A New Class of Completely Self‐Designing Clinical Trials

A flexible method is proposed for group sequentially performed clinical trials which allows for an adaptive, data‐driven sample size reassessment at each stage. By also adaptively assigning different weights to the several stages the total number of study parts can be steered to an intended early or late end of the trial in dependence on all information available prior to a stage. Although at each stage the null hypothesis is tested on rejection, the full level‐α‐test is preserved at the end of the study. The proposed method is not restricted to normally distributed responses. The discussed adaptive designing is a useful tool provided that a priori information about parameters involved in the trial are not available or subject to uncertainty. The presented learning algorithm enables the complete self‐designing of a study.     

Adaptive dose-finding: Proof of concept with type I error control

We consider an adaptive dose‐finding study with two stages. The doses for the second stage will be chosen based on the first stage results. Instead of considering pairwise comparisons with placebo, we apply one test to show an upward trend across doses. This is a possibility according to the ICH‐guideline for dose‐finding studies (ICH‐E4). In this article, we are interested in trend tests based on a single contrast or on the maximum of multiple contrasts. We are interested in flexibly choosing the Stage 2 doses including the possibility to add doses. If certain requirements for the interim decision rules are fulfilled, the final trend test that ignores the adaptive nature of the trial (naïve test) can control the type I error. However, for the more common case that these requirements are not fulfilled, we need to take the adaptivity into account and discuss a method for type I error control. We apply the general conditional error approach to adaptive dose‐finding and discuss special issues appearing in this application. We call the test based on this approach Adaptive Multiple Contrast Test. For an example, we illustrate the theory discussed before and compare the performance of several tests for the adaptive design in a simulation study.     

Trendtests with adaptive scoring

The concept of adaptive two‐stage designs is applied to the problem of testing the equality of several normal means against an ordered (monotone) alternative. The likelihood‐ratio‐test proposed by Bartholomew is known to have favorable power properties when testing against a monotonic trend. Tests based on contrasts provide a flexible way to incorporate available information regarding the pattern of the unknown true means through appropriate specification of the scores. The basic idea of the presented concept is the combination of Bartholomew 's test (first stage) with an “adaptive score test” (second stage) which utilizes the information resulting from isotonic regression estimation at the first stage. In a Monte Carlo simulation study the adaptive scoring procedure is compared to the non‐adaptive two‐stage procedure using the Bartholomew test at both stages. We found that adaptive scoring may improve the power of the two stage design, in particular if the sample size at the first stage is considerably larger than at the second stage.     

Time‐to‐event continual reassessment method incorporating treatment cycle information with application to an oncology phase I trial

Delayed dose limiting toxicities (i.e. beyond first cycle of treatment) is a challenge for phase I trials. The time‐to‐event continual reassessment method (TITE‐CRM) is a Bayesian dose‐finding design to address the issue of long observation time and early patient drop‐out. It uses a weighted binomial likelihood with weights assigned to observations by the unknown time‐to‐toxicity distribution, and is open to accrual continually. To avoid dosing at overly toxic levels while retaining accuracy and efficiency for DLT evaluation that involves multiple cycles, we propose an adaptive weight function by incorporating cyclical data of the experimental treatment with parameters updated continually. This provides a reasonable estimate for the time‐to‐toxicity distribution by accounting for inter‐cycle variability and maintains the statistical properties of consistency and coherence. A case study of a First‐in‐Human trial in cancer for an experimental biologic is presented using the proposed design. Design calibrations for the clinical and statistical parameters are conducted to ensure good operating characteristics. Simulation results show that the proposed TITE‐CRM design with adaptive weight function yields significantly shorter trial duration, does not expose patients to additional risk, is competitive against the existing weighting methods, and possesses some desirable properties.     

