Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis

Multiple Sclerosis (MS) progresses at an unpredictable rate, but predictions on the disease course in each patient would be extremely useful to tailor therapy to the individual needs. We explore different machine learning (ML) approaches to predict whether a patient will shift from the initial Relapsing-Remitting (RR) to the Secondary Progressive (SP) form of the disease, using only “real world” data available in clinical routine. The clinical records of 1624 outpatients (207 in the SP phase) attending the MS service of Sant'Andrea hospital, Rome, Italy, were used. Predictions at 180, 360 or 720 days from the last visit were obtained considering either the data of the last available visit (Visit-Oriented setting), comparing four classical ML methods (Random Forest, Support Vector Machine, K-Nearest Neighbours and AdaBoost) or the whole clinical history of each patient (History-Oriented setting), using a Recurrent Neural Network model, specifically designed for historical data. Missing values were handled by removing either all clinical records presenting at least one missing parameter (Feature-saving approach) or the 3 clinical parameters which contained missing values (Record-saving approach). The performances of the classifiers were rated using common indicators, such as Recall (or Sensitivity) and Precision (or Positive predictive value). In the visit-oriented setting, the Record-saving approach yielded Recall values from 70% to 100%, but low Precision (5% to 10%), which however increased to 50% when considering only predictions for which the model returned a probability above a given “confidence threshold”. For the History-oriented setting, both indicators increased as prediction time lengthened, reaching values of 67% (Recall) and 42% (Precision) at 720 days. We show how “real world” data can be effectively used to forecast the evolution of MS, leading to high Recall values and propose innovative approaches to improve Precision towards clinically useful values

El museo como dispositivo de espectacularización de la naturaleza

La presente investigación se desarrolla desde el pensamiento del discurso y el dispositivo propuesto por Michael Foucault, adaptado para el estudio de espacios expositivos desarrollado por Susana Herrera Lima. Se discute el concepto de espectacularización desde el pensamiento de Guy Debord. Este estudio es una combinación de las propuestas del análisis crítico del discurso de Sigfried Jäger y la teoría fundamentada de Strauss y Corbin y se realizó con la participación de seis museos de Quintana Roo. En el trabajo se plantea al museo como un dispositivo de espectacularización que escenifica una verdad a partir de fragmentos discursivos y omisiones que determinan lo que es la naturaleza y dictan las maneras como se relaciona la sociedad con ella. De esta forma, el museo tiene la capacidad de legitimar una versión embellecida de la realidad natural que se presenta en otros medios de comunicación. A la par, es un dispositivo que puede hacer visibles los elementos que conforman el concepto de naturaleza e invisibilizar los que no la han de integrar. Los museos de Quintana Roo demostraron que en el fenómeno de espectacularización, el museo tiene una participación muy diversa. Algunos confirman los efectos discursivos del espectáculo, mientras que otros confrontan la hipótesis. En todos los casos se acepta que la espectacularización es una condición ontogénica del museo, pero cuyo papel en la lógica estratégica del discurso museográfico no es homogénea

Genetic and non-genetic risk factors for early-onset pancreatic cancer

Early-onset pancreatic cancer (EOPC) represents 5-10% of all pancreatic ductal adenocarcinoma (PDAC) cases, and the etiology of this form is poorly understood. It is not clear if established PDAC risk factors have the same relevance for younger patients. This study aims to identify genetic and non-genetic risk factors specific to EOPC.A genome-wide association study was performed, analysing 912 EOPC cases and 10 222 controls, divided into discovery and replication phases. Furthermore, the associations between a polygenic risk score (PRS), smoking, alcohol consumption, type 2 diabetes and PDAC risk were also assessed.Six novel SNPs were associated with EOPC risk in the discovery phase, but not in the replication phase. The PRS, smoking, and diabetes affected EOPC risk. The OR comparing current smokers to never-smokers was 2.92 (95% CI 1.69-5.04, P = 1.44 × 10-4). For diabetes, the corresponding OR was 14.95 (95% CI 3.41-65.50, P = 3.58 × 10-4).In conclusion, we did not identify novel genetic variants associated specifically with EOPC, and we found that established PDAC risk variants do not have a strong age-dependent effect. Furthermore, we add to the evidence pointing to the role of smoking and diabetes in EOPC

Persistent Megalocystic Ovary Following in Vitro Fertilization in a Postpartum Patient with Polycystic Ovarian Syndrome

