Does Central Statistical Monitoring Improve Data Quality? An Analysis of 1,111 Sites in 159 Clinical Trials.

BACKGROUND: Central monitoring aims at improving the quality of clinical research by pro-actively identifying risks and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. This paper, focusing on statistical data monitoring (SDM), is the second of a series that attempts to quantify the impact of central monitoring in clinical trials. MATERIAL AND METHODS: Quality improvement was assessed in studies using SDM from a single large central monitoring platform. The analysis focused on a total of 1111 sites that were identified as at-risk by the SDM tests and for which the study teams conducted a follow-up investigation. These sites were taken from 159 studies conducted by 23 different clinical development organizations (including both sponsor companies and contract research organizations). Two quality improvement metrics were assessed for each selected site, one based on a site data inconsistency score (DIS, overall -log10 P-value of the site compared with all other sites) and the other based on the observed metric value associated with each risk signal. RESULTS: The SDM quality metrics showed improvement in 83% (95% CI, 80-85%) of the sites across therapeutic areas and study phases (primarily phases 2 and 3). In contrast, only 56% (95% CI, 41-70%) of sites showed improvement in 2 historical studies that did not use SDM during study conduct. CONCLUSION: The results of this analysis provide clear quantitative evidence supporting the hypothesis that the use of SDM in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.

Does Central Monitoring Lead to Higher Quality? An Analysis of Key Risk Indicator Outcomes.

BACKGROUND: Central monitoring, which typically includes the use of key risk indicators (KRIs), aims at improving the quality of clinical research by pro-actively identifying and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. However, there has to-date been a relative lack of direct quantitative evidence published supporting the claim that central monitoring actually leads to improved quality. MATERIAL AND METHODS: Nine commonly used KRIs were analyzed for evidence of quality improvement using data retrieved from a large central monitoring platform. A total of 212 studies comprising 1676 sites with KRI signals were used in the analysis, representing central monitoring activity from 23 different sponsor organizations. Two quality improvement metrics were assessed for each KRI, one based on a statistical score (p-value) and the other based on a KRI's observed value. RESULTS: Both KRI quality metrics showed improvement in a vast majority of sites (82.9% for statistical score, 81.1% for observed KRI value). Additionally, the statistical score and the observed KRI values improved, respectively by 66.1% and 72.4% on average towards the study average for those sites showing improvement. CONCLUSION: The results of this analysis provide clear quantitative evidence supporting the hypothesis that use of KRIs in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.

Detection of Fraud in a Clinical Trial Using Unsupervised Statistical Monitoring.

BACKGROUND: A central statistical assessment of the quality of data collected in clinical trials can improve the quality and efficiency of sponsor oversight of clinical investigations. MATERIAL AND METHODS: The database of a large randomized clinical trial with known fraud was reanalyzed with a view to identifying, using only statistical monitoring techniques, the center where fraud had been confirmed. The analysis was conducted with an unsupervised statistical monitoring software using mixed-effects statistical models. The statistical analyst was unaware of the location, nature, and extent of the fraud. RESULTS: Five centers were detected as atypical, including the center with known fraud (which was ranked 2). An incremental analysis showed that the center with known fraud could have been detected after only 25% of its data had been reported. CONCLUSION: An unsupervised approach to central monitoring, using mixed-effects statistical models, is effective at detecting centers with fraud or other data anomalies in clinical trials.

Central statistical monitoring of investigator-led clinical trials in oncology.

Investigator-led clinical trials are pragmatic trials that aim to investigate the benefits and harms of treatments in routine clinical practice. These much-needed trials represent the majority of all trials currently conducted. They are however threatened by the rising costs of clinical research, which are in part due to extensive trial monitoring processes that focus on unimportant details. Risk-based quality management focuses, instead, on "things that really matter". We discuss the role of central statistical monitoring as part of risk-based quality management. We describe the principles of central statistical monitoring, provide examples of its use, and argue that it could help drive down the cost of randomized clinical trials, especially investigator-led trials, whilst improving their quality.

Detection of atypical data in multicenter clinical trials using unsupervised statistical monitoring.

