Family-wise Error Research Articles

Structural plasticity of the contralesional hippocampus and its subfields in patients with glioma.

To characterize the structural plasticity of the contralesional hippocampus and its subfields in patients with unilateral glioma. 3D T1-weighted MRI images were collected from 55 patients with tumors infiltrating the left (HipL, n = 27) or right (HipR, n = 28) hippocampus, along with 30 age- and sex-matched healthy controls (HC). Gray matter volume differences of the contralesional hippocampal regions and three control regions (superior frontal gyrus, caudate nucleus, and superior occipital gyrus) were evaluated using voxel-based morphometry (VBM) analyses. Volumetric differences in the hippocampus and its subregional volume were measured using the FreeSurfer software. Compared with HC, patients with unilateral hippocampal glioma exhibited significantly larger gray matter volume in the contralesional hippocampus and parahippocampal regions (cluster = 571 voxels for HipL; cluster 1 = 538 voxels and cluster 2 = 88 voxels for HipR; family-wise error corrected p < 0.05). No significant alterations were found in control regions. Volumetric analyses showed the same trend in the contralesional hippocampal subregions for both patient groups, including the CA1 head, CA3 head, hippocampus amygdala transition area (HATA), fimbria, and the granule cell molecular layer of the dentate gyrus head (GC-ML-DG head). Notably, the differences of the contralesional HATA (HipL: η2 = 0.418, corrected p = 0.002; HipR: η2 = 0.313, corrected p = 0.052) and fimbria (HipL: η2 = 0.450, corrected p < 0.001; HipR: η2 = 0.358, corrected p = 0.012) still held after the Bonferroni correction. Our findings provide evidence for macrostructural plasticity of the contralateral hippocampus in patients with unilateral hippocampal glioma. Specifically, HATA and fimbria exhibit great potential in this process. • Glioma infiltration of the hippocampal regions induces a significant increase in gray matter volume on the contralateral side. • Specifically, the HATA and fimbria regions exhibit favorable plastic potential in the process of lesion-induced structural remolding.

Familywise error rate control for block response-adaptive randomization.

Response-adaptive randomization allows the probabilities of allocating patients to treatments in a clinical trial to change based on the previously observed response data, in order to achieve different experimental goals. One concern over the use of such designs in practice, particularly from a regulatory viewpoint, is controlling the type I error rate. To address this, Robertson and Wason (Biometrics, 2019) proposed methodology that guarantees familywise error rate control for a large class of response-adaptive designs by re-weighting the usual -test statistic. In this article, we propose an improvement of their method that is conceptually simpler, in the context where patients are allocated to the experimental treatment arms in a trial in blocks (i.e. groups) using response-adaptive randomization. We show the modified method guarantees that there will never be negative weights for the contribution of each block of data to the adjusted test statistics, and can also provide a substantial power advantage in practice.

Online error rate control for platform trials.

Platform trials evaluate multiple experimental treatments under a single master protocol, where new treatment arms are added to the trial over time. Given the multiple treatment comparisons, there is the potential for inflation of the overall typeI error rate, which is complicated by the fact that the hypotheses are tested at different times and are not necessarily pre-specified. Online error rate control methodology provides a possible solution to the problem of multiplicity for platform trials where a relatively large number of hypotheses are expected to be tested over time. In the online multiple hypothesis testing framework, hypotheses are tested one-by-one over time, where at each time-step an analyst decides whether to reject the current null hypothesis without knowledge of future tests but based solely on past decisions. Methodology has recently been developed for online control of the false discovery rate as well as the familywise error rate (FWER). In this article, we describe how to apply online error rate control to the platform trial setting, present extensive simulation results, and give some recommendations for the use of this new methodology in practice. We show that the algorithms for online error rate control can have a substantially lower FWER than uncorrected testing, while still achieving noticeable gains in power when compared with the use of a Bonferroni correction. We also illustrate how online error rate control would have impacted a currently ongoing platform trial.

