Optimal designs for clinical trials with second-order polynomial treatment effects

The effect of adding intermediate measures on the efficiency of treatment effect estimation is considered for a second-order polynomial treatment effect, equidistant time-points, different covariance structures and two optimality criteria, assuming either a fixed sample size or a fixed budget. The benefit of adding intermediate measures (at the expense of subjects) depends strongly on the assumed covariance structure and is hardly affected by the two used optimality criteria (Ds or c). For a fixed sample size, the increase in efficiency by adding intermediate measures is large for a compound symmetric structure and small for a first-order auto-regressive structure. For a first-order auto-regressive structure with measurement error, the results depend on the covariance parameter values. For a fixed budget and linear cost function, the design with only three measures per subject is often highly efficient. If the structure resembles compound symmetry and the cost per subject is eight or more times larger than the cost per repeated measure, however, more than three measures are required to obtain highly efficient treatment effect estimators. If the covariance structure is unknown, the optimal design based on a first-order auto-regressive structure with measurement error is preferable in terms of robustness against misspecification of the covariance structure. Given a design with three repeated measures and a second-order polynomial treatment effect, equidistant time-points are either optimal (Ds-) or highly efficient (c-optimality criterion). The results are illustrated by a practical example.     

Estimating treatment effects from randomized clinical trials with noncompliance and loss to follow-up: the role of instrumental variable methods

Perfectly implemented randomized clinical trials, particularly of complex interventions, are extremely rare. Almost always they are characterized by imperfect adherence to the randomly allocated treatment and variable amounts of missing outcome data. Here we start by describing a wide variety of examples and then introduce instrumental variable methods for the analysis of such trials. We concentrate mainly on situations in which compliance is all or nothing (either the patient receives the allocated treatment or they do not--in the latter case they may receive no treatment or a treatment other than the one allocated). The main purpose of the review is to illustrate the use of latent class (finite mixture) models, using maximum likelihood, for complier-average causal effect estimation under varying assumptions concerning the mechanism of the missing outcome data.     

Structural mean models for compliance analysis in randomized clinical trials and the impact of errors on measures of exposure

Partial compliance with assigned treatment regimes is common in drug trials and calls for a causal analysis of the effect of treatment actually received. As such observed exposure is no longer randomized, selection bias must be carefully accounted for. The framework of potential outcomes allows this by defining a subject-specific treatment-free reference outcome, which may be latent and is modelled in relation to the observed (treated) data. Causal parameters enter these structural models explicitly. In this paper we review recent progress in randomization-based inference for structural mean modelling, from the additive linear model to the structural generalized linear models. An arsenal of tools currently available for standard association regression has steadily been developed in the structural setting, providing many parallel features to help randomization-based inference. We argue that measurement error on exposure is an important practical complication that has, however, not yet been addressed. We show how standard additive linear structural mean models are robust against unbiased measurement error and how efficient, asymptotically unbiased inference can be drawn when the degree of measurement error bias is known. The impact of measurement error is illustrated in a blood pressure example and finite sample properties are verified by simulation. We end with a plea for more and careful use of this methodology and point to directions for further development.     

Bivariate random effects models for meta-analysis of comparative studies with binary outcomes: Methods for the absolute risk difference and relative risk

Multivariate meta-analysis is increasingly utilised in biomedical research to combine data of multiple comparative clinical studies for evaluating drug efficacy and safety profile. When the probability of the event of interest is rare, or when the individual study sample sizes are small, a substantial proportion of studies may not have any event of interest. Conventional meta-analysis methods either exclude such studies or include them through ad hoc continuality correction by adding an arbitrary positive value to each cell of the corresponding 2?×?2 tables, which may result in less accurate conclusions. Furthermore, different continuity corrections may result in inconsistent conclusions. In this article, we discuss a bivariate Beta-binomial model derived from Sarmanov family of bivariate distributions and a bivariate generalised linear mixed effects model for binary clustered data to make valid inferences. These bivariate random effects models use all available data without ad hoc continuity corrections, and accounts for the potential correlation between treatment (or exposure) and control groups within studies naturally. We then utilise the bivariate random effects models to reanalyse two recent meta-analysis data sets.     

Group sequential testing in dental clinical trials with longitudinal data on multiple outcome variables

In this article, methods are proposed for design and analysis of clinical trials that gather longitudinal data on multiple outcome variables. A valid test of the null hypothesis of no treatment group differences can be obtained for any choice of a working alternative hypothesis and a working covariance matrix for the outcome variables. Increased power can be achieved by accurate modeling of the true treatment effect and covariance structure. Implementation of the procedure is simple using existing software for generalized estimating equations. The procedure is an extension of the 'derived variable' technique (univariate analysis applied to a linear combination of the outcome variables) and also of O'Brien's generalized least squares test. The procedure is extended to allow sequential testing using an arbitrary division of the total type I error rate among repeated hypothesis tests. The methods are illustrated by the design of a study on the safety of dental amalgam fillings, which served as the motivation for the research.     