PHENOTYPIC AND GENOTYPIC CONVERGENCES ARE INFLUENCED BY HISTORICAL CONTINGENCY AND ENVIRONMENT IN YEAST

Different organisms have independently and recurrently evolved similar phenotypic traits at different points throughout history. This phenotypic convergence may be caused by genotypic convergence and in addition, constrained by historical contingency. To investigate how convergence may be driven by selection in a particular environment and constrained by history, we analyzed nine life‐history traits and four metabolic traits during an experimental evolution of six yeast strains in four different environments. In each of the environments, the population converged toward a different multivariate phenotype. However, the evolution of most traits, including fitness components, was constrained by history. Phenotypic convergence was partly associated with the selection of mutations in genes involved in the same pathway. By further investigating the convergence in one gene, BMH1, mutated in 20% of the evolved populations, we show that both the history and the environment influenced the types of mutations (missense/nonsense), their location within the gene itself, as well as their effects on multiple traits. However, these effects could not be easily predicted from ancestors’ phylogeny or past selection. Combined, our data highlight the role of pleiotropy and epistasis in shaping a rugged fitness landscape.     

A statistical model for under- or overdispersed clustered and longitudinal count data

We propose a likelihood-based model for correlated count data that display under- or overdispersion within units (e.g. subjects). The model is capable of handling correlation due to clustering and/or serial correlation, in the presence of unbalanced, missing or unequally spaced data. A family of distributions based on birth-event processes is used to model within-subject underdispersion. A computational approach is given to overcome a parameterization difficulty with this family, and this allows use of common Markov Chain Monte Carlo software (e.g. WinBUGS) for estimation. Application of the model to daily counts of asthma inhaler use by children shows substantial within-subject underdispersion, between-subject heterogeneity and correlation due to both clustering of measurements within subjects and serial correlation of longitudinal measurements. The model provides a major improvement over Poisson longitudinal models, and diagnostics show that the model fits well.     

Dopamine D4 receptor and serotonin transporter gene effects on the longitudinal development of infant temperament

Existing studies of the effect on infant temperament of the 48 base pair variable number of tandem repeats polymorphism in exon 3 of the dopamine D4 receptor gene, DRD4 VNTR, and the serotonin transporter-linked polymorphic region, 5-HTTLPR, have provided contradictory results, and age seems to be an important factor. The present study investigated the effect of these two polymorphisms on the stability of infant temperament between 4 and 9 months of age. Furthermore, the effect of a recently discovered single nucleotide polymorphism which modulates the 5-HTTLPR (rs25531) was investigated in relation to infant temperament. The study sample consisted of 90 infants, who were assessed by parental report at the two ages under consideration using the Revised Infant Behavior Questionnaire. It was found that infants carrying the 7-repeat allele of the DRD4 VNTR had higher levels of Negative Affect. Furthermore, there was an interaction between DRD4 VNTR and 5-HTTLPR genotype such that infants with the DRD4 VNTR 7-repeat allele and the highest expressing 5-HTTLPR genotype (L(A) L(A) ) had the highest level of Negative Affect. These effects were largely driven by scores on the Falling Reactivity scale. Genetic effects were stable across age. The results emphasize the need for developmental studies of genetic effects on temperament.     

Frequency of family dinner and adolescent body weight status: evidence from the national longitudinal survey of youth, 1997

Objective: To explore associations between overweight status and the frequency of family dinners (FFD) for adolescents and how those associations differ across race and ethnicity. Research Methods and Procedures: A sample of 5014 respondents between 12 and 15 years of age from the 1997 wave of the National Longitudinal Survey of Youth 1997 (NLSY97) was used. BMI was calculated using self‐reported height and weight; 13.3% of respondents qualified as overweight, 16.4% qualified as at‐risk‐of‐overweight, and 1.9% qualified as underweight. The remainder were normal weight. FFD was defined as the number of times respondents had dinner with their families in a typical week in the past year. Multinomial logistic regression models were estimated separately for non‐Hispanic whites vs. blacks and Hispanics for odds of belonging to the other weight categories compared with normal weight. A supplementary longitudinal analysis estimated the odds of change in overweight status between 1997 and 2000. Results: In 1997, the FFD distribution was as follows: 0, 8.3%; 1 or 2, 7.3%; 3 or 4, 13.4%; 5 or 6, 28.1%; 7, 42%. For whites, higher FFD was associated with reduced odds of being overweight in 1997, reduced odds of becoming overweight, and increased odds of ceasing to be overweight by 2000. No such associations were found for blacks and Hispanics. Discussion: Reasons for racial and ethnic differences in the relationship between FFD and overweight may include differences in the types and portions of food consumed at family meals. More research is needed to verify this.     

