dataesr/scientific-paragraphs-categorization huggingface dataset:
Systematic literature review Search strategy A PubMed search was conducted for peer-reviewed publications reporting primary incidence, mortality or seroprevalence data in any language in countries under the European Medicines Agency (EMA) plus Swizerland. The search was limited to articles published on or after January 1st, 1995 and restricted to human studies. The full search string used was "Varicella AND (mortality OR complications OR epidemiology OR seroprevalence OR prevalence OR incidence) AND ("Europe"[Mesh] OR Austria OR Belgium OR Bulgaria OR Croatia OR Cyprus OR "Czech Republic" OR Denmark OR Estonia OR Finland OR France OR Germany OR Greece OR Hungary OR Iceland OR Ireland OR Italy OR Latvia OR Liechtenstein OR Lithuania OR Luxembourg OR Malta OR Netherlands OR Norway OR Poland OR Portugal OR Romania OR Slovenia OR Slovakia OR Spain OR Sweden OR "United Kingdom" OR Switzerland)".
Eligibility criteria Studies were eligible for inclusion if: 1) they provided data for one or more of the outcomes of interest in the general population, 2) the data were collected before the introduction of universal varicella immunization for countries where universal varicella immunization has been introduced, and 3) the study was published on or after January 1st 1995. Studies were excluded if they did not contain primary data or if the study population was not representative of the general population in terms of varicella transmission dynamics and/or risk of infection (e. g. immunosuppressed patients, imprisoned individuals, or day care workers).
Data extraction Two reviewers (MB, MR) screened titles and abstracts. Discrepancies were extensively discussed and no third reviewer was necessary to resolve disagreements. Evaluation of full text eligibility and data extraction was conducted by a single reviewer (MR). For articles published in languages other than English, reviewers were able to directly read and extract articles in Dutch, German, French, Swedish, Italian, Portuguese and Spanish. For one article in Icelandic, translation software was used for the body text. Legends for the tables and the abstract were provided in English by the journal. For quality control, a sample of 10% of the papers was re-extracted by a third reviewer (TV). The following data was extracted and stored in an MS Excel grid when available: author, journal, year of publication, country, study design, setting (community, primary care, hospital, other), population, case ascertainment, age range, sample size, and incidence or proportion with 95% confidence intervals (CIs).
Incidence estimation We aimed to estimate the annual incidence rates of varicella cases that 1) occurred in the community (with or without health care visit), 2) resulted in an ambulatory primary health care visit, 3) required hospitalisation, or 4) caused death. Data sources were used for incidence estimation if: 1) studies attained a quality score of 6 or more; 2) data collection was conducted for at least 1 year; and 3) agespecific data was provided. In cases where the same data source was used to report incidence for different time periods, we selected the source with the longest time period covered and/or most recent data for inclusion in our analyses. We excluded data derived from mandatory notification systems which may be substantially affected by underreporting  [10] , except for countries where mandatory notification was the only data source available.
Incidence estimation for countries with data Few studies in Europe have assessed the incidence rate of varicella at the community level. We therefore opted to derive the annual age-specific varicella incidence (per 100,000) from seroprevalence studies, which are commonly available. Particularly, for each country we first estimated age-specific seroprevalence using the catalytic model with a piecewise constant force of infection. Then, from these estimated profiles, we derivedincidence rates (and 95% CIs) as differences in seroprevalences for six age groups, < 5, 5-9, 10-14, 15-19, 20-39 and 40+ years. This approach assumes lifelong immunity, time homogeneity and non-differential mortality. For more details on the methodology used, we refer to Bollaerts et al. (Bollaerts K, Riera-Montes M, Hens N et al.
A systematic review of varicella seroprevalence in European countries before universal childhood immunization: deriving incidence from seroprevalence data. Submitted 2017). For incidence rates at the primary care and hospital level, we relied upon the published age-specific data for countries with more extensive information. For countries with more than one estimate, we provide a range with the lowest and highest estimates. Varicella-specific mortality data was obtained from the World Health Organisation (WHO) European Detailed Mortality Database (DMDB)  [11]. The DMDB contains mortality data by cause of death (ICD-9 or ICD-10 codes), age and sex. Other country-specific mortality data sources identified during the SLR were found either to rely upon the same data source that feeds into the WHO DMDB or to provide comparable results.
