluster effects in the analysis of complications of coronary angioplasty.

In the analysis of binary response data from many types of large studies, the data are likely to have arisen from multiple centers, resulting in a within-center correlation for the response. Such correlation, or clustering, occurs when outcomes within centers tend to be more similar to each other than to outcomes in other centers. In studies where there is also variability among centers with respect to the exposure of interest, analysis of the exposure-outcome association may be confounded, even after accounting for within-center correlations. We apply several analytic methods to compare the risk of major complications associated with two strategies, staged and combined procedures, for performing percutaneous transluminal coronary angioplasty (PTCA), a mechanical means of relieving blockage of blood vessels due to atherosclerosis. Combined procedures are used in some centers as a cost-cutting strategy. We performed a number of population-averaged and cluster-specific (conditional) analyses, which (a) make no adjustments for center effects of any kind; (b) make adjustments for the effect of center on only the response; or (c) make adjustments for both the effect of center on the response and the relationship between center and exposure. The method used for this third approach decomposes the procedure type variable into within-center and among-center components, resulting in two odds ratio estimates. The naive analysis, ignoring clusters, gave a highly significant effect of procedure type (OR = 1.6). Population average models gave marginally to very nonsignificant estimates of the OR for treatment type ranging from 1.6 to 1.2 with adjustment only for the effect of centers on response. These results depended on the assumed correlation structure. Conditional (cluster-specific) models and other methods that decomposed the treatment type variable into among- and within-center components all found no within-center effect of procedure type (OR = 1.02, consistently) and a considerable among-center effect. This among-center variability in outcomes was related to the proportion of patients who receive combined procedures and was found even when conditioned on procedure type (within-center) and other patient- and center-level covariates. This example illustrates the importance of addressing the potential for center effects to confound an outcome-exposure association when average exposure varies across clusters. While conditional approaches provide estimates of the within-cluster effect, they do not provide information about among-center effects. We recommend using the decomposition approach, as it provides both types of estimates.

Mixed effects logistic regression models for longitudinal binary response data with informative drop-out.

A shared parameter model with logistic link is presented for longitudinal binary response data to accommodate informative drop-out. The model consists of observed longitudinal and missing response components that share random effects parameters. To our knowledge, this is the first presentation of such a model for longitudinal binary response data. Comparisons are made to an approximate conditional logit model in terms of a clinical trial dataset and simulations. The naive mixed effects logit model that does not account for informative drop-out is also compared. The simulation-based differences among the models with respect to coverage of confidence intervals, bias, and mean squared error (MSE) depend on at least two factors: whether an effect is a between- or within-subject effect and the amount of between-subject variation as exhibited by variance components of the random effects distributions. When the shared parameter model holds, the approximate conditional model provides confidence intervals with good coverage for within-cluster factors but not for between-cluster factors. The converse is true for the naive model. Under a different drop-out mechanism, when the probability of drop-out is dependent only on the current unobserved observation, all three models behave similarly by providing between-subject confidence intervals with good coverage and comparable MSE and bias but poor within-subject confidence intervals, MSE, and bias. The naive model does more poorly with respect to the within-subject effects than do the shared parameter and approximate conditional models. The data analysis, which entails a comparison of two pain relievers and a placebo with respect to pain relief, conforms to the simulation results based on the shared parameter model but not on the simulation based on the outcome-driven drop-out process. This comparison between the data analysis and simulation results may provide evidence that the shared parameter model holds for the pain data.

Accommodating negative intracluster correlation with a mixed effects logistic model for bivariate binary data.

We extend the random intercept logistic model to accommodate negative intracluster correlations for bivariate binary response data. This approach assumes a single random effect per cluster, but entails separate affine transformations of this random effect for the two responses of the pair. We show this approach works for two data sets and a simulation, whereas other mixed effects approaches fail. The two data sets are from a crossover trial and a developmental toxicity study of the effects of chemical exposure on malformation risk among rat pups. Comparisons are made with the conditional likelihood approach and with generalized estimating equations estimation of the population-averaged logit model. Simulations show the conditional likelihood approach does not perform well for moderate to strong negative correlations, as a positive intracluster correlation is assumed. The proposed mixed effects approach appears to be slightly more conservative than the population-averaged approach with respect to coverage of confidence intervals. Nonetheless, the statistical literature suggests that mixed effects models provide information in addition to that provided by population-averaged models under scientific contexts such as crossover trials. Extensions to trivariate and higher-dimensional responses also are addressed. However, such extensions require certain constraints on the correlation structure.

A randomized controlled trial of weight reduction and exercise for diabetes management in older African-American subjects.

OBJECTIVE: To evaluate a weight loss and exercise program designed to improve diabetes management in older African-Americans. RESEARCH DESIGN AND METHODS: Overweight African-Americans (n = 64) ages 55-79 years with NIDDM were randomized to either an intervention (12 weekly group sessions, 1 individual session, and 6 biweekly group sessions) or usual care (1 individual session, and 6 biweekly group sessions) or usual care (1 class and 2 informational mailings). Clinical and behavioral variables were assessed at 0, 3, and 6 months of treatment. RESULTS: Significant net differences in the intervention versus usual care were observed for weight (-2.0 kg, P = 0.006), physical activity, and dietary intake of fat, saturated fat, cholesterol, and nutrition knowledge at 3 months (all P < 0.05) and for weight at 6 months (-2.4 kg; P = 0.006) and mean HbA1c values at 3 and 6 months (respectively, -1.6 and -2.4%, both P < 0.01). After the adjustment for changes in weight and activity, the intervention participants were approximately twice as likely to have a one unit decrease in HbA1c value as those in usual care. Blood pressure increase sin usual care participants resulted in net differences (intervention minus control) at 3 and 6 months of -3.3 (P = 0.09) and -4.0 (P = 0.05) mmHg diastolic, respectively, and -8.4 (P = 0.06) and -5.9 (P > 0.10) mmHg systolic, respectively. Blood lipid profiles improved more in intervention than usual care participants, but not significantly. CONCLUSIONS: The intervention program was effective in improving glycemic and blood pressure control. The decrease in HbA1c values was generally independent of the relatively modest changes in dietary intake, weight, and activity and may reflect indirect program effects on other aspects of self-care.

