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ImportanceThere is a lack of validated biomarkers for disability progression independent of relapse activity (PIRA) in multiple sclerosis (MS).ObjectiveTo determine how serum glial fibrillary acidic protein (sGFAP) and serum neurofilament light chain (sNfL) correlate with features of disease progression vs acute focal inflammation in MS and how they can prognosticate disease progression.Design, Setting, and ParticipantsData were acquired in the longitudinal Swiss MS cohort (SMSC; a consortium of tertiary referral hospitals) from January 1, 2012, to October 20, 2022. The SMSC is a prospective, multicenter study performed in 8 centers in Switzerland. For this nested study, participants had to meet the following inclusion criteria: cohort 1, patients with MS and either stable or worsening disability and similar baseline Expanded Disability Status Scale scores with no relapses during the entire follow-up; and cohort 2, all SMSC study patients who had initiated and continued B-cell–depleting treatment (ie, ocrelizumab or rituximab).ExposuresPatients received standard immunotherapies or were untreated.Main Outcomes and MeasuresIn cohort 1, sGFAP and sNfL levels were measured longitudinally using Simoa assays. Healthy control samples served as the reference. In cohort 2, sGFAP and sNfL levels were determined cross-sectionally.ResultsThis study included a total of 355 patients (103 [29.0%] in cohort 1: median [IQR] age, 42.1 [33.2-47.6] years; 73 female patients [70.9%]; and 252 [71.0%] in cohort 2: median [IQR] age, 44.3 [33.3-54.7] years; 156 female patients [61.9%]) and 259 healthy controls with a median [IQR] age of 44.3 [36.3-52.3] years and 177 female individuals (68.3%). sGFAP levels in controls increased as a function of age (1.5% per year; P P = .01), and were 14.9% higher in women than in men (P = .004). In cohort 1, patients with worsening progressive MS showed 50.9% higher sGFAP levels compared with those with stable MS after additional sNfL adjustment, whereas the 25% increase of sNfL disappeared after additional sGFAP adjustment. Higher sGFAP at baseline was associated with accelerated gray matter brain volume loss (per doubling: 0.24% per year; P z scores were higher in patients developing future confirmed disability worsening compared with those with stable disability (1.94 [0.36-2.23] vs 0.71 [−0.13 to 1.73]; P = .002); this was not significant for sNfL. However, the combined elevation of z scores of both biomarkers resulted in a 4- to 5-fold increased risk of confirmed disability worsening (hazard ratio [HR], 4.09; 95% CI, 2.04-8.18; P P Conclusions and RelevanceResults of this cohort study suggest that sGFAP is a prognostic biomarker for future PIRA and revealed its complementary potential next to sNfL. sGFAP may serve as a useful biomarker for disease progression in MS in individual patient management and drug development.

Measures of atrophy in the whole brain can be used to reliably assess treatment effect in clinical trials of patients with multiple sclerosis (MS). Trials assessing the effect of treatment on grey matter (GM) and white matter (WM) atrophy are very informative, but hindered by technical limitations. This study aimed to measure GM and WM volume changes, using a robust longitudinal method, in patients with relapsing MS randomized to cladribine tablets 3.5 mg/kg or placebo in the CLARITY study.We analysed T1-weighted magnetic resonance sequences using SIENA-XL, from 0 to 6 months (cladribine, n = 267; placebo, n = 265) and 6 to 24 months (cladribine, n = 184; placebo, n = 186). Mean percentage GM and WM volume changes (PGMVC and PWMVC) were compared using a mixed-effect model.More GM and WM volume loss was found in patients taking cladribine versus those taking placebo in the first 6 months of treatment (PGMVC: cladribine: -0.53 vs. placebo: -0.25 [p = 0.045]; PWMVC: cladribine: -0.49 vs. placebo: -0.34 [p = 0.137]), probably due to pseudoatrophy. However, over the period 6 to 24 months, GM volume loss was significantly lower in patients on cladribine than in those on placebo (PGMVC: cladribine: -0.90 vs. placebo: -1.27 [p = 0.026]). In this period, volume changes in WM were similar in the two treatment arms (p = 0.52).After a short period of pseudoatrophy, treatment with cladribine 3.5 mg/kg significantly reduced GM atrophy in comparison with placebo. This supports the relevance of GM damage in MS and may have important implications for physical and cognitive disability progression.