Characterization and ontogenetic expression analysis of the myosin light chains from the fast white muscle of mandarin fish Siniperca chuatsi

Three full-length complementary DNA (cDNA) clones were isolated encoding the skeletal myosin light chain 1 (MLC1; 1237 bp), myosin light chain 2 (MLC2; 1206 bp) and myosin light chain 3 (MLC3; 1079 bp) from the fast white muscle cDNA library of mandarin fish Siniperca chuatsi. The sequence analysis indicated that MLC1 and MLC3 were not produced from differentially spliced messenger RNAs (mRNA) as reported in birds and rodents but were encoded by different genes. The MLC2 encodes 170 amino acids, which include four EF-hand (helix-loop-helix) structures. The primary structures of the Ca(2+)-binding domain were well conserved among the MLC2s of seven other fish species. The ontogenetic expression analysis by real-time PCR showed that the three light-chain mRNAs were first detected in the gastrula stage, and their expression increased from the tail bud stage to the larval stage. All three MLC mRNAs showed longitudinal expression variation in the fast white muscle of S. chuatsi, especially MLC1 which was highly expressed at the posterior area. Taken together, the study provides a better understanding about the MLC gene structure and their expression pattern in muscle development of S. chuatsi.     

Relationship between root caries and cardiac dysrhythmia

doi: 10.1111/j.1741‐2358.2010.00367.x
Relationship between root caries and cardiac dysrythmia Background: Cardiac dysrhythmia are frequently found in the elderly population because of conduction system disease and ageing. Recent reports have suggested that dental caries and periodontal disease are predictors of coronary heart events. However, this hypothesis remains largely unproven. Objective: This study investigated the relationship between root caries and cardiac dysrhythmia in an elderly population. Subjects and methods: Among 600 subjects, 233 who were dentate at baseline underwent a baseline examination and subsequent annual investigations, including an oral examination and a 12‐lead electrocardiogram, for a 4‐year period. Analysis of covariance (ancova) was used to assess the number of sites with root caries between subjects with mean C‐reactive protein (CRP) serum level of <3.0 mg/l and those with the mean CRP serum level ≥3.0 mg/l. Logistic regression analysis was performed to assess relationship between root caries and cardiac dysrhythmia. Results: A high mean CRP serum level group had a significantly higher number of sites with root caries than a low CRP group (p < 0.001). Number of sites with root caries events was significantly associated with cardiac dysrhythmia among non‐smokers (odds ratio, 5.84; p = 0.040). These results suggest that root caries is related to the incidence of dysrhythmias in non‐smokers. Conclusions: We conclude that non‐smoking elders with root caries lesions are at an elevated risk for dysrhythmias.     

MORPHOLOGICAL RATES OF ANGIOSPERM SEED SIZE EVOLUTION

The evolution of seed size among angiosperms reflects their ecological diversification in a complex fitness landscape of life‐history strategies. The lineages that have evolved seeds beyond the upper and lower boundaries that defined nonflowering seed plants since the Paleozoic are more dispersed across the angiosperm phylogeny than would be expected under a neutral model of phenotypic evolution. Morphological rates of seed size evolution estimated for 40 clades based on 17,375 species ranged from 0.001 (Garryales) to 0.207 (Malvales). Comparative phylogenetic analysis indicated that morphological rates are not associated with the clade's seed size but are negatively correlated with the clade's position in the overall distribution of angiosperm seed sizes; clades with seed sizes closer to the angiosperm mean had significantly higher morphological rates than clades with extremely small or extremely large seeds. Likewise, per‐clade taxonomic diversification rates are not associated with the seed size of the clade but with where the clade falls within the angiosperm seed size distribution. These results suggest that evolutionary rates (morphological and taxonomic) are elevated in densely occupied regions of the seed morphospace relative to lineages whose ecophenotypic innovations have moved them toward the edges.     

