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Controlled trials of therapy in fibromyalgia syndrome.

Many different interventions have been studied in the therapy of fibromyalgia syndrome (Tables 1 and 2). While most have been effective, in general these trials have been short term. Furthermore, important or substantial improvement, when it has been assessed, occurs in only small proportions of patients. Long-term, comparative trials of both efficacy and toxicity are necessary. Trials such as these require large numbers of patients (compared with placebo-controlled trials, which are generally impractical in long-duration trials due to the large numbers of dropouts in the placebo arm) and therefore are expensive and difficult to accomplish. Two other approaches offer potential solutions to the problem of adequate long-term comparative trials: (a) N-of-1 trials and (b) meta-analysis. N-of-1 trials have the advantage of random assignment, double-blinding and multiple potential comparisons in the same patient. Meta-analysis involves combining the results of studies, which individually may have conflicting results and lack adequate statistical power, to reach an overall result with sufficient statistical power to make meaningful conclusions, especially with respect to comparative efficacy. Peluso and colleagues (1993) have performed a recent meta-analysis of available therapies in fibromyalgia syndrome and found that the effect-size (a standardized measure of the efficacy of a given therapy) of several non-medication therapies such as electroacupuncture exceeded that of traditional medication therapies. Unfortunately, lack of uniformity in the use of outcome measures across included trials and the small numbers of comparable non-medication trials makes definitive conclusions regarding relative efficacy of therapies difficult. Nevertheless, application of meta-analytic methods such as these should facilitate future comparisons of different interventions. Ideally, future clinical trials in fibromyalgia syndrome should employ the same outcome measures to permit application of these methods. Few trials have assessed improvement in functional status. Functional status measures such as the HAQ (Fries et al., 1980), the Fibromyalgia Impact Questionnaire (Burckhardt et al, 1991) or similar instruments should be employed in future studies of therapy in fibromyalgia. Given that individual modalities appear to confer relatively modest benefit on average. Combination approaches are reasonable, although randomized, blinded trials to assess these approaches are methodologically complex. Several preliminary studies which have addressed this approach appear promising (see Chapter 12; Goldenberg et al, 1993). Finally, no studies have yet assessed the comparative cost-efficacy of available treatments. Controlled trials which address the cost-efficacy of commonly employed, but unproven treatments such as physiotherapy chiropractic manipulation and injection techniques are urgently needed.

Antidepressive Agents↗

Improving permutation test power for group analysis of spatially filtered MEG data.

Non-parametric statistical methods, such as permutation, are flexible tools to analyze data when the population distribution is not known. With minimal assumptions and better statistical power compared to the parametric tests, permutation tests have recently been applied to the spatially filtered magnetoencephalography (MEG) data for group analysis. To perform permutation tests on neuroimaging data, an empirical maximal null distribution has to be found, which is free from any activated voxels, to determine the threshold to classify the voxels as active at a given probability level. An iterative procedure is used to determine the distribution by computing the null distribution, which is recomputed when a possible activated voxel is found within the current distributions. Besides the high computational costs associated with this approach, there is no guarantee that all activated voxels are excluded when constructing the maximal null distribution, which may reduce the statistical power. In this study, we propose a novel way to construct the maximal null distribution from the data of the resting period. The approach is tested on the MEG data from a somatosensory experiment, and demonstrated that the approach could improve the power of the permutation test while reducing the computational cost at the same time.

Adult↗

On the power of multivariate latent growth curve models to detect correlated change.

We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris (1985) were used to evaluate the power to detect slope covariances. Even with large samples (N = 500) and several longitudinal occasions (4 or 5), statistical power to detect covariance of slopes was moderate to low unless growth curve reliability at study onset was above .90. Studies using LGCMs may fail to detect slope correlations because of low power rather than a lack of relationship of change between variables. The present findings allow researchers to make more informed design decisions when planning a longitudinal study and aid in interpreting LGCM results regarding correlated interindividual differences in rates of development.

Aging↗

Assessment of adjuvant trials in breast cancer.

In this paper, we discuss the analytic problems associated with the evaluation of overall survival for breast cancer adjuvant studies and results of pooling data from the published literature to determine if there is evidence showing an overall survival advantage to adjuvant therapy. An investigation of the effect of competing causes of death shows that trials on older patients have low statistical power. Hence many of the current trials have low statistical power and may fail to find overall survival advantage for adjuvant therapy even when a benefit exists. The implications of the assessment of short-term follow-up are discussed in the context of the heterogeneous distribution of residual disease after primary treatment. Short-term follow-up (less than 5 yr) precludes anyone from making any conclusions about benefit for patients with small residual tumor burdens who constitute the patient subgroup most likely to benefit from adjuvant therapy. We reviewed 15 published randomized trials (each having a control group receiving no systemic therapy) to determine if overall survival has been increased by adjuvant therapy. We conclude that there is a benefit from some chemotherapy regimens given to node-positive premenopausal women. However, the published data for tamoxifen are mixed, with some trials showing benefit and others not. As more follow-up time is accumulated, this matter should be settled.