Background and purpose: In the REFLEX trial (ClinicalTrials.gov identifier: NCT00404352), patients with a first clinical demyelinating event (FCDE) displayed significantly delayed onset of multiple sclerosis (MS; McDonald criteria) when treated with subcutaneous interferon beta-1a (sc IFN β-1a) versus placebo. This post hoc analysis evaluated the effect of sc IFN β-1a on spatio-temporal evolution of disease activity, assessed by changes in T2 lesion distribution, in specific brain regions of such patients and its relationship with conversion to MS. Methods: Post hoc analysis of baseline and 24-month magnetic resonance imaging data from FCDE patients who received sc IFN β-1a 44 μg once or three times weekly, or placebo in the REFLEX trial. Patients were grouped according to McDonald MS status (converter/non-converter) or treatment (sc IFN β-1a/placebo). For each patient group, a baseline lesion probability map (LPM) and longitudinal new/enlarging and shrinking/disappearing LPMs were created. Lesion location/frequency of lesion occurrence were assessed in the white matter. Results: At Month 24, lesion frequency was significantly higher in the anterior thalamic radiation (ATR) and corticospinal tract (CST) of converters versus non-converters (p

Objective: To investigate the clinical relevance of individual profiles of cortical and white matter lesion myelin content changes combining magnetisation transfer imaging (MTI) and 11C-PiB-positron emission tomography (PET) in patients with multiple sclerosis (MS). Methods: MTI and [11C]PiB-PET acquired in 19 patients with MS followed up over 2–4 months and in seven healthy controls (HCs), were employed to generate individual maps of cortical and white matter (WM) lesion myelin content changes, respectively. These maps were used to calculate individual indices of demyelination and remyelination, and to investigate their association with clinical scores. Results: Cortical remyelination ranged between 1% and 5% of the total cortical volume (17%–45% of the cortical volume demyelinated at baseline). WM lesion remyelination ranged between 8% and 22% of the lesional volume. An extensive cortical remyelination was associated with a shorter disease duration (rho = −0.63, p = 0.01) and, in combination with WM lesion remyelination, explained 68%–70% of the variance of clinical scores ( p Conclusion: Our multimodal and multicompartment approach allows us to explore single-patient cortical and WM lesion demyelination and remyelination, and to generate clinically relevant indices of myelin repair. These indices may be used as outcome measures in clinical trials, thus increasing the chance to identify successful promyelinating treatments in patients with MS.

to evaluate the impact on total mortality of the COVID-19 pandemic in Italy, by country of birth.historic cohort study based on administrative databases.the study is based on subjects included in the Base Register of Individuals of the Italian National Institute of Statistics on 01.01.2019, aged 35-64 years, and followed-up until 31.07.2021.age-standardized mortality rates were computed to analyse trends in overall mortality by country of birth grouped in three categories: 1. Italy and other high developed countries; 2. European countries with strong migratory pressure (EU-SMP); 3, non-European countries with strong migratory pressure (non-EU-SMP). Variations in mortality rates during the pandemic (March 2020-July 2021) with respect to the pre-pandemic period (January 2019-February 2020) were measured and compared across groups using mortality rate ratios (MRR) estimated by Poisson regression models, separately for men and women.the cohort includes 26,199,241 individuals, of whom 172,847 died during the follow-up. Over the whole period, mortality was consistently lower in individuals born in non-EU-SMP countries as compared to those born in Italy and other high developed countries. During the first pandemic wave (March-April 2020), individuals born in non-EU-SMP countries had higher excesses as compared to those born in Italy or other high developed countries (MRRs: 1.42 vs 1.28 in men and 1.30 vs 1.11 in women). Similar results were observed during the pandemic period October 2020-April 2021, when the MRRs were 1.37 vs 1.20 in men and 1.30 vs 1.11 in women. In the same period, the excess mortality among individuals born in EU-SMP did not significantly differ from that observed among those born in Italy and other high developed countries.in Italy, excess mortality during the COVID-19 pandemic was higher among immigrants born in non-EU-SMP countries as compared to the native population and immigrants born in high developed countries.

Objective To assess the dynamics of “pseudo‐atrophy,” the accelerated brain volume loss observed after initiation of anti‐inflammatory therapies, in patients with multiple sclerosis (MS). Methods Monthly magnetic resonance imaging (MRI) data of patients from the IMPROVE clinical study (NCT00441103) comparing relapsing‐remitting MS patients treated with interferon beta‐1a (IFNβ‐1a) for 40 weeks versus those receiving placebo (16 weeks) and then IFNβ‐1a (24 weeks) were used to assess percentage of gray (PGMVC) and white matter (PWMVC) volume changes. Comparisons of PGMVC and PWMVC slopes were performed with a mixed effect linear model. In the IFNβ‐1a‐treated arm, a quadratic term was included in the model to evaluate the plateauing effect over 40 weeks. Results Up to week 16, PGMVC was −0.14% per month in the placebo and −0.27% per month in treated patients (P

