Literatura académica sobre el tema "Disease progression score"

Background: Composite scores have been increasingly used in trials for Alzheimer’s disease (AD) to detect disease progression, such as the AD Composite Score (ADCOMS) in the lecanemab trial. Objective: To develop a new composite score to improve the prediction of outcome change. Methods: We proposed to develop a new composite score based on the statistical model in the ADCOMS, by removing duplicated sub-scales and adding the model selection in the partial least squares (PLS) regression. Results: The new AD composite Score with variable Selection (ADSS) includes 7 cognitive sub-scales. ADSS can increase the sensitivity to detect disease progression as compared to the existing total scores, which leads to smaller sample sizes using the ADSS in trial designs. Conclusions: ADSS can be utilized in AD trials to improve the success rate of drug development with a high sensitivity to detect disease progression in early stages.

Abstract Background The optimal endoscopic target in early Crohn’s disease (CD) that limits long-term disease complications is unknown. Methods We analysed medical records from patients who had follow-up data since the end of CALM. Patients with Crohn’s disease endoscopic index of severity (CDEIS) scores at the end of CALM were included. The primary outcome was a composite of major adverse outcomes reflecting CD progression: new internal fistula/abscess, stricture, perianal fistula/abscess, CD hospitalisation, or CD surgery since the end of CALM. We compared median CDEIS and per cent improvement from baseline CDEIS. Youden index analysis was used to identify optimal CDEIS cut-off score associated with CD progression. Kaplan–Meier and Cox regression methods were used to compare rates of progression by different CDEIS targets. Multivariable models were adjusted for age, prior surgery, and stricturing behaviour. Results 110 patients with median age 28 (IQR 22–38) years, disease duration 0.2 (0.1–0.5) years, and median follow up of 3.1 (1.9–4.4) years were included. Eleven per cent had a history of stricture, 5.5% history of surgery, and 52% were originally in the tight control arm of the CALM study. Median CDEIS score at end of CALM was 3 (0–5.4) and 32 (29%) patients had disease progression. Baseline median CDEIS score was similar between those with and without progression [10.9 (7.5–15.5) vs. 11.9 (8–17.5)]. Median CDEIS score at the end of CALM was higher among those with progression [1.3 (0–5.1) vs. 4.9 (3–9.1), p < 0.001)]. Patients within higher quartiles of CDEIS score had higher rates of progression over time (Figure 1). Patients without disease progression had a greater median decrease in CDEIS score from baseline to end of CALM [90% (60–100%) vs. 50% (30–80%), p < 0.001]. The optimal CDEIS score cut-off was 2 with sensitivity 84%, specificity 60% and NPV 90% for progression. Patients with CDEIS ≤ 2 had less progression over time compared with patients with > 50% improvement from baseline CDEIS (not reaching CDEIS ≤ 2) and those not meeting either endpoint (Figure 2). On adjusted analysis, CDEIS score ≤ 2 was associated with a decreased risk of progression (aHR 0.23, 95% CI 0.09–0.56). Conclusion In early CD, a CDEIS score ≤ 2 is optimal cut-off associated with a lower risk of disease progression.

ObjectiveTo assess the ability of functional measures to detect disease progression in dysferlinopathy over 6 months and 1 year.MethodsOne hundred ninety-three patients with dysferlinopathy were recruited to the Jain Foundation's International Clinical Outcome Study for Dysferlinopathy. Baseline, 6-month, and 1-year assessments included adapted North Star Ambulatory Assessment (a-NSAA), Motor Function Measure (MFM-20), timed function tests, 6-minute walk test (6MWT), Brooke scale, Jebsen test, manual muscle testing, and hand-held dynamometry. Patients also completed the ACTIVLIM questionnaire. Change in each measure over 6 months and 1 year was calculated and compared between disease severity (ambulant [mild, moderate, or severe based on a-NSAA score] or nonambulant [unable to complete a 10-meter walk]) and clinical diagnosis.ResultsThe functional a-NSAA test was the most sensitive to deterioration for ambulant patients overall. The a-NSAA score was the most sensitive test in the mild and moderate groups, while the 6MWT was most sensitive in the severe group. The 10-meter walk test was the only test showing significant change across all ambulant severity groups. In nonambulant patients, the MFM domain 3, wrist flexion strength, and pinch grip were most sensitive. Progression rates did not differ by clinical diagnosis. Power calculations determined that 46 moderately affected patients are required to determine clinical effectiveness for a hypothetical 1-year clinical trial based on the a-NSAA as a clinical endpoint.ConclusionCertain functional outcome measures can detect changes over 6 months and 1 year in dysferlinopathy and potentially be useful in monitoring progression in clinical trials.ClinicalTrials.gov identifier:NCT01676077.

