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International audience; Data sharing enhances the value of medical research and builds trust in clinical trials, but more biomedical researchers need to be trained in these approaches, which include meta-research, data science and ethical, legal and social issues.

Summary For randomized clinical trials where a single, primary, binary endpoint would require unfeasibly large sample sizes, composite endpoints (CEs) are widely chosen as the primary endpoint. Despite being commonly used, CEs entail challenges in designing and interpreting results. Given that the components may be of different relevance and have different effect sizes, the choice of components must be made carefully. Especially, sample size calculations for composite binary endpoints depend not only on the anticipated effect sizes and event probabilities of the composite components but also on the correlation between them. However, information on the correlation between endpoints is usually not reported in the literature which can be an obstacle for designing future sound trials. We consider two-arm randomized controlled trials with a primary composite binary endpoint and an endpoint that consists only of the clinically more important component of the CE. We propose a trial design that allows an adaptive modification of the primary endpoint based on blinded information obtained at an interim analysis. Especially, we consider a decision rule to select between a CE and its most relevant component as primary endpoint. The decision rule chooses the endpoint with the lower estimated required sample size. Additionally, the sample size is reassessed using the estimated event probabilities and correlation, and the expected effect sizes of the composite components. We investigate the statistical power and significance level under the proposed design through simulations. We show that the adaptive design is equally or more powerful than designs without adaptive modification on the primary endpoint. Besides, the targeted power is achieved even if the correlation is misspecified at the planning stage while maintaining the type 1 error. All the computations are implemented in R and illustrated by means of a peritoneal dialysis trial.

Randomized clinical trials in oncology typically utilize time-to-event endpoints such as progression-free survival or overall survival as their primary efficacy endpoints, and the most commonly used statistical test to analyze these endpoints is the log-rank test. The power of the log-rank test depends on the behavior of the hazard ratio of the treatment arm to the control arm. Under the assumption of proportional hazards, the log-rank test is asymptotically fully efficient. However, this proportionality assumption does not hold true if there is a delayed treatment effect. Cancer immunology has evolved over time and several cancer vaccines are available in the market for treating existing cancers. This includes sipuleucel-T for metastatic hormone-refractory prostate cancer, nivolumab for metastatic melanoma, and pembrolizumab for advanced nonsmall-cell lung cancer. As cancer vaccines require some time to elicit an immune response, a delayed treatment effect is observed, resulting in a violation of the proportional hazards assumption. Thus, the traditional log-rank test may not be optimal for testing immuno-oncology drugs in randomized clinical trials. Moreover, the new immuno-oncology compounds have been shown to be very effective in prolonging overall survival. Therefore, it is desirable to implement a group sequential design with the possibility of early stopping for overwhelming efficacy. In this paper, we investigate the max-combo test, which utilizes the maximum of two weighted log-rank statistics, as a robust alternative to the log-rank test. The new test is implemented for two-stage designs with possible early stopping at the interim analysis time point. Two classes of weights are investigated for the max-combo test: the Fleming and Harrington (1981) (Formula presented.) weights and the Magirr and Burman (2019) modest (Formula presented.) weights.

SummaryWe analyze the age and sex distribution of the reported COVID-19 deaths in Austria. In accordance with international studies, the Austrian data also suggests that the risk of death increases substantially with age. The observed age dependency of the proportions of registered COVID-19 deaths in relation to the population sizes in the age groups is approximately exponential, similar to the age dependency of the general age specific mortality rate. Furthermore, we compare the general age specific mortality rate in Austria with the estimates of the SARS-CoV‑2 infection fatality rate by Ferguson et al. (2020). The parallels to the general age specific mortality rates do not imply that COVID-19 does not pose an additional risk. On the contrary, it follows from the structure and magnitude of the infection fatality rate that it is substantial, especially for higher age groups. However, since in many cases persons with severe pre-existing conditions are affected, it is not yet possible to estimate what effects COVID-19 will have on life expectancy.

Late antibody-mediated rejection (ABMR) is a leading cause of kidney allograft failure. Uncontrolled studies have suggested efficacy of the proteasome inhibitor bortezomib, but no systematic trial has been undertaken to support its use in ABMR. In this randomized, placebo-controlled trial (the Bortezomib in Late Antibody-Mediated Kidney Transplant Rejection [BORTEJECT] Trial), we investigated whether two cycles of bortezomib (each cycle: 1.3 mg/m2 intravenously on days 1, 4, 8, and 11) prevent GFR decline by halting the progression of late donor-specific antibody (DSA)–positive ABMR. Forty-four DSA-positive kidney transplant recipients with characteristic ABMR morphology (median time after transplant, 5.0 years; pretransplant DSA documented in 19 recipients), who were identified on cross-sectional screening of 741 patients, were randomly assigned to receive bortezomib (n=21) or placebo (n=23). The 0.5-ml/min per 1.73 m2 per year (95% confidence interval, −4.8 to 5.8) difference detected between bortezomib and placebo in eGFR slope (primary end point) was not significant (P=0.86). We detected no significant differences between bortezomib- and placebo-treated groups in median measured GFR at 24 months (33 versus 42 ml/min per 1.73 m2; P=0.31), 2-year graft survival (81% versus 96%; P=0.12), urinary protein concentration, DSA levels, or morphologic or molecular rejection phenotypes in 24-month follow-up biopsy specimens. Bortezomib, however, associated with gastrointestinal and hematologic toxicity. In conclusion, our trial failed to show that bortezomib prevents GFR loss, improves histologic or molecular disease features, or reduces DSA, despite significant toxicity. Our results reinforce the need for systematic trials to dissect the efficiency and safety of new treatments for late ABMR.