Incidence estimation for countries without data To obtain age-specific community, primary care and hospital incidence estimates for countries without data, we took a 2-step approach. Firstly, we tried to build prediction models for each outcome and age group, calibrated using information from the countries with data. Secondly, when the model failed to predict (i. e. non-significance of any of the potential predictor variables), we extrapolated the minimum and maximum observed estimates within the same age group from countries with data (Table  2 ). Particularly, we built a linear regression model based on the incidences in the younger age groups and countrylevel prediction variables that have been shown to be associated with country-level differences in varicella transmissibility and health care use  [12, 13]  (Additional file 2): proportion of children <3 years that receive no formal childcare  [14] , population density  [14] , inequality in income distribution  [14] , proportion of people at risk of poverty  [14] , total health expenditure  [15] , proportion of households with 1, 2, 3, and 4 or more children  [14] , number of annual consultations of a medical doctor per inhabitant  [14] , and number of acute hospital discharges per 100 population  [14].
Estimation of annual number of cases To estimate the annual country-specific numbers of varicella-associated community cases, ambulatory primary care consultations, hospitalisations, and deaths per age group, we applied age-specific community incidence, PCI, HI, and mortality rates to each country's population. Population data was obtained from Eurostat for the latest year available (2015)  [14]. The total annual number of cases within Europe was then calculated by summing the number of cases for each country. The numbers of varicella-associated community cases and deaths are presented as point estimates with 95% CIs, while the numbers of varicella-related primary care consultations and hospitalisations are presented as a range. We compared the estimated annual country-specific numbers of varicella-associated community cases to the numbers reported to EUVAC.
NET, in order to estimate the underreporting of the disease. EUVAC. NET is a European surveillance network for selected vaccinepreventable diseases that was active until 2011 and was hosted by the Staten Serum Institute (SSI), Denmark. It incorporated 18 countries; all EU Member States up to 2011, as well as Croatia, Iceland, Norway, Switzerland and Turkey. Number of varicella cases were reported annually by all countries. We compared the EUVAC. NET data of 2009-2010 to our results, and calculated the ratio of reported to estimated number of cases, expressed in percentages.
Systematic literature review The literature search was conducted in PubMed on October 2nd 2015. Identification of grey literature sources was conducted between October and December 2015. We identified 120 data sources from 31 countries for extraction (Fig. 1 )  [5, 7, 8, 11,. Most data sources (97/120) scored the maximum in terms of quality assessment (score of 8). Only one data source scored less than 6. A table summarizing the main characteristics of all selected data sources, and a summarised version of the full data extraction table is provided in Additional files 3 and 4. The most frequently found unique data source was on seroprevalence (n = 52) , followed by hospitalisation (n = 39)  [23, 27, 40,   2 ). Data on all four outcomes was only available for six countries (Belgium, France, Italy, the Netherlands, Spain and the UK).
The main strength of our study is that we followed a systematic approach to quantify age-specific varicella incidence. In this way, we maximised transparency and comparability across countries. We based our estimates on the best available evidence, as obtained through a comprehensive SLR of the epidemiology of varicella. To estimate varicella incidence at community level we used seroprevalence data. Unlike other surveillance data, seroprevalence data are not affected by health care seeking or under-reporting and therefore provide a more accurate    [10, 40, 129]. 3 -5 3 -3 0 -0 Luxembourg a 49-59 4-5 1 -1 1 -1 1 -1 0 -1 Malta a 56-68 2-3 1 -2 1 -2 2 -2 1 Our study has several limitations. Data sources providing PCI, HI and mortality may be affected by underascertainment and underreporting, and we may therefore Table  6  Age-specific annual mortality incidence (/100,000) of varicella in European countries before the introduction of universal childhood immunization programs have underestimated the number of primary care visits, hospitalisations and deaths.
Studies in the UK, Ireland and Spain among pregnant women have also shown that foreign-born women are more likely to be susceptible to varicella  [36, 44, 47, 57]. There is a lack of studies addressing the impact of immigration on varicella epidemiology. Most seroprevalence surveys are carried out using residual serum samples with no information on immigration status  [41]. As evidenced by van Rijckevorsel et al. [64] , varicella serological profiles may show geographical differences within countries, with urban areas (being areas where immigration is typically concentrated) often presenting a higher proportion of varicella susceptible adults. To estimate varicella mortality, we used data from the WHO DMDB  [11]. Mortality causes are coded using International Classification of Diseases (ICD)-9 or ICD-10 and it is difficult to ascertain the accuracy of the coding.