Background and objectivesAt least 20 susceptibility loci of IgA nephropathy have been identified by genome-wide association studies to date. Whether these loci were associated with disease progression is unclear.Design, setting, participants, & measurementsWe enrolled 613 adult patients with IgA nephropathy for a follow-up of ≥12 months. All 20 IgA nephropathy susceptibility loci were selected and their tag single nucleotide polymorphisms (SNPs) were genotyped. After strict quality control, 16 SNPs and 517 patients with IgA nephropathy were eligible for subsequent analysis. Progression was defined as ESKD or 50% decrease in eGFR. A stepwise Cox regression analysis of all SNPs on Akaike information criterion was performed to select the best model.ResultsA four-SNP model, rs11150612 (ITGAM-ITGAX), rs7634389 (ST6GAL1), rs2412971 (HORMAD2), and rs2856717 (HLA-DQ/DR), was selected as the best predictive model. The genetic risk score calculated on the basis of the four SNPs was independently associated with disease progression before (hazard ratio [HR], 1.65; 95% confidence interval [95% CI], 1.29 to 2.12) and after adjustment by a recently reported clinical model (HR, 1.29; 95% CI, 1.03 to 1.62) or clinical–pathologic model (HR, 1.35; 95% CI, 1.03 to 1.77). Compared with low genetic risk, patients with middle genetic risk had a 2.12-fold (95% CI, 1.33 to 3.40) increase of progression risk, whereas patients with high genetic risk had 3.61-fold (95% CI, 2.00 to 6.52) progression risk increase. In addition, incorporation of genetic risk score could potentially increase discrimination of the clinical model (c-statistic increase from 0.83 to 0.86) or the clinical–pathologic model (c-statistic increase from 0.82 to 0.85) in predicting 5-year progression risk.ConclusionsThe four-SNP genetic risk score was independently associated with IgA nephropathy progression and could enhance the performance of clinical and clinical–pathologic risk models.

IntroductionNew statistical methodology, known as progression models for repeated measures (PMRM), can estimate the slowing of progression (percentage slowing or time delay) of Alzheimer’s disease from trial data on disease-modifying therapies. We compared the PMRM methodology with mixed models for repeated measures (MMRM) and Cox time-to-event analysis on simulated trial data with respect to their power and interpretability of estimates.MethodsTwo novel models were included: PMRM (estimating slowing of progression and allowing different rates across visits) and proportional-slowing PMRM. Clinical Dementia Rating (CDR) Sum of Boxes score and progression to dementia as assessed by CDR global score were the primary outcomes for MMRM/PMRM and the Cox model, respectively. Subject-level placebo arm trajectories were jointly simulated based on estimated CDR mean trajectories and joint temporal correlation structure of 538 amyloid-positive patients with mild cognitive impairment who met typical disease-modifying trial inclusion criteria from the Alzheimer’s Disease Neuroimaging Initiative study. Active arm trajectories were simulated to show an average 20 percent slowing of disease progression, compared with placebo, at each visit. We conducted 1,000 simulations across multiple scenarios, varying the number of patients per arm (200 to 700) and clinical trial duration (18 to 36 months).ResultsThe power of PMRM models was greater than that of MMRM, and much greater than that of the Cox model whose power never exceeded 45 percent. PMRM models accurately estimated the underlying treatment effect (median 20% slowed progression, which translated to a delay in progression of 5 and 7 months at trial durations of 24 and 36 months, respectively), unlike quantifications of the MMRM (median estimated 25% reduction in decline), and the Cox model (median estimated hazard ratio of 0.9).ConclusionsFor disease-modifying therapies, PMRM estimates may have a more intuitive clinical interpretation in terms of delayed progression than MMRM or Cox models and enable a description of the amount of time spent in less severe disease stages. Among all the methods studied, PMRM offered the best combination of interpretability and power.

The severity of Parkinson’s disease (PD) is developed by multifactorial factors. Falls can worsen disease severity. We previously found that frontal assessment battery (FAB) score was associated with a higher risk of future falls. This eight-year follow-up study aimed to verify whether factors including low FAB score can be the risk of PD progression based on the Hoehn and Yahr scale. In total, 95 patients were initially enrolled in this research and 45 were included in the final follow-up. Then, the cohort was classified into patients with and without disease progression, defined by upgrade of Hoehn-Yahr stage. Differences in clinical characteristics between patients with disease progression and those without were evaluated using the Mann–Whitney U test. Eighteen independent variables were evaluated via a univariate logistic regression analysis. Of the 45 patients enrolled, 32 had disease progression and 13 had no progression. Age (p = 0.033), BFI score (p = 0.003), Zung self-rating depression (p = 0.011), and anxiety scale (p = 0.026) were significantly increased in patients who had disease progression than those with no disease progression. On multivariate logistic regression analysis, brief fatigue inventory (BFI) score (OR = 1.048, p = 0.045, 95% CI = 1.001–1.098) was significantly related to disease progression. All BFI subscores related to general fatigue. Fatigue could predict the progression of motor dysfunction severity over a longitudinal duration in patients with PD with disease progression, having declining physical and mental fatigue.

