A graphical approach to sequentially rejective multiple test procedures

A simple and flexible graphical approach for adaptive group-sequential clinical trials

In this article, we introduce a graphical approach to testing multiple hypotheses in group-sequential clinical trials allowing for midterm design modifications. It is intended for structured study objectives in adaptive clinical trials and extends the graphical group-sequential designs from Maurer and Bretz (Statistics in Biopharmaceutical Research 2013; 5: 311-320) to adaptive trial designs. The resulting test strategies can be visualized graphically and performed iteratively. We illustrate the methodology with two examples from our clinical trial practice. First, we consider a three-armed gold-standard trial with the option to reallocate patients to either the test drug or the active control group, while stopping the recruitment of patients to placebo, after having demonstrated superiority of the test drug over placebo at an interim analysis. Second, we consider a confirmatory two-stage adaptive design with treatment selection at interim.

A shortcut for multiple testing on the directed acyclic graph of gene ontology

Background

Gene set testing has become an important analysis technique in high throughput microarray and next generation sequencing studies for uncovering patterns of differential expression of various biological processes. Often, the large number of gene sets that are tested simultaneously require some sort of multiplicity correction to account for the multiplicity effect. This work provides a substantial computational improvement to an existing familywise error rate controlling multiplicity approach (the Focus Level method) for gene set testing in high throughput microarray and next generation sequencing studies using Gene Ontology graphs, which we call the Short Focus Level.

Results

The Short Focus Level procedure, which performs a shortcut of the full Focus Level procedure, is achieved by extending the reach of graphical weighted Bonferroni testing to closed testing situations where restricted hypotheses are present, such as in the Gene Ontology graphs. The Short Focus Level multiplicity adjustment can perform the full top-down approach of the original Focus Level procedure, overcoming a significant disadvantage of the otherwise powerful Focus Level multiplicity adjustment. The computational and power differences of the Short Focus Level procedure as compared to the original Focus Level procedure are demonstrated both through simulation and using real data.

Conclusions

The Short Focus Level procedure shows a significant increase in computation speed over the original Focus Level procedure (as much as ∼15,000 times faster). The Short Focus Level should be used in place of the Focus Level procedure whenever the logical assumptions of the Gene Ontology graph structure are appropriate for the study objectives and when either no a priori focus level of interest can be specified or the focus level is selected at a higher level of the graph, where the Focus Level procedure is computationally intractable.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0349-3) contains supplementary material, which is available to authorized users.

Adaptive graph-based multiple testing procedures

Multiple testing procedures defined by directed, weighted graphs have recently been proposed as an intuitive visual tool for constructing multiple testing strategies that reflect the often complex contextual relations between hypotheses in clinical trials. Many well-known sequentially rejective tests, such as (parallel) gatekeeping tests or hierarchical testing procedures are special cases of the graph based tests. We generalize these graph-based multiple testing procedures to adaptive trial designs with an interim analysis. These designs permit mid-trial design modifications based on unblinded interim data as well as external information, while providing strong family wise error rate control. To maintain the familywise error rate, it is not required to prespecify the adaption rule in detail. Because the adaptive test does not require knowledge of the multivariate distribution of test statistics, it is applicable in a wide range of scenarios including trials with multiple treatment comparisons, endpoints or subgroups, or combinations thereof. Examples of adaptations are dropping of treatment arms, selection of subpopulations, and sample size reassessment. If, in the interim analysis, it is decided to continue the trial as planned, the adaptive test reduces to the originally planned multiple testing procedure. Only if adaptations are actually implemented, an adjusted test needs to be applied. The procedure is illustrated with a case study and its operating characteristics are investigated by simulations.

Pasireotide versus continued treatment with octreotide or lanreotide in patients with inadequately controlled acromegaly (PAOLA): a randomised, phase 3 trial

BACKGROUND

Many patients with acromegaly do not achieve biochemical control despite receiving high doses of the first-generation somatostatin analogues octreotide or lanreotide. In the PAOLA trial, we aimed to assess the efficacy and safety of two different doses of the somatostatin analogue pasireotide long-acting release compared with active control (octreotide or lanreotide) in patients with inadequately controlled acromegaly.