Acknowledgements The authors would like to thank  Martine Sabbe  ( WIV-ISP, Belgium ),  Jan Kyncl  ( SZU, Czech Republic ),  Daniel Levy-Bruhl  ( InVS, France ),  Thorolfur Gudnason  ( Landlaeknir, Iceland ),  Suzanne Cotter  ( HSE, Ireland), Joke Bilcke (Antwerp University ), Alies van Lier (RIVM),  Hester de Melker (RIVM) ,  Maria Cristina Rota  ( Istituto Superiore di Sanità Rome, Italy ) and  Paloma Carrillo-Santisteve (ECDC)  for providing data sources and/or references. The authors also thank  Marc Baay  ( P95 ) for support with the systematic literature review and  Sally Jackson  ( P95 ) for writing services.
Drug combination analysis. Different concentrations of tenofovir (0, 0. 1, 0. 5, 1. 25, 2. 5, 5 or 10 μM) and M48U1 (0, 0. 001, 0. 005, 0. 03, 0. 15, 0. 75 or 1. 5 μM) were co-formulated in 0. 25% HEC and tested in activated PBMCs challenged with HIV-1 BaL (5 ng/ml of HIV-1 gag p24) using the protocol described above. The HIV-1 gag p24 content was determined at seven days post-infection in the culture supernatants using the HIV-1 p24 antigen ELISA kit (Biomerieux). The data were analyzed using an isobologram according to previously reported methods  [45] [46] [47]. In brief, IC 50 values were used to calculate the fractional inhibitory concentration (FIC) as follows: FICx (EC 50 of compound "X" in combination/IC 50 of compound alone); FICy (IC 50 of compound "Y" in combination/IC 50 of compound alone).
Total DNA amount was determined by spectrophotometry. The amplification was carried out as follows: an initial cycle of denaturation step at 95 °C for 15 minutes, followed by 10 cycles of denaturation at 95 °C for 15 seconds and annealing/extension at 68 °C for 35 seconds, and a final 35 cycles of denaturation at 95 °C for 15 seconds and annealing/extension with fluorescence acquisition at 68 °C for 35 seconds. At the end of the amplification cycles, a quantitative analysis was performed by interpolation of the data obtained using a standard curve. The data were normalized to those of a parallel amplification of the β-globin gene as described previously  31. The manufacturer specified that the limit of detection of the assay was three viral copies/500 ng total DNA.
Statistical analyses. The results were expressed as the mean ± standard deviations (SD) of three separate experiments performed in duplicate or triplicate. Non-parametric Mann Whitney, one-way ANOVA and two-way ANOVA followed by Bonferroni test were used for the statistical comparisons. The IC 50 and 95% CI values were calculated using the Prism (GraphPad Software, San Diego, CA) and ic50tk (www. ic50. tk) software.
25%. After this incubation, these solutions were used to resuspend activated PBMCs for 2 hours at 37 °C. HIV-1 replication was monitored by a HIV-1 p24 ELISA assay on the cell culture supernatants performed on day 7 post-infection. The data were expressed as the means ± standard deviations (±SD) of the level of HIV-1 gag p24 relative to untreated controls (set to 100%). Three experiments in triplicate were performed. of HIV-1 transmission, we also analysed the antiretroviral activity of 1 or 6. 7 μM M48U1 in 0. 25% HEC and 5 or 20 μM tenofovir in 0. 25% HEC in TZM-bl cells challenged separately with two T/F IMCs, pREJO. c/2864 and pTHRO. c/2626. As shown in Fig. 2C, D , a clear decrease in viral infectivity was observed when experiments were performed in the presence of M48U1 or tenofovir).