This thesis describes the development of an objective motor score (OMS) of Parkinson's disease that utilizes the Quantitative Motor Assessment Tool (QMAT) developed through efforts by the Intel Corporation and the Kinetics Foundation. Parkinson's disease (PD) is a movement disorder which is a member of a group of neurodegenerative diseases marked by the depletion or impairment of dopamine-producing cells in the brain. Since PD is chronic and degenerative, treatments are intended to either improve the quality of life for sufferers by superficially treating symptoms or slow and ultimately reverse the progression of the disease. No blood test or biomarker exists, so current assessment of the disease relies on a subjective tool called the Unified Parkinson's disease rating scale (UPDRS) which is a coarse scale that requires costly clinical administration and is subject to rater bias. The objective motor score described in this thesis exhibits excellent clinimetric properties, having demonstrated usability, validity, reliability, and responsiveness. It was calibrated to the motor section of the UPDRS, but in addition to high correlation with the motor UPDRS, it demonstrated an excellent ability to track deep brain stimulation treatment levels and to detect improvement in motor function of subjects due to dopaminergic treatment. With an excellent intraclass correlation coefficient, the OMS is a reliable measure and due to the objective nature of the test, it does not suffer from rater bias. Though these results come from the development phase, they suggest that confirmatory studies will firmly establish the excellent properties of the OMS. While further studies are in motion to improve upon the sensitivity of the OMS by exploring metrics of voice recordings and paced tapping tests, the OMS presented here is a complete and usable tool for assessing the severity of PD-related symptoms. In conjunction with the QMAT, it is ready to be used in clinical trials, clinical practice, and even in the homes of patients who suffer from PD. This makes it an invaluable tool that could begin to replace the UPDRS for use in PD research, reducing costs and confounding factors in studies as well as extending their capabilities into the home.

La démence frontotemporale (DFT) représente le deuxième type de démence le plus fréquent chez les adultes de moins de 65 ans. Il n’existe aucun traitement capable de guérir cette maladie. Dans ce contexte, il est essentiel d’identifier des biomarqueurs capables d’évaluer la progression de la maladie. Cette thèse a deux objectifs. Premièrement, analyser les profils d’expression des microARNs circulants prélevés dans le plasma sanguin de participants, afin d’identifier si l’expression de certains microARNs est corrélée au statut mutationnel et à la progression de la maladie. Deuxièmement, proposer des méthodes pour intégrer des données transversales de type microARN et de neuroimagerie pour estimer la progression de la maladie. Nous avons mené trois études. D’abord, nous avons analysé des échantillons de plasma provenant de porteurs d’une expansion dans le gène C9orf72. Ensuite, nous avons testé toutes les signatures de microARNs identifiées dans la littérature comme biomarqueurs potentiels de la DFT ou de la sclérose latérale amyotrophique (SLA), dans deux cohortes indépendantes. Enfin, dans notre troisième étude, nous avons proposé une nouvelle méthode, utilisant un autoencodeur variationnel multimodal supervisé, qui estime à partir d’échantillons de petite taille un score de progression de la maladie en fonction de données transversales d’expression de microARNs et de neuroimagerie. Les travaux menés dans cette thèse interdisciplinaire ont montré qu’il est possible d’utiliser des biomarqueurs non invasifs, tels que les microARNs circulants et l’imagerie par résonance magnétique, pour évaluer la progression de maladies neurodégénératives rares telles que la DFT et la SLA
Frontotemporal dementia (FTD) represents the second most common type of dementia in adults under the age of 65. Currently, there are no treatments that can cure this condition. In this context, it is essential that biomarkers capable of assessing disease progression are identified. This thesis has two objectives. First, to analyze the expression patterns of microRNAs taken from blood samples of patients, asymptomatic individuals who have certain genetic mutations causing FTD, and controls, to identify whether the expressions of some microRNAs correlate with mutation status and disease progression. Second, this work aims at proposing methods for integrating cross-sectional data from microRNAs and neuroimaging to estimate disease progression. We conducted three studies. Initially, we focused on plasma samples from C9orf72 expansion carriers. We identified four microRNAs whose expressions correlated with the clinical status of the participants. Next, we tested all microRNA signatures identified in the literature as potential biomarkers of FTD or amyotrophic lateral sclerosis (ALS), in two groups of individuals. Finally, in our third work, we proposed a new approach, using a supervised multimodal variational autoencoder, that estimates a disease progression score from cross-sectional microRNA expression and neuroimaging datasets with small sample sizes. The work conducted in this interdisciplinary thesis showed that it is possible to use non-invasive biomarkers, such as circulating microRNAs and magnetic resonance imaging, to assess the progression of rare neurodegenerative diseases such as FTD and ALS