METHODS

In a multicentre, randomised, phase 3 trial, we enrolled eligible patients aged 18 years or older with acromegaly who were inadequately controlled (5-point, 2 h mean growth hormone concentration >2·5 μg/L and insulin-like growth factor 1 [IGF-1] concentration >1·3 times the upper normal limit) and had received 30 mg octreotide long-acting repeatable or 120 mg lanreotide (Somatuline Autogel; Ipsen, UK) as monotherapy for 6 months or longer. We randomly assigned patients in a 1:1:1 ratio with an interactive voice-web response system to receive 40 mg pasireotide long-acting release once every 28 days for 24 weeks, 60 mg pasireotide long-acting release once every 28 days for 24 weeks, or continued treatment with octreotide or lanreotide (active control). Patients were stratified according to previous treatment (octreotide or lanreotide) and growth hormone concentrations at screening (2·5-10 μg/L and >10 μg/L). Patients and study investigators were not masked to study drug assignment but were masked to pasireotide dose allocation. The primary endpoint was number of patients achieving biochemical control, defined as mean growth hormone concentration less than 2·5 μg/L and normalised IGF-1 concentration. Efficacy analyses were based on intention to treat. This trial is registered with ClinicalTrials.gov, number NCT01137682.

FINDINGS

Between Dec 17, 2010, and Aug 6, 2012, 198 patients were enrolled and randomly assigned to pasireotide 40 mg (n=65), pasireotide 60 mg (n=65), or active control (n=68) groups. At 24 weeks, ten (15%) patients in the pasireotide 40 mg group and 13 (20%) patients in the pasireotide 60 mg group achieved biochemical control, compared with no patients in the active control group (absolute difference from control group 15·4%, 95% CI 7·6-26·5, p=0·0006 for pasireotide 40 mg group, 20·0%, 11·1-31·8, p<0·0001 for pasireotide 60 mg group). The most common adverse events were hyperglycaemia (21 [33%] for treatment with 40 mg pasireotide, 19 [31%] with 60 mg pasireotide, and nine [14%] with active control), diabetes (13 [21%], 16 [26%], and five [8%]), and diarrhoea (ten [16%], 12 [19%], and three [5%]); most were grade 1 or 2 in severity. Serious adverse events were reported in six (10%) patients in the pasireotide 40 mg group, two (3%) in the pasireotide 60 mg group, and three (5%) in the active control group.

INTERPRETATION

Pasireotide provides superior efficacy compared with continued treatment with octreotide or lanreotide, and could become the new standard pituitary-directed treatment in patients with acromegaly who are inadequately controlled using first-generation somatostatin analogues.

FUNDING

Novartis Pharma AG. Financial support for medical editorial assistance was provided by Novartis Pharmaceuticals Corporation.

Allocating recycled significance levels in group sequential procedures for multiple endpoints

Graphical approaches have been proposed in the literature for testing hypotheses on multiple endpoints by recycling significance levels from rejected hypotheses to unrejected ones. Recently, they have been extended to group sequential procedures (GSPs). Our focus in this paper is on the allocation of recycled significance levels from rejected hypotheses to the stages of the GSPs for unrejected hypotheses. We propose a delayed recycling method that allocates the recycled significance level from Stage r onward, where r is prespecified. We show that r cannot be chosen adaptively to coincide with the random stage at which the hypothesis from which the significance level is recycled is rejected. Such an adaptive GSP does not always control the FWER. One can choose r to minimize the expected sample size for a given power requirement. We illustrate how a simulation approach can be used for this purpose. Several examples, including a clinical trial example, are given to illustrate the proposed procedure.

Secukinumab in plaque psoriasis--results of two phase 3 trials

BACKGROUND

Interleukin-17A is considered to be central to the pathogenesis of psoriasis. We evaluated secukinumab, a fully human anti-interleukin-17A monoclonal antibody, in patients with moderate-to-severe plaque psoriasis.

METHODS

In two phase 3, double-blind, 52-week trials, ERASURE (Efficacy of Response and Safety of Two Fixed Secukinumab Regimens in Psoriasis) and FIXTURE (Full Year Investigative Examination of Secukinumab vs. Etanercept Using Two Dosing Regimens to Determine Efficacy in Psoriasis), we randomly assigned 738 patients (in the ERASURE study) and 1306 patients (in the FIXTURE study) to subcutaneous secukinumab at a dose of 300 mg or 150 mg (administered once weekly for 5 weeks, then every 4 weeks), placebo, or (in the FIXTURE study only) etanercept at a dose of 50 mg (administered twice weekly for 12 weeks, then once weekly). The objective of each study was to show the superiority of secukinumab over placebo at week 12 with respect to the proportion of patients who had a reduction of 75% or more from baseline in the psoriasis area-and-severity index score (PASI 75) and a score of 0 (clear) or 1 (almost clear) on a 5-point modified investigator's global assessment (coprimary end points).