The data were expressed as the means ± standard deviations (±SD) of the level of HIV-1 gag p24 relative to untreated controls (set to 100%) for every HIV-1 strain. Three experiments in triplicate were performed. Analysis of antiretroviral activity of 1 μM M48U1 in 0. 25% HEC (C) or 5 μM tenofovir in 0. 25% HEC (D) performed in TZM-bl cells infected with pREJO. c/2864 and pTHRO. c/2626 T/F IMCs. The percentage of infection of each T/F was calculated comparing the relative luminescence units (RLUs) of the virus control wells, after subtraction of cell control RLUs and the data were expressed as the means ± standard deviations (±SD). Each sample was performed in triplicate and was repeated in three independent experiments. the two drugs (Fig. 3B ). The Trypan Blue exclusion assay was employed to determine whether these co-treatments could exert cytotoxic effects that would explain the antiretroviral effects of the drugs.
To develop a In the presence of these drugs, the tissue samples were challenged with the HIV-1 BaL strain (25 ng p24/well) for 24 hours. Total DNA was purified from the tissues on day 4 post-infection and was analysed by qPCR. When 6. 7 μM M48U1 was used with 20 μM tenofovir, no proviral DNA was detectable. The data were expressed as the means ± standard deviations (±SD) of the number of copies of proviral DNA/200 ng total DNA and the fold-inhibition was calculated as the mean with respect to HIV-1-infected samples treated with HEC hydrogel (0. 25%) without any antiretroviral drug. Three experiments in triplicate or duplicate were performed. ND: not detected. microbicide able to prevent HIV-1 transmission, it is essential to evaluate the activity of M48U1 on several primary virus strains, including transmitted/founder strains.
Data Collection and Sample Analysis Data from all 210 originally randomized patients were available for a summary of baseline characteristics and reported trial primary outcome measure (aGVHD requiring steroid therapy). Additional outcome data (grade II-IV aGVHD, grade III-IV aGVHD, cGVHD, relapse, death) were available from the original trial data for only 209 patients (data missing for 1 patient on the placebo arm). From these original 209 patients, additional long-term clinical data (beyond the data available at study closure through full duration of surviving patient follow-up) were secured from 95% of the patients at risk for events (obtained for 99 of the 104 patients alive at trial closure). Investigators at the various sites were contacted to update study records with the following long-term data: duration of follow-up, maximal grade of aGVHD, maximal grade of cGVHD, attainment of complete remission from primary disease, primary disease relapse, date of death, cause of death, and date of last contact.
2 mg/kg (arm C). Cells were stained with L/D yellow, and surfaces were stained with CD3 PB, CD4 Alexa Fluor 700, CD15 PerCp-Cy5. 5, CD25 PE-Cy7, and CD127-Alexa Fluor 647 (BD Biosciences, San Jose, CA). The cells were then fixed and permeabilized using the Foxp3 buffer set (BD Biosciences), and then stained with Foxp3-PE. In another panel, cells were surface-stained with L/D yellow, CD3 PB, CD4 Alexa Fluor 700, CD15 Percp-Cy5. 5, CD8 APC-H7, CD127 Alexa Fluor 647, CD45RA FITC, and CCR7 PE-Cy7. Cells were analyzed by flow cytometry (LSRII; BD Biosciences). Results from each post-transplantation time window (on therapy [days +11 to +35], washed [days +81 to +101], and long-term follow-up [day +365 ± 30) were compared between arms A and C. Neither absolute lymphocyte count nor T cell count data were available, and thus the absolute number of Treg or central memory subsets could not be derived.
aGVHD The primary endpoint of the trial was not achieved. Analysis of data on study closure (n = 210) demonstrated that the addition of daclizumab at doses of 0. 3 mg/kg and 1. 2 mg/kg to a standard immunosuppressive regimen of cyclosporine/methotrexate did not decrease the 100-day incidence of aGVHD necessitating high-dose steroid therapy: 66% for arm A, 72% for arm B, and 75% for arm C (P >. 05). All subsequent analyses reported here are based on the complete data available in both the original and long-term follow-up datasets (n = 209). The cumulative incidence of any grade IIIIV aGVHD was similar in the 3 arms (38% for arm A, 42% for arm B, and 47% for arm C; P >. 05) (Figure  1 ). With one exception, subgroup analyses of patients stratified on the basis of sex, age (<20 years versus ≥20 years), HLA match (matched versus mismatched), geographical study site (FHCRC versus United States non-FHCRC versus non-United States), and relapse risk category (low versus high) showed no statistically significant differences in the incidence or severity of aGVHD.