Background The ASTERIX project developed a number of novel methods suited to study small populations. The objective of this exercise was to evaluate the applicability and added value of novel methods to improve drug development in small populations, using real world drug development programmes as reported in European Public Assessment Reports. Methods The applicability and added value of thirteen novel methods developed within ASTERIX were evaluated using data from 26 European Public Assessment Reports (EPARs) for orphan medicinal products, representative of rare medical conditions as predefined through six clusters. The novel methods included were ‘innovative trial designs’ (six methods), ‘level of evidence’ (one method), ‘study endpoints and statistical analysis’ (four methods), and ‘meta-analysis’ (two methods) and they were selected from the methods developed within ASTERIX based on their novelty; methods that discussed already available and applied strategies were not included for the purpose of this validation exercise. Pre-requisites for application in a study were systematized for each method, and for each main study in the selected EPARs it was assessed if all pre-requisites were met. This direct applicability using the actual study design was firstly assessed. Secondary, applicability and added value were explored allowing changes to study objectives and design, but without deviating from the context of the drug development plan. We evaluated whether differences in applicability and added value could be observed between the six predefined condition clusters. Results and discussion Direct applicability of novel methods appeared to be limited to specific selected cases. The applicability and added value of novel methods increased substantially when changes to the study setting within the context of drug development were allowed. In this setting, novel methods for extrapolation, sample size re-assessment, multi-armed trials, optimal sequential design for small sample sizes, Bayesian sample size re-estimation, dynamic borrowing through power priors and fall-back tests for co-primary endpoints showed most promise - applicable in more than 40% of evaluated EPARs in all clusters. Most of the novel methods were applicable to conditions in the cluster of chronic and progressive conditions, involving multiple systems/organs. Relatively fewer methods were applicable to acute conditions with single episodes. For the chronic clusters, Goal Attainment Scaling was found to be particularly applicable as opposed to other (non-chronic) clusters. Conclusion Novel methods as developed in ASTERIX can improve drug development programs. Achieving optimal added value of these novel methods often requires consideration of the entire drug development program, rather than reconsideration of methods for a specific trial. The novel methods tested were mostly applicable in chronic conditions, and acute conditions with recurrent episodes. Electronic supplementary material The online version of this article (10.1186/s13023-018-0925-0) contains supplementary material, which is available to authorized users.

Background To assess uncertainty in regulatory decision-making for orphan medicinal products (OMP), a summary of the current basis for approval is required; a systematic grouping of medical conditions may be useful in summarizing information and issuing recommendations for practice. Methods A grouping of medical conditions with similar characteristics regarding the potential applicability of methods and designs was created using a consensus approach. The 125 dossiers for authorised OMP published between 1999 and 2014 on the EMA webpage were grouped accordingly and data was extracted from European Public Assessment Reports (EPARs) to assess the extent and robustness of the pivotal evidence supporting regulatory decisions. Results 88% (110/125) of OMP authorizations were based on clinical trials, with 35% (38/110) including replicated pivotal trials. The mean (SD) number of pivotal trials per indication was 1.4 (0.7), and the EPARs included a median of three additional non-pivotal supportive studies. 10% of OMPs (13/125) were authorised despite only negative pivotal trials. One-third of trials (53/159) did not include a control arm, one-third (50/159) did not use randomisation, half the trials (75/159) were open-label and 75% (119/159) used intermediate or surrogate variables as the main outcome. Chronic progressive conditions led by multiple system/organs, conditions with single acute episodes and progressive conditions led by one organ/system were the groups where the evidence deviated most from conventional standards. Conditions with recurrent acute episodes had the most robust datasets. The overall size of the exposed population at the time of authorisation of OMP − mean(SD) 190.5 (202.5) − was lower than that required for the qualification of clinically-relevant adverse reactions. Conclusions The regulatory evidence supporting OMP authorization showed substantial uncertainties, including weak protection against errors, substantial use of designs unsuited for conclusions on causality, use of intermediate variables, lack of a priorism and insufficient safety data to quantify risks of relevant magnitude. Grouping medical conditions based on clinical features and their methodological requirements may facilitate specific methodological and regulatory recommendations for the study of OMP to strengthen the evidence base. Electronic supplementary material The online version of this article (10.1186/s13023-018-0926-z) contains supplementary material, which is available to authorized users.