Introduzione: La Sclerosi Laterale Amiotrofica (SLA) è una malattia del motoneurone devastante e ancora incurabile. Le cause della SLA sono sconosciute, ma fattori nutrizionali e di stile di vita come il consumo di caffè e tè, il consumo di alcol e il fumo di sigaretta possono influire sul tasso di progressione della malattia. Tuttavia, i metodi ei risultati della ricerca attualmente utilizzati (valutazione puntuale e non cumulativa di quantità/frequenza) non valutano adeguatamente l'effetto del consumo di caffè e tè, dell'assunzione di alcol e del fumo di sigaretta. Questo è uno dei motivi per cui l'analisi dei fattori di stile di vita nutrizionale per le persone con SLA in diversi studi a volte ha risultati contrastanti. Questo studio ha utilizzato un nuovo approccio per valutare il ruolo dei fattori di rischio potenzialmente modificabili sulla progressione della SLA. Questo studio ha utilizzato il consumo cumulativo di caffè e tè nel corso della vita, il consumo di alcol e i carichi di fumo di sigaretta. Il consumo a vita di caffè e tè, il consumo di alcol e il fumo di sigaretta vengono applicati nella pratica di oncologi, dietologi e altre aree della medicina, ma non nella pratica neurologica. Questi valori ci consentono di stimare l'effetto cumulativo del consumo di caffè e tè, del consumo di alcol e del fumo di sigaretta sul decorso della malattia, anche per dosi da basse a moderate. Uno studio simile è stato condotto per la sclerosi multipla, un'altra malattia autoimmune e degenerativa del sistema nervoso centrale. Se alcuni fattori dello stile di vita potenzialmente modificabili potrebbero avere un impatto sulla progressione della SM, potrebbero essere suggeriti possibili interventi e potrebbero essere scoperti possibili indizi per comprendere la patogenesi della progressione. Obiettivi: Questa tesi di dottorato mirava a valutare il ruolo del consumo di caffè e tè, del consumo di alcol e del fumo di sigaretta come fattori di rischio potenzialmente modificabili sul tasso di progressione della SLA. Ulteriori obiettivi erano valutare un possibile ruolo del consumo di caffè e tè per tutta la vita sulla progressione e sulla gravità della sclerosi multipla e la loro possibile interazione con il fumo e l'uso di alcol; per indagare se il consumo di caffè e tè interagisce con i geni di rischio di suscettibilità HLA nel determinare la progressione della SM, come studio comparativo. Soggetti e metodi: In questo studio multicentrico trasversale sono stati reclutati 241 pazienti, 96 femmine e 145 maschi; l'età media all'esordio era 59,9±11,8 anni. Secondo i criteri di El Escorial, 74 erano SLA accertata, 77 probabili, 55 possibili e 35 sospettate; 187 pazienti hanno avuto esordio spinale e 54 bulbare. I pazienti sono stati classificati in tre gruppi, secondo ΔFS (derivato dal punteggio ALS Functional Rating Scale-Revised e dalla durata della malattia dall'esordio): progressori lenti (81), intermedi (80) e veloci (80). Il disegno dello studio comparativo “The Impact of Lifetime Coffee and Tea Loads on Multiple Sclerosis Severity” era uno studio trasversale, a 208 pazienti ammessi consecutivamente al Dipartimento di Neurologia è stato chiesto di completare il “Questionario sullo stile di vita” (parte del Progetto Europeo di Indagine Prospettica su Cancro e Nutrizione). Una stima dell'intensità del consumo (bevande/giorno) è stata calcolata come somma ponderata del numero medio di bicchieri standard bevuti al giorno a diverse età. Una misura del carico di vita dell'esposizione è stata espressa in termini di tazze-anno. La gravità della malattia è stata stimata dal Multiple Sclerosis Severity Score (MSSS). Risultati: Gli attuali consumatori di caffè erano 179 (74,3%), 34 (14,1%) non erano consumatori, 22 (9,1%) ex consumatori, mentre sei (2,5%) consumavano solo caffè decaffeinato. Il log-ΔFS era debolmente correlato con la durata del consumo di caffè (p=0,034), ma non con il numero di tazze all'anno (p=0,932). Gli attuali consumatori di tè erano 101 (41,9%), 6 (2,5%) erano ex consumatori e 134 (55,6%) non consumatori. Tra 107 consumatori attuali ed ex, 27 (25,2%) hanno consumato solo tè verde, 51 (47,7%) altri tipi di tè e 29 (27,1%) entrambi. Il log-ΔFS era debolmente correlato con la durata del consumo di altri tipi di tè (p=0,028), ma non con il numero di tazze all'anno. I fumatori attuali erano 44 (18,3%), 187 (77,6%) non fumatori e 10 (4,1%) ex fumatori. L'età di esordio della SLA era più bassa nei fumatori attuali rispetto ai non fumatori e il ΔFS era lieve, anche se non significativamente, più alto per i fumatori di > 14 sigarette/giorno. Gli attuali bevitori di alcol erano 147 (61,0%), 5 pazienti (2,1%) erano ex bevitori e 89 (36,9%) non bevitori. Il log-ΔFS era debolmente correlato con la durata del consumo di alcol (p=0,038), ma non con il numero di drink al giorno o gli anni di consumo. Nello studio "The Impact of Lifetime Coffee and Tea Loads on Multiple Sclerosis Severity" non abbiamo trovato alcun trend con la quantità di caffè bevuto sia per l'intensità che per le esposizioni cumulative. L'analisi multivariata non ha mostrato alcuna associazione tra consumo di caffè e tè (tazze/giorno) e MSSS. Per quanto riguarda il consumo di tè, non abbiamo trovato alcuna correlazione con la gravità della sclerosi multipla, misurata con MSSS, età di esordio o forma clinica. Rispetto ai non consumatori, gli OR erano 1,27 per i bevitori di caffè e 0,68 per i bevitori di tè. Conclusioni: lo studio non supporta l'ipotesi che il consumo di caffè o tè sia associato al tasso di progressione della SLA. I risultati di questo studio multicentrico trasversale evidenziano un possibile ruolo minore del fumo, ma non del consumo di alcol nel peggioramento della progressione della malattia. I risultati dello studio comparativo "The Impact of Lifetime Coffee and Tea Loads on Multiple Sclerosis Severity" non supportano l'ipotesi che l'assunzione di caffè o tè sia associata a una diversa gravità o progressione della SM, contrariamente ad altre malattie neurodegenerative. Tuttavia, non possiamo escludere un possibile effetto di dosi più elevate di caffè o tè o un effetto su un sottogruppo di pazienti.
Introduction: Amyotrophic Lateral Sclerosis (ALS) is a devastating and still untreatable motor neuron disease. The causes of ALS are unknown, but nutritional and lifestyle factors such as coffee and tea consumption, alcohol drinking, and cigarette smoking may impact the rate of disease progression. However, the currently used research methods and outcomes (punctual and not cumulative evaluation of quantity/frequency) do not adequately assess the effect of coffee and tea consumption, and alcohol intake, and cigarette smoking. This is one of the reasons why the nutritional lifestyle factors analysis for people with ALS in different studies sometimes has conflicting results. This study used a new approach to assess the role of potentially modifiable risk factors on the ALS progression. This study used cumulative lifetime coffee and tea consumption, alcohol drinking, and cigarette smoking loads. Lifetime coffee and tea consumption, alcohol drinking, and cigarette smoking loads are applied in the practice of oncologists, dieticians, and other areas of medicine, but not in neurological practice. These values allow us to estimate the cumulative effect of coffee and tea consumption, alcohol drinking, and cigarette smoking on disease course, even for low to moderate doses. A similar study was done for Multiple Sclerosis, another autoimmune and degenerative disease of the central nervous system. If some potentially modifiable lifestyle factors could impact on MS progression, possible interventions may be suggested, and possible clues to understand the pathogenesis of progression may be uncovered. Objectives: This PhD thesis aimed to evaluate the role of coffee and tea consumption, alcohol drinking, and cigarette smoking as potentially modifiable risk factors on ALS progression rate. Additional goals were to assess a possible role of lifetime coffee and tea consumption on Multiple Sclerosis progression and severity and their possible interaction with smoking and alcohol use; to investigate whether coffee and tea consumption interacts with HLA susceptibility risk genes in determining MS progression, as a comparative study. Subjects and Methods: In this multicentre cross-sectional study were recruited 241 patients, 96 females and 145 males; the mean age at onset was 59.9±11.8 years. According to El Escorial criteria, 74 were definite ALS, 77 probable, 55 possible, and 35 suspected; 187 patients had spinal onset and 54 bulbar. The patients were categorized into three groups, according to ΔFS (derived from ALS Functional Rating Scale-Revised score and disease duration from onset): slow (81), intermediate (80), and fast progressors (80). The design of the comparative study “The Impact of Lifetime Coffee and Tea Loads on Multiple Sclerosis Severity” was a cross-sectional study, 208 patients consecutively admitted to the Department of Neurology were asked to complete the “Questionnaire of Lifestyle” (part of the European Prospective Investigation into Cancer and Nutrition project). An estimation of the intensity of drinking (drinks/day) was calculated as the weighted sum of the mean number of standard cups drunk per day at different ages. A measure of lifetime load of the exposure was was expressed in terms of cups-year. Disease severity was estimated by the Multiple Sclerosis Severity Score (MSSS). Results: Current coffee consumers were 179 (74.3%), 34 (14.1%) were non-consumers, 22 (9.1%) former consumers, whereas six (2.5%) consumed decaffeinate coffee only. The log-ΔFS was weakly correlated with the duration of coffee consumption (p=0.034), but not with the number of cups-year (p=0.932). Current tea consumers were 101 (41.9%), 6 (2.5%) were former-consumers, and 134 (55.6%) non-consumers. Among 107 current and former consumers, 27 (25.2%) consumed only green tea, 51 (47.7%) other types of tea, and 29 (27.1%) both. The log-ΔFS was weakly correlated with the consumption duration of other tea types (p=0.028), but not with the number of cups-year. Current smokers were 44 (18.3%), 187 (77.6%) were non-smokers, and 10 (4.1%) former smokers. Age of ALS onset was lower in current smokers than non-smokers, and the ΔFS was slight, although not significantly, higher for smokers of >14 cigarettes/day. Current alcohol drinkers were 147 (61.0%), 5 patients (2.1%) were former-drinkers, and 89 (36.9%) non-drinkers. The log-ΔFS was weakly correlated with the duration of alcohol consumption (p=0.038), but not with the number of drinks-day or the drink-years. In the study “The Impact of Lifetime Coffee and Tea Loads on Multiple Sclerosis Severity” we did not find any trend with the quantity of coffee drunk for both the intensity and cumulative exposures. The multivariable analysis did not show any association between coffee and tea consumption (cups/day) and MSSS. Regarding tea consumption, we found no correlation with Multiple Sclerosis severity, measured with the MSSS, age at onset, or clinical form. Compared to non-consumers, the ORs were 1.27 for coffee drinkers, and 0.68 for tea drinkers. Conclusions: The study does not support the hypothesis that coffee or tea consumption is associated with ALS progression rate. The results of this cross-sectional multicenter study evidence a possible minor role for smoking, but not for alcohol drinking in worsening disease progression. The results of the comparative study “The Impact of Lifetime Coffee and Tea Loads on Multiple Sclerosis Severity” do not support the hypothesis that coffee or tea intake is associated with a different severity or progression of MS, contrarily to other neurodegenerative diseases. However, we cannot exclude a possible effect of higher doses of coffee or tea or an effect on a subgroup of patients.