Modelling population heterogeneity in sensitivity and specificity of a multi-stage screen for obstructive sleep apnoea.

We propose a model-based approach for modelling population heterogeneity in terms of sensitivity and specificity of multi-stage screening procedures that consists of multiple tests ordered according to criteria such as cost and invasiveness. It is assumed that a patient proceeds to the next test only if they test positive for the current test. An overall positive result occurs if a patient tests positive for all tests. A dropout occurs when a subject tests positive for a test but does not proceed to subsequent tests. Chinchilli proposed estimates of sensitivity and specificity based upon ratios of multinomial sample probabilities for such a multi-stage procedure in a homogeneous population. The method proposed here accommodates population heterogeneity with generalized linear models and transformation-based confidence intervals. In contrast to the approach of Chinchilli, such an approach provides model-based tests of population differences, narrower confidence intervals that satisfy boundary constraints, and a method for accommodating dropouts without the need for prespecified weights. The proposed method is motivated by the need to assess age differences in the accuracy of a multi-stage test for obstructive sleep apnoea.

Evaluation of contrast densities in the diagnosis of carotid stenosis by CT angiography.

OBJECTIVE: This study assesses intravascular density produced by ionic and nonionic contrast material and its effect on visualization of stenoses by CT angiography. MATERIALS AND METHODS: CT angiography was performed using a 32-vessel phantom to study grades of luminal stenoses (0-100%), three lengths of stenoses (1, 3, and 5 mm), and two angles of inclination into the stenoses (45 degrees and 75 degrees). Scans were obtained with a slice thickness of 2 mm, a slice interval of 1.5 mm, a pitch of 1.0, a voltage of 120 kV, and a current of both 100 and 200 mA. Vessels were oriented parallel to the z-axis, and opacified with ionic and nonionic contrast material that had densities of 100, 150, 200, 250, 300, and 350 H. Cross-sectional luminal diameters were measured in and out of the stenoses. Edge definition and halo artifact for each vessel were graded by an investigator who was unaware of the contrast material density used. RESULTS: A contrast density of 150 H as revealed by CT angiography yielded the most accurate stenosis measurements with ionic contrast material. For nonionic contrast material, attenuation values of 150 and 200 H produced the best results on CT angiography. A density of 100 H or greater than 250 H significantly increased the error of vessel measurement (p = .001) for both types of contrast material. For the two current levels tested (100 and 200 mA), no statistical difference was found. CONCLUSION: The accuracy of CT angiography in measuring carotid stenosis depends on the luminal attenuation value. An optimum contrast density is 150 H for ionic contrast material; for nonionic contrast material, 150-200 H (at the window and level settings of 300 H and 40 H).

Technical factors of CT angiography studied with a carotid artery phantom.

PURPOSE: To evaluate scanning parameters (conventional versus spiral CT, section thickness, and pitch) and vessel orientation in the performance of CT angiography. METHODS: Conventional CT and 1.0-, 1.5-, and 2.0-pitch spiral CT acquisitions of a carotid phantom designed with vessels oriented parallel to the z-axis, 45 degrees oblique, and perpendicular to the z-axis were obtained with section thicknesses of 2, 4, and 8 mm. The phantom contained 32 vessels with 0% to 100% stenoses. Normal and stenotic luminal diameters were measured and the number of artifacts was assessed. RESULTS: No overall difference was observed among conventional and spiral CT acquisitions obtained with pitches of 1.0, 1.5, and 2.0. With thicker sections, CT angiographic accuracy decreased and artifacts increased. The three-vessel orientations were relatively comparable in accuracy in terms of the percentage of stenosis measured. Vessels parallel to the z-axis suffered less artifactual degradation. Unique artifacts, such as luminal distortion and beam hardening, were observed in vessels oriented at 45 degrees and perpendicular to the z-axis. CONCLUSION: Use of thinner sections with vessels oriented parallel to the z-axis optimizes CT angiographic quality. There is no apparent degradation with the use of spiral CT, and a pitch of 1.5 or 2.0 provides results equivalent to 1.0-pitch spiral studies.

Population-averaged and cluster-specific models for clustered ordinal response data.

We compare population-averaged and cluster-specific models for clustered ordinal data. We consider generalized estimating equations and constrained equations maximum likelihood estimation of population-averaged cumulative logit regression models, and mixed effects estimation of cluster-specific cumulative logit regression models. A previously reported relationship between population-averaged and cluster-specific parameters for the binary logistic link appears to hold for analogous parameters under the cumulative logit link. We address these issues in the context of data from two cross-over clinical trials.

A mixed effects model for multivariate ordinal response data including correlated discrete failure times with ordinal responses.

The mixed effects model for binary responses due to Conaway (1990, A Random Effects Model for Binary Data) is extended to accommodate ordinal responses in general and discrete time survival data with ordinal responses in particular. Given a multinomial likelihood, cumulative complementary log-log link function, and log-gamma random effects distribution, the resulting marginal likelihood has a closed form. As a result, a Newton-Raphson estimation procedure is feasible without resorting to numerical, approximation-based, or Monte Carlo integration techniques. The parameters in the model have a proportional hazards interpretation in terms of multivariate discrete time data with ordinal responses. Using data from a psychological example, the proposed method is compared with other mixed effects approaches as well as population-averaged models.