The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes.

Identifying subgroups of patients with an enhanced response to a new treatment has become an area of increased interest in the last few years. When there is knowledge about possible subpopulations with an enhanced treatment effect before the start of a trial it might be beneficial to set up a testing strategy, which tests for a significant treatment effect not only in the full population, but also in these prespecified subpopulations. In this paper, we present a parametric multiple testing approach for tests in multiple populations for dose‐finding trials. Our approach is based on the MCP‐Mod methodology, which uses multiple comparison procedures (MCPs) to test for a dose–response signal, while considering multiple possible candidate dose–response shapes. Our proposed methods allow for heteroscedastic error variances between populations and control the family‐wise error rate over tests in multiple populations and for multiple candidate models. We show in simulations that the proposed multipopulation testing approaches can increase the power to detect a significant dose–response signal over the standard single‐population MCP‐Mod, when the specified subpopulation has an enhanced treatment effect.

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017. The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods., Comment: 9 pages, 3 figures

If the response to treatment depends on genetic biomarkers, it is important to identify predictive biomarkers that define (sub-)populations where the treatment has a positive benefit risk balance. One approach to determine relevant subpopulations are subgroup analyses where the treatment effect is estimated in biomarker positive and biomarker negative groups. Subgroup analyses are challenging because several types of risks are associated with inference on subgroups. On the one hand, by disregarding a relevant subpopulation a treatment option may be missed due to a dilution of the treatment effect in the full population. Furthermore, even if the diluted treatment effect can be demonstrated in an overall population, it is not ethical to treat patients that do not benefit from the treatment when they can be identified in advance. On the other hand, selecting a spurious subpopulation increases the risk to restrict an efficacious treatment to a too narrow fraction of a potential benefiting population. We propose to quantify these risks with utility functions and investigate nonadaptive study designs that allow for inference on subgroups using multiple testing procedures as well as adaptive designs, where subgroups may be selected in an interim analysis. The characteristics of such adaptive and nonadaptive designs are compared for a range of scenarios.

Background: Clinical trials are typically designed using the classical frequentist framework to constrain type I and II error rates. Sample sizes required in such designs typically range from hundreds to thousands of patients which can be challenging for rare diseases. It has been shown that rare disease trials have smaller sample sizes than non-rare disease trials. Indeed some orphan drugs were approved by the European Medicines Agency based on studies with as few as 12 patients. However, some studies supporting marketing authorisation included several hundred patients. In this work, we explore the relationship between disease prevalence and other factors and the size of interventional phase 2 and 3 rare disease trials conducted in the US and/or EU. We downloaded all clinical trials from Aggregate Analysis of ClinialTrials.gov (AACT) and identified rare disease trials by cross-referencing MeSH terms in AACT with the list from Orphadata. We examined the effects of prevalence and phase of study in a multiple linear regression model adjusting for other statistically significant trial characteristics.Results: Of 186941 ClinicalTrials.gov trials only 1567 (0.8%) studied a single rare condition with prevalence information from Orphadata. There were 19 (1.2%) trials studying disease with prevalence Conclusions: We found that prevalence was associated with the size of phase 3 trials with trials of rarer diseases noticeably smaller than the less rare diseases trials where phase 3 rarer disease (prevalence

DNA methylation is part of the epigenetic gene regulation complex, which is relevant for the pathogenesis of cancer. We performed a genome-wide search for methylated CpG islands in tumors and corresponding non-malignant lung tissue samples of 101 stages I-III non-small cell lung cancer (NSCLC) patients by combining methylated DNA immunoprecipitation and microarray analysis. Overall, we identified 2414 genomic positions differentially methylated between tumor and non-malignant lung tissue samples. Ninety-seven percent of them were found to be tumor-specifically methylated. Annotation of these genomic positions resulted in the identification of 477 tumor-specifically methylated genes of which many are involved in regulation of gene transcription and cell adhesion. Tumor-specific methylation was confirmed by a gene-specific approach. In the majority of tumors, methylation of certain genes was associated with loss of their protein expression determined by immunohistochemistry. Treatment of NSCLC cells with epigenetically active drugs resulted in upregulated expression of many tumor-specifically methylated genes analyzed by gene expression microarrays suggesting that about one-third of these genes are transcriptionally regulated by methylation. Moreover, comparison of methylation results with certain clinicopathological characteristics of the patients suggests that methylation of HOXA2 and HOXA10 may be of prognostic relevance in squamous cell carcinoma (SCC) patients. In conclusion, we identified a large number of tumor-specifically methylated genes in NSCLC patients. Expression of many of them is regulated by methylation. Moreover, HOXA2 and HOXA10 methylation may serve as prognostic parameters in SCC patients. Overall, our findings emphasize the impact of methylation on the pathogenesis of NSCLCs.