BACKGROUND/AIMS: A risk-based approach to clinical research may include a central statistical assessment of data quality. We investigated the operating characteristics of unsupervised statistical monitoring aimed at detecting atypical data in multicenter experiments. The approach is premised on the assumption that, save for random fluctuations and natural variations, data coming from all centers should be comparable and statistically consistent. Unsupervised statistical monitoring consists of performing as many statistical tests as possible on all trial data, in order to detect centers whose data are inconsistent with data from other centers. METHODS: We conducted simulations using data from a large multicenter trial conducted in Japan for patients with advanced gastric cancer. The actual trial data were contaminated in computer simulations for varying percentages of centers, percentages of patients modified within each center and numbers and types of modified variables. The unsupervised statistical monitoring software was run by a blinded team on the contaminated data sets, with the purpose of detecting the centers with contaminated data. The operating characteristics (sensitivity, specificity and Youden's J-index) were calculated for three detection methods: one using the p-values of individual statistical tests after adjustment for multiplicity, one using a summary of all p-values for a given center, called the Data Inconsistency Score, and one using both of these methods. RESULTS: The operating characteristics of the three methods were satisfactory in situations of data contamination likely to occur in practice, specifically when a single or a few centers were contaminated. As expected, the sensitivity increased for increasing proportions of patients and increasing numbers of variables contaminated. The three methods showed a specificity better than 93% in all scenarios of contamination. The method based on the Data Inconsistency Score and individual p-values adjusted for multiplicity generally had slightly higher sensitivity at the expense of a slightly lower specificity. CONCLUSIONS: The use of brute force (a computer-intensive approach that generates large numbers of statistical tests) is an effective way to check data quality in multicenter clinical trials. It can provide a cost-effective complement to other data-management and monitoring techniques.

Working memory in posterior cortical atrophy.

We used an ad hoc created neuropsychological battery to evaluate in details both verbal and visuospatial working memory (WM) in patients with posterior cortical atrophy (PCA, n = 5). PCA is a rare, early-onset neurodegenerative dementia, often due to Alzheimer's disease (AD) pathology. Clinically, PCA patients present with visual, visuospatial, and visuomotor deficits, and no memory complaints. PCA patients' patterns of performance were compared with those of 11 typical, amnestic AD patients matched for disease severity, as well as with 17 age-matched healthy controls. Both groups of patients had impaired WM performance compared to controls. However, PCA patients were more impaired than typical AD patients for both verbal and visuospatial WM. Moreover, PCA patients showed a more consistent impairment of visuospatial WM, as compared with verbal WM. Systematic WM evaluation should be part of the standard assessment in PCA. WM deficits affect patients' quality of life and can be detrimental to rehabilitation programs.

Functional Connectivity of Ventral and Dorsal Visual Streams in Posterior Cortical Atrophy.

BACKGROUND: Posterior cortical atrophy (PCA) induces progressive dysfunction of ventral and dorsal visual networks. Little is known, however, about corresponding changes in functional connectivity (FC). OBJECTIVES: To investigate FC changes in the visual networks, their relationship with cortical atrophy, and the association with Alzheimer's disease (AD) pathology. METHODS: Ten PCA patients and 28 age-matched controls participated in the study. Using resting state fMRI, we measured FC in ventral and dorsal cortical visual networks, defined on the basis of a priori knowledge of long-range white matter connections. To assess the relationships with AD, we determined AD biomarkers in cerebrospinal fluid and FC in the default mode network (DMN), which is vulnerable to AD pathology. Voxel-based morphometry analysis assessed the pattern of grey matter (GM) atrophy. RESULTS: PCA patients showed GM atrophy in bilateral occipital and inferior parietal regions. PCA patients had lower FC levels in a ventral network than controls, but higher FC in inferior components of the dorsal network. In particular, the increased connectivity correlated with greater GM atrophy in occipital regions. All PCA patients had positive cerebrospinal fluid biomarkers for AD; however, FC in global DMN did not differ from controls. CONCLUSIONS: FC in PCA reflects brain structure in a non-univocal way. Hyperconnectivity of dorsal networks may indicate aberrant communication in response to posterior brain atrophy or processes of neural resilience during the initial stage of brain dysfunction. The lack of difference from controls in global DMN FC highlights the atypical nature of PCA with respect to typical AD.

Alpha and beta EEG power reflects L-dopa acute administration in parkinsonian patients.