Important work has been done to measure legislative effectiveness in the U.S. Congress and to explain the individual characteristics that drive it. Much less attention, however, has been devoted to study the extent to which legislative effectiveness depends on the legislators' social connections. We address this issue with a new model of legislative effectiveness that formalizes the role of social connections, and we test its predictions using the network of cosponsorship links in the 109th–113th Congresses. We propose a new empirical strategy that addresses network endogeneity by implementing a two‐step Heckman correction based on an original instrument: the legislators' alumni connections. We find that social connections are a significant determinant of legislative effectiveness. We also study the influence of legislators' characteristics in shaping the network effects. In doing so, we provide new insights into how social connectedness interacts with factors such as seniority, partisanship, and legislative leadership in determining legislators' effectiveness.

Background: Source-based morphometry (SBM) was recently used for non-random “patterns” of gray matter (GM) atrophy or white matter (WM) microstructural damage. Objective: To assess whether and to what extent such patterns may be inter-related in MS. Methods: SBM was applied to images of GM concentration and fractional anisotropy (FA) in MS patients ( n = 41, median EDSS = 1) and normal controls (NC, n = 28). The same procedure was repeated on an independent and similar data set (39 MS patients and 13 NC). Results: We found in MS patterns of GM atrophy and reduced FA ( p Conclusion: In relatively early MS, we found a close link between deep GM atrophy pattern and WM damage while sensorimotor and posterior cortex patterns were partially independent from WM damage and perhaps related to primary mechanisms. Patterns were clinically relevant.

To assess the impact of the COVID-19 pandemic on all-cause mortality in Italy during the first wave of the epidemic, taking into consideration the geographical heterogeneity of the spread of COVID-19.This study is a retrospective, population-based cohort study using national statistics throughout Italy. Survival analysis was applied to data aggregated by day of death, age groups, sex, and Italian administrative units (107 provinces). We applied Cox models to estimate the relative hazards (RH) of excess mortality, comparing all-cause deaths in 2020 with the expected deaths from all causes in the same time period. The RH of excess deaths was estimated in areas with a high, moderate, and low spread of COVID-19. We reported the estimate also restricting the analysis to the period of March-April 2020 (first peak of the epidemic).The study population consisted of 57,204,501 individuals living in Italy as of January 1, 2020. The number of excess deaths was 36,445, which accounts for 13.4% of excess mortalities from all causes during January-May 2020 (i.e., RH = 1.134; 95% confidence interval (CI): 1.129-1.140). In the macro-area with a relatively higher spread of COVID-19 (i.e., incidence rate, IR): 450-1,610 cases per 100,000 residents), the RH of excess deaths was 1.375 (95% CI: 1.364-1.386). In the area with a relatively moderate spread of COVID-19 (i.e., IR: 150-449 cases) it was 1.049 (95% CI: 1.038-1.060). In the area with a relatively lower spread of COVID-19 (i.e., IR: 30-149 cases), it was 0.967 (95% CI: 0.959-0.976). Between March and April (peak months of the first wave of the epidemic in Italy), we estimated an excess mortality from all causes of 43.5%. The RH of all-cause mortality for increments of 500 cases per 100,000 residents was 1.352 (95% CI: 1.346-1.359), corresponding to an increase of about 35%.Our analysis, making use of a population-based cohort model, estimated all-cause excess mortality in Italy taking account of both time period and of COVID-19 geographical spread. The study highlights the importance of a temporal/geographic framework in analyzing the risk of COVID-19-epidemy related mortality.

there is increasing concern that the COVID-19 pandemic has disproportionately affected the most vulnerable individuals.to determine whether education inequalities have widened during the first wave of the COVID-19 pandemic in Italy. DESIGN: historic cohort study based on administrative databases.the study was based on subjects registered in the Base Register of Individuals on 01.01.2019, aged=35 years, and followed-up until 30.06.2020.education inequalities in mortality before, during the first phase (March-April), and during the second phase (May-June) of the first pandemic wave in Italy were measured through the mortality rate ratios (MRRs). MMRs were estimated through negative binomial models. The interaction term between period and education was tested through the likelihood ratio test.the cohort included 37,976,670 individuals, and 719,665 of them died over the follow-up. In high pandemic areas, the MRR among less educated men were: 1.48 (95%CI 1.42-1.55) in the pre-pandemic period, 1.45 (95%CI 1.36-1.55) in the first phase and 1.42 (95%CI 1.30-1.56) in the second phase of the pandemic (p-value: 0.92). Corresponding figures among women were: 1.26 (95%CI 1.21-1.32), 1.39 (95%CI 1.30-1.49), and 1.35 (95%CI 1.23-1.48); p-value: 0.03. The MRRs substantially increased in the first pandemic phase among women aged 35-64 years (from 1.48 to 1.98; p-value; 0.011) and 65-79 years (from 1.22 to 1.51; p-value: 0.017). During the second phase, the MRRs returned to the values observed before the pandemic.in Italy, education inequality in mortality widened during the COVID-19 pandemic among working-age women and those aged 65-79 years.