Adaptive clinical trials attract great attention from academia, industry and regulatory authorities. Both the European Medicines Agency and the US FDA have clarified their positions in recently issued (final or draft) guidance documents. With this background, current trends and issues were analyzed in a panel discussion at the International Society for Biopharmaceutical Statistics (ISBS) meeting in March 2011. In this article, members of the panel summarize their thoughts based on this discussion.

The confirmatory analysis of pre-specified multiple hypotheses has become common in pivotal clinical trials. In the recent past multiple test procedures have been developed that reflect the relative importance of different study objectives, such as fixed sequence, fallback, and gatekeeping procedures. In addition, graphical approaches have been proposed that facilitate the visualization and communication of Bonferroni-based closed test procedures for common multiple test problems, such as comparing several treatments with a control, assessing the benefit of a new drug for more than one endpoint, combined non-inferiority and superiority testing, or testing a treatment at different dose levels in an overall and a subpopulation. In this paper, we focus on extended graphical approaches by dissociating the underlying weighting strategy from the employed test procedure. This allows one to first derive suitable weighting strategies that reflect the given study objectives and subsequently apply appropriate test procedures, such as weighted Bonferroni tests, weighted parametric tests accounting for the correlation between the test statistics, or weighted Simes tests. We illustrate the extended graphical approaches with several examples. In addition, we describe briefly the gMCP package in R, which implements some of the methods described in this paper.

To determine the incidence and risk factors of early postpartum hysterectomy at the University Hospital in Vienna.Retrospective case-control study.General Hospital Vienna, a tertiary referral center.All 15,858 women who gave birth between 1st January 2003 and 31st December 2008.Analysis of all cases of early postpartum hysterectomy using data from the clinical documentation system.Postpartum hysterectomy done during or within 24 hours of birth.The incidence of early postpartum hysterectomy was 1.39/1,000. Abnormally adherent placenta was the most common cause for hysterectomy followed by uterine atony and uterine rupture. There were no maternal deaths. Abnormal placentation, increased blood loss and lower gestational age were significant risk factors in women undergoing hysterectomy. The newborns of these women had a lower birthweight, significantly lower Apgar scores at 1 and 5 minutes and were more often transferred to the neonatal intensive care unit (NICU). An additional analysis in a sample of women with uterine atony identified age as risk factor for hysterectomy.Abnormal placentation, increased blood loss, low gestational age and maternal age are risk factors for early postpartum hysterectomy.

Department of Anesthesia, General Intensive Care and Pain Control,Vienna Human Pain Research Group, Medical University Vienna, Vienna, AustriaBackground: Combining ropivacaine with sufentanil forintrathecal (i.t.) analgesia inlabor is well recognized, butinformation on dosing is limited. This study aimed todetermine the ED 50 of i.t. ropivacaine and to assess theeffect of adding defined low doses of sufentanil.Methods: This was a two-phase, double-blind, rando-mized and prospective study. One hundred and fifteenparturients receiving combined spinal epidural analgesiawere allocated to one of four groups to receive ropivacaineor sufentanil alone or in combination. In phase one,sufentanil dose–response wascalculated using logisticregression. In phase two, ED 50 of ropivacaine and of thecombination with a fixed dosage of sufentanil at ED 20 andED 40 was evaluated using the technique of up–downsequential allocation. Analgesic effectiveness was assessed15min after injection using a 100mm visual analog scale,with o10mm lasting for 45min defined as effective.Furthermore, side effects and duration were recorded.Results: The ED 50 of i.t. ropivacaine was 4.6mg [95%confidence intervals (95% CI) 4.28, 5.31]. Adding sufenta-nil at ED 20 significantly decreased the ED 50 of i.t.ropivacaine to 2.1mg (95%CI 1.75, 2.5) (Po0.005); atED 40, the reduction was similar (Po0.005). Combiningsufentanil with ropivacaine resulted in a dose-indepen-dent prolongation of analgesia. Besides pruritus, whichwas well tolerated, there were no differences in sideeffects.Conclusion: Adding sufentanil at ED 20 results in a morethan 50% dose-sparing effect of ropivacaine and consider-ably prolongs analgesia. Increasing dosage implicates noclinical benefit.

We provide a method for obtaining confidence intervals, point estimates, and p-values for the primary effect size parameter at the end of a two-arm group sequential clinical trial in which adaptive changes have been implemented along the way. The method is based on applying the adaptive hypothesis testing procedure of Müller and Schäfer (2001, Biometrics 57, 886-891) to a sequence of dual tests derived from the stage-wise adjusted confidence interval of Tsiatis, Rosner, and Mehta (1984, Biometrics 40, 797-803). In the nonadaptive setting this confidence interval is known to provide exact coverage. In the adaptive setting exact coverage is guaranteed provided the adaptation takes place at the penultimate stage. In general, however, all that can be claimed theoretically is that the coverage is guaranteed to be conservative. Nevertheless, extensive simulation experiments, supported by an empirical characterization of the conditional error function, demonstrate convincingly that for all practical purposes the coverage is exact and the point estimate is median unbiased. No procedure has previously been available for producing confidence intervals and point estimates with these desirable properties in an adaptive group sequential setting. The methodology is illustrated by an application to a clinical trial of deep brain stimulation for Parkinson's disease.