Adult↗

Some statistical considerations for the interpretation of trials of combined androgen therapy.

Since 1989, there have been strongly conflicting opinions regarding the validity of the proposition that an antiandrogen added to standard hormonal therapy could improve the outcome in patients with newly diagnosed metastatic prostate cancer. To some degree, these conflicting opinions arose from misinterpretations of a number of "negative" clinical trials. The misinterpretations happened because these "negative" trials had insufficient statistical power to refute the reported "positive trial", and information illustrating their statistical power was absent from their reports. Thus, readers were not given the necessary information to distinguish between negative and inconclusive results. In addition, many of the negative reports were early analyses of ongoing clinical trials, a practice that always should be avoided. This article reviews and illustrates the statistical principles that are applicable to the interpretation of low-powered negative clinical trials and discusses the design and conduct of clinical trials.

Androgen Antagonists↗

Screening for breast cancer and mortality reduction among women 40-49 years of age.

The recent withdrawal of screening support for women ages 40-49 years is not scientifically supported. The subgroup analyses that have been used severely compromise the statistical power of the trials. None of the trials has the statistical power to be able to provide clear proof of benefit for screening women ages 40-49 years because none of the trials involved sufficient numbers of women in these age groups. Despite having not been designed to evaluate women ages 40-49 years as a separate group, five of the eight randomized, controlled trials have demonstrated mortality reductions for these women that range from 22% to 49%. In addition, data from other nonrandomized trials show that there is no difference in survival for women ages 40-49 years than for women ages 50-59 years. The detection rate for small, early cancers, using modern mammography, is similar for women in both decades. There is no scientific reason to believe that there is a sudden change in detection or cure at age 50 years, or even at menopause. The available data suggest that women ages 40-49 years can benefit from screening, just as can women ages 50-59 years.

Adult↗

Dealing with variability in food production chains: a tool to enhance the sensitivity of epidemiological studies on phytochemicals.

BACKGROUND: Many epidemiological studies have tried to associate the intake of certain food products with a reduced risk for certain diseases. Results of these studies are often ambiguous, conflicting, or show very large deviations of trends. Nevertheless, a clear and often reproduced inverse association is observed between total vegetable and fruit consumption and cancer risk. Examples of components that have been indicated to have a potential protective effect in food and vegetables include antioxidants, allium compounds and glucosinolates. AIM: The food production chain can give a considerable variation in the level of bioactive components in the products that are consumed. In this paper the effects of this variability in levels of phytochemicals in food products on the sensitivity of epidemiological studies are assessed. METHODS: Information on the effect of variation in different steps of the food production chain of Brassica vegetables on their glucosinolate content is used to estimate the distributions in the levels in the final product that is consumed. Monte Carlo simulations of an epidemiological cohort study with 30,000 people have been used to assess the likelihood of finding significant associations between food product intake and reduced cancer risk. RESULTS: By using the Monte Carlo simulation approach, it was shown that if information on the way of preparation of the products by the consumer was quantified, the statistical power of the study could at least be doubled. The statistical power could be increased by at least a factor of five if all variation of the food production chain could be accounted for. CONCLUSIONS: Variability in the level of protective components arising from the complete food production chain can be a major disturbing factor in the identification of associations between food intake and reduced risk for cancer. Monte Carlo simulation of the effect of the food production chain on epidemiological cohort studies has identified possible improvements in the set up of such studies. The actual effectiveness of food compounds already identified as cancer-protective by current imprecise methods is likely to be much greater than estimated at present.

Anticarcinogenic Agents↗

Evaluation of the bioequivalence of highly-variable drugs and drug products.