AIM: To evaluate the effect of an acute L-dopa administration on eye-closed resting state electroencephalographic (EEG) activity of cognitively preserved Parkinsonian patients. METHODS: We examined 24 right-handed patients diagnosed as uncomplicated probable Parkinson's disease (PD). Each patient underwent Unified Parkinson's Disease Rating Scale (UPDRS)-part-III evaluation before and 60 min after an oral load of L-dopa-methyl-ester/carbidopa 250/25 mg. Resting condition eyes-closed EEG data were recorded both pre- and post L-dopa load. Absolute EEG power values were calculated at each scalp derivation for Delta, Theta, Alpha and Beta frequency bands. UPDRS scores (both global and subscale scores) and EEG data (power values of different frequency bands for each scalp derivation) were submitted to a statistical analysis to compare Pre and Post L-Dopa conditions. Finally, a correlation analysis was carried out between EEG spectral content and UPDRS scores. RESULTS: Considering EEG power spectral analysis, no statistically significant differences arose on Delta and Theta bands after L-dopa intake. Conversely, Alpha and Beta rhythms significantly increased on centro-parietal scalp derivations, as a function of L-dopa administration. Correlation analysis indicated a significant negative correlation between Beta power increase on centro-parietal areas and UPDRS subscores (Rigidity of arms and Bradykinesia). A minor significant negative correlation was also found between Alpha band increase and resting tremor. CONCLUSIONS: Assuming that a significant change in EEG power spectrum after L-dopa intake may be related to dopaminergic mechanisms, our findings are consistent with the hypothesis that dopaminergic defective networks are implicated in cortical oscillatory abnormalities at rest in non-demented PD patients.

Relationship among diffusion tensor imaging, EEG activity, and cognitive status in mild cognitive impairment and Alzheimer's disease patients.

Magnetic resonance (MR) diffusion tensor imaging (DTI) can detect microstructural alterations by means of fractional anisotropy (FA) in patients with dementia, also in relation to cognitive status. The present study aimed at investigating the possible relation among white matter damage in DTI, quantitative electroencephalography (EEG) spectral power, and cognitive status in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients. Forty-seven subjects (8 moderate AD, 18 mild AD, 12 MCI, and 9 healthy controls) underwent brain MR, neuropsychological evaluation, and resting EEG recording. A progressive increase of EEG delta and theta spectral power was observed from controls to patients, mainly in more anterior areas, with a parallel widespread decrease of beta power. Moreover, a progressive decrease of FA from controls to patients in frontal areas and in the corpus callosum (genu) was observed. Correlation analyses indicated convergence among EEG rhythms changes, DTI values, and cognitive status mainly over anterior areas. The decrease of FA values and EEG spectral power changes might represent markers of neurodegenerative dysfunction, possibly preceding macrostructural atrophy.

Intronic rs2147363 variant in ATP7B transcription factor-binding site associated with Alzheimer's disease.

Copper homeostasis abnormalities have been shown to be associated with Alzheimer's disease (AD), possibly by accelerating amyloid-ß toxicity and plaque formation. The ATP7B gene plays a key role in controlling body copper balance. Our previous studies showed an association between ATP7B variants and AD risk. Among these variants, an intronic single nucleotide polymorphism, rs2147363, was associated with AD risk. In order to understand this intronic association, we screened a population of 286 AD patients and 283 healthy controls, and verified the presence of other functional coding variants in linkage disequilibrium (LD). Then we searched for a regulatory function region close to rs2147363. An LD analysis revealed the presence of an LD between rs2147363 and a Wilson's disease-causing variant, rs7334118. However, this mutation did not explain the observed genetic association. Conversely, in silico analyses of rs2147363 functionality highlighted that this variant is located in a binding site of a transcription factor, and is, consequently, associated with regulatory function. These data suggest that the genetic variation in cis-regulatory elements located in non-coding regions can have a role in determining ATP7B functionality and account for some of the AD missing hereditability.

ATP7B variants as modulators of copper dyshomeostasis in Alzheimer's disease.

To understand the role of the key copper-regulating gene, ATP7B, in copper dyshomeostasis associated with Alzheimer's disease (AD), we analyzed the serum levels of copper, ceruloplasmin and 'free' (i.e., non-ceruloplasmin bound) copper in 399 patients with AD and 303 elderly healthy controls. We also performed analyses of informative variants of ATP7B. AD patients had higher levels of copper and free copper than controls. Individuals with free copper levels higher than 1.6 µmol/L (the upper value of the normal reference range) were more frequent among cases (p < 0.001). Among these individuals, those who were carriers of the ATP7B variants accounted for a large proportion of the free copper levels, specifically in the AD group (p < 0.01). Our results suggest the existence of a 'copper dysfunction' phenotype of sporadic AD which has a genetic basis. They also suggest that free copper is a risk factor for this disorder, modulating additional pathways leading to the disease cascade.