RESULTS

The proportion of patients who met the criterion for PASI 75 at week 12 was higher with each secukinumab dose than with placebo or etanercept: in the ERASURE study, the rates were 81.6% with 300 mg of secukinumab, 71.6% with 150 mg of secukinumab, and 4.5% with placebo; in the FIXTURE study, the rates were 77.1% with 300 mg of secukinumab, 67.0% with 150 mg of secukinumab, 44.0% with etanercept, and 4.9% with placebo (P<0.001 for each secukinumab dose vs. comparators). The proportion of patients with a response of 0 or 1 on the modified investigator's global assessment at week 12 was higher with each secukinumab dose than with placebo or etanercept: in the ERASURE study, the rates were 65.3% with 300 mg of secukinumab, 51.2% with 150 mg of secukinumab, and 2.4% with placebo; in the FIXTURE study, the rates were 62.5% with 300 mg of secukinumab, 51.1% with 150 mg of secukinumab, 27.2% with etanercept, and 2.8% with placebo (P<0.001 for each secukinumab dose vs. comparators). The rates of infection were higher with secukinumab than with placebo in both studies and were similar to those with etanercept.

CONCLUSIONS

Secukinumab was effective for psoriasis in two randomized trials, validating interleukin-17A as a therapeutic target. (Funded by Novartis Pharmaceuticals; ERASURE and FIXTURE ClinicalTrials.gov numbers, NCT01365455 and NCT01358578, respectively.).

Informative simultaneous confidence intervals in hierarchical testing

BACKGROUND AND OBJECTIVES

In clinical trials involving multiple tests it is often difficult to obtain informative simultaneous confidence intervals (SCIs). In particular in hierarchical testing, no quantification of effects is possible for the first tested (and most important) hypothesis after its rejection. Our goal is a construction of SCIs that are always informative.

METHODS

We present an approach where the level is split after rejection of each hypothesis to obtain an informative confidence bound. The splitting weights are continuous functions of the parameters. Our method is realizable by a simple algorithm and is illustrated by an intuitive graphical representation.

RESULTS

We show theoretically and by an example that the new SCIs always provide information when a hypothesis is rejected. The power to reject the first hypothesis is not smaller than for the classical fixed-sequence procedure. The price for the extra information is a small power loss in the hypotheses proceeding the most important one.

CONCLUSIONS

Given the substantial gain in information, a small loss of power for the non-primary hypotheses seems often acceptable. Especially in the context of non-inferiority trials, this method is a useful alternative. The flexibility in the choice of the weight functions makes the procedure attractive for applications.

A modest proposal for dropping poor arms in clinical trials

This paper presents a simple procedure for clinical trials comparing several arms with control. Demand for streamlining the evaluation of new treatments has led to phase III clinical trials with more arms than would have been used in the past. In such a setting, it is reasonable that some arms may not perform as well as an active control. We introduce a simple procedure that takes advantage of negative results in some comparisons to lessen the required strength of evidence for other comparisons. We evaluate properties analytically and use them to support claims made about multi-arm multi-stage designs.

Ambivalent role of pFAK-Y397 in serous ovarian cancer--a study of the OVCAD consortium

Background

Focal adhesion kinase (FAK) autophosphorylation seems to be a potential therapeutic target but little is known about the role and prognostic value of FAK and pFAK in epithelial ovarian cancer (EOC). Recently, we validated a gene signature classifying EOC patients into two subclasses and revealing genes of the focal adhesion pathway as significantly deregulated.

Methods

FAK expression and pFAK-Y397 abundance were elucidated by immunohistochemistry and microarray analysis in 179 serous EOC patients. In particular the prognostic value of phosphorylated FAK (pFAK-Y397) and FAK in advanced stage EOC was investigated.

Results

Multiple Cox-regression analysis showed that high pFAK abundance was associated with improved overall survival (HR 0.54; p = 0.034). FAK was positive in a total of 92.2% (n = 165) and high pFAK abundance was found in 36.9% (n = 66). High pFAK abundance (36.9% ; n = 66) was associated with either nodal positivity and/or distant metastasis (p = 0.030). Whole genome gene expression data revealed a connection of the FAK-pFAK-Y397 axis and the mTOR-S6K1 pathway, shown to play a major role in carcinogenesis.