Diagnostic test analyses in search of their gold standard: latent class analyses with random effects

We review methods for analysing the performance of several diagnostic tests when patients must be classified as having a disease or not, when no gold standard is available. For latent class analysis (LCA) to provide consistent estimates of sensitivity, specificity and prevalence, traditionally 'independent errors conditional on disease status' have been assumed. Recent approaches derive estimators under more flexible assumptions. However, all likelihood-based approaches suffer from the sparseness of tables generated by this type of data; an issue which is often ignored. In light of this, we examine the potential and limitations of LCAs of diagnostic tests. We are guided by a data set of visceral leishmaniasis tests. In the example, LCA estimates suggest that the traditional reference test, parasitology, has poor sensitivity and underestimates prevalence. From a technical standpoint, including more test results in one analysis yields increasing degrees of sparseness in the table which are seen to lead to discordant values of asymptotically equivalent test statistics and eventually lack of convergence of the LCA algorithm. We suggest some strategies to cope with this.     

Randomized trials with polyunsaturated fatty acid interventions in preterm and term infants: Functional and clinical outcomes

The role of polyunsaturated fatty acids (PUFA) in infant nutrition has now been well studied through many randomized controlled trials (RCT) that provide us with high-quality evidence, particularly in relation to efficacy. As a result of a systematic search of the literature for RCT of supplementation of formulas of term and preterm infants with long-chain polyunsaturated fatty acids (LC-PUFA), we have identified 21 studies that have physiological responses or growth as outcomes. There have been 11 RCT involving preterm infants, and many of these claim a beneficial effect on visual, neural, or developmental outcomes. There are some reports of negative effects on growth in relation to the addition of n−3 LC-PUFA to preterm formulas but not when AA is added with n−3 LC-PUFA. Small studies have shown no differences in prostanoid formation or peroxidative stress between n−3 IC-PUFA-supplemented and unsupplemented infants. There have been 10 RCT involving term infants; whereas some studies report an effect on visual/neural/developmental outcomes, an equal number report no effect. There have been no reports of negative effects of n−3 LC-PUFA on growth in term infants. In summary, there appear to be few safety concerns relating to the use of LC-PUFA in infant nutrition. The potential medium- and long-term effects of including these compounds in the early diet of infants remain to be assessed.     

An attempt to simulate the bowing phenomenon in tenter with simple models

The bowing phenomenon throughout a tenter was experimentally observed with a pilot plant of successive biaxial stretching. The observed results were compared with simulated ones, by which the deformation behaviors of film in a tenter were predicted, with the assumption that the film was homogeneous isotropic, homogeneous anisotropic, heterogeneous isotropic, or heterogeneous anisotropic for a two-dimensional elastic body with an FEM. Comparatively good agreement between the simulated and observed results was obtained for a heterogeneous anisotropic elastic body with an initial mesh, involving in advance a plastic deformation part. © 1993 John Wiley & Sons, Inc.     

Scale-up effects due to near-wall channelling in isothermal adsorption columns: on the limitations in the use of plug flow models

The influence of the near-wall channelling phenomenon on the scale-up effects of adsorption column is analysed numerically. The radial fluid velocity profile is approximated by using the extended Brinkman model. The broadening of breakthrough curves during a change in adsorption column diameter is predicted either from the two-dimensional model of non-linear, favorable adsorption with local fluid velocity included directly in the differential mass balance equation or from the plug flow model with the influence of the flow distribution involved in the value of the effective axial dispersion coefficient. The predicted scale-up parameters are compared with available experimental data. Under discussion are the operating conditions which make the scale-up effects due to near-wall channelling significant and possible improper application of the dispersed plug flow model.     

Scale errors in model tests on granular media with special reference to silo models

Theoretical solutions to silo problems are only given in a relatively few cases, mainly because of difficulties in formulating the constitutive equations for the silo medium. Wide use has therefore been made of model tests. In the present paper use is made of the centrifuge techniques to check the limitations of the method normally applied, in which model tests are performed neglecting the influence of volume forces.It is found that the single method can be used for materials normally considered to be non-cohesive, provided the model is not too small. This verifies Weber's assumptions for such models.The centrifuge method is recommended for cohesive materials, and an experimental technique for measuring pressure and visualizing flow patterns is described.     

