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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Luis Antonio Díaz; Eduardo Fuentes-López; Gustavo Ayares; Francisco Idalsoaga; +57 Authors

    Alcoholic hepatitis; Cirrhosis; Outcome prediction Hepatitis alcohòlica; Cirrosi; Predicció de resultats Hepatitis alcohólica; Cirrosis; Predicción de resultados Background & aims: Model for End-Stage Liver Disease (MELD) score better predicts mortality in alcohol-associated hepatitis (AH) but could underestimate severity in women and malnourished patients. Using a global cohort, we assessed the ability of the MELD 3.0 score to predict short-term mortality in AH. Methods: This was a retrospective cohort study of patients admitted to hospital with AH from 2009 to 2019. The main outcome was all-cause 30-day mortality. We compared the AUC using DeLong's method and also performed a time-dependent AUC with competing risks analysis. Results: A total of 2,124 patients were included from 28 centres from 10 countries on three continents (median age 47.2 ± 11.2 years, 29.9% women, 71.3% with underlying cirrhosis). The median MELD 3.0 score at admission was 25 (20-33), with an estimated survival of 73.7% at 30 days. The MELD 3.0 score had a better performance in predicting 30-day mortality (AUC:0.761, 95%CI:0.732-0.791) compared with MELD sodium (MELD-Na; AUC: 0.744, 95% CI: 0.713-0.775; p = 0.042) and Maddrey's discriminant function (mDF) (AUC: 0.724, 95% CI: 0.691-0.757; p = 0.013). However, MELD 3.0 did not perform better than traditional MELD (AUC: 0.753, 95% CI: 0.723-0.783; p = 0.300) and Age-Bilirubin-International Normalised Ratio-Creatinine (ABIC) (AUC:0.757, 95% CI: 0.727-0.788; p = 0.765). These results were consistent in competing-risk analysis, where MELD 3.0 (AUC: 0.757, 95% CI: 0.724-0.790) predicted better 30-day mortality compared with MELD-Na (AUC: 0.739, 95% CI: 0.708-0.770; p = 0.028) and mDF (AUC:0.717, 95% CI: 0.687-0.748; p = 0.042). The MELD 3.0 score was significantly better in predicting renal replacement therapy requirements during admission compared with the other scores (AUC: 0.844, 95% CI: 0.805-0.883). Conclusions: MELD 3.0 demonstrated better performance compared with MELD-Na and mDF in predicting 30-day and 90-day mortality, and was the best predictor of renal replacement therapy requirements during admission for AH. However, further prospective studies are needed to validate its extensive use in AH. Impact and implications: Severe AH has high short-term mortality. The establishment of treatments and liver transplantation depends on mortality prediction. We evaluated the performance of the new MELD 3.0 score to predict short-term mortality in AH in a large global cohort. MELD 3.0 performed better in predicting 30- and 90-day mortality compared with MELD-Na and mDF, but was similar to MELD and ABIC scores. MELD 3.0 was the best predictor of renal replacement therapy requirements. Thus, further prospective studies are needed to support the wide use of MELD 3.0 in AH. JPA and MA receive support from the Chilean Government through the Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT 1200227 to JPA and 1191145 to MA). RB is a recipient of NIAAA U01AA021908 and U01AA020821.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ JHEP Reportsarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    JHEP Reports
    Article . 2023 . Peer-reviewed
    License: CC BY NC ND
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    JHEP Reports
    Article . 2022
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    JHEP Reports
    Article . 2023
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ JHEP Reportsarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      JHEP Reports
      Article . 2023 . Peer-reviewed
      License: CC BY NC ND
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      JHEP Reports
      Article . 2022
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      JHEP Reports
      Article . 2023
      Data sources: DOAJ
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Lorenzo Gerratana; Jean-Yves Pierga; James M Reuben; Andrew A Davis; +30 Authors