PURPOSE: To establish procedures for the effective evaluation of bioequivalence (BE) for highly-variable drugs and drug products (HVD/P). METHODS: 2- and 4-period crossover BE studies with 24 subjects were simulated which generally assumed within-subject coefficients of variation of 40%. The relationship between the fraction of studies in which BE was accepted (the statistical power) and the ratio of geometric means (GMR) of the two formulations was evaluated for various methods of analysis. These included, primarily, scaled average BE (ABE), the corresponding approach of expanding BE limits (BEL), and, for comparison, unscaled ABE and scaled individual BE (IBE). RESULTS: Scaled ABE and expanding BEL showed very similar properties in both 2- and 4-period studies. They had steeper power curves than scaled IBE. Unscaled ABE had very low statistical power. The acceptance of BE by unscaled and scaled ABE and expanding BEL was almost independent of subject-by-formulation interaction and the ratio of within-subject variations of the two formulations. By contrast, the conclusions reached by scaled IBE were strongly affected by these parameters. CONCLUSIONS: Scaled ABE and expanding BEL evaluate BE effectively for HVD/P in both 2- and 4-period investigations. However, additional, useful information can be obtained from 4-period studies.

Analysis of Variance↗

Iterative versus filtered backprojection reconstruction for statistical parametric mapping of PET activation measurements: a comparative case study.

The significance of task-induced cerebral blood flow responses, assessed using statistical parametric mapping, depends, among other things, on the signal-to-noise ratio (SNR) of these responses. Generally, positron emission tomography sinograms of H(2)(15)O activation studies are reconstructed using filtered backprojection (FBP). Alternatively, the acquired data can be reconstructed using an iterative reconstruction procedure. It has been demonstrated that the application of iterative reconstruction methods improves image SNR as compared with FBP. The aim of this study was to compare FBP with iterative reconstruction, to assess the statistical power of H(2)(15)O-PET activation studies using statistical parametric mapping. For this case study, PET data originating from a bimanual motor task were reconstructed using both FBP and maximum likelihood expectation maximization (ML-EM), an iterative algorithm. Both resulting data sets were statistically analyzed using statistical parametric mapping. It was found, with this dataset, that the statistical analysis of the iteratively reconstructed data confirm the a priori expected physiological response. In addition, increased Z scores were obtained in the iteratively reconstructed data. In particular, for the expected task-related response, activation of the posterior border of the left angular gyrus, the Z score increased from 3.00 to 3.96. Furthermore, the number of statistically significant clusters doubled while their volume increased by more than 50%. In conclusion, iterative reconstruction has the potential to increase the statistical power in H(2)(15)O-PET activation studies as compared with FBP reconstruction.

Brain Mapping↗

From Peaks to Power: Systematic Evaluation of Chromatographic Sampling Reveals Determinants of Quantification and Biological Discovery in DIA Proteomics.

Modern DIA proteomics increasingly emphasizes throughput and depth for large-cohort studies, but methods are often optimized using proxy metrics that can mask losses in quantifiable signal and statistical power. Here, we evaluate how data points per peak and other chromatographic features jointly contribute to quantification and downstream biological discovery. Using a matrix-matched calibration curve dataset, we checked how the number of data points per peak (DPPP) affects the limits of detection and quantification (LOD/LOQ). Reduced DPPP minimally affected LOD but substantially degraded LOQ. Feature modeling and nonparametric association analyses identified precursor peak area as the strongest feature-level predictor of LOQ, whereas DPPP showed weaker and context-dependent effects. Simulations of chromatographic peak integration recapitulated these trends, showing that increased sampling primarily improves integration precision, while quantitative accuracy is strongly governed by peak height and peak shape. Finally, when comparing 20 cancer vs 20 control plasma samples processed with Seer Proteograph, the decrease in DPPP led to a loss of statistical significance for proteins with low-abundance precursors. These findings argue that DIA optimization should prioritize LOQ and statistical power metrics─not identifications alone─by balancing sampling density with chromatographic peak height and quality to maximize useful biological signal.

Proteomics↗

Clinical trial simulation: a tool for understanding study failures and preventing them.

Execution models describe protocol deviations from a specified study design. When a clinical trial is planned, it is generally supposed that it will be executed according to a specific protocol that defines all aspects of the experimental design, from its beginning to its completion. Adherence to the protocol will allow estimation of the treatment outcome (safety and efficacy) with sufficient statistical power, or at least that is what is assumed. In reality, however, deviations from the protocol may lead to failure of the study to achieve its stated aims. In anticipation of protocol deviations that contribute to inflated residual variability and decreased study statistical power, trial designers tend to overpower studies in a rather arbitrary way. It is difficult to estimate quantitatively the consequences of one protocol deviation on statistical study power and, a fortiori, it is almost impossible to do it for a combination of protocol deviations. One way to study the consequences of model deviations is by using modelling and simulation techniques, and more specifically longitudinal stochastic models that can describe individual behaviours. Thus, execution models are powerful tools for identifying weaknesses or limitations in a proposed study design, which may be anticipated, avoided or resolved in order to increase robustness of the study design prior to implementation of the actual clinical study. As such, they are an integral component of clinical trial simulation and an essential tool in clinical trial design.