We present a model of endogenous network formation to recover unobserved social networks using only observable outcomes. We propose a novel equilibrium concept that allows for a sharp characterization of equilibrium behavior and that yields a unique prediction under testable conditions. While the equilibrium is characterized by a large number of nonlinear equations, we show that it can be efficiently employed to recover the networks by an appropriately designed approximate Bayesian computation method. We apply the model to recover the network of social links between lawmakers in the U.S. Congress using data from the 109th to 113th legislatures. We show that social connections are important for legislators' productivities and we identify some of the key determinants of network centralities in the U.S. Congress.

The mechanisms responsible for the favorable clinical course in multiple sclerosis (MS) remain unclear. In this longitudinal study, we assessed whether magnetic resonance imaging (MRI)-based changes in focal and diffuse brain damage are associated with a long-term favorable MS diseases course. We found that global brain and gray matter (GM) atrophy changes were milder in MS patients with long-standing disease (⩾30 years from onset) and favorable (no/minimal disability) clinical course than in sex-age-matched disable MS patients, independently of lesions accumulation. Data showed that different trajectories of volume changes, as reflected by mild GM atrophy, may characterize patients with long-term favorable evolution.

Introduction: Excess mortality (EM) is a valid indicator of COVID-19’s impact on public health. Several studies regarding the estimation of EM have been conducted in Italy, and some of them have shown conflicting values. We focused on three estimation models and compared their results with respect to the same target population, which allowed us to highlight their strengths and limitations. Methods: We selected three estimation models: model 1 (Maruotti et al.) is a Negative-Binomial GLMM with seasonal patterns; model 2 (Dorrucci et al.) is a Negative Binomial GLM epidemiological approach; and model 3 (Scortichini et al.) is a quasi-Poisson GLM time-series approach with temperature distributions. We extended the time windows of the original models until December 2021, computing various EM estimates to allow for comparisons. Results: We compared the results with our benchmark, the ISS-ISTAT official estimates. Model 1 was the most consistent, model 2 was almost identical, and model 3 differed from the two. Model 1 was the most stable towards changes in the baseline years, while model 2 had a lower cross-validation RMSE. Discussion: Presently, an unambiguous explanation of EM in Italy is not possible. We provide a range that we consider sound, given the high variability associated with the use of different models. However, all three models accurately represented the spatiotemporal trends of the pandemic waves in Italy.

COVID-19 dramatically influenced mortality worldwide, in Italy as well, the first European country to experience the Sars-Cov2 epidemic. Many countries reported a two-wave pattern of COVID-19 deaths; however, studies comparing the two waves are limited. The objective of the study was to compare all-cause excess mortality between the two waves that occurred during the year 2020 using nationwide data. All-cause excess mortalities were estimated using negative binomial models with time modeled by quadratic splines. The models were also applied to estimate all-cause excess deaths “not directly attributable to COVD-19”, i.e., without a previous COVID-19 diagnosis. During the first wave (25th February−31st May), we estimated 52,437 excess deaths (95% CI: 49,213–55,863) and 50,979 (95% CI: 50,333–51,425) during the second phase (10th October−31st December), corresponding to percentage 34.8% (95% CI: 33.8%–35.8%) in the second wave and 31.0% (95%CI: 27.2%–35.4%) in the first. During both waves, all-cause excess deaths percentages were higher in northern regions (59.1% during the first and 42.2% in the second wave), with a significant increase in the rest of Italy (from 6.7% to 27.1%) during the second wave. Males and those aged 80 or over were the most hit groups with an increase in both during the second wave. Excess deaths not directly attributable to COVID-19 decreased during the second phase with respect to the first phase, from 10.8% (95% CI: 9.5%–12.4%) to 7.7% (95% CI: 7.5%–7.9%), respectively. The percentage increase in excess deaths from all causes suggests in Italy a different impact of the SARS-CoV-2 virus during the second wave in 2020. The decrease in excess deaths not directly attributable to COVID-19 may indicate an improvement in the preparedness of the Italian health care services during this second wave, in the detection of COVID-19 diagnoses and/or clinical practice toward the other severe diseases.