Conclusion

The role of pFAK-Y397 remains controversial: although high pFAK-Y397 abundance is associated with distant and lymph node metastases, it is independently associated with improved overall survival.

An Application of Graphical Approach to Construct Multiple Testing Procedures in a Hypothetical Phase III Design

Many multiple testing procedures (MTP) have been developed in recent years. Among these new procedures, the graphical approach is flexible and easy to communicate with non-statisticians. A hypothetical Phase III clinical trial design is introduced in this manuscript to demonstrate how graphical approach can be applied in clinical product development. In this design, an active comparator is used. It is thought that this test drug under development could potentially be superior to this comparator. For comparison of efficacy, the primary endpoint is well established and widely accepted by regulatory agencies. However, an important secondary endpoint based on Phase II findings looks very promising. The target dose may have a good opportunity to deliver superiority to the comparator. Furthermore, a lower dose is included in case the target dose may demonstrate potential safety concerns. This Phase III study is designed as a non-inferiority trial with two doses, and two endpoints. This manuscript will illustrate how graphical approach is applied to this design in handling multiple testing issues.

Methylphenidate hydrochloride modified-release in adults with attention deficit hyperactivity disorder: a randomized double-blind placebo-controlled trial

Introduction

Treatment options for adults with attention deficit hyperactivity disorder (ADHD) are limited. The study was conducted to confirm the clinically effective and safe dose of methylphenidate hydrochloride modified-release (MPH-LA) in adults with ADHD and evaluate the maintenance of effect of MPH-LA.

Methods

The study consisted of three treatment phases. The double-blind dose-confirmation phase: 9-week double-blind period (3-week titration period, 6-week fixed dose) with randomization to MPH-LA 40, 60, or 80 mg/day or placebo. The real-life dose-optimization phase: a 5-week re-titration period to optimal dose; and the double-blind maintenance of effect phase, a 6-month double-blind randomized placebo-controlled maintenance of effect phase. The three co-primary endpoints were change in Diagnostic and Statistical Manual of Mental Disorders-IV ADHD Rating Scale (DSM-IV ADHD RS) and Sheehan Disability Scale (SDS) total scores from baseline to end of 9-week confirmation phase and the percentage of treatment failures during the 6-month maintenance of effect phase.

Results

725 of 863 screened patients were randomized to 40 (N = 181), 60 (N = 182), or 80 mg (N = 181) MPH-LA or placebo (N = 181), and 584 (80.6%) completed. 489 (83.7%) of completers were re-randomized to the double-blinded maintenance of effect phase and 235 (48.1%) of them completed. Improvement from baseline in DSM-IV ADHD RS (P < 0.0001 for all comparisons) and SDS (40 mg, P = 0.0003; 60 mg, P = 0.0176; 80 mg, P < 0.0001) total scores was significantly greater vs. placebo for all MPH-LA doses. Treatment failure rate was significantly lower with MPH-LA (21.3%) versus placebo (49.6%) during the 6-month maintenance of effect phase. Safety profile was consistent with the profile for MPH-LA in children; percentage of serious adverse events was comparable between all MPH-LA arms (1.3%) and placebo (1.5%), while percentage of adverse events was higher in MPH-LA arms.

Conclusion

MPH-LA provided and maintained significant symptomatic and functional improvement in adult ADHD patients.

Electronic supplementary material

The online version of this article (doi:10.1007/s12325-013-0085-5) contains supplementary material, which is available to authorized users.

Opportunities and challenges of combined effect measures based on prioritized outcomes

Many authors have proposed different approaches to combine multiple endpoints in a univariate outcome measure in the literature. In case of binary or time-to-event variables, composite endpoints, which combine several event types within a single event or time-to-first-event analysis are often used to assess the overall treatment effect. A main drawback of this approach is that the interpretation of the composite effect can be difficult as a negative effect in one component can be masked by a positive effect in another. Recently, some authors proposed more general approaches based on a priority ranking of outcomes, which moreover allow to combine outcome variables of different scale levels. These new combined effect measures assign a higher impact to more important endpoints, which is meant to simplify the interpretation of results. Whereas statistical tests and models for binary and time-to-event variables are well understood, the latter methods have not been investigated in detail so far. In this paper, we will investigate the statistical properties of prioritized combined outcome measures. We will perform a systematical comparison to standard composite measures, such as the all-cause hazard ratio in case of time-to-event variables or the absolute rate difference in case of binary variables, to derive recommendations for different clinical trial scenarios. We will discuss extensions and modifications of the new effect measures, which simplify the clinical interpretation. Moreover, we propose a new method on how to combine the classical composite approach with a priority ranking of outcomes using a multiple testing strategy based on the closed test procedure.