Arachidonic acid to eicosapentaenoic acid ratio in blood correlates positively with clinical symptoms of depression

In this study of 20 moderately to severely depressed patients, diagnosed using current research diagnostic criteria and excluding known bipolar affective disorder and reactive depression, we investigated relationships between severity of depression and levels and ratios of n-3 and n-6 long-chain polyunsaturated fatty acids (PUFA) in plasma and erythrocyte phospholipids (PL). Severity of depression was measured using the 21-item Hamilton depression rating scale (HRS) and a second linear rating scale (LRS) of severity of depressive symptoms that omitted anxiety symptoms. There was a significant correlation between the ratio of erythrocyte PL arachidonic acid (AA) to eicosapentaenoic acid (EPA) and severity of depression as rated by the HRS (P<0.05) and the LRS for depression (P< 0.01). There was also a significant negative correlation between erythrocyte EPA and the LRS (P<0.05). The AA/EPA ratio in plasma PL and the ratio of erythrocyte long-chain (C₂₀ and C₂₂ carbon) n-6 to long-chain n-3 PUFA were also significantly correlated with the LRS (P<0.05). These findings do not appear to be simply explained by differences in dietary intake of EPA. We cannot determine whether the high ratios of AA/EPA in both plasma and erythrocyte PL are the result of depression or whether tissue PUFA change predate the depressive symptoms. We suggest, however, that our findings provide a basis for studying the effect of the nutritional supplementation of depressed subjects, aimed at reducing the AA/EPA ratio in tissues and severity of depression.     

Assessment of soy phytoestrogens' effects on bone turnover indicators in menopausal women with osteopenia in Iran: a before and after clinical trial

Background  

Osteoporosis is the gradual declining in bone mass with age, leading to increased bone fragility and fractures. Fractures in hip and spine are known to be the most important complication of the disease which leads in the annual mortality rate of 20% and serious morbidity rate of 50%. Menopause is one of the most common risk factors of osteoporosis. After menopause, sex hormone deficiency is associated with increased remodeling rate and negative bone balance, leading to accelerated bone loss and micro-architectural defects, resulting into increased bone fragility.     

Comparison of analytical and CFD models with regard to micron particle deposition in a human 16-generation tracheobronchial airway model

A representative human tracheobronchial tree has been geometrically represented with adjustable triple-bifurcation units (TBUs) in order to effectively simulate local and global micron particle depositions. It is the first comprehensive attempt to compute micron-particle transport in a (Weibel Type A) 16-generation model with realistic inlet conditions. The CFD modeling predictions are compared to experimental observations as well as analytical modeling results. Based on the findings with the validated computer simulation model, the following conclusions can be drawn:(i) Surprisingly, simulated inspiratory deposition fractions for the entire tracheobronchial region (say, G0–G15) with repeated TBUs in parallel and in series agree rather well with those calculated using analytical/semi-empirical expressions. However, the predicted particle-deposition fractions based on such analytical formulas differ greatly from the present simulation results for most local bifurcations, due to the effects of local geometry and resulting local flow features and particle distributions. Clearly, the effects of realistic geometries, flow structures and particle distributions in different individual bifurcations accidentally cancel each other so that the simulated deposition efficiencies during inspiration in a relatively large airway region may agree quite well with those obtained from analytical expressions. Furthermore, with the lack of local resolution, analytical models do not provide any physical insight to the air–particle dynamics in the tracheobronchial region.(ii) The maximum deposition enhancement factors (DEF) may be in the order of 10² to 10³ for micron particles in the tracheobronchial airways, implying potential health effects when the inhaled particles are toxic.(iii) The presence of sedimentation for micron particles in lower bronchial airways may change the local impaction-based deposition patterns seen for larger airways and hence reduces the maximum DEF values.(iv) Rotation of an airway bifurcation cause a significant impact on distal bifurcations rather than on the proximal ones. Such geometric effects are minor when compared to the effects of airflow and particle transport/deposition history, i.e., upstream effects.     

Molecular evolution of a defined DNA sequence with accumulation of mutations in a single round by a dual approach to random chemical mutagenesis (DuARCheM)

Directed evolution has paved the way to a new era of protein and nucleic acid molecules with improved and enhanced properties. The utmost important component of directed evolution is random mutations in a defined DNA sequence. The utility of random chemical mutagenesis in directed evolution studies is dwindling due to the inherent flaws with whole-organism mutagenesis and the in vitro approach. Here, we report a novel Dual Approach to Random Chemical Mutagenesis (DuARCheM) to introduce random mutations in a defined DNA fragment. DuARCheM involves in vivo chemical mutagenesis and in vitro genetic manipulations. The resulting library revealed an accumulation of mutations in its members. These results imply that the parent mutation is carried in the further generations within the same library. This method might help to change random chemical mutagenesis because the combination of in vivo and in vitro approaches mimics the amplification and mutation that is performed by PCR-based mutagenesis, and at the same time the mutations are confined to the desired gene. Moreover, the mutagen pressure is greater in chemical mutagenesis than in a Taq-polymerase-based error-prone system. Concomitant amplification and mutation in the DuARCheM method leads to a better spectrum of mutants because the plasmid construct is exponentially amplified in the presence of mutagen pressure, unlike in the in vitro chemical mutagenesis system in which the template molecule does not replicate. This work is able to nullify all the disadvantages that are associated with random chemical mutagenesis, and could make random chemical mutagenesis an indispensable tool in directed evolution studies.     