Recent advances in data collection, computing power, and theoretical modeling have stimulated a growing literature in economics and political science studying how social networks affect policy making. We survey this literature focusing on two main aspects. First, we discuss the literature studying how (and if) social connections in Congress affect legislative behavior. We then discuss how social connections affect the relationship between policy makers and the outside world, focusing on lobbying; the importance of family, caste, and ethnic networks; and social media and public activism. In our discussion, we highlight the key methodological challenges in this literature, how they have been addressed, and the prospects for future research.

We study a simple dynamic principal-agent model in which the agent’s types are serially correlated. In these models, the standard approach consists of first solving a relaxed version in which only local incentive compatibility constraints are considered, and then in proving that the local constraints are sufficient for implementability. We explore the conditions under which this approach is valid and can be used to characterize the profit maximizing contract. We show that the approach works when the allocation in the relaxed problem is monotonic in the types, a condition that is satisfied in most solved examples. This condition, however, is violated in general environments: when the time horizon is long enough and serial correlation is sufficiently high, global incentive compatibility constraints are binding. By fully characterizing a simple two period example, we uncover a number of interesting features of the optimal contract that cannot be observed in the special environments in which the standard approach works. Finally, we show that even in complex environments, approximately optimal allocations can be easily characterized by focusing on a particular class of contracts in which the allocation is forced to be monotonic.

Importance The mechanisms driving neurodegeneration and brain atrophy in relapsing multiple sclerosis (RMS) are not completely understood. Objective To determine whether disability progression independent of relapse activity (PIRA) in patients with RMS is associated with accelerated brain tissue loss. Design, Setting, and Participants In this observational, longitudinal cohort study with median (IQR) follow-up of 3.2 years (2.0-4.9), data were acquired from January 2012 to September 2019 in a consortium of tertiary university and nonuniversity referral hospitals. Patients were included if they had regular clinical follow-up and at least 2 brain magnetic resonance imaging (MRI) scans suitable for volumetric analysis. Data were analyzed between January 2020 and March 2021. Exposures According to the clinical evolution during the entire observation, patients were classified as those presenting (1) relapse activity only, (2) PIRA episodes only, (3) mixed activity, or (4) clinical stability. Main Outcomes and Measures Mean difference in annual percentage change (MD-APC) in brain volume/cortical thickness between groups, calculated after propensity score matching. Brain atrophy rates, and their association with the variables of interest, were explored with linear mixed-effect models. Results Included were 1904 brain MRI scans from 516 patients with RMS (67.4% female; mean [SD] age, 41.4 [11.1] years; median [IQR] Expanded Disability Status Scale score, 2.0 [1.5-3.0]). Scans with insufficient quality were excluded (n = 19). Radiological inflammatory activity was associated with increased atrophy rates in several brain compartments, while an increased annualized relapse rate was linked to accelerated deep gray matter (GM) volume loss. When compared with clinically stable patients, patients with PIRA had an increased rate of brain volume loss (MD-APC, -0.36; 95% CI, -0.60 to -0.12; P = .02), mainly driven by GM loss in the cerebral cortex. Patients who were relapsing presented increased whole brain atrophy (MD-APC, -0.18; 95% CI, -0.34 to -0.02; P = .04) with respect to clinically stable patients, with accelerated GM loss in both cerebral cortex and deep GM. No differences in brain atrophy rates were measured between patients with PIRA and those presenting relapse activity. Conclusions and Relevance Our study shows that patients with RMS and PIRA exhibit accelerated brain atrophy, especially in the cerebral cortex. These results point to the need to recognize the insidious manifestations of PIRA in clinical practice and to further evaluate treatment strategies for patients with PIRA in clinical trials.

We study a dynamic model of environmental protection in which the level of pollution is a state variable that strategically links policy making periods. Policymakers are forward looking but politically motivated: they have heterogeneous preferences and do not fully internalize the cost of pollution. This type of political economy model is often reduced to a "modified" planner's problem, and yields predictions that are qualitatively similar to a planner's constrained optimum, albeit with a bias: too much pollution in the steady state (or, in other applications, too little investment in public goods, too much public debt, etc.). We highlight conditions under which this reduction is not possible, and the dynamic time inconsistency generated by the political process is responsible for a new type of distortion. Under these conditions, there are equilibria in which, for a generic economy and generic initial conditions, the state evolves in complex cycles, or unpredictable chaotic dynamics. Depending on the fundamentals of the economy, these equilibria may generate ergodic distributions that consistently overshoot the planner's steady state of pollution, or that fluctuate around it.