Pharmacodynamic processes and disease progression are increasingly characterized with pharmacometric models. However, modelling options for discrete-type responses remain limited, although these response variables are commonly encountered clinical endpoints. Types of data defined as discrete data are generally ordinal, e.g. symptom severity, count, i.e. event frequency, and time-to-event, i.e. event occurrence. Underlying assumptions accompanying discrete data models need investigation and possibly adaptations in order to expand their use. Moreover, because these models are highly non-linear, estimation with linearization-based maximum likelihood methods may be biased. The aim of this thesis was to explore pharmacometric methods and novel models for discrete data through (i) the investigation of benefits of treating discrete data with different modelling approaches, (ii) evaluations of the performance of several estimation methods for discrete models, and (iii) the development of novel models for the handling of complex discrete data recorded during (pre-)clinical studies. A simulation study indicated that approaches such as a truncated Poisson model and a logit-transformed continuous model were adequate for treating ordinal data ranked on a 0-10 scale. Features that handled serial correlation and underdispersion were developed for the models to subsequently fit real pain scores. The performance of nine estimation methods was studied for dose-response continuous models. Other types of serially correlated count models were studied for the analysis of overdispersed data represented by the number of epilepsy seizures per day. For these types of models, the commonly used Laplace estimation method presented a bias, whereas the adaptive Gaussian quadrature method did not. Count models were also compared to repeated time-to-event models when the exact time of gastroesophageal symptom occurrence was known. Two new model structures handling repeated time-to-categorical events, i.e. events with an ordinal severity aspect, were introduced. Laplace and two expectation-maximisation estimation methods were found to be performing well for frequent repeated time-to-event models. In conclusion, this thesis presents approaches, estimation methods, and diagnostics adapted for treating discrete data. Novel models and diagnostics were developed when lacking and applied to biological observations.