Acquired Immunodeficiency Syndrome↗

Power and sample assessments for tests of hypotheses on cost-effectiveness ratios.

We address the issue of statistical power and sample size for cost-effectiveness studies. Tests of hypotheses on the cost-effectiveness ratio (CER) are constructed from the net cost and incremental effectiveness measures. When the difference in effectiveness is known, we derive formulae for statistical power and sample size assessments for one- and two-sided tests of hypotheses of the CER. We also construct a test of the joint hypothesis of cost-effectiveness and effectiveness and derive an expression connecting power and sample size. Our methods account for the correlation between cost and effectiveness and lead to smaller sample size requirements than comparative methods that ignore the correlation. The implications of our formulae for cost-effectiveness studies are illustrated through numerical examples. When compared with trials designed to demonstrate effectiveness alone, our results indicate that a trial appropriately powered to demonstrate cost-effectiveness might require sample sizes many times greater.

Confidence Intervals↗

Vitamin A for non-measles pneumonia in children.

BACKGROUND: Acute respiratory infections, mostly in the form of pneumonia, are the leading causes of death in children under five years of age in developing countries. Some clinical trials have demonstrated that vitamin A supplementation reduces the severity of respiratory infection and mortality in children with measles. OBJECTIVES: To determine whether adjunctive vitamin A is effective in infants and children diagnosed with non-measles pneumonia. SEARCH STRATEGY: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library Issue 4, 2004); MEDLINE (1996 to November Week 3, 2004); EMBASE (1990 to September 2004); LILACS (9 January 2004); CINAHL (1990 to November 2004); Biological Abstracts (1990 to November 2004) and Current Contents (1990 to September 2004); and the Chinese Biomedicine Database (CBM) (1994 to November 2004). SELECTION CRITERIA: Only parallel-arm, randomised and quasi-randomised controlled trials in which children (younger than 15 years old) with non-measles pneumonia were treated with adjunctive vitamin A were included. DATA COLLECTION AND ANALYSIS: Two authors independently extracted data and assessed trial quality. Study authors were contacted for additional information. MAIN RESULTS: Five trials involving 1453 infants and children were included. There was no significant reduction in the mortality associated with pneumonia in children treated with vitamin A compared to those who were not (pooled odds ratio (OR) 1.49; 95% confidence interval (CI) 0.66 to 3.35). In addition, there was a lack of a statistically significant effect on duration of stay in hospital (weighted mean difference (WMD) 0.08; 95% CI -0.43 to 0.59). Vitamin A was associated with a 39% reduction in antibiotic firstline failure (OR 0.65; 95% CI 0.42 to 1.01). Children receiving vitamin A were no more likely to experience vomiting (OR 0.77; 95% CI 0.45 to 1.33), diarrhoea (OR 0.57; 95% CI 0.31 to 1.05), bulging of the fontanelles (OR 8.25; 95% CI 0.44 to 155.37) or irritability (OR 0.93, 95% CI 0.56 to 1.57) than those not receiving vitamin A. There was no statistical significance between vitamin A and placebo groups (OR 0.90; 95% CI -1.10 to 2.90) in chest x-ray results. Disease severity after supplementary high-dose vitamin A was significantly worse in children who received vitamin A compared with placebo. Low-dose vitamin A was associated with a significant reduction in the recurrent rate of bronchopneumonia (OR 0.12; 95% CI 0.03 to 0.46). AUTHORS' CONCLUSIONS: The evidence did not suggest a significant reduction with vitamin A adjunctive treatment in mortality, measures of morbidity, nor an effect on the clinical course of pneumonia in children with non-measles pneumonia. However, not all studies measured all outcomes, limiting the number of studies that could be incorporated into the meta-analyses, so that there may have been a lack of statistical power to detect statistically significant differences.

Child↗

On statistical tests of phylogenetic tree imbalance: the Sackin and other indices revisited.

We investigate the distribution of statistical measures of tree imbalance in large phylogenies. More specifically, we study normalized versions of the Sackin's index and the number of subtrees of given sizes. Using the connection with structures from theoretical computer science, we provide precise description for the limiting distribution under the null hypothesis of Yule trees. Corrected p-values are then computed, and the statistical power of these statistics for testing the Yule model against a model of biased speciation is evaluated from simulations. As an illustration, the tests are applied to the HIV-1 reconstructed phylogeny.