Frontoparietal 18F-FDG-PET hypo-metabolism in Lennox-Gastaut syndrome: Further evidence highlighting the key network

IntroductionLennox Gastaut syndrome (LGS) can be conceptualised as a “secondary network epilepsy”, in which the shared electroclinical manifestations reflect epileptic recruitment of a common brain network, despite a range of underlying aetiologies. We aimed to identify the key networks recruited by the epileptic process of LGS using interictal 2-deoxy-2-(18F)fluoro-D-glucose positron emission tomography (18F-FDG-PET). MethodsGroup analysis of cerebral 18F-FDG-PET, comparing 21 patients with LGS (mean age = 15 years) and 18 pseudo-controls (mean age = 19 years), studied at Austin Health Melbourne, between 2004 and 2015. To minimise the influence of individual patient lesions in the LGS group, we only studied brain hemispheres without structural MRI abnormalities. The pseudo-control group consisted of age- and sex-matched patients with unilateral temporal lobe epilepsy, using only the hemispheres contralateral to the side of epilepsy. Voxel-wise permutation testing compared 18F-FDG-PET uptake between groups. Associations were explored between areas of altered metabolism and clinical variables (age of seizure onset, proportion of life with epilepsy, and verbal/nonverbal ability). Penetrance maps were calculated to explore spatial consistency of altered metabolic patterns across individual patients with LGS. ResultsAlthough not always readily apparent on visual inspection of individual patient scans, group analysis revealed hypometabolism in a network of regions including prefrontal and premotor cortex, anterior and posterior cingulate, inferior parietal lobule, and precuneus (p < 0.05, corrected for family-wise error). These brain regions tended to show a greater reduction in metabolism in non-verbal compared to verbal LGS patients, although this difference was not statistically significant. No areas of hypermetabolism were detected on group analysis, although ∼25 % of individual patients showed increased metabolism (relative to pseudo-controls) in the brainstem, putamen, thalamus, cerebellum, and pericentral cortex. DiscussionInterictal hypometabolism in frontoparietal cortex in LGS is compatible with our previous EEG-fMRI and SPECT studies showing that interictal bursts of generalised paroxysmal fast activity and tonic seizures recruit similar cortical regions. This study provides further evidence that these regions are central to the electroclinical expression of LGS.

Alterations in Resting-State MR Functional Connectivity of the Central Autonomic Network in Multiple System Atrophy and Relationship with Disease Severity.

The central autonomic network (CAN) plays a critical role in the body's sympathetic and parasympathetic control. However, functional connectivity (FC) changes of the CAN in patients with multiple system atrophy (MSA) remain unknown. To investigate FC alterations of CAN in MSA patients. Prospective. Eighty-two subjects (47 patients with MSA [44.7% female, 60.5 ± 6.9 years], 35 age- and sex-matched healthy controls [HC] [57.1% female, 62.5 ± 6.6 years]). 3-T, resting-state functional magnetic resonance imaging (rs-fMRI) using gradient echo-planar imaging (EPI), T1-weighted three-dimensional magnetization-prepared rapid gradient echo (3D MPRAGE) structural MRI. FC alterations were explored by using core modulatory regions of CAN as seeds, including midcingulate cortex, insula, amygdala, and ventromedial prefrontal cortex. Bartlett factor score (BFS) derived from a factor analysis of clinical assessments on disease severity was used as a grouping factor for moderate MSA (mMSA: BFS < 0) and severe MSA (sMSA: BFS > 0). For FC analysis, the one-way ANCOVA with cluster-level family-wise error correction (statistical significance level of P < 0.025), and post hoc t-testing with Bonferroni correction or Tamhane's T2 correction (statistical significance level of adjusted-P < 0.05) were adopted. Correlation was assessed using Pearson correlation or Spearman correlation (statistical significance level of P < 0.05). Compared with HC, patients with MSA exhibited significant FC aberrances between the CAN and brain areas of sensorimotor control, limbic network, putamen, and cerebellum. For MSA patients, most FC alterations of CAN, especially concerning FC between the right anterior insula and right primary sensorimotor cortices, were found to be significantly correlated with disease severity. FC changes were found to be more significant in sMSA group than in mMSA group when compared with HCs. MSA shows widespread FC changes of CAN, suggesting that abnormal functional integration of CAN may be involved in disease pathogenesis of MSA. 2 TECHNICAL EFFICACY: Stage 3.

