A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Web-based analysis of adherence to influenza vaccination among French healthcare workers

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Metagenomic Next-Generation Sequencing Reveals Individual Composition and Dynamics of Anelloviruses during Autologous Stem Cell Transplant Recipient Management

Over recent years, there has been increasing interest in the use of the anelloviruses, the major component of the human virome, for the prediction of post-transplant complications such as severe infections. Due to an important diversity, the comprehensive characterization of this viral family over time has been poorly studied. To overcome this challenge, we used a metagenomic next-generation sequencing (mNGS) approach with the aim of determining the individual anellovirus profile of autologous stem cell transplant (ASCT) patients. We conducted a prospective pilot study on a homogeneous patient cohort regarding the chemotherapy regimens that included 10 ASCT recipients. A validated viral mNGS workflow was used on 108 plasma samples collected at 11 time points from diagnosis to 90 days post-transplantation. A complex interindividual variability in terms of abundance and composition was noticed. In particular, a strong sex effect was found and confirmed using quantitative PCR targeting torque teno virus, the most abundant anellovirus. Interestingly, an important turnover in the anellovirus composition was observed during the course of the disease revealing a strong intra-individual variability. Although more studies are needed to better understand anellovirus dynamics, these findings are of prime importance for their future use as biomarkers of immune competence

Tazemetostat in Combination with R-CHOP in Patients with High-Risk, Frontline Follicular Lymphoma (Epi-RCHOP): A Phase II Study from the Lysa

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Clinicopathological features and survival in EBV-positive diffuse large B-cell lymphoma not otherwise specified

International audienceAbstract In this retrospective study, we report 70 cases of Epstein-Barr virus (EBV)+ diffuse large B-cell lymphoma not otherwise specified (DLBCL-NOS) among 1696 DLBCL-NOS cases diagnosed between 2006 and 2019 (prevalence of 4.1%). At diagnosis, median age was 68.5 years; 79% of the cases presented with an advanced-stage disease (III-IV), 48% with extranodal lesions, and 14% with an hemophagocytic lymphohistiocytosis (HLH) (8 at diagnosis and 1 on therapy). A total of 46 cases presented a polymorphic pattern, and 21 were monomorphic. All had a non-germinal center B phenotype, with the majority of tumor cells expressing CD30 and programmed death ligand 1 (98% and 95%, respectively). Type II and III EBV latency was seen in 88% and 12% of the cases, respectively. Patients were treated with immunochemotherapy (59%) or chemotherapy (22%), and 19% received palliative care due to advanced age and altered performance status. After a median follow-up of 48 months, progression-free survival (PFS) and overall survival (OS) at 5 years were 52