    Biomarker; Liquid biopsy; Machine learning Biomarcadores; Biopsia líquida; Aprendizaje automático Biomarcadors; Biòpsia líquida; Aprenentatge automàtic Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier’s performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS). The study was supported by Lynn Sage Cancer Research Foundation and the the CRO Aviano 5x1000 2014 per la Ricerca Sanitaria, Cancer Specific Intramural Grant. The funding sources had no role in the study design, data collection, data analysis, interpretation, or writing of the manuscript.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Archivio istituziona...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    The Oncologist
    Article . 2021
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Thomas Chatzikonstantinou; Lydia Scarfò; Georgios Karakatsoulis; Eva Minga; +138 Authors

    Background: Patients with chronic lymphocytic leukemia (CLL) have a higher risk of developing other malignancies (OMs) compared to the general population. However, the impact of CLL-related risk factors and CLL-directed treatment is still unclear and represents the focus of this work. Methods: We conducted a retrospective international multicenter study to assess the incidence of OMs and detect potential risk factors in 19,705 patients with CLL, small lymphocytic lymphoma, or high-count CLL-like monoclonal B-cell lymphocytosis, diagnosed between 2000 and 2016. Data collection took place between October 2020 and March 2022. Findings: In 129,254 years of follow-up after CLL diagnosis, 3513 OMs were diagnosed (27.2 OMs/1000 person-years). The most common hematological OMs were Richter transformation, myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Non-melanoma skin (NMSC) and prostate cancers were the most common solid tumors (STs). The only predictor for MDS and AML development was treatment with fludarabine and cyclophosphamide with/without rituximab (FC ± R) (OR = 3.7; 95% CI = 2.79–4.91; p < 0.001). STs were more frequent in males and patients with unmutated immunoglobulin heavy variable genes (OR = 1.77; 95% CI = 1.49–2.11; p < 0.001/OR = 1.89; 95% CI = 1.6–2.24; p < 0.001). CLL-directed treatment was associated with non-melanoma skin and prostate cancers (OR = 1.8; 95% CI = 1.36–2.41; p < 0.001/OR = 2.11; 95% CI = 1.12–3.97; p = 0.021). In contrast, breast cancers were more frequent in untreated patients (OR = 0.17; 95% CI = 0.08–0.33; p < 0.001). Patients with CLL and an OM had inferior overall survival (OS) than those without. AML and MDS conferred the worst OS (p < 0.001). Interpretation: OMs in CLL impact on OS. Treatment for CLL increased the risk for AML/MDS, prostate cancer, and NMSC. FCR was associated with increased risk for AML/MDS. Funding: AbbVie, and EU/ EFPIA Innovative Medicines Initiative Joint Undertaking HARMONY grant n° 116026. CA extern

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Universitätsbibliogr...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    OPUS Augsburg
    Article . 2023
    License: CC BY NC ND
    Data sources: OPUS Augsburg
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dopico, Eva; Del-Rei, Rodrigo Pimenta; Espinoza, Bertha; Ubillos, Itziar; +9 Authors

