Comprehensive investigation of predictive processing: A cross- and within-cognitive domains fMRI meta-analytic approach.

Predictive processing (PP) stands as a predominant theoretical framework in neuroscience. While some efforts have been made to frame PP within a cognitive domain-general network perspective, suggesting the existence of a "prediction network," these studies have primarily focused on specific cognitive domains or functions. The question of whether a domain-general predictive network that encompasses all well-established cognitive domains exists remains unanswered. The present meta-analysis aims to address this gap by testing the hypothesis that PP relies on a large-scale network spanning across cognitive domains, supporting PP as a unified account toward a more integrated approach to neuroscience. The Activation Likelihood Estimation meta-analytic approach was employed, along with Meta-Analytic Connectivity Mapping, conjunction analysis, and behavioral decoding techniques. The analyses focused on prediction incongruency and prediction congruency, two conditions likely reflective of core phenomena of PP. Additionally, the analysis focused on a prediction phenomena-independent dimension, regardless of prediction incongruency and congruency. These analyses were first applied to each cognitive domain considered (cognitive control, attention, motor, language, social cognition). Then, all cognitive domains were collapsed into a single, cross-domain dimension, encompassing a total of 252 experiments. Results pertaining to prediction incongruency rely on a defined network across cognitive domains, while prediction congruency results exhibited less overall activation and slightly more variability across cognitive domains. The converging patterns of activation across prediction phenomena and cognitive domains highlight the role of several brain hubs unfolding within an organized large-scale network (Dynamic Prediction Network), mainly encompassing bilateral insula, frontal gyri, claustrum, parietal lobules, and temporal gyri. Additionally, the crucial role played at a cross-domain, multimodal level by the anterior insula, as evidenced by the conjunction and Meta-Analytic Connectivity Mapping analyses, places it as the major hub of the Dynamic Prediction Network. Results support the hypothesis that PP relies on a domain-general, large-scale network within whose regions PP units are likely to operate, depending on the context and environmental demands. The wide array of regions within the Dynamic Prediction Network seamlessly integrate context- and stimulus-dependent predictive computations, thereby contributing to the adaptive updating of the brain's models of the inner and external world.

Posttraumatic stress disorder (PTSD) prevalence: an umbrella review.

Posttraumatic stress disorder (PTSD) is one of the most serious and incapacitating mental diseases that can result from trauma exposure. The exact prevalence of this disorder is not known as the literature provides very different results, ranging from 2.5% to 74%. The aim of this umbrella review is to provide an estimation of PTSD prevalence and to clarify whether the prevalence depends on the assessment methods applied (structured interview v. self-report questionnaire) and on the nature of the traumatic event (interpersonal v. not-interpersonal). A systematic search of major databases and additional sources (Google Scholar, EBSCO, Web of Science, PubMed, Galileo Discovery) was conducted. Fifty-nine reviews met the criteria of this umbrella review. Overall PTSD prevalence was 23.95% (95% confidence interval 95% CI 20.74-27.15), with no publication bias or significant small-study effects, but a high level of heterogeneity between meta-analyses. Sensitivities analyses revealed that these results do not change after removing meta-analysis also including data from underage participants (23.03%, 95% CI 18.58-27.48), nor after excluding meta-analysis of low quality (24.26%, 95% CI 20.46-28.06). Regarding the impact of diagnostic instruments on PTSD prevalence, the results revealed a lack of significant differences in PTSD prevalence when structured v. self-report instruments were applied (p = 0.0835). Finally, PTSD prevalence did not differ following event of intentional (25.42%, 95% CI 19.76-31.09) or not intentional (22.48%, 95% CI 17.22-27.73) nature (p = 0.4598). The present umbrella review establishes a robust foundation for future research and provides valuable insights on PTSD prevalence.

The Emotion Authenticity Recognition (EAR) test: normative data of an innovative test using dynamic emotional stimuli to evaluate the ability to recognize the authenticity of emotions expressed by faces.

Despite research has massively focused on how emotions conveyed by faces are perceived, the perception of emotions' authenticity is a topic that has been surprisingly overlooked. Here, we present the Emotion Authenticity Recognition (EAR) test, a test specifically developed using dynamic stimuli depicting authentic and posed emotions to evaluate the ability of individuals to correctly identify an emotion (emotion recognition index, ER Index) and classify its authenticity (authenticity recognition index (EA Index). The EAR test has been validated on 522 healthy participants and normative values are provided. Correlations with demographic characteristics, empathy and general cognitive status have been obtained revealing that both indices are negatively correlated with age, and positively with education, cognitive status and different facets of empathy. The EAR test offers a new ecological test to assess the ability to detect emotion authenticity that allow to explore the eventual social cognitive deficit even in patients otherwise cognitively intact.