Traditional multiplicity adjustment methods in clinical trials

This tutorial discusses important statistical problems arising in clinical trials with multiple clinical objectives based on different clinical variables, evaluation of several doses or regiments of a new treatment, analysis of multiple patient subgroups, etc. Simultaneous assessment of several objectives in a single trial gives rise to multiplicity. If unaddressed, problems of multiplicity can undermine integrity of statistical inferences. The tutorial reviews key concepts in multiple hypothesis testing and introduces main classes of methods for addressing multiplicity in a clinical trial setting. General guidelines for the development of relevant and efficient multiple testing procedures are presented on the basis of application-specific clinical and statistical information. Case studies with common multiplicity problems are used to motivate and illustrate the statistical methods presented in the tutorial, and software implementation of the multiplicity adjustment methods is discussed.

Multiplicity: discussion points from the Statisticians in the Pharmaceutical Industry multiplicity expert group

In May 2012, the Committee of Health and Medicinal Products issued a concept paper on the need to review the points to consider document on multiplicity issues in clinical trials. In preparation for the release of the updated guidance document, Statisticians in the Pharmaceutical Industry held a one-day expert group meeting in January 2013. Topics debated included multiplicity and the drug development process, the usefulness and limitations of newly developed strategies to deal with multiplicity, multiplicity issues arising from interim decisions and multiregional development, and the need for simultaneous confidence intervals (CIs) corresponding to multiple test procedures. A clear message from the meeting was that multiplicity adjustments need to be considered when the intention is to make a formal statement about efficacy or safety based on hypothesis tests. Statisticians have a key role when designing studies to assess what adjustment really means in the context of the research being conducted. More thought during the planning phase needs to be given to multiplicity adjustments for secondary endpoints given these are increasing in importance in differentiating products in the market place. No consensus was reached on the role of simultaneous CIs in the context of superiority trials. It was argued that unadjusted intervals should be employed as the primary purpose of the intervals is estimation, while the purpose of hypothesis testing is to formally establish an effect. The opposing view was that CIs should correspond to the test decision whenever possible.

Multiplicity considerations for subgroup analysis subject to consistency constraint

A significant heterogeneity in response across subgroups of a clinical trial implies that the average response from the overall population might not characterize the treatment effect; and as noted by different regulatory guidances, can cause concerns in interpreting study findings and might lead to restricting treatment labeling. However, along with the challenges raised by the heterogeneity, recently there has been growing interest in taking advantage of the expected variability in response across subgroups to increase the chance of success of a trial by designing the trial with objectives of establishing efficacy claims for the total population and a targeted subgroup. For such trials, there have been several approaches to address the multiplicity issue with the two paths of success. This manuscript advocates the utility of setting a threshold on the treatment effect for the subgroups at the design stage to guide determination of the population labeling when significant findings for the total population have been established. Specifically, it proposes that licensing treatment for the total population requires, in addition to significant findings for this population, that the treatment effect in the least benefited (complementary) subgroup meets the treatment effect threshold at a minimum; otherwise, the treatment would be restricted to the targeted subgroup only. Setting such a threshold can be based on clinical considerations, including toxicity and adverse events, in addition to treatment effect in the subgroup. This manuscript expands some of the multiplicity approaches to account for the threshold requirement and investigates the impact of the threshold requirement on study power.

Partition testing in confirmatory adaptive designs with structured objectives

In this paper, we propose a partition testing for adaptive clinical trials with structured study objectives. The proposed approach is a combination of the graphical approach with partition testing. The proposed approach enables one to handle many types of structured objectives, to tailor a multiple test procedure to given structured objectives, and to draw sensible conclusions in adaptive clinical trials. In addition, the proposed approach reduces to the Bonferroni-based graphical approaches that can allow adaptations such as treatment selection and sample size reassessment during the course of the trial. Some practical aspects of the proposed approach are investigated via a simulation study.