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases (dementia) among the aged population. In this paper, we propose a unique machine learning-based framework to discriminate subjects with the first classification of AD. The training data, preprocessing, feature selection, and classifiers all affect the output of machine-learning-based methods for AD classification. This chapter discusses a new comprehensive scheme called Progression Prediction and Classification of Alzheimer’s Disease using MRI (PPC-AD-MRI). Considering the data gathered with T1-weighted MRI clinical OASIS progressive information, the consequences have been evaluated in terms of precision, recall, F1 score, and accuracy. This recommended model with enhanced accuracy confirms its suitability for use in AD classification. Other methods can also be used successfully in the disease’s early detection and diagnosis in medicine and healthcare.

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease associated with a high degree of morbidity and mortality in its more advanced stages. Antifibrotic therapies are generally effective in delaying the progression of disease; however, some patients continue to progress despite treatment. Lung transplantation is a surgical option for selected patients with advanced pulmonary fibrosis that increases their overall survival and quality of life. Changes in the Lung Allocation Score (LAS) in 2005 have resulted in increased transplants and decreased waitlist mortality in this population. Indications for transplant evaluation and listing include the clinical progression of the disease and related mortality risk ≥50% at 2 years without a transplant. Patients with clinically rapid deterioration or acute flares needing hospitalization can be bridged to transplant on extracorporeal support while remaining ambulatory and free from mechanical ventilation.

Exposures to fine particulate matter PM2.5 and ozone O3 are associated with Alzheimer’s disease (AD) risk. Mexico City residents have lifetime exposures to PM2.5 and O3 above annual USEPA standards and their brains contain high redox, combustion, and friction-derived magnetite nanoparticles. AD pathological changes with subcortical pre-tangle stages in infancy and cortical tau pre-tangles, NFT Stages I-II, and amyloid phases 1–2 are identified by the 2nd decade. Given their AD continuum, a reliable identification of cognitive impairment is of utmost importance. The Montreal Cognitive Assessment (MoCA) was administered to 517 urbanites, age 21.60 ± 5.88 years, with 13.69 ± 1.28 formal education years, in Mexican PM2.5 polluted cities. MoCA score was 23.92 ± 2.82, and 24.7% and 30.3% scored ≤24 and ≤22, respectively (MCI ≤ 24, AD ≤ 22). Cognitive deficits progressively targeted Visuospatial, Executive, Language, and Memory domains, body mass index (BMI) impacting total scores negatively (p = 0.0008), aging driving down Executive, Visuospatial, and Language index scores (p < 0.0001, 0.0037, and 0.0045), and males performing better in Executive tasks. Average age for AD MoCA scores was 22.38 ± 7.7 years. Residency in polluted cities is associated with progression of multi-domain cognitive impairment affecting 55% of Mexican seemingly healthy youth. Normal BMI ought to be a neuroprotection goal. MoCA provides guidance for further mandatory neuropsychological testing in young populations. Identifying and lowering key neurotoxicants impacting neural risk trajectories in the developing brain and monitoring cognitive performance would greatly facilitate multidisciplinary early diagnosis and prevention of AD in high risk young populations. Cognitive deficits hinder development of those representing the force moving the country in future years.