Gradient Organization of Space, Time, and Numbers in the Brain: A Meta-analysis of Neuroimaging Studies.

In this study, we ran a meta-analysis of neuroimaging studies to pinpoint the neural regions that are commonly activated across space, time, and numerosity, and we tested the existence of gradient transitions among these magnitude representations in the brain. Following PRISMA guidelines, we included in the meta-analysis 112 experiments (for space domain), 114 experiments (time domain), and 115 experiments (numerosity domain), and we used the activation likelihood estimation method. We found a system of brain regions that was commonly recruited in all the three magnitudes, which included bilateral insula, the supplementary motor area (SMA), the right inferior frontal gyrus, and bilateral intraparietal sulci. Gradiental transitions between different magnitudes were found along all these regions but insulae, with space and numbers leading to gradients mainly over parietal regions (and SMA) whereas time and numbers mainly over frontal regions. These findings provide evidence for the GradiATOM theory (Gradient Theory of Magnitude), suggesting that spatial proximity given by overlapping activations and gradients is a key aspect for efficient interactions and integrations among magnitudes.

Disentangling interoceptive abilities in alexithymia.

In recent years, research on interoceptive abilities (i.e., sensibility, accuracy, and awareness) and their associations with emotional experience has flourished. Yet interoceptive abilities in alexithymia-a personality trait characterized by a difficulty in the cognitive interpretation of emotional arousal, which impacts emotional experience-remain under-investigated, thereby limiting a full understanding of subjective emotional experience processing. Research has proposed two contrasting explanations thus far: in one model, the dimensions of interoceptive sensibility and accuracy in alexithymia would increase; in the other model, they would decrease. Surprisingly, the contribution of interoceptive awareness has been minimally researched. In this study (N = 182), the relationship between participants' level of alexithymia and the three interoceptive dimensions was tested. Our results show that the higher the level of alexithymia is, the higher interoceptive accuracy and sensibility (R2 = 0.29 and R2 = 0.14); conversely, the higher the level of alexithymia is, the lower interoceptive awareness (R2 = 0.36). Moreover, an ROC analysis reveals that interoceptive awareness is the most accurate predictor of alexithymia, yielding over 92% accuracy. Collectively, these results support a coherent understanding of interoceptive abilities in alexithymia, whereby the dissociation of interoceptive accuracy and awareness may explain the underlying psycho-physiological mechanisms of alexithymia. A possible neurocognitive mechanism is discussed which suggests insurgence of psychosomatic disorders in alexithymia and related psychotherapeutic approaches.

Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes.

Schizophrenia has been conceived as a disorder of brain connectivity, but it is unclear how this network phenotype is related to the underlying genetics. We used morphometric similarity analysis of MRI data as a marker of interareal cortical connectivity in three prior case-control studies of psychosis: in total, n = 185 cases and n = 227 controls. Psychosis was associated with globally reduced morphometric similarity in all three studies. There was also a replicable pattern of case-control differences in regional morphometric similarity, which was significantly reduced in patients in frontal and temporal cortical areas but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in morphometric similarity was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms and pathways. In addition, genes that were normally overexpressed in cortical areas with reduced morphometric similarity were significantly up-regulated in three prior post mortem studies of schizophrenia. We propose that this combined analysis of neuroimaging and transcriptional data provides insight into how previously implicated genes and proteins as well as a number of unreported genes in their topological vicinity on the protein interaction network may drive structural brain network changes mediating the genetic risk of schizophrenia.

From ATOM to GradiATOM: Cortical gradients support time and space processing as revealed by a meta-analysis of neuroimaging studies.