Electrodes covered with random arrays of microdroplets: heterogeneous electron transfer coupled to catalytic reaction at the liquid/liquid interface in the prism film geometry approximation

A model for the catalytic (EC’) mechanism on the three-phase electrode arrangement is developed. It is assumed that a solid electrode surface is partly covered by an insulating solution of substance A in an organic liquid which is immiscible with water and immersed into an aqueous solution of a depolarizer and a supporting electrolyte. At the liquid/liquid interface the substance A reacts with the aqueous phase product of the electrode reaction occurring at the uncovered parts of the electrode with regeneration of the depolarizer. An average cyclic voltammetry response, a distribution of the current density and a pure kinetic current are calculated using a finite difference method.     

Some observations on the concept of the degree of crystallinity in cellulose fibers with reference to moisture effects

A conceptual effort has been made here to reconcile two approaches of defining the degree of crystallinity by the x-ray diffraction method, (a) one as proportion of x-ray diffracting matter in the entire fibrous material, and (b) another as the extent of qualitative perfection of the crystalline region only, since these two approaches often lead to opposite conclusions from the same set of observations.     

The inhibitive effects of azasterols on sterol metabolism and growth and development in insects with special reference to the tobacco hornworm

Several monoazasterols were found to be potent inhibitors of Δ²⁴- and Δ^22,24- reductase enzyme(s) in the tobacco hornworm,Manduca sexta (Johannson). Certain of these inhibitors also prevented normal larval development and pupation in the hornworm at dietary concentrations in the parts per million range. Comparative studies with several different insects indicated differences between the species with respect to the effects of the azasterols. The relationship of azasterol structure to the inhibitory effect(s) on sterol metabolism and larval development is discussed. One of 12 papers to be published from the “Sterol Symposium” presented at the AOCS Meeting, New Orleans, April 1970.     

Modelling of combined mass transfer-kinetic effects in an enzyme membrane reactor system with a direct approach to the identification of intrinsic rate parameters

A methodology for identifying non-linear parameters in a generalised Briggs-Haldane rate expression for immobilised enzyme membrane flow reactors has been developed for the intermediate case where mutually rate-controlling processes of mass transfer and enzymatic reaction prevail. The technological significance of the estimation procedure lies in the ability of the algorithm to handle parameter identification in non-linear, two-point boundary value problems which are prevalent in both immobilised enzyme and non-enzymic heterogeneous catalysed reactor systems. The methodology was successfully implemented on an experimental level using quasi-steady-state conversion data for the model system of urea/collagen-urease in a spiral-wound, biocatalytic reactor module. By using a novel procedure of pepsin pretreatment of the collagen host membrane before enzyme impregnation, followed by glutaraldehyde crosslinking, it was possible to enhance the activity and stability of the immobilised enzyme complex to relatively high levels where interphase and intraphase diffusional limitations mutually controlled the rate of reaction. Information on the coefficient of mass transfer at the interface between solid and fluid phases was also obtained as part of the estimation procedure.     

Capture rates of the European pine sawfly, Neodiprion sertifer, in pheromone traps, with special regard to effects of wind speed

Males of the European pine sawfly, Neodiprion sertifer Geoffr., were marked and released downwind from pheromone traps, baited with 100 g of the sex pheromone (2S,3S,7S)-3,7-dimethyl-2-pentadecyl acetate. Males were released 5 m downwind from one trap, or downwind from five traps, 50 m or 200 m away. The average capture rates after 24 hr were 21.5%, 17.7% and 3.8%, respectively. The capture rate was highest at moderate wind speeds (1–2 m/sec) in the 50 m experiments, whereas it decreased above wind speeds of 1.5 m/sec in the 200 m experiments. With no precipitation and >13.5°C during overcast, wind speed is presumably the most important climatic factor for N. sertifer males flying upwind to a pheromone source. Travel time, the elapsed time form take-off to landing on the trap, varied considerably, and the shortest recorded travel times were 1, 6 and 45 min for the 5, 50, and 200 m experiments, respectively. The trap efficiency i.e., number of captured males per number of males that landed on the trap, was estimated at 52% in the 5 m experiments. The sampling range after 24 hr was calculated at approximately 400 m by regression analysis. The combination of the males' flight ability during upwind progress and their longevity (12 days), suggests a potentially large seasonal sampling range of the traps used in this study.