The prevalence of non-alcoholic fatty liver disease (NAFLD) has increased in the last years up to 25% in the adult population. This disease includes a large spectrum of disorders, from simple fatty liver disease to cirrhosis and Hepatocellular Carcinoma (HCC), and they are related to chronic metabolic conditions. NAFLD is characterized by the presence of at least 5% of hepatic steatosis without evidence of hepatocellular injury. The diagnosis of this disease should be of exclusion and focused on its progression, treatment, and identification of the prognosis. The European Association for the Study of the Liver (EASL), the National Institute for Health and Care Excellence (NICE), the Italian Association for the Study of the Liver (AISF), and the American Association for the Study of the Liver (AASLD), published their Clinical Guidelines that have identified the criteria for the diagnosis of NAFLD, several, using imaging or histological diagnostic methods, although they imply a different approach and screening. The Fatty Liver Index and the NAFLD Liver Fat Score are used by 3 out of 5 Guidelines and they are easily calculated using blood tests and clinical information. Other non-invasive scales for NAFLD are the NAFLD fibrosis score (NFS), Fib-4, AST/ALT ratio index; also the ELF panel, Fibrometer, Fibrotest, Hepascore; and some imaging techniques that include transient elastography, magnetic resonance elastography (MRE), and shear wave elastography. Finally, proteomic’s and glycomic’s technologic biomarkers are currently under investigation and recent use, such as Cytokeratin 18 and Sirtuin 1. Still, liver biopsy remains the gold standard to distinguish between steatohepatitis and simple steatosis, using the histological classification and staging scoring systems of NAFLD Activity Score (NAS) and the Steatosis Activity Fibrosis (SAF), to evaluate the disease’s activity.

Alzheimer's disease (AD) is a neurodegenerative disease affecting an estimated 6.5 million Americans and is expected to double in the next thirty years. The only treatments that patients can receive for the disease are to slow the disease progression, which is more effective if the disease is diagnosed early. A popular form of early diagnosis used by doctors is to analyze the brain's electroencephalogram (EEG). EEG measures electrical activity by placing electrodes on the scalp or surgically placing electrodes inside the brain. Given the electrical activity measurements of the brain, high and low-frequency signals are traditionally filtered during preprocessing as previously believed to be noise or irrelevant information. However, we believe this filtered data contains valuable information that can help doctors diagnose Alzheimer's patients earlier. We use novel machine learning models, such as transformers, and additionally use metrics such as accuracy, precision, recall, and F1 score to evaluate the model performance. Our methods result in higher accuracy compared to current machine learning methods. Our best-performing transformer resulted in an accuracy of 0.846, while the best-performing non-transformer model resulted in an accuracy of 0.564.

Juvenile scleroderma syndromes, including the systemic and the localized varieties, represent the third most frequent chronic rheumatic conditions in paediatric rheumatology after juvenile idiopathic arthritis and systemic lupus erythematosus. Juvenile systemic sclerosis (JSSc) has a variety of clinical manifestations, sometimes different from the adult form. Children show a significantly less frequent involvement of all organs, except for arthritis and myositis which are slightly more common than in adults. Indeed, the overall clinical outcome is better. In most JSSc cases with fatal course, the disease progression is rapid due to the early involvement of internal organs. The recently proposed classification for JSSc enables earlier and more definite diagnoses and provides clear criteria to standardize the conduct of clinical trials. Juvenile localized scleroderma (JLS), also known as morphoea, is much more frequent than JSSc. It comprises a group of distinct conditions which involve the skin and subcutaneous tissues. They range from very small plaques of fibrosis involving only the skin, to diseases which may cause significant functional and cosmetic deformity, with a variety of extracutaneous features. Monitoring of JLS includes semiquantitative clinical scoring methods, a computerized skin score, infrared thermography, and high-frequency ultrasound. Treatment varies from topical glucocorticoids, calcipotriene, or phototherapy, as in circumscribed morphoea, to systemic drugs when there is a significant risk for disability, as in linear scleroderma and generalized or pansclerotic morphoea. A recent randomized controlled trial has confirmed the efficacy of methotrexate in these conditions or mycophenolate mofetil in refractory cases.

The present study shows first attempts to automatically classify oncology treatment responses on the basis of the textual conclusion sections of radiology reports according to the RECIST classification. After a robust and extended manual annotation of 543 conclusion sections (5-to-50-word long), and after the training of several machine learning techniques (from traditional machine learning to deep learning), the best results show an accuracy score of 0.90 for a two-class classification (non-progressive vs. progressive disease) and of 0.82 for a four-class classification (complete response, partial response, stable disease, progressive disease) both with Logistic Regression approach. Some innovative solutions are further suggested to improve these scores in the future.

Diabetes mellitus is a serious and a rapidly growing public health problem that affects millions of people. It usually co-exists with other medical conditions, and its prevalence is increasing year by year reaching epidemic proportions. Diabetes is fast gaining the status of a potential epidemic in India. Patients’ adherence to their anti-diabetic medications is a critical and important factor to prevent serious undesirable complications and to reduce the health care resource utilizations. This study focuses on assessing the risk factors, evaluating disease progression, improving management and medication adherence through patient counselling. A prospective observational study was conducted in rural area of Mangalagiri for 6 months August –January(2018-19).Subjects satisfying study criteria are enrolled by obtaining signed inform consent form. Subject information was gathered by data collection form containing demographic details, prescribed medications and were secured. Each patient was counselled in every review. Morisky medication adherence scale-8 was filled by every subject before and after counselling. Medication adherence score was calculated by MMAS-8. Study identified that patient counselling was successful with significant changes in life style modifications, dietary patterns, decreased alcohol consumption. Medication adherence was also improved which was low at the commencement of the study. In this study there was a significant improvement in quality of health education and adherence to medication in diabetics taking part in an educational session focusing on the importance of anti-diabetes medication and adherence to it.