Planning and evaluating clinical trials with composite time-to-first-event endpoints in a competing risk framework

Composite endpoints combine several events of interest within a single variable. These are often time-to-first-event data, which are analyzed via survival analysis techniques. To demonstrate the significance of an overall clinical benefit, it is sufficient to assess the test problem formulated for the composite. However, the effect observed for the composite does not necessarily reflect the effects for the components. Therefore, it would be desirable that the sample size for clinical trials using composite endpoints provides enough power not only to detect a clinically relevant superiority for the composite but also to address the components in an adequate way. The single components of a composite endpoint assessed as time-to-first-event define competing risks. We consider multiple test problems based on the cause-specific hazards of competing events to address the problem of analyzing both a composite endpoint and its components. Thereby, we use sequentially rejective test procedures to reduce the power loss to a minimum. We show how to calculate the sample size for the given multiple test problem by using a simply applicable simulation tool in SAS. Our ideas are illustrated by two clinical study examples.

Statistical challenges in drug approval trials that use patient-reported outcomes

This article describes challenging aspects of the use of patient-reported outcome instruments in clinical trials for drug approval, in our perspective as statistical reviewers at the US Food and Drug Administration. We discuss aspects of planning and interpreting results in clinical trials (1) adapting an existing patient-reported outcome instrument for use in clinical trials, (2) using multi-item patient-reported outcomes and (3) missing patient-reported outcome values from many subjects over time. These challenges are illustrated with multiple examples from different clinical trials for different indications. We finally discuss important considerations in labeling.

Simultaneous confidence regions for closed tests, including Holm-, Hochberg-, and Hommel-related procedures

The derivation of simultaneous confidence regions for some multiple-testing procedures (MTPs) of practical interest has remained an unsolved problem. This is the case, for example, for Hochberg's step-up MTP and Hommel's more powerful MTP that is neither a step-up nor a step-down procedure. It is shown in this article how the direct approach used previously by the author to construct confidence regions for certain closed-testing procedures (CTPs) can be extended to a rather general setup. The general results are then applied to a situation with one-sided inferences and CTPs belonging to a class studied by Wei Liu. This class consists of CTPs based on ordered marginal p-values. It includes Holm's, Hochberg's, and Hommel's MTPs. A property of the confidence regions derived for these three MTPs is that no confidence assertions sharper than rejection assertions can be made unless all null hypotheses are rejected. Briefly, this is related to the fact that these MTPs are quite powerful. The class of CTPs considered includes, however, also MTPs related to Holm's, Hochberg's, and Hommel's MTPs that are less powerful but are such that confidence assertions sharper than rejection assertions are possible even if not all null hypotheses are rejected. One may thus choose and prespecify such an MTP, though this is at the cost of less rejection power.

Role of TRAP1 and estrogen receptor alpha in patients with ovarian cancer -a study of the OVCAD consortium

BACKGROUND

The role of the tumor necrosis factor receptor associated protein 1 (TRAP1) - supposed to be involved in protection of cells from apoptosis and oxidative stress - has just started to be investigated in ovarian cancer. TRAP1 has been shown to be estrogen up-regulated in estrogen receptor α (ERα) positive ovarian cancer cells. The clinical impact of TRAP1 is not clear so far and the significance of ERα expression as therapeutic and prognostic marker is still controversial. Therefore, we investigated the importance of TRAP1 together with ERα in regard to clinicopathological parameters, chemotherapy response, and survival.

METHODS AND RESULTS

Expressions of TRAP1 and ERα were evaluated by immunohistochemical staining of tissue microarrays comprised of 208 ovarian cancer samples. TRAP1 was highly expressed in 55% and ERα was expressed in 52% of all cases. High TRAP1 expression correlated significantly with ERα (p<0.001) but high TRAP1 expression was also found in 42% of ERα negative cases. High TRAP1 expression correlated significantly with favorable chemotherapy-response (HR = 0.48; 95%CI 0.24-0.96, p=0.037) and showed a significant impact on overall survival (OS) (HR = 0.65; 95%CI 0.43-0.99, p = 0.044). ERα expression was a favorable prognostic factor for OS in univariate and multivariate analyses. Interestingly, the combined pattern (ERα positive and/or TRAP1-high) revealed the strongest independent and significant positive influence on OS (HR=0.41; 95%CI 0.27-0.64).