Internal pilots for observational studies

Study planning often involves selecting an appropriate sample size. Power calculations require specifying an effect size and estimating “nuisance” parameters, e.g. the overall incidence of the outcome. For observational studies, an additional source of randomness must be estimated: the rate of the exposure. A poor estimate of any of these parameters will produce an erroneous sample size. Internal pilot (IP) designs reduce the risk of this error ‐ leading to better resource utilization ‐ by using revised estimates of the nuisance parameters at an interim stage to adjust the final sample size. In the clinical trials setting, where allocation to treatment groups is pre‐determined, IP designs have been shown to achieve the targeted power without introducing substantial inflation of the type I error rate. It has not been demonstrated whether the same general conclusions hold in observational studies, where exposure‐group membership cannot be controlled by the investigator. We extend the IP to observational settings. We demonstrate through simulations that implementing an IP, in which prevalence of the exposure can be re‐estimated at an interim stage, helps ensure optimal power for observational research with little inflation of the type I error associated with the final data analysis.     

Liver enzymes as a predictor for incident diabetes in a Japanese population: the Hisayama study

Objective: We studied the relationship between liver enzymes and the development of diabetes in a general Japanese population. Research Methods and Procedures: A total of 1804 non‐diabetic subjects 40 to 79 years of age were followed‐up prospectively for a mean of 9.0 years. Results: During the follow‐up, 135 subjects developed diabetes. In both sexes, the age‐adjusted cumulative incidence of diabetes increased significantly with elevating quartiles of serum γ‐glutamyltransferase (GGT) and alanine aminotransferase (ALT) levels. This pattern was also observed in aspartate aminotransferase (AST) quartiles for men but not for women. In multivariate analyses after adjusting for comprehensive risk factors and other liver enzymes, the risk of developing diabetes was significantly higher in the highest GGT quartile than in the lowest quartile [odds ratio (OR), 2.54; 95% confidence interval (CI), 1.03 to 6.26 for men; OR, 5.73; 95% CI, 1.62 to 20.19 for women]. Similar results were observed in ALT quartiles (OR, 2.32; 95% CI, 0.91 to 5.92 for men; OR, 4.40; 95% CI, 1.38 to 14.06 for women) but not in AST quartiles in either sex. Significant positive associations of GGT and ALT with diabetes were seen within each stratified category of risk factors, namely fasting insulin, BMI, waist‐to‐hip ratio, high‐sensitivity C‐reactive protein, and alcohol consumption. In receiver operating characteristic analyses, the areas under the receiver operating characteristic curve of GGT and ALT were significantly larger than that of AST, fasting insulin, waist‐to‐hip ratio, or C‐reactive protein. Discussion: Our findings suggest that serum GGT and ALT concentrations are strong predictors of diabetes in the general population, independent of known risk factors.     

Changes in carotenoid‐based plumage colour in relation to age in European Serins Serinus serinus

Yearling birds generally display duller colours than adults. This may be due to selection favouring birds with more intensely coloured plumage or to an increase in colour after the first complete moult. Most research to date on the topic has been carried out on species with structural plumage coloration or with carotenoid‐based coloration that is produced by the unmodified deposition of pigments. However, no study has been carried out on species whose carotenoids are metabolically modified before deposition. In this study, we assess age‐related changes in the carotenoid‐based coloration of European Serins, a species that metabolically processes carotenoids before they can be deposited into feathers. Birds were captured over consecutive years and we carried out both cross‐sectional and longitudinal analysis. Adults had significantly greater values of lightness and chroma than yearling birds. However, there were no changes in plumage colour when analysing the same individuals captured in subsequent seasons. Plumage lightness and chroma of adult males after moult were related to body mass, suggesting a role of body condition on plumage coloration. Our results suggest that changes in plumage coloration with age in European Serins are due to a selection process that favours more intensely coloured individuals.     