Acquired Immunodeficiency Syndrome↗

Selection and evaluation of air pollution exposure indicators based on geographic areas.

Geographic exposure indicators (GEIs) use point estimates of ambient air pollutant concentrations to characterize the exposure of populations residing within a specified area. Both zone- and proximity-type GEIs have been widely employed in epidemiological studies and other applications to identify regions or populations at high risk. Their use requires a number of assumptions, for example, pollutant concentrations should be homogeneous within the area, and concentrations should differ between areas in a predictable manner. These assumptions have not been rigorously examined. This paper evaluates the most common types of GEIs as surrogate measures of ambient air pollutant exposures. Statistical measures proposed to evaluate GEIs include accuracy, homogeneity, misclassification and statistical power. GEIs and statistical measures are evaluated in two case studies that use different air pollution sources and an air quality dispersion model. The case studies show that pollutant levels may vary substantially within a small area, and significant errors and exposure misclassification may result if the GEI represents a large geographic area. GEIs based on residential proximity to a pollution source should not be used for elevated emission sources, and the use of proximity measures is discouraged for ground level sources. A systematic evaluation is suggested to evaluate and improve the accuracy of the GEIs used in epidemiological and other applications.

Air Pollution↗

Comparison of PET [15O]water studies with 6-minute and 10-minute interscan intervals: single-subject and group analyses.

The authors recently showed that [15O]water PET data obtained with a short interscan interval (6 minutes) produced similar results whether or not the residual background from the previous scan is subtracted. The purpose of the present study was to compare scans obtained during motor activation using a short (6-minute) interscan interval protocol with those obtained with a standard (10-minute) protocol in the same scanning session. Single-subject and group analyses were performed using Worsley's method, which uses a pooled variance estimate and statistical parametric mapping with a local variance estimate. High consistency in both the activation maps, i.e., the number of activated motor brain structures and the Talairach coordinates of peak intensities of the activated regions, was obtained in the 6- and 10-minute studies in both single-subject and group analyses. However, in comparison to the 6-minute studies, a larger cluster size of activated brain regions and an approximately 20% higher peak activation in these regions were observed in the 10-minute studies with the same number of replicates. Analysis of these results suggests that using a 6-minute interval with an increased number of replications, i.e., without changing the subject's total study duration, should produce comparable statistical power to that of the 10-minute interval for group analysis and increased statistical power for single-subject analyses that use a local variance estimate because of increased degrees of freedom. Alternatively, with a small increase in the number of scans and the use of a 6-minute interscan interval, a comparable level of statistical significance may be achieved for single-subject experiments that use a local variance estimate, with an overall shortening of the study duration.

Adult↗

The inheritance of metabolic flux: expressions for the within-sibship mean and variance given the parental genotypes.

Recent developments have related quantitative trait expression to metabolic flux. The present paper investigates some implications of this for statistical aspects of polygenic inheritance. Expressions are derived for the within-sibship genetic mean and genetic variance of metabolic flux given a pair of parental, diploid, n-locus genotypes. These are exact and hold for arbitrary numbers of gene loci, arbitrary allelic values at each locus, and for arbitrary recombination fractions between adjacent gene loci. The within-sibship, genetic variance is seen to be simply a measure of parental heterozygosity plus a measure of the degree of linkage coupling within the parental genotypes. Approximations are given for the within-sibship phenotypic mean and variance of metabolic flux. These results are applied to the problem of attaining adequate statistical power in a test of association between allozymic variation and inter-individual variation in metabolic flux. Simulations indicate that statistical power can be greatly increased by augmenting the data with predictions and observations on progeny statistics in relation to parental allozyme genotypes. Adequate power may thus be attainable at small sample sizes, and when allozymic variation is scored at a only small fraction of the total set of loci whose catalytic products determine the flux.

Animals↗

School-based substance abuse prevention: a review of the state of the art in curriculum, 1980-1990.

Substance use prevention studies published between 1980 and 1990 are reviewed for content, methodology and behavioral outcomes. Studies were classified based on the inclusion of 12 content areas: Information, Decision Making, Pledges, Values Clarification, Goal Setting, Stress Management, Self-Esteem, Resistance Skills Training, Life Skills Training, Norm Setting, Assistance and Alternatives. Six groups of programs (Information/Values Clarification, Affective Education, Social Influence, Comprehensive, Alternatives and Incomplete programs) are identified. Reports are analyzed for two major threats to validity, selection bias and statistical power. Program groups generally have similar selection biases but have important differences in statistical power. Comprehensive and Social Influence programs are found to be most successful in preventing the onset of substance use.

Adolescent↗