A Minimum Bayes Factor Based Threshold for Activation Likelihood Estimation

Activation likelihood estimation (ALE) is among the most used algorithms to perform neuroimaging meta-analysis. Since its first implementation, several thresholding procedures had been proposed, all referred to the frequentist framework, returning a rejection criterion for the null hypothesis according to the critical p-value selected. However, this is not informative in terms of probabilities of the validity of the hypotheses. Here, we describe an innovative thresholding procedure based on the concept of minimum Bayes factor (mBF). The use of the Bayesian framework allows to consider different levels of probability, each of these being equally significant. In order to simplify the translation between the common ALE practice and the proposed approach, we analised six task-fMRI/VBM datasets and determined the mBF values equivalent to the currently recommended frequentist thresholds based on Family Wise Error (FWE). Sensitivity and robustness toward spurious findings were also analyzed. Results showed that the cutoff log10(mBF) = 5 is equivalent to the FWE threshold, often referred as voxel-level threshold, while the cutoff log10(mBF) = 2 is equivalent to the cluster-level FWE (c-FWE) threshold. However, only in the latter case voxels spatially far from the blobs of effect in the c-FWE ALE map survived. Therefore, when using the Bayesian thresholding the cutoff log10(mBF) = 5 should be preferred. However, being in the Bayesian framework, lower values are all equally significant, while suggesting weaker level of force for that hypothesis. Hence, results obtained through less conservative thresholds can be legitimately discussed without losing statistical rigor. The proposed technique adds therefore a powerful tool to the human-brain-mapping field.

Statistical methods for exploring spontaneous adverse event reporting databases for drug-host factor interactions

BackgroundDrug toxicity does not affect patients equally; the toxicity may only exert in patients who possess certain attributes of susceptibility to specific drug properties (i.e., drug-host interaction). This concept is crucial for personalized drug safety but remains under-studied, primarily due to methodological challenges and limited data availability. By monitoring a large volume of adverse event reports in the postmarket stage, spontaneous adverse event reporting systems provide an unparalleled resource of information for adverse events and could be utilized to explore risk disparities of specific adverse events by age, sex, and other host factors. However, well-formulated statistical methods to formally address such risk disparities are currently lacking.MethodsIn this paper, we present a statistical framework to explore spontaneous adverse event reporting databases for drug-host interactions and detect risk disparities in adverse drug events by various host factors, adapting methods for safety signal detection. We proposed four different methods, including likelihood ratio test, normal approximation test, and two tests using subgroup ratios. We applied our proposed methods to simulated data and Food and Drug Administration (FDA) Adverse Event Reporting Systems (FAERS) and explored sex-/age-disparities in reported liver events associated with specific drug classes.ResultsThe simulation result demonstrates that two tests (likelihood ratio, normal approximation) can detect disparities in adverse drug events associated with host factors while controlling the family wise error rate. Application to real data on drug liver toxicity shows that the proposed method can be used to detect drugs with unusually high level of disparity regarding a host factor (sex or age) for liver toxicity or to determine whether an adverse event demonstrates a significant unbalance regarding the host factor relative to other events for the drug.ConclusionThough spontaneous adverse event reporting databases require careful data processing and inference, the sheer size of the databases with diverse data from different countries provides unique resources for exploring various questions for drug safety that are otherwise impossible to address. Our proposed methods can be used to facilitate future investigation on drug-host interactions in drug toxicity using a large number of reported adverse events.

An Extended Framework of Multiple Testing in Group Sequential Design.