On the Use of the Shapiro‐Wilk Test in Two‐Stage Adaptive Inference for Paired Data from Moderate to Very Heavy Tailed Distributions

Paired data arises in a wide variety of applications where often the underlying distribution of the paired differences is unknown. When the differences are normally distributed, the t‐test is optimum. On the other hand, if the differences are not normal, the t‐test can have substantially less power than the appropriate optimum test, which depends on the unknown distribution. In textbooks, when the normality of the differences is questionable, typically the non‐parametric Wilcoxon signed rank test is suggested. An adaptive procedure that uses the Shapiro‐Wilk test of normality to decide whether to use the t‐test or the Wilcoxon signed rank test has been employed in several studies. Faced with data from heavy tails, the U.S. Environmental Protection Agency (EPA) introduced another approach: it applies both the sign and t‐tests to the paired differences, the alternative hypothesis is accepted if either test is significant. This paper investigates the statistical properties of a currently used adaptive test, the EPA's method and suggests an alternative technique. The new procedure is easy to use and generally has higher empirical power, especially when the differences are heavy‐tailed, than currently used methods.     

A Hierarchical Bayesian Design for Phase I Trials of Novel Combinations of Cancer Therapeutic Agents

Summary We propose a hierarchical model for the probability of dose‐limiting toxicity (DLT) for combinations of doses of two therapeutic agents. We apply this model to an adaptive Bayesian trial algorithm whose goal is to identify combinations with DLT rates close to a prespecified target rate. We describe methods for generating prior distributions for the parameters in our model from a basic set of information elicited from clinical investigators. We survey the performance of our algorithm in a series of simulations of a hypothetical trial that examines combinations of four doses of two agents. We also compare the performance of our approach to two existing methods and assess the sensitivity of our approach to the chosen prior distribution.     

Inference for a RPW‐Type Clinical Trial with Repeated Monitoring for the Treatment of Rheumatoid Arthritis

The present paper describes a controlled clinical trial to investigate the effect of Pulsed Electro‐Magnetic Field for the treatment of sequentially entering patients with Rheumatoid Arthritis. According to the study design, repeated monitorings of the patients are carried out to assess their clinical status. The allocation of the entering patients to either a therapy group or a placebo group is done using a newly designed adaptive allocation rule termed as randomized longitudinal play‐the‐winner rule. A discussion of some inference procedures is followed by the analysis of a real data, which shows a clear preference of the therapy over the placebo. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Optimal adaptive two‐stage designs for phase II cancer clinical trials

In oncology, single‐arm two‐stage designs with binary endpoint are widely applied in phase II for the development of cytotoxic cancer therapies. Simon's optimal design with prefixed sample sizes in both stages minimizes the expected sample size under the null hypothesis and is one of the most popular designs. The search algorithms that are currently used to identify phase II designs showing prespecified characteristics are computationally intensive. For this reason, most authors impose restrictions on their search procedure. However, it remains unclear to what extent this approach influences the optimality of the resulting designs. This article describes an extension to fixed sample size phase II designs by allowing the sample size of stage two to depend on the number of responses observed in the first stage. Furthermore, we present a more efficient numerical algorithm that allows for an exhaustive search of designs. Comparisons between designs presented in the literature and the proposed optimal adaptive designs show that while the improvements are generally moderate, notable reductions in the average sample size can be achieved for specific parameter constellations when applying the new method and search strategy.     

Quantitative variability of 342 plasma proteins in a human twin population

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis‐SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood‐based biomarker studies.