To assess the inter-rater and intra-rater reliability and validity of the original and a modified Medical Research Council scale for testing muscle strength in radial palsy.Prospective, randomized validation study.Thirty-one patients with peripheral paresis of radial innervated forearm muscles were included.Wrist extension, finger extension and grip strength were evaluated by manual muscle testing. Dynamometric measurement of grip strength was performed. Pair-wise weighted kappa coefficients were calculated to determine inter-rater and intra-rater reliability. The 2 scores were compared using the signed-rank test. Spearman's correlation coefficients of the maximal relative force measurements with the median (over-raters) Medical Research Council and modified Medical Research Council scores were calculated to determine validity.Inter-rater agreement of the Medical Research Council scale (finger extension: 0.77; wrist extension: 0.78; grip strength: 0.78) and the modified Medical Research Council scale (finger extension: 0.81; wrist extension: 0.78; grip strength: 0.81) as well as intra-rater agreement of the Medical Research Council scale (finger extension: 0.86; wrist extension: 0.82; grip strength: 0.84) and the modified Medical Research Council scale (finger extension: 0.84, wrist extension: 0.81; grip strength: 0.88) showed almost perfect agreement. Spearman's correlation coefficients of the maximal relative force measurements with the median Medical Research Council and modified Medical Research Council score were both 0.78.Medical Research Council and modified Medical Research Council scales are measurements with substantial inter-rater and intra-rater reliability in evaluating forearm muscles.

Background Systemic inflammation and apoptosis-specific immune activation play a major role in acute coronary syndromes (ACS) including acute myocardial infarction (AMI). The role of systemic and coronary obtained inflammatory plasma protein interleukin-1β precursor (IL-1βp), IL-1β-converting enzyme (ICE) and the apoptosis-specific caspase-cleaved cytokeratin-18 (ccCK-18) are not known in ACS. Materials and methods Plasma samples were obtained from stable angina (SA, n = 34), unstable angina (UA, n = 37) and patients with AMI (n = 39). Coronary blood was acquired by means of thrombectomy devices (X-sizer) in AMI patients. IL-1βp, ICE and ccCK-18 were determined by enzyme-linked immunosorbent assay (ELISA). Group comparisons were evaluated by parametric Tukey test. Multivariate logistic regression analysis was performed to determine predictive values of IL-1βp, ICE and ccCK-18 as compared to creatine kinase (CK) and troponin T (TnT) in order to relate these markers with the occurrence of myocardial damage. Results IL-1βp, ICE and ccCK-18 were identified to be significantly altered in the peripheral blood of patients suffering from AMI as compared to SA and UA. ROC curves were plotted and revealed that ccCK-18 is a novel sensitive marker for the detection of myocardial damage as compared to TnT or CK. (AUC ccCK-18 0·925, TnT AUC 0·62 and CK AUC 0·858.) Moreover, ICE and ccCK-18 were significantly increased at the site of coronary occlusion as compared to peripheral blood samples in AMI patients (both P

For clinical trials with interim analyses conditional rejection probabilities play an important role when stochastic curtailment or design adaptations are performed. The conditional rejection probability gives the conditional probability to finally reject the null hypothesis given the interim data. It is computed either under the null or the alternative hypothesis. We investigate the properties of the conditional rejection probability for the one sided, one sample t-test and show that it can be non monotone in the interim mean of the data and non monotone in the non-centrality parameter for the alternative. We give several proposals how to implement design adaptations (that are based on the conditional rejection probability) for the t-test and give a numerical example. Additionally, the conditional rejection probability given the interim t-statistic is investigated. It does not depend on the unknown σ and can be used in stochastic curtailment procedures. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

In recent months one of the most controversially discussed topics among regulatory agencies, the pharmaceutical industry, journal editors, and academia has been the sharing of patient-level clinical trial data. Several projects have been started such as the European Medicines Agency´s (EMA) “proactive publication of clinical trial data”, the BMJ open data campaign, or the AllTrials initiative. The executive director of the EMA, Dr. Guido Rasi, has recently announced that clinical trial data on patient level will be published from 2014 onwards (although it has since been delayed). The EMA draft policy on proactive access to clinical trial data was published at the end of June 2013 and open for public consultation until the end of September 2013. These initiatives will change the landscape of drug development and publication of medical research. They provide unprecedented opportunities for research and research synthesis, but pose new challenges for regulatory authorities, sponsors, scientific journals, and the public. Besides these general aspects, data sharing also entails intricate biostatistical questions such as problems of multiplicity. An important issue in this respect is the interpretation of multiple statistical analyses, both prospective and retrospective. Expertise in biostatistics is needed to assess the interpretation of such multiple analyses, for example, in the context of regulatory decision-making by optimizing procedural guidance and sophisticated analysis methods.