CONCLUSION

Immunohistochemical evaluation of TRAP1 together with ERα provides significant prognostic information. TRAP1 alone is significantly associated with chemotherapy response and overall survival, rendering TRAP1 as interesting scientific and therapeutic target.

A new partition testing strategy for multiple endpoints

To evaluate efficacy in multiple endpoints in confirmatory clinical trials is a challenging problem in multiple hypotheses testing. The difficulty comes from the different importance of each endpoint and their underlying correlation. Current approaches to this problem, which test the efficacy in certain dose-endpoint combinations and collate the results, are based on closed testing or partition testing. Despite their different formulations, all current approaches test their dose-endpoint combinations as intersection hypotheses and apply various union-intersection tests. Likelihood ratio test is seldom used owing to the extensive computation and lack of consistent inferences. In this article, we first generalize the formulation of multiple endpoints problem to include the cases of alternative primary endpoints and co-primary endpoints. Then we propose a new partition testing approach that is based on consonance-adjusted likelihood ratio test. The new procedure provides consistent inferences, and yet, it is still conservative and does not rely on the estimation of endpoint correlation or independence assumptions that might be challenged by regulatory agencies.

Observation and execution of upper-limb movements as a tool for rehabilitation of motor deficits in paretic stroke patients: protocol of a randomized clinical trial

Background

Evidence exist that motor observation activates the same cortical motor areas that are involved in the performance of the observed actions. The so called “mirror neuron system” has been proposed to be responsible for this phenomenon. We employ this neural system and its capability to re-enact stored motor representations as a tool for rehabilitating motor control. In our new neurorehabilitative schema (videotherapy) we combine observation of daily actions with concomitant physical training of the observed actions focusing on the upper limbs. Following a pilot study in chronic patients in an ambulatory setting, we currently designed a new multicenter clinical study dedicated to patients in the sub-acute state after stroke using a home-based self-induced training. Within our protocol we assess 1) the capability of action observation to elicit rehabilitational effects in the motor system, and 2) the capacity of this schema to be performed by patients without assistance from a physiotherapist. The results of this study would be of high health and economical relevance.

Methods/design

A controlled, randomized, multicenter, paralleled, 6 month follow-up study will be conducted on three groups of patients: one group will be given the experimental treatment whereas the other two will participate in control treatments. All patients will undergo their usual rehabilitative treatment beside participation in the study. The experimental condition consists in the observation and immediate imitation of common daily hand and arm actions. The two parallel control groups are a placebo group and a group receiving usual rehabilitation without any trial-related treatment. Trial randomization is provided via external data management. The primary efficacy endpoint is the improvement of the experimental group in a standardized motor function test (Wolf Motor Function Test) relative to control groups. Further assessments refer to subjective and qualitative rehabilitational scores. This study has been reviewed and approved by the ethics committee of Aachen University.

Discussion

This therapy provides an extension of therapeutic procedures for recovery after stroke and emphasizes the importance of action perception in neurorehabilitation The results of the study could become implemented into the wide physiotherapeutic practice, for example as an ad on and individualized therapy.

Multiplicity adjustment for composite binary endpoints

BACKGROUND

Binary composite outcome measures are increasingly used as primary endpoints in clinical trials. Composite endpoints combine several events of interest within a single variable. However, as the effect observed for the composite does not necessarily reflect the effects for the individual components, it is recommended in the literature to additionally evaluate each component separately.

OBJECTIVES

The task is to define an adequate multiple test procedure which focuses on the composite outcome measure but allows for a confirmatory interpretation of the components in case of large effects.

METHODS

In this paper, we determine the correlation matrix for a multiple binary endpoint problem of a composite endpoint and its components based on the normal approximation test statistic for rates. Thereby, we assume multinomial distributed components. We use this correlation to calculate the adjusted local significance levels. We discuss how to use our approach for a more informative formulation of the test problem. Our work is illustrated by two clinical trial examples.

RESULTS

By taking into account the special correlation structure between a binary composite outcome and its components, an adequate multiple test procedure to assess the composite and its components can be defined based on an approximate multivariate normal distribution without much loss in power compared to a test problem formulated exclusively for the composite.

CONCLUSIONS

By incorporating the correlation under the null hypotheses, the global power for the multiple test problem assessing both the composite and its components can be increased as compared to simple Bonferroni-adjustment. Thus, a confirmatory analysis of the composite and its components might be possible without a large increase in sample size as compared to a single endpoint problem formulated exclusively for the composite.