Global analysis of dynamical decision-making models through local computation around the hidden saddle.

Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient) behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity.

Transcranial magnetic stimulation studies in Alzheimer's disease.

Although motor deficits affect patients with Alzheimer's disease (AD) only at later stages, recent studies demonstrated that primary motor cortex is precociously affected by neuronal degeneration. It is conceivable that neuronal loss is compensated by reorganization of the neural circuitries, thereby maintaining motor performances in daily living. Effectively several transcranial magnetic stimulation (TMS) studies have demonstrated that cortical excitability is enhanced in AD and primary motor cortex presents functional reorganization. Although the best hypothesis for the pathogenesis of AD remains the degeneration of cholinergic neurons in specific regions of the basal forebrain, the application of specific TMS protocols pointed out a role of other neurotransmitters. The present paper provides a perspective of the TMS techniques used to study neurophysiological aspects of AD showing also that, based on different patterns of cortical excitability, TMS may be useful in discriminating between physiological and pathological brain aging at least at the group level. Moreover repetitive TMS might become useful in the rehabilitation of AD patients. Finally integrated approaches utilizing TMS together with others neuro-physiological techniques, such as high-density EEG, and structural and functional imaging as well as biological markers are proposed as promising tool for large-scale, low-cost, and noninvasive evaluation of at-risk populations.

Molecular characterization of paediatric idiopathic hypereosinophilia.

The hypereosinophilic syndromes (HES) include a group of heterogeneous diseases characterized by the persistent increase of the number of eosinophils in blood and bone marrow. Few cases of paediatric hypereosinophilia (pHES) have been described in the literature. Early identification of pHES that may evolve towards a lymphomyeloproliferative disease is relevant in light of prognostic and therapeutic implications. Molecular features of 10 pHES patients were analysed at presentation and during their clinical course, including analysis of BCR-ABL1 and FIP1L1/PDGFRA fusion genes, quantitation of WT1 gene copy number and clonality of T-cell receptor (TCR) and immunoglobulin heavy chain (IGH). All patients had normal karyotype and germline TCR configuration. Five children showed IGH clonality at presentation: of these, two developed a B non-Hodgkin lymphoma and a B-lineage acute lymphocytic leukaemia at six and 12 months respectively, two spontaneously reverted to a polyclonal IGH profile during the follow-up, and the last one persisted with pHES without B-clonal evolution after 19 months. One patient had a PDGFRA/FIP1L1 fusion and achieved hematologic and molecular remission after imatinib therapy. IGH rearrangement was observed to be a frequent molecular feature of pHES and may precede B-cell clonal expansion and evolution into B-cell malignancies in children.

Cortical neuromodulation modifies cerebral vasomotor reactivity.

BACKGROUND AND PURPOSE: Cerebral vasomotor reactivity (VMR) is a capability of cerebral vessels to dilate in response to hypercapnia. Transcranial direct current stimulation (tDCS) effects on cerebral hemodynamics have been poorly studied. METHODS: Ten healthy subjects underwent anodal/cathodal tDCS on the left motor cortex. Before and after tDCS, VMR assessment by transcranial Doppler and an electrocardiogram were performed. Normalized low-frequency band power of heart rate variability and its reactivity from basal to VMR condition (LFN(react)) were estimated as relative markers of sympathetic activation. tDCS exerted a polarity-specific effect on both VMR (P=0.0001) and LFN(react) (P=0.001). Anodal tDCS decreased VMR by 3.4%/mm Hg CO(2) bilaterally and increased LFN(react), whereas cathodal tDCS increased VMR by 0.8%/mm Hg CO(2) bilaterally and reduced LFN(react). CONCLUSIONS: Cerebral VMR is modified by tDCS. Based on the consensual changes with heart rate variability, we can hypothesize that the sympathetic nervous system could modulate the bihemispheric modification of VMR. Further studies are needed to confirm this hypothesis.