    Chagas disease; Chimeric antigens; Trypanosoma cruzi Malaltia de Chagas; Antígens quimèrics; Trypanosoma cruzi Enfermedad de Chagas; Antígenos quiméricos; Trypanosoma cruzi BACKGROUND: Chronic Chagas Disease (CD) diagnosis is based on serological methods employing crude, semipurified or recombinant antigens, which may result in low sensitivity or cross-reactivity. To reduce these restrictions, we developed a strategy involving use of molecules containing repetitive fragments of Trypanosoma cruzi conserved proteins. Diagnostic performance of IBMP-8.1 and IBMP-8.4 chimeric antigens (Molecular Biology Institute of Paraná - IBMP in Portuguese acronym) was assessed to diagnose T. cruzi-infected and non-infected immigrants living in Barcelona (Spain), a non-endemic setting for Chagas disease. METHODS: Reactivity of IBMP-8.1 and IBMP-8.4 was assessed using an in-house automated ELISA with 347 positive and 331 negative individuals to Chagas disease. Antigenic cross-reactivity was measured with sera samples from pregnant women with Toxoplasma gondii (n = 98) and Zika virus (n = 75) antibodies. RESULTS: The area under the curve values was 1 and 0.99 for the IBMP-8.1 and IBMP-8.4 proteins, respectively, demonstrating excellent diagnostic accuracy. The reactivity index was higher for IBMP-8.1 than IBMP-8.4 in positive samples and no significant difference in reactivity index was observed in negative samples. Sensitivity ranged from 99.4% for IBMP-8.1 to 99.1% for IBMP-8.4 and was not statistically different. Specificity for IBMP-8.1 reached 100 and 99.7% for IBMP-8.4, both nearly 100% accurate. No antigenic cross-reactivity was observed and reactivity index was similar to that for negative Chagas disease individuals. CONCLUSIONS: Our results showed an outstanding performance of IBMP-8.1 and IBMP-8.4 chimeric antigens by ELISA and suggest both chimeric antigens could also be used for Chagas disease diagnosis in immigrants living in non-endemic settings.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DOAJ
    Article . 2019
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    BMC Infectious Diseases
    Article . 2019
    Data sources: DOAJ-Articles
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Infectious Diseases
    Article . 2019 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Infectious Diseases
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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      BMC Infectious Diseases
      Article . 2019
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      BMC Infectious Diseases
      Article . 2019 . Peer-reviewed
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      BMC Infectious Diseases
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    Authors: Andrea Di Matteo; Andrea Di Matteo; Erica Moscioni; Maria Giovanna Lommano; +53 Authors

    Muscle echogenicity; Musculoskeletal ultrasound; Rheumatic diseases Ecogenicidad muscular; Ecografía musculoesquelética; Enfermedades reumáticas Ecogenicitat muscular; Ecografia musculoesquelètica; Malalties reumàtiques Objectives: To investigate the inter/intra-reliability of ultrasound (US) muscle echogenicity in patients with rheumatic diseases. Methods: Forty-two rheumatologists and 2 radiologists from 13 countries were asked to assess US muscle echogenicity of quadriceps muscle in 80 static images and 20 clips from 64 patients with different rheumatic diseases and 8 healthy subjects. Two visual scales were evaluated, a visual semi-quantitative scale (0–3) and a continuous quantitative measurement (“VAS echogenicity,” 0–100). The same assessment was repeated to calculate intra-observer reliability. US muscle echogenicity was also calculated by an independent research assistant using a software for the analysis of scientific images (ImageJ). Inter and intra reliabilities were assessed by means of prevalence-adjusted bias-adjusted Kappa (PABAK), intraclass correlation coefficient (ICC) and correlations through Kendall’s Tau and Pearson’s Rho coefficients. Results: The semi-quantitative scale showed a moderate inter-reliability [PABAK = 0.58 (0.57–0.59)] and a substantial intra-reliability [PABAK = 0.71 (0.68–0.73)]. The lowest inter and intra-reliability results were obtained for the intermediate grades (i.e., grade 1 and 2) of the semi-quantitative scale. “VAS echogenicity” showed a high reliability both in the inter-observer [ICC = 0.80 (0.75–0.85)] and intra-observer [ICC = 0.88 (0.88–0.89)] evaluations. A substantial association was found between the participants assessment of the semi-quantitative scale and “VAS echogenicity” [ICC = 0.52 (0.50–0.54)]. The correlation between these two visual scales and ImageJ analysis was high (tau = 0.76 and rho = 0.89, respectively). Conclusion: The results of this large, multicenter study highlighted the overall good inter and intra-reliability of the US assessment of muscle echogenicity in patients with different rheumatic diseases. RH and JH were supported by Ministry of Health, Czech Republic – conceptual development of research organization, Motol University Hospital, Prague, Czech Republic (00064203).