The therapeutic armamentarium available for treatment of rheumatoid arthritis (RA) has changed significantly over the past 30 years, transforming the therapeutic landscape and prognosis for a substantial proportion of patients with RA. Combination therapies represent an important therapeutic paradigm for management of rheumatoid arthritis. The rationale for combination therapies is clear and demonstrated to bring treatment benefit to patients achieving lower disease activity scores and reduced radiologic progression according to ‘treat-to-target’ principles. A rigorous evidence-based debate is required involving not only parameters related to disease activity scores and radiologic progression, but related to the cost-effectiveness analysis of using many of these newer agents compared to older csDMARDs. This chapter addresses the evidence related to the utilization of combination strategies for the management of RA as compared to monotherapy.

Background: The Mini Linguistic State Examination (MLSE) was developed in British English as a 20-minutes Primary Progressive Aphasia (PPA) screening test (Garrard, P. et al, 2012). Its tasks are: picture naming; listening comprehension of sentence; comprehension of single word; word repetition; sentence repetition; reading; writing; semantic association; and figure description. The MLSE was later translated to Italian and Spanish (Patel, N. et al, 2020) due to the following features: applicability by clinicians without expertise in language; sensitivity for diagnosis, distinction and progression of PPA subtypes; ability to identify features of atypical forms of PPA. Objective: Translation, cultural adaptation, standardization and validation of the MLSE English version to Brazilian Portuguese, allowing its application for PPA screening in the Brazilian population. Methods: Five controls were evalu- ated in order to verify tasks intelligibility of the first Brazilian Portuguese version of the MLSE. A control performed the test via telemedicine. The highest possible score was 100. Results: All controls were female. One subject was left-handed. Mean age was 50,4 (+- 12,94) years with mean schooling of 17 (+- 3,28) years. Mean Mini Mental State Examination score was 28,6 (+- 1,52), while mean MLSE score was 98,2 (+- 1,40). Conclusion: All MLSE tasks were intelligible to five individuals without aphasia. Subsequently more controls with different ranges of age and schooling will be evaluated for standardization.

Background: Visual atrophy scales from the medial temporal region are auxiliary biomarker methods in Alzheimer’s Disease(AD).They may correlated with progression from preclinical to clinical AD. Objective: We aimed to compare medial temporal lobe atrophy (MTA) and entorhinal cortex atrophy (ERICA) scales for magnetic resonance image as a useful tool for probable AD diagnosis and evaluate their accuracy, sensitivity and specificity, regarding clinical diagnosis and 11C-PIB-PET. Methods: 2 neurologists blinded to diagnosis classified 113 adults (over 65y) through MTA and ERICA scales and correlated with sociodemographic data, amyloid brain cortical burden through the 11C-PIB-PET and clinical cognitive status, divided into 30 cognitive unimpaired (CU) individuals, 52 MCI and 31 dementia compatible with AD (DCAD). Results: Inter-rater reliability of these atrophy scales was excellent (0.8- 1) by Cohen analysis. CU group had significantly lower MTA scores (median value 0) than ERICA (median value 1)for both hemispheres. 11C-PIB-PET was positive in 45% of the whole sample. In MCI and DCAD groups, ERICA depicted greater sensitivity and MTA greater specificity. Accuracy was under 70% for both scores in all clinical groups. Conclusion: Our study achieved a moderate sensitivity for ERICA score and could be a better screening tool for DCAD or MCI than MTA score. But, none of them could be considered a useful biomarker in preclinical AD.

Introduction: Inflammation underlies the pathogenesis of numerous neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). In ALS, the complement system has been implicated in the neuropathology of disease and disease progression. Pegcetacoplan, a subcutaneously administered C3 complement inhibitor, is being investigated in hematology, nephrology, and neurology. The current clinical study (NCT04579666) is investigating whether pegcetacoplan can improve survival and function in people diagnosed with apparent sporadic ALS. Objectives and Methodology: Evaluate the efficacy and safety of pegcetacoplan compared to placebo among people diagnosed with ALS in a global, multicenter, randomized, double-blind, placebo-controlled, phase 2 study. Approximately 228 patients diagnosed with apparent sporadic ALS, ≥18 years of age and with an ALS Functional Rating Scale-Revised (ALSFRS-R) score ≥30, slow vital capacity (SVC) ≥60% of the predicted value at screening, and with symptom onset within 72 weeks before screening, are eligible for enrollment. After screening, patients will be randomized 2:1 to treatment groups receiving either subcutaneous pegcetacoplan (1080 mg) or placebo twice weekly for a duration of 52 weeks. The primary efficacy endpoint is the difference in the Combined Assessment of Function and Survival (CAFS) ranked score at 52 weeks after treatment initiation. Additional, secondary functional efficacy (ALSFRS-R, percent SVC, muscle strength, quality of life, and caregiver burden) and safety endpoints will be analyzed at 52 weeks. After the placebo-controlled period, all patients will have the option to receive pegcetacoplan in an open-label period for an additional 52 weeks. Results: This ongoing study is currently enrolling participants. Conclusions: Results of this study will determine the role of complement and C3 inhibition in patients with ALS.