According to the ATOM (A Theory Of Magnitude), formulated by Walsh more than fifteen years ago, there is a general system of magnitude in the brain that comprises regions, such as the parietal cortex, shared by space, time and other magnitudes. The present meta-analysis of neuroimaging studies used the Activation Likelihood Estimation (ALE) method in order to determine the set of regions commonly activated in space and time processing and to establish the neural activations specific to each magnitude domain. Following PRISMA guidelines, we included in the analysis a total of 112 and 114 experiments, exploring space and time processing, respectively. We clearly identified the presence of a system of brain regions commonly recruited in both space and time that includes: bilateral insula, the pre-supplementary motor area (pre-SMA), the right frontal operculum and the intraparietal sulci. These regions might be the best candidates to form the core magnitude neural system. Surprisingly, along each of these regions but the insula, ALE values progressed in a cortical gradient from time to space. The SMA exhibited an anterior-posterior gradient, with space activating more-anterior regions (i.e., pre-SMA) and time activating more-posterior regions (i.e., SMA-proper). Frontal and parietal regions showed a dorsal-ventral gradient: space is mediated by dorsal frontal and parietal regions, and time recruits ventral frontal and parietal regions. Our study supports but also expands the ATOM theory. Therefore, we here re-named it the 'GradiATOM' theory (Gradient Theory of Magnitude), proposing that gradient organization can facilitate the transformations and integrations of magnitude representations by allowing space- and time-related neural populations to interact with each other over minimal distances.

Brain age prediction: A comparison between machine learning models using region- and voxel-based morphometric data.

Brain morphology varies across the ageing trajectory and the prediction of a person's age using brain features can aid the detection of abnormalities in the ageing process. Existing studies on such "brain age prediction" vary widely in terms of their methods and type of data, so at present the most accurate and generalisable methodological approach is unclear. Therefore, we used the UK Biobank data set (N = 10,824, age range 47-73) to compare the performance of the machine learning models support vector regression, relevance vector regression and Gaussian process regression on whole-brain region-based or voxel-based structural magnetic resonance imaging data with or without dimensionality reduction through principal component analysis. Performance was assessed in the validation set through cross-validation as well as an independent test set. The models achieved mean absolute errors between 3.7 and 4.7 years, with those trained on voxel-level data with principal component analysis performing best. Overall, we observed little difference in performance between models trained on the same data type, indicating that the type of input data had greater impact on performance than model choice. All code is provided online in the hope that this will aid future research.

Neuroanatomical abnormalities in first-episode psychosis across independent samples: a multi-centre mega-analysis.

BACKGROUND: Neuroanatomical abnormalities in first-episode psychosis (FEP) tend to be subtle and widespread. The vast majority of previous studies have used small samples, and therefore may have been underpowered. In addition, most studies have examined participants at a single research site, and therefore the results may be specific to the local sample investigated. Consequently, the findings reported in the existing literature are highly heterogeneous. This study aimed to overcome these issues by testing for neuroanatomical abnormalities in individuals with FEP that are expressed consistently across several independent samples. METHODS: Structural Magnetic Resonance Imaging data were acquired from a total of 572 FEP and 502 age and gender comparable healthy controls at five sites. Voxel-based morphometry was used to investigate differences in grey matter volume (GMV) between the two groups. Statistical inferences were made at p < 0.05 after family-wise error correction for multiple comparisons. RESULTS: FEP showed a widespread pattern of decreased GMV in fronto-temporal, insular and occipital regions bilaterally; these decreases were not dependent on anti-psychotic medication. The region with the most pronounced decrease - gyrus rectus - was negatively correlated with the severity of positive and negative symptoms. CONCLUSIONS: This study identified a consistent pattern of fronto-temporal, insular and occipital abnormalities in five independent FEP samples; furthermore, the extent of these alterations is dependent on the severity of symptoms and duration of illness. This provides evidence for reliable neuroanatomical alternations in FEP, expressed above and beyond site-related differences in anti-psychotic medication, scanning parameters and recruitment criteria.

Switching to ocrelizumab in RRMS patients at risk of PML previously treated with extended interval dosing of natalizumab.

Discontinuation of natalizumab in patients with relapsing-remitting multiple sclerosis (RRMS) at risk of progressive multifocal leukoencephalopathy (PML) is associated with disease reactivation. Forty-two RRMS patients, who switched from an extended interval dose (EID) of natalizumab to ocrelizumab, underwent magnetic resonance imaging (MRI) and clinical monitoring during washout and after ocrelizumab starting. During the first 3 months, disease reactivation was observed in five (12%) patients; 6 months after ocrelizumab starting, no further relapses were recorded, and Expanded Disability Status Scale (EDSS) remained stable in 38 (90%) patients. In conclusion, ocrelizumab could be considered a choice to mitigate the risk of disease reactivation in patients previously treated with natalizumab-EID.