SummaryObjectiveOvarian hyperstimulation syndrome (OHSS) is more severe when pregnancy occurs, as the developing pregnancy produces human chorionic gonadotropin, which stimulates the ovary's persistent growth. If no pregnancy occurs, the syndrome will typically resolve within 1 week. In a maintained pregnancy, slow resolution of symptoms usually occurs over 1-2 months.Case ReportA 31-year-old woman, gravida 2, para 1, aborta 1, with polycystic ovary syndrome underwent in vitro fertilization (IVF) with clomiphene citrate and follicle-stimulating hormone/gonadotropin releasing hormone-antagonist stimulation. During transvaginal oocyte retrieval, enlarged bilateral ovaries were noted. She had an episode of OHSS after IVF/embryo transfer, for which paracentesis was performed three times. Pregnancy was achieved. Throughout antenatal examinations, bilateral ovaries were enlarged. She delivered a healthy baby by cesarean section at term. However, 1 month after delivery, the bilateral ovary had not shrunk, and levels of tumor markers CA125 and CA199 were 50.84 and 41.34 U/mL, respectively. At laparotomy for suspected malignancy, both adnexae formed “kissing ovaries”, which were multinodulated with yellow serous fluid. Specimens from wedge resection submitted for frozen section showed a benign ovarian cyst. The final pathology report showed bilateral follicle cysts.ConclusionWith the increasing use of gonadotropins in the management of infertility, ovarian enlargement secondary to hyperstimulation is common. Generally, symptoms appear between the 6th and 13th weeks of pregnancy and disappear thereafter. The hyperstimulated ovary often subsides after the first trimester. This case is unusual as the megalocystic ovary persisted after delivery. To the best of our knowledge, we report the first case of enlarged bilateral ovaries persisting 2 months after delivery

Disease-Modifying Therapies and Coronavirus Disease 2019 Severity in Multiple Sclerosis

Objective: This study was undertaken to assess the impact of immunosuppressive and immunomodulatory therapies on the severity of coronavirus disease 2019 (COVID-19) in people with multiple sclerosis (PwMS). Methods: We retrospectively collected data of PwMS with suspected or confirmed COVID-19. All the patients had complete follow-up to death or recovery. Severe COVID-19 was defined by a 3-level variable: mild disease not requiring hospitalization versus pneumonia or hospitalization versus intensive care unit (ICU) admission or death. We evaluated baseline characteristics and MS therapies associated with severe COVID-19 by multivariate and propensity score (PS)-weighted ordinal logistic models. Sensitivity analyses were run to confirm the results. Results: Of 844 PwMS with suspected (n = 565) or confirmed (n = 279) COVID-19, 13 (1.54%) died; 11 of them were in a progressive MS phase, and 8 were without any therapy. Thirty-eight (4.5%) were admitted to an ICU; 99 (11.7%) had radiologically documented pneumonia; 96 (11.4%) were hospitalized. After adjusting for region, age, sex, progressive MS course, Expanded Disability Status Scale, disease duration, body mass index, comorbidities, and recent methylprednisolone use, therapy with an anti-CD20 agent (ocrelizumab or rituximab) was significantly associated (odds ratio [OR] = 2.37, 95% confidence interval [CI] = 1.18-4.74, p = 0.015) with increased risk of severe COVID-19. Recent use (<1 month) of methylprednisolone was also associated with a worse outcome (OR = 5.24, 95% CI = 2.20-12.53, p = 0.001). Results were confirmed by the PS-weighted analysis and by all the sensitivity analyses. Interpretation: This study showed an acceptable level of safety of therapies with a broad array of mechanisms of action. However, some specific elements of risk emerged. These will need to be considered while the COVID-19 pandemic persists

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score > 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p < 0.001), RR = 2.19 for ICU admission (p < 0.001), and RR = 2.43 for death (p < 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon

GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

Genetic determinants of telomere length and risk of pancreatic cancer: A PANDoRA study

Telomere deregulation is a hallmark of cancer. Telomere length measured in lymphocytes (LTL) has been shown to be a risk marker for several cancers. For pancreatic ductal adenocarcinoma (PDAC) consensus is lacking whether risk is associated with long or short telomeres. Mendelian randomization approaches have shown that a score built from SNPs associated with LTL could be used as a robust risk marker. We explored this approach in a large scale study within the PANcreatic Disease ReseArch (PANDoRA) consortium. We analyzed 10 SNPs (ZNF676-rs409627, TERT-rs2736100, CTC1-rs3027234, DHX35-rs6028466, PXK-rs6772228, NAF1-rs7675998, ZNF208-rs8105767, OBFC1-rs9420907, ACYP2-rs11125529 and TERC-rs10936599) alone and combined in a LTL genetic score (“teloscore”, which explains 2.2% of the telomere variability) in relation to PDAC risk in 2,374 cases and 4,326 controls. We identified several associations with PDAC risk, among which the strongest were with the TERT-rs2736100 SNP (OR = 1.54; 95%CI 1.35–1.76; p = 1.54 × 10−10) and a novel one with the NAF1-rs7675998 SNP (OR = 0.80; 95%CI 0.73–0.88; p = 1.87 × 10−6, ptrend = 3.27 × 10−7). The association of short LTL, measured by the teloscore, with PDAC risk reached genome-wide significance (p = 2.98 × 10−9 for highest vs. lowest quintile; p = 1.82 × 10−10 as a continuous variable). In conclusion, we present a novel genome-wide candidate SNP for PDAC risk (TERT-rs2736100), a completely new signal (NAF1-rs7675998) approaching genome-wide significance and we report a strong association between the teloscore and risk of pancreatic cancer, suggesting that telomeres are a potential risk factor for pancreatic cancer