In the literature various multiple test procedures to compare k treatments with a control have been investigated. They can be applied to establish either treatment efficacy or treatment safety. In this paper we propose procedures which control the multiple level α with respect to efficacy and safety simultaneously. On the one hand we consider a method with stagewise rejective adjustments of local levels applied to appropriately defined subfamilies of null hypotheses. When order restrictions are assumed to hold among the parameters of interest we can alternatively split the multiple level between the families of efficacy and safety null hypotheses. If either all treatments are declared to be safe or all are declared to be effective then the other family can be tested at the full multiple level α, respectively. The methods are compared in a simulation study.

This article deals with sample size reassessment for adaptive two-stage designs based on conditional power arguments utilizing the variability observed at the first stage. Fisher's product test for the p-values from the disjoint samples at the two stages is considered in detail for the comparison of the means of two normal populations. We show that stopping rules allowing for the early acceptance of the null hypothesis that are optimal with respect to the average sample size may lead to a severe decrease of the overall power if the sample size is a priori underestimated. This problem can be overcome by choosing designs with low probabilities of early acceptance or by midtrial adaptations of the early acceptance boundary using the variability observed in the first stage. This modified procedure is negligibly anticonservative and preserves the power.

Proschan and Hunsberger (1995) suggest the use of a conditional error function to construct a two stage test that meets the α level and allows a very flexible reassessment of the sample size after the interim analysis. In this note we show that several adaptive designs can be formulated in terms of such an error function. The conditional power function defined similarly provides a simple method for sample size reassessment in adaptive two stage designs.

Win–stay, lose–shift strategies in repeated games are based on an aspiration level. A move is repeated if and only if the outcome, in the previous round, was satisficing in the sense that the pay-off was at least as high as the aspiration level. We investigate the conditions under which adaptive mechanisms acting on the aspiration level (selection, for instance, or learning) can lead to an efficient outcome; in other words, when can satisficing become optimizing? Analytical results for 2 times 2-games are presented. They suggest that in a large variety of social interactions, self-centred rules (based uniquely on one's own pay-off) cannot suffice.

Win–stay, lose–shift, the principle to retain a successful action is a simple and general learning rule that can be applied to all types of repeated decision problems. In this paper I consider win–stay, lose–shift strategies with diverse memory sizes and strategies that adapt their aspiration levels, i.e. the payoff level considered as "success'’. I study their evolution for the Prisoner's Dilemma, as well as in a rapidly changing environment, where a randomly selected game is assigned to the players. For win–stay, lose–shift strategies with memory one the average payoffs are computed and their evolutionary stability is discussed. Using computer simulations I show that the win–stay, lose–shift strategies with longer memory are very successful both for the Prisoner's Dilemma, where cooperation dominates even for high noise levels, and the randomly assigned games, where the players achieve nearly the expected Pareto optimal payoffs. I discuss the impact of noise and show that the memory length of the players increases with the noise level. These results indicate that the win–stay, lose–shift principle is a very successful strategy in repeated games with noise.

Objective Dynamometric trunk muscle strength and endurance tests are performed widely within the rehabilitation management of chronic low back pain. The aim of this study was to examine the accuracy and long-term reliability of these measurements in patients with chronic low back pain. Design Cross-sectional study. Subjects Thirty-two patients with chronic low back pain, 19 healthy controls and 15 patients with chronic headache matched for age, sex and body mass index. Methods Both patient groups and healthy controls performed isokinetic and isometric trunk extensor and flexor tests on a Biodex 2000 dynamometer. The Biering-Sorensen test served to examine back muscle endurance. Borg-Category-Ratio-Scales CR-10 rated participants' body experience immediately before and after the testing. Patients with chronic low back pain repeated measurements after 3 weeks. Results Among dynamometric tests, isokinetic measurements revealed the best area under the curve (AUC = 0.89) for the discrimination between patients with chronic low back pain and healthy controls. Reliability testing revealed highly significant learning effects for isometric trunk flexion and isokinetic measurements. The Biering-Sorensen test demonstrated excellent accuracy (AUC = 0.93) and no learning effects. Borg-category-ratio-scale ratings were not associated with the observed changes. Conclusion In chronic low back pain dynamometric trunk muscle measures are limited to muscle function assessment purposes. Monitoring treatment outcome in these patients with these measures appears to be problematic because of learning effects. Based on our findings, we recommend the Biering-Sorensen test for management of chronic low back pain rehabilitation.