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    Frontiers in Medicine
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      Frontiers in Medicine
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    Authors: Vahdat, Linda T.; Schmid, Peter; Forero-Torres, Andres; Blackwell, Kimberly; +14 Authors

    Breast cancer; Cancer Càncer de mama; Càncer Cáncer de mama; Cáncer The METRIC study (NCT#0199733) explored a novel antibody–drug conjugate, glembatumumab vedotin (GV), targeting gpNMB that is overexpressed in ~40% of patients with triple-negative breast cancer (TNBC) and associated with poor prognosis. The study was a randomized, open-label, phase 2b study that evaluated progression-free survival (PFS) of GV compared with capecitabine in gpNMB-overexpressing TNBC. Patients who had previously received anthracycline and taxane-based therapy were randomized 2:1 to receive, GV (1.88 mg/kg IV q21 days) or capecitabine (2500 mg/m2 PO daily d1–14 q21 days). The primary endpoint was RECIST 1.1 PFS per independent, blinded central review. In all, 327 patients were randomized to GV (213 treated) or capecitabine (92 treated). Median PFS was 2.9 months for GV vs. 2.8 months for capecitabine. The most common grade ≥3 toxicities for GV were neutropenia, rash, and leukopenia, and for capecitabine were fatigue, diarrhea, and palmar-plantar erythrodysesthesia. The study did not meet the primary endpoint of improved PFS over capecitabine or demonstrate a relative risk/benefit improvement over capecitabine. Funding provided by Celldex Therapeutics, Inc.

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    npj Breast Cancer
    Article . 2021 . Peer-reviewed
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    npj Breast Cancer
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      npj Breast Cancer
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      npj Breast Cancer
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    Authors: Nowotny, Hanna; Neumann, Uta; Tardy-Guidollet, Véronique; Ahmed, S Faisal; +40 Authors

    OBJECTIVE: To assess the current medical practice in Europe regarding prenatal dexamethasone (Pdex) treatment of congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency. DESIGN AND METHODS: A questionnaire was designed and distributed, including 17 questions collecting quantitative and qualitative data. Thirty-six medical centres from 14 European countries responded and 30 out of 36 centres were reference centres of the European Reference Network on Rare Endocrine Conditions, EndoERN. RESULTS: Pdex treatment is currently provided by 36% of the surveyed centres. The treatment is initiated by different specialties, that is paediatricians, endocrinologists, gynaecologists or geneticists. Regarding the starting point of Pdex, 23% stated to initiate therapy at 4-5 weeks postconception (wpc), 31% at 6 wpc and 46 % as early as pregnancy is confirmed and before 7 wpc at the latest. A dose of 20 µg/kg/day is used. Dose distribution among the centres varies from once to thrice daily. Prenatal diagnostics for treated cases are conducted in 72% of the responding centres. Cases treated per country and year vary between 0.5 and 8.25. Registries for long-term follow-up are only available at 46% of the centres that are using Pdex treatment. National registries are only available in Sweden and France. CONCLUSIONS: This study reveals a high international variability and discrepancy in the use of Pdex treatment across Europe. It highlights the importance of a European cooperation initiative for a joint international prospective trial to establish evidence-based guidelines on prenatal diagnostics, treatment and follow-up of pregnancies at risk for CAH. Contains fulltext : 283126.pdf (Publisher’s version ) (Open Access)

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    Acta Endocrinologica
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    Radboud Repository
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    Acta Endocrinologica
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    Authors: Alessandro Busca; Jon Salmanton-García; Paolo Corradini; Francesco Marchesi; +25 Authors

    The EHA-IDWP developed an observational registry collecting data on COVID-19 infection in patients who received CAR T-cell therapy. Prevalence of COVID-19 was 4.8%, and overall mortality was 50%, highlighting the need for prevention of infection in these patients. ispartof: BLOOD ADVANCES vol:6 issue:7 pages:1427-1433 ispartof: location:United States status: published

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    Blood Advances
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    Article . 2022
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    Article . 2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dareng, Eileen O.; Tyrer, Jonathan P.; Barnes, Daniel R.; Jones, Michelle R.; +230 Authors

    Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs. ispartof: EUROPEAN JOURNAL OF HUMAN GENETICS vol:30 issue:3 pages:349-362 ispartof: location:England status: published

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    https://www.repository.cam.ac....
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