results IL-17F induced qualitatively similar inflammatory responses to IL-17A in skin and joint cells. neutralisation of IL-17A and IL-17F with bimekizumab more effectively suppressed in vitro cytokine responses and neutrophil chemotaxis than inhibition of IL-17A or IL-17F alone. the poC trial met both prespecified efficacy success criteria and showed rapid, profound responses in both joint and skin (pooled top three doses vs placebo at week 8: American College of rheumatology 20% response criteria 80. 0% vs 16. 7% (posterior probability >99%); psoriasis Area and Severity Index 100% response criteria 86. 7% vs 0%), sustained to week 20, without unexpected safety signals. Conclusions these data support IL-17F as a key driver of human chronic tissue inflammation and the rationale for dual neutralisation of IL-17A and IL-17F in psA and related conditions.
Study design PA0007 was a phase 1b, randomised, double-blind, placebo-controlled, PoC study evaluating the safety, pharmacokinetic (PK) and clinical efficacy of multiple doses of bimekizumab in patients with PsA (NCT02141763). The study was conducted in accordance with the applicable regulatory and International Council for Harmonisation, Good Clinical Practice requirements, the ethical principles originating in the Declaration of Helsinki and local laws. The protocol was reviewed and approved by the relevant ethics committees. All patients provided documented consent prior to study entry. The study was conducted at three sites, one each in the Republic of Moldova, the UK and Bulgaria, between June 2014 and August 2015. Patients were randomised to one of five treatment regimens: intravenous administration on three separate occasions (weeks 0, 3 and 6) of one of the following dose regimens or matched placebo: 1.
Statistical analysis For the blockade experiments in synoviocytes and primary NHDFs, a one-way analysis of variance (ANOVA) with Fisher's least significant difference (LSD) post-hoc test was used to assess overall differences between the groups and IgG control. A one-tailed paired t-test was chosen for the comparison between the anti-IL-17A and bimekizumab groups. Mean and standard error of the mean (SEM) were presented. As predefined in the analysis plan, data from the three highest bimekizumab dose groups were pooled (the lowest dose group was expected to produce suboptimal efficacy and was therefore only included in the safety and PK data sets) and all placebo data were also pooled for summary and statistical inference purposes. A sample size of 50 was deemed sufficient to meet the primary study objectives (safety, tolerability and PK), and to detect a difference of the pooled treatment group from pooled placebo group in ACRn with >90% probability based on a frequentist approach.
To give further confidence about the effect size, the posterior probability that bimekizumab improvement over placebo exceeds a clinically relevant effect (ie, approximately 25% difference from placebo in ACR20 terms) was required to be ≥70%. The clinically relevant effect was determined after assessment of the efficacy data from a TNF inhibitor clinical study (NCT01087788). 15 For ease of interpretation, posterior estimates and 95% credible intervals (CrI) for ACR20 only are presented. Further details on the statistical methods are described in online supplementary information.
Proof of concept: clinical efficacy of bimekizumab on joints and skin in patients with psoriatic arthritis A summary of the clinical efficacy of the three highest dose groups of bimekizumab on measures of disease activity in joints and skin is presented in table  3. The prespecified efficacy success criteria of this study were met as Bayesian analysis indicated a >99% probability that joint response rates, as defined by ACRn and ACR20, at week 8 are greater with bimekizumab than with placebo (online supplementary table s2 and s3). Additionally, there was also a >99% probability that the ACRn and ACR20 response rates with bimekizumab at week 8 exceeded a clinically relevant threshold (defined based on results from a TNF inhibitor clinical study (NCT01087788)). 15 Therefore, both of the prespecified efficacy success criteria of this study were met.
In the context of previous reports with anti-IL-17A and anti-IL-17RA antibodies,  [26] [27] [28]  it is important to note the absence of opportunistic infections (including tuberculosis), inflammatory bowel disease and suicide-related events in this trial. In line with the increased susceptibility for fungal infections emerging with anti-IL-17A antibodies, we observed two cases of candidiasis (oropharyngeal and vulvovaginal), both of which were mild and resolved with local treatment. The clinical study met its predefined efficacy criterion, demonstrating superiority of bimekizumab over both placebo and the predefined clinically relevant threshold using ACRn at week 8. Currently, anti-TNF therapy is considered the SoC biological treatment for PsA; therefore, the clinically relevant threshold was based on a pivotal randomised controlled trial with TNF blockade in patients with PsA (NCT01087788).