The risk of infection in patients with multiple sclerosis treated with disease-modifying therapies: A Delphi consensus statement.

The risk of infection associated with immunomodulatory or immunosuppressive disease-modifying drugs (DMDs) in patients with multiple sclerosis (MS) has been increasingly addressed in recent scientific literature. A modified Delphi consensus process was conducted to develop clinically relevant, evidence-based recommendations to assist physicians with decision-making in relation to the risks of a wide range of infections associated with different DMDs in patients with MS. The current consensus statements, developed by a panel of experts (neurologists, infectious disease specialists, a gynaecologist and a neuroradiologist), address the risk of iatrogenic infections (opportunistic infections, including herpes and cryptococcal infections, candidiasis and listeria; progressive multifocal leukoencephalopathy; human papillomavirus and urinary tract infections; respiratory tract infections and tuberculosis; hepatitis and gastrointestinal infections) in patients with MS treated with different DMDs, as well as prevention strategies and surveillance strategies for the early identification of infections. In the discussion, more recent data emerged in the literature were taken into consideration. Recommended risk reduction and management strategies for infections include screening at diagnosis and before starting a new DMD, prophylaxis where appropriate, monitoring and early diagnosis.

Vaccinations in patients with multiple sclerosis: A Delphi consensus statement.

BACKGROUND: Patients with multiple sclerosis (MS) are at increased risk of infection. Vaccination can mitigate these risks but only if safe and effective in MS patients, including those taking disease-modifying drugs. METHODS: A modified Delphi consensus process (October 2017-June 2018) was used to develop clinically relevant recommendations for making decisions about vaccinations in patients with MS. A series of statements and recommendations regarding the efficacy, safety and timing of vaccine administration in patients with MS were generated in April 2018 by a panel of experts based on a review of the published literature performed in October 2017. RESULTS: Recommendations include the need for an 'infectious diseases card' of each patient's infectious and immunisation history at diagnosis in order to exclude and eventually treat latent infections. We suggest the implementation of the locally recommended vaccinations, if possible at MS diagnosis, otherwise with vaccination timing tailored to the planned/current MS treatment, and yearly administration of the seasonal influenza vaccine regardless of the treatment received. CONCLUSION: Patients with MS should be vaccinated with careful consideration of risks and benefits. However, there is an urgent need for more research into vaccinations in patients with MS to guide evidence-based decision making.

Integrating machining learning and multimodal neuroimaging to detect schizophrenia at the level of the individual.

Schizophrenia is a severe psychiatric disorder associated with both structural and functional brain abnormalities. In the past few years, there has been growing interest in the application of machine learning techniques to neuroimaging data for the diagnostic and prognostic assessment of this disorder. However, the vast majority of studies published so far have used either structural or functional neuroimaging data, without accounting for the multimodal nature of the disorder. Structural MRI and resting-state functional MRI data were acquired from a total of 295 patients with schizophrenia and 452 healthy controls at five research centers. We extracted features from the data including gray matter volume, white matter volume, amplitude of low-frequency fluctuation, regional homogeneity and two connectome-wide based metrics: structural covariance matrices and functional connectivity matrices. A support vector machine classifier was trained on each dataset separately to distinguish the subjects at individual level using each of the single feature as well as their combination, and 10-fold cross-validation was used to assess the performance of the model. Functional data allow higher accuracy of classification than structural data (mean 82.75% vs. 75.84%). Within each modality, the combination of images and matrices improves performance, resulting in mean accuracies of 81.63% for structural data and 87.59% for functional data. The use of all combined structural and functional measures allows the highest accuracy of classification (90.83%). We conclude that combining multimodal measures within a single model is a promising direction for developing biologically informed diagnostic tools in schizophrenia.

Simultaneous quantification of natural and inducible regulatory T-cell subsets during interferon-ß therapy of multiple sclerosis patients.