BACKGROUND AND AIMS: The aim of the study was to compare the clinical outcome of additional percutaneous ethanol instillation (PEI) against no further treatment in patients with hepatocellular carcinoma receiving hormonal treatment with long-acting octreotide. METHODS: In a randomized controlled trial conducted in a tertiary care center, a total of 61 patients with inoperable hepatocellular carcinoma were treated with long-acting octreotide 30 mg i.m. once a month and randomly assigned to receive either PEI (31 patients) or no further treatment (30 patients). RESULTS: Median survival time did not significantly differ between the long-acting octreotide plus PEI group (14 months; 95% CI: 9–28 months) and the long-acting octreotide alone group (22 months; 95% CI: 10–30 months) (logrank test P = 0.9). Similarly, an analysis stratifying for tumor diameter (< 5 cm or 5–8 cm) showed no significant survival differences between PEI or non-PEI treatment (logrank test P = 0.68). Progression-free survival according to RECIST was similar in the two groups (median: 3 months [3–6 months 95% CI] vs. 6 months [3–7 months 95% CI], logrank test P = 0.63). Time of local tumor control did not significantly differ between the two groups (6 months vs. 6 months). The course of alpha-fetoprotein levels and the reported quality of life were similar in the two groups. CONCLUSIONS: The addition of PEI to treatment with long-acting octreotide in patients with hepatocellular carcinoma did not result in better overall survival, longer progression-free survival or longer time of local tumor control.

This June, Peter Bauer – chief editor of Biometrical Journal from 2000–2003 and member of the editorial board since 1996 – celebrated his 65th birthday. Peter Bauer became known as one of the originators of the “adaptive designs”, a field of research that recently gained considerable popularity, not only among academia but likewise among regulatory bodies and the pharmaceutical industry. It is characteristic for Peter Bauer, that while “adaptive designs” make their way into main stream statistics, he is already on the search for new challenges and now works, among others, on statistical problems relevant to bioinformatics. His sense for dynamic research areas can be easily seen from his whole professional career where he covered a wide range of research fields including informatics, binomial and poisson processes, model robustness, optimal designs, multiple testing, sequential analysis, adaptive designs and bioinformatics. Peter Bauer started his scientific career at the medical faculty of the University of Vienna, was appointed 1985 as head of the Department of Medical Documentation and Statistics in Cologne and returned to the University of Vienna in 1994 to become the head of the Department of Medical Statistics at the medical faculty. Besides his co-operation in many clinical research projects he built up an active research group. He currently decided to accept the lead of the Core Unit for Medical Statistics and Informatics, the superordinate unit of his and several other departments since the faculty became an independent university in 2004. In view of the proceeding structural changes at the new Medical University taking this lead is just one more example for his persistent willingness to explore new challenges. As a physicist by education, Peter Bauer was part of the pioneering epoch of medical computer science in Vienna. In the late sixties he developed a programming language to model chemical reactions and worked on computer based diagnostic programs for liverdiseases. Confronted with the need for statistical expertise at the medical faculty, he turned to statistics and became a British Council Research Fellow at the Department of Statistics in Edinburgh where David Finney was department head at this time. He returned to Vienna, fascinated by the British school of medical statistics, and got involved in several challenging consulting projects that were the starting point of methodological research papers. Motivated by practical experience with high dimensional compartment models he developed a method to specify the power for the discrimination between different regression models and investigated the related statistical design concept nowadays known as T-optimality. The method was published in two research papers of the “Biometrische Zeitschrift” (Bauer, 1975a, b) one year before the journal was renamed to “Biometrical Journal”. Another example for his practically oriented methodological research is the analysis of a cross-sectional study on the caries protective effects of fluorid. To model the hazard for the occurrence of caries Peter Bauer forestalled the development of frailty models (Bauer et al., 1980, 1982). In a fruitful cooperation with Peter Hackl he contributed to the theory of quality control and multiple testing. Peter Bauer published his first paper on multiple comparisons in 1985 in the Biometrical Journal (Bauer and Hackl, 1985). The multiplicity issue in statistical inference was the subject of many subsequent works with applications in dose finding (e.g. Budde and Bauer, 1989; Bauer and Budde, 1994; Bauer et al., 1998; Bauer, Brannath and Posch, 2000), model selection (Bauer, P tscher and Hackl, 1988), equivalence testing (e.g. Bauer and Bauer, 1994)