Here, we consider testing multiple hypotheses in group sequential trials. A graphical multiple test procedure was proposed for group sequential trials using weighted Bonferroni test. In this paper, we extend the framework for the graph-based group sequential procedure by applying a modified weighted Simes test. The proposed procedure preserves the familywise error rate. Simulations are conducted to evaluate the performances of the proposed procedure. The proposed procedures are also illustrated with a numerical example.

Some Multiplicity Adjustment Procedures for Clinical Trials with Sequential Design and Multiple Endpoints

This article proposes some new multiplicity adjustment procedures for clinical trials with multiple endpoints and multiple interim analyses. The proposed sequential procedures, adapting the popular multiple comparison procedures for fixed time-point design and using α-spending for each endpoint, are shown to strongly control the family-wise Type-1 error rate and provide powerful yet versatile multiplicity adjustment solutions for monitoring multiple endpoints via interim analyses.

Bayesian lesion-deficit inference with Bayes factor mapping: Key advantages, limitations, and a toolbox

Statistical lesion-symptom mapping is largely dominated by frequentist approaches with null hypothesis significance testing. They are popular for mapping functional brain anatomy but are accompanied by some challenges and limitations. The typical analysis design and the structure of clinical lesion data are linked to the multiple comparison problem, an association problem, limitations to statistical power, and a lack of insights into evidence for the null hypothesis. Bayesian lesion deficit inference (BLDI) could be an improvement as it collects evidence for the null hypothesis, i.e. the absence of effects, and does not accumulate α-errors with repeated testing. We implemented BLDI by Bayes factor mapping with Bayesian t-tests and general linear models and evaluated its performance in comparison to frequentist lesion-symptom mapping with a permutation-based family-wise error correction. We mapped the voxel-wise neural correlates of simulated deficits in an in-silico-study with 300 stroke patients, and the voxel-wise and disconnection-wise neural correlates of phonemic verbal fluency and constructive ability in 137 stroke patients. Both the performance of frequentist and Bayesian lesion-deficit inference varied largely across analyses. In general, BLDI could find areas with evidence for the null hypothesis and was statistically more liberal in providing evidence for the alternative hypothesis, i.e. the identification of lesion-deficit associations. BLDI performed better in situations in which the frequentist method is typically strongly limited, for example with on average small lesions and in situations with low power, where BLDI also provided unprecedented transparency in terms of the informative value of the data. On the other hand, BLDI suffered more from the association problem, which led to a pronounced overshoot of lesion-deficit associations in analyses with high statistical power. We further implemented a new approach to lesion size control, adaptive lesion size control, that, in many situations, was able to counter the limitations imposed by the association problem, and increased true evidence both for the null and the alternative hypothesis. In summary, our results suggest that BLDI is a valuable addition to the method portfolio of lesion-deficit inference with some specific and exclusive advantages: it deals better with smaller lesions and low statistical power (i.e. small samples and effect sizes) and identifies regions with absent lesion-deficit associations. However, it is not superior to established frequentist approaches in all respects and therefore not to be seen as a general replacement. To make Bayesian lesion-deficit inference widely accessible, we published an R toolkit for the analysis of voxel-wise and disconnection-wise data.

Voxel-based morphometric magnetic resonance imaging evaluation of small head fetus: A comparative study with normal developmental fetus.

To explore the application value of voxel-based morphometric (VBM) in prenatal diagnosis of microcephaly. A retrospective study of magnetic resonance imaging of fetuses with microcephaly was performed using a single-shot fast spin echo sequence; semiautomatic segmentation of grey matter (GM), white matter (WM), and cerebrospinal fluid (CSF); calculation of their volumes; and VBM analysis of their GM. Two independent samples t-test was used to statistically analyse the fetal GM volume in the microcephaly and normal control groups. Total intracranial volume (TIV), GM volume, WM volume, and CSF volume were linearly regressed against gestational age and compared between the two groups. In the fetus with microcephaly, GM volume of frontal lobe, temporal lobe, cuneus, anterior central gyrus, and posterior central gyrus decreased significantly (P < 0.001, corrected by family-wise error at mass level). The GM volume of microcephaly was significantly lower than that of the control group (except for 28 weeks of gestation) (P < 0.05). TIV, GM volume, WM volume, and CSF volume were all positively correlated with gestational age, and the curves in the microcephaly group were all lower than those in the control group. Compared with the normal control group, the GM volume of microcephaly fetuses decreased, and there were significant differences in many brain regions through VBM analysis.

Step-down multiple testing procedures for the overall population and partitioning subgroups

ABSTRACT Multiple comparisons procedures are described for two-armed studies where there is a primary hypothesis and one or more ordered secondary hypotheses in the scenario where the objective is to test for an effect on the overall population and/or nonoverlapping subgroups that partition the population. This scenario arises when the subgroups are defined by disease etiology or by other patient characteristics such as genetic factors, age, sex, or race, and the treatment may have differential effects in the subgroups. The procedures described control the family-wise error rate in the strong sense at a specified level α.

Reverse graphical approaches for multiple test procedures

ABSTRACT The graphical approach has been proposed as a general framework for clinical trial designs involving multiple hypotheses, where decisions are made only based on the observed marginal p -values. The graphical approach starts from a graph that includes all hypotheses as vertices and gradually removes some vertices when their corresponding hypotheses are rejected. In this paper, we propose a reverse graphical approach, which starts from a set of singleton graphs and gradually adds vertices into graphs until rejection of a set of hypotheses is made. Proofs of familywise error rate control are provided. A simulation study is conducted for statistical power analysis, and a case study is included to illustrate how the proposed approach can be applied to clinical studies.

Early neurotransmitters changes in prodromal frontotemporal dementia: A GENFI study

BackgroundNeurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches. MethodsIn the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission.We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD. ResultsIn prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01). ConclusionsThis study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms.

Gray and white matter abnormalities in major depressive disorder patients and its associations with childhood adversity

ObjectiveEarly life stress of childhood adversity (CA) may result in major depressive disorder (MDD) by sensitizing individuals to proximal stressors in life events. The neurobiological changes that underlie adult depression may result from the absence of proper care and supervision of caregivers. We aimed to find both gray and white matter abnormalities in MDD patients, who reported the experiences of CA. MethodsThe present study examined cortical alterations in 54 patients with MDD and 167 healthy controls (HCs) using voxel-based morphology and fractional anisotropy (FA) tract-based spatial statistics (TBSS). Both patients and HCs were administered the self-questionnaire clinical scale (the Korean translation of the Childhood Trauma Questionnaire CTQK). Pearson's correlation analysis was performed to find the associations between FA and CTQK. ResultsThe MDD group showed a significant decrease in gray matter (GM) in the left rectus at both the cluster and peak levels after family-wise error correction. The TBSS results showed significantly reduced FA in widespread regions, including the corpus callosum (CC), superior corona radiata, cingulate gyrus, and superior longitudinal fasciculus. The CA was negatively correlated with the FA in CC and crossing pontine tract. ConclusionOur findings demonstrated GM atrophy and white matter (WM) connectivity changes in patients with MDD. The major findings of the widespread FA reduction in WM provided the evidence of brain alterations in MDD. We further propose that the WM would be vulnerable to emotional, physical, and sexual abuse in early childhood during the brain development.

Practical basket design for binary outcomes with control of family-wise error rate

BackgroundA basket trial is a type of clinical trial in which eligibility is based on the presence of specific molecular characteristics across subpopulations with different cancer types. The existing basket designs with Bayesian hierarchical models often improve the efficiency of evaluating therapeutic effects; however, these models calibrate the type I error rate based on the results of simulation studies under various selected scenarios. The theoretical control of family-wise error rate (FWER) is important for decision-making regarding drug approval.MethodsIn this study, we propose a new Bayesian two-stage design with one interim analysis for controlling FWER at the target level, along with the formulations of type I and II error rates. Since the difficulty lies in the complexity of the theoretical formulation of the type I error rate, we devised the simulation-based method to approximate the type I error rate.ResultsThe proposed design enabled adjustment of the cutoff value to control the FWER at the target value in the final analysis. The simulation studies demonstrated that the proposed design can be used to control the well-approximated FWER below the target value even in situations where the number of enrolled patients differed among subpopulations.ConclusionsThe accrual number of patients is sometimes unable to reach the pre-defined value; therefore, existing basket designs may not ensure defined operating characteristics before beginning the trial. The proposed design that enables adjustment of the cutoff value to control FWER at the target value based on the results in the final analysis would be a better alternative.

Sex-specific differences in resting-state functional brain activity in pediatric concussion

Pediatric concussion has a rising incidence and can lead to long-term symptoms in nearly 30% of children. Resting state functional magnetic resonance imaging (rs-fMRI) disturbances are a common pathological feature of pediatric concussion, though no studies have explicitly examined sex-differences with respect to this outcome, precluding a sex-specific understanding of the functional neuropathology of pediatric concussion. Therefore, we performed a secondary data analysis of rs-fMRI data collected on children with concussion (n = 29) recruited from in a pediatric hospital setting, with greater than 12:1 matched control data accessed from the open-source ABIDE-II database. Seed-based and region of interest (ROI) analyses were used to examine sex-based rs-fMRI differences; threshold-free cluster enhancement (TFCE) and a family-wise error (FWE) corrected p-values were used to identify significantly different clusters. In comparing females with concussion to healthy females, groupwise differences were observed irrespective of seed selected. Notably, we observed (in order of largest effect) hypo-connectivity between the anterior cingulate cortex of the salience network and the thalamus and precuneus (TFCE = 1473.5, p-FWE < 0.001) and the cingulate gyrus (TFCE = 769.3, p-FWE = 0.009), and the seed (posterior cingulate cortex (PCC)) of the default mode network and the paracingulate gyrus (TFCE = 1275.7, p-FWE < 0.001), occipital pole right (TFCE = 1045.0, p-FWE = 0.001), and sub-callosal cortex (TFCE = 844.9, p-FWE = 0.005). Hyper-connectivity was observed between the salience network seed and the cerebellum (TFCE = 1719.3, p-FWE < 0.001) and the PCC and the thalamus (TFCE = 1198.3, p-FWE < 0.001), cuneal cortex (1070.9, p-FWE = 0.001), and lateral occipital cortex left (TFCE = 832.8, p-FWE = 0.006). ROI analyses showed 10 and 5 significant clusters of hypo- and hyper-connectivity in females, respectively. Only one cluster of difference was found between males with concussion and healthy males on seed-based analyses, and 3 clusters on ROI analyses. There are alterations in rs-fMRI in females with concussion at one-month post-injury that are minimally present in males, which provides further evidence that recovery timelines in pediatric concussion may differ by sex.

Functional neuroanatomy of craving in heroin use disorder: voxel-based meta-analysis of functional magnetic resonance imaging (fMRI) drug cue reactivity studies

ABSTRACT Background: The neuroanatomy of craving, typically investigated using the functional magnetic resonance imaging (fMRI) drug cue reactivity (FDCR) paradigm, has been shown to involve the mesocorticolimbic, nigrostriatal, and corticocerebellar systems in several substances. However, the neuroanatomy of craving in heroin use disorder is still unclear. Objective: The current meta-analysis examines previous research on the neuroanatomy of craving in abstinent individuals with opioid use disorder (OUD). Method: Seven databases were searched for studies comparing abstinent OUD versus healthy controls on drug > neutral contrast interaction at the whole-brain level. Voxel-based meta-analysis was performed using seed-based d mapping with permuted subject images (SDM-PSI). Thresholds were set at a family-wise error rate of less than 5% with the default pre-processing parameters of SDM-PSI. Results: A total of 10 studies were included (296 OUD and 187 controls). Four hyperactivated clusters were identified with Hedges’ g of peaks that ranged from 0.51 to 0.82. These peaks and their associated clusters correspond to the three systems identified in the previous literature: a) mesocorticolimbic, b) nigrostriatal, and c) corticocerebellar. There were also newly revealed hyperactivation regions including the bilateral cingulate, precuneus, fusiform gyrus, pons, lingual gyrus, and inferior occipital gyrus. The meta-analysis did not reveal areas of hypoactivation. Conclusion: Recommendations based on the functional neuroanatomical findings of this meta-analysis include pharmacological interventions such as buprenorphine/naloxone and cognitive-behavioral treatments such as cue-exposure combined with HRV biofeedback. In addition, research should utilize FDCR as pre- and post-measurement to determine the effectiveness and mechanism of action of such interventions.

Adaptive Endpoints Selection with Application in Rare Disease

In rare diseases, there are many unanswered questions that are critical to clinical development. Among them, one important question is how to choose primary endpoints that translate into meaningful improvement of health outcomes for patients while maximizing trial probability of success at the same time. A natural history study is often recommended by regulatory agencies. Following this traditional approach has dampened enthusiasm for many drug developers because it entails much higher cost and longer timeline. We propose to use an innovative design that allows adaptation on primary endpoint(s) so that learning about disease endpoints can be done within the pivotal trial itself through a subset of patients (i.e., informational cohort). The overall Family Wise Error Rate (FWER) will be controlled through the use of combination test following partition testing principle. A case example in patients with Pompe disease is used to show that the proposed innovative design maintains robust power across treatment effect scenarios while traditional fixed design bears the high risk of failure due to incorrect endpoint selection. Even if multiple endpoints can be included as primary, the proposed innovative design can still improve power over traditional designs by optimizing alpha allocations in cases with differential treatment effects.

Regional white matter and gray matter damage and cognitive performances in multiple sclerosis according to sex.

In this study, we investigated whether regional distribution of white matter (WM) lesions, normal-appearing [NA] WM microstructural abnormalities and gray matter (GM) atrophy may differently contribute to cognitive performance in multiple sclerosis (MS) patients according to sex. Using the same scanner, brain 3.0T MRI was acquired for 287 MS patients (females = 173; mean age = 42.1 [standard deviation, SD = 12.7] years; relapsing-remitting = 196, progressive = 91; median Expanded Disability Status Scale = 2.5 [interquartile range, IQR = 1.5-5.0]; median disease duration = 12.1 [IQR = 6.3-19.0] years; treatment: none = 70, first-line = 130, second-line = 87) and 172 healthy controls (HC) (females = 92; mean age = 39.3 [SD = 14.8] years). MS patients underwent also Rao's neuropsychological battery. Using voxel-wise analyses, we investigated in patients sex-related differences in the association of cognitive performances with WM lesions, NAWM fractional anisotropy (FA) and GM volumes (p < 0.01, family-wise error [FWE]). Sixty-six female (38%) and 48 male (42%) MS patients were cognitively impaired, with no significant between-group difference (p = 0.704). However, verbal memory performance was worse in males (p = 0.001), whereas verbal fluency performance was worse in females (p = 0.004). In both sexes, a higher T2-hyperintense lesion prevalence in cognitively-relevant WM tracts was significantly associated with worse cognitive performance (p ≤ 0.006), with stronger associations in females than males in global cognition (p ≤ 0.004). Compared to sex-matched HC, male and female MS patients had widespread lower NAWM FA and GM volume (p < 0.01). In both sexes, worse cognitive performance was associated with widespread reduced NAWM FA (p < 0.01), with stronger associations in females than males in global cognition and verbal memory (p ≤ 0.009). Worse cognitive performance was significantly associated with clusters of cortical GM atrophy in males (p ≤ 0.007) and mainly with deep GM atrophy in females (p ≤ 0.006). In this study, only limited differences in cognitive performances were found between male and female MS patients. A disconnection syndrome due to focal WM lesions and diffuse NAWM microstructural abnormalities seems to be more relevant in female MS patients to explain cognitive impairment.