BACKGROUND: The mechanisms underlying the therapeutic activity of interferon-ß in multiple sclerosis are still not completely understood. In the present study, we evaluated the short and long-term effects of interferon-ß treatment on different subsets of regulatory T cells in relapsing-remitting multiple sclerosis patients biologically responsive to treatment because of mixovirus resistance protein A inducibility. METHODS: In this prospective longitudinal study, subsets of natural regulatory T cells (naïve, central memory and effector memory) and inducible regulatory T cells (Tr1), as well as in vitro-induced regulatory T cells (Tr1-like cells), were simultaneously quantified by flow cytometry in samples prepared from 148 therapy-naïve multiple sclerosis patients obtained before and after 6, 12, 18, and 24 months of interferon-ß-1a treatment. mRNA for interleukin-10 and Tr1-related genes (CD18, CD49b, and CD46, together with Cyt-1 and Cyt-2 CD46-associated isoforms) were quantified in Tr1-like cells. RESULTS: Despite profound inter-individual variations in the modulation of all regulatory T-cell subsets, the percentage of natural regulatory T cells increased after 6, 12, and 24 months of interferon-ß treatment. This increase was characterized by the expansion of central and effector memory regulatory T-cell subsets. The percentage of Tr1 significantly enhanced at 12 months of therapy and continued to be high at the subsequent evaluation points. Patients experiencing relapses displayed a higher percentage of naïve regulatory T cells and a lower percentage of central memory regulatory T cells and of Tr1 before starting interferon-ß therapy. In addition, an increase over time of central memory and of Tr1 was observed only in patients with stable disease. However, in vitro-induced Tr1-like cells, prepared from patients treated for 24 months, produced less amount of interleukin-10 mRNA compared with pre-treatment Tr1-like cells. CONCLUSION: Interferon-ß induces the expansion of T regulatory subsets endowed with a high suppressive activity, especially in clinically stable patients. The overall concurrent modulation of natural and inducible regulatory T-cell subsets might explain the therapeutic effects of interferon-ß in multiple sclerosis patients.

Detecting schizophrenia at the level of the individual: relative diagnostic value of whole-brain images, connectome-wide functional connectivity and graph-based metrics.

BACKGROUND: Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient. METHODS: Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology. RESULTS: Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions. CONCLUSION: These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the 'dysconnectivity hypothesis' of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.

Should frequent MRI monitoring be performed in natalizumab-treated MS patients? A contribution to a recent debate.

BACKGROUND: Brain magnetic resonance imaging (MRI) is the most effective surveillance tool for the detection of asymptomatic progressive multifocal leukoencephalopathy (PML). However, the optimal frequency for routine MRI surveillance is under-investigated. OBJECTIVE: To understand whether, upon their first MRI appearance, PML lesions present a difference in volume when comparing patients who frequently underwent MRI surveillance (3/4 months) with those who were assessed at longer intervals (6/12 months) and to understand the impact of the volume of lesions on clinical outcome. METHODS: The data of patients included in the Italian PML cohort were retrospectively analysed. Patients who had all the pre-diagnostic MRI scans available (n = 37) were included. The volume of PML lesion was calculated by manually outlining the PML lesion. RESULTS: Compared with patients who underwent MRI examination at least every 4 months, patients who were assessed less frequently had a lesion of significantly higher volume (median: 2567 (883-3583) vs. 664 mm3 (392-963) p = 0.006) and suffered a higher rate of disability (median: 2.25 expanded disability status scale points (-2.5 to 8) vs. 0.5 (-1 to 2.5) p = 0.004). CONCLUSION: The positive clinical outcome of patients undergoing frequent MRI surveillance and the small volume of the PML lesion upon first appearance justify a frequent surveillance using MRI in patients at high risk of PML.

Where is the "where" in the brain? A meta-analysis of neuroimaging studies on spatial cognition.

Spatial representations are processed in the service of several different cognitive functions. The present study capitalizes on the Activation Likelihood Estimation (ALE) method of meta-analysis to identify: (a) the shared neural activations among spatial functions to reveal the "core" network of spatial processing; (b) the specific neural activations associated with each of these functions. Following PRISMA guidelines, a total of 133 fMRI and PET studies were included in the meta-analysis. The overall analysis showed that the core network of spatial processing comprises regions that are symmetrically distributed on both hemispheres and that include dorsal frontoparietal regions, presupplementary motor area, anterior insula, and frontal operculum. The specific analyses revealed the brain regions that are selectively recruited for each spatial function, such as the right temporoparietal junction for shift of spatial attention, the right parahippocampal gyrus, and the retrosplenial cortex for navigation and spatial long-term memory. The findings are integrated within a systematic review of the neuroimaging literature and a new neurocognitive model of spatial cognition is proposed.

Early diagnosis of progressive multifocal leucoencephalopathy: longitudinal lesion evolution.