We performed a long-term follow-up examination in children and adolescents with migraine and tension-type headache (TTH) in order to investigate the evolution of clinical features and headache diagnoses, to compare International Classification of Headache Disorders (ICHD)-I and ICHD-II criteria and to identify prognostic factors. We re-examined 227 patients (52.4± female, age 17.6 ± 3.1 years) 6.6 ± 1.6 years after their first presentation to a headache centre using identical semistructured questionnaires. Of 140 patients initially diagnosed with migraine, 25.7± were headache free, 48.6± still had migraine and 25.7± had TTH at follow-up. Of 87 patients with TTH, 37.9± were headache free, 41.4± still had TTH and 20.7± had migraine. The number of subjects with definite migraine was higher in ICHD-II than in ICHD-I at baseline and at follow-up. The likelihood of a decrease in headache frequency decreased with a changing headache location at baseline ( P < 0.0001), with the time between baseline and follow-up ( P = 0.0019), and with an initial diagnosis of migraine ( P = 0.014). Female gender and a longer time between headache onset and first examination tended to have an unfavourable impact. In conclusion, 30± of the children and adolescents presenting to a headache centre because of migraine or TTH become headache-free in the long-term. Another 20–25± shift from migraine to TTH or vice versa. ICHD-II criteria are superior to those of ICHD-I in identifying definite migraine in children and adolescents presenting to a headache centre. The prognosis is adversely affected by an initial diagnosis of migraine and by changing headache location, and it tends to be affected by an increasing time between headache onset and first presentation.

The evaluation of health-related quality of life is an established criterion for the evaluation of therapeutic measurement. Especially in the English language, a great number of different questionnaires have been developed. The original, English-language 12-item Oxford shoulder score (OSS) is a recently developed and validated patient-completed outcome measure specifically designed for the evaluation of patients suffering from shoulder pathology other than instability. Because of the lack of a comparable instrument in German, this questionnaire was translated into German and subsequently tested for validity and reliability in a cross-sectional study. Translation of the OSS was done according to the guidelines in the literature. One hundred two patients completed the German version of the OSS and the SF-36. Additionally, the Constant shoulder score and the UCLA shoulder score were included into the validation process. The psychometric properties feasibility and patient-burden parameters were also tested. The patients completed all questionnaires. The mean time required for completing the OSS was 3 min, 25 s; the mean time required for evaluation of the questionnaire was 35 s. The internal consistency tested by the Cronbach’s alpha (0.94) was high. The reproducibility tested by two different methods showed no significant difference. The construct validity showed a significant correlation between the OSS and the other scores. The instrument proved to be valid by demonstrating the same correlations predicted by standard clinical assessments and a generic patient-based instrument. Application and evaluation in clinical trial proved feasible and minimally time consuming. Therefore, the German translation of the Oxford shoulder score is a valid and reliable tool, applicable to outcome studies on shoulder patients.

Le probleme pose par l'utilisation simultanee de tests sequentiels de non inferiorite et de superiorite d'un nouveau traitement compare a un groupe controle beneficiant d'un traitement actif est etudie ici dans le cadre des plans sequentiel groupes et des plans adaptatifs a deux etapes, en considerant des familles hierarchiques continues d'hypotheses nulles unilaterales. Le fait que les frontieres decisionnelles correspondant aux hypotheses nulles individuelles puissent varier dans l'espace des parametres constitue un point fondamental. Cela permet de construire des plans experimentaux ou, par exemple, une regle d'arret stricte peut etre determinee, rejetant ou acceptant simultanement toutes les hypotheses nulles individuelles. Une autre possibilite consiste a obtenir des frontieres d'arret de type «monitoring», qui laissent a l'experimentateur une certaine flexibilite: il peut alors decider, lors de l'analyse intermediaire, si la marge de non inferiorite atteinte a cette etape lui convient, ou s'il souhaite l'adapter pour la seconde etape. Si l'on decide de passer a cette deuxieme etape, il peut alors realiser des modifications du plan en cours d'essai (par exemple reevaluer le nombre de sujets a inclure). L'approche proposee permet de «depenser» par exemple une fraction moindre du risque alpha pour etablir la preuve precoce d'une non inferiorite que la preuve precoce d'une superiorite du nouveau traitement. Plusieurs exemples types illustrent ces propositions.

We performed a cross-cultural adaptation of the “ Minnesota Living with Heart Failure Questionnaire” (LHFQ) for use in German-speaking chronic heart failure patients. The instrument was translated and back translated, pre-tested and reviewed by a committee. The German version was tested in 114 patients with chronic heart failure. Reliability was assessed by a test-retest procedure and Cronbach’ s coefe cient alpha of internal consistency (0.94). To assess concurrent validity, we compared the LHFQ sum scores with the New York Heart Association classie cation rating (r = 0.53; p < 0.0001), the 6-minute walk (r = i0.39; p < 0.0001), the left ventricular ejection fraction (r = i0.24; p = 0.011) and big-endothelin (r = 0.27; p = 0.004). Construct validity on the LHFQ scores in comparison with the Medical Outcomes Study SF-36 Health Survey (MOS SF36) was signie cant ( i0.41 to i0.74; all p < 0.0001). The reliability and validity of the German version of the LHFQ was proved; the questionnaire can be recommended for use in future clinical trials.

Orphanet journal of rare diseases : OJRD 11(1), 78 (2016). doi:10.1186/s13023-016-0464-5, Published by BioMed Central, London