OBJECTIVE: Early diagnosis of natalizumab-related progressive multifocal leucoencephalopathy (NTZ-PML) in multiple sclerosis has been deemed a major priority by the regulatory agencies but has yet to become a reality. The current paper aims to: (1) investigate whether patients with NTZ-PML pass through a prolonged presymptomatic phase with MRI abnormalities, (2) estimate the longitudinal PML lesion volume increase during the presymptomatic phase and (3) estimate the presymptomatic phase length and its impact on therapy duration as a risk stratification parameter. METHODS: All Italian patients who developed NTZ-PML between 2009 and 2018 were included. The data of patients with available prediagnostic MRI were analysed (n=41). Detailed clinical and neuroradiological information was available for each participant. RESULTS: (1) PML lesions were detectable in the presymptomatic phase in 32/41 (78%) patients; (ii) the lesion volume increased by 62.8 % for each month spent in the prediagnostic phase; (3) the prediagnostic phase length was 150.8±74.9 days; (4) PML MRI features were detectable before the 24th month of therapy in 31.7 % of patients in our cohort. CONCLUSIONS: Considering the latency of PML clinical manifestation, the presymptomatic phase length supports the usefulness of MRI surveillance every 3-4 months. Early diagnosis could prompt a better outcome for patients due to the relationship between lesion volume and JC virus infection. The insight from this study might also have an impact on risk stratification algorithms, as therapy duration as a parameter of stratification appears to need reassessment.

Four cases of natalizumab-related PML: a less severe course in extended interval dosing?

BACKGROUND: Progressive multifocal leukoencephalopathy (PML) is a severe adverse event of natalizumab (NTZ). The administration of NTZ with extended interval dosing (EID) has been proposed as a strategy to potentially reduce the incidence of PML while maintaining its therapeutic efficacy. METHODS: In the current paper, we describe 4 cases of NTZ-PML in EID included in the Italian PML cohort. RESULTS: The patients developed PML after at least 38 NTZ infusions. Their John Cunningham virus (JCv) index was > 1.5, and patients had not previously used immunosuppressant. Two patients were asymptomatic at PML onset, while two had mild motor impairment of the right hand and anomia, respectively. All of them had undetectable viral load but one (37 JCv copies/ml). In all patients, MRI revealed unilobar lesions with deferred contrast enhancement suggestive of immune reconstitution. The clinical course ended with a favorable clinical outcome (ΔEDSS up to 1). CONCLUSIONS: Although PML in EID seems to occur less frequently than in conventional dosing regimen, strict monitoring of high-risk patients contributed to the indolent course observed in the four described cases, characterized by a prolonged pre-symptomatic phase, paucisymptomatic onset, low JCv load, less severe functional impairment during immune reconstitution, and a mild disability burden.

To do or not to do? plasma exchange and timing of steroid administration in progressive multifocal leukoencephalopathy.

OBJECTIVE: To retrospectively analyze the effect of plasma exchange (PLEX; yes = PLEX+ , no = PLEX- ) and steroids administration timing (prophylactically [proST] or therapeutically [therST]) on the longitudinal clinical course of patients with natalizumab-related progressive multifocal leukoencephalopathy (PML) and full-blown immune reconstitution inflammatory syndrome (PML-IRIS). METHODS: Clinical and radiological data of 42 Italian patients with PML were analyzed. Patient's data are available until 12 months after PML diagnosis. PLEX and steroids treatment as time-dependent covariates were entered in: (1) a Cox model to investigate their impact on full-blown PML-IRIS latency; (2) an analysis of variance ANOVA to investigate their impact on IRIS duration; and (3) a linear mixed model to assess their impact on the longitudinal clinical course (measured by means of Expanded Disability Status Scale [EDSS]). RESULTS: Treatment with PLEX was not associated to PML-IRIS latency (hazard ratio [HR] = 1.05; p = 0.92), but once IRIS emerged, its duration was significantly longer in patients who underwent PLEX (101 vs 54 days in PLEX+ and PLEX- patients; p = 0.028). Receiving proST versus therST was not associated to IRIS latency (HR = 0.67; p = 0.39) or duration (p = 0.95). Patients who underwent proST had a significantly higher EDSS increase during PML (0.09 EDSS points per month; p = 0.04) as compared to those who had therST. INTERPRETATION: This study highlights that: (1) caution on the use of PLEX should be considered as the current data do not support a beneficial effect of PLEX and (2) caution on the early use of steroids is suggested because their prophylactic use to prevent full-blown PML-IRIS seems to negatively impact on the longitudinal disability course. Ann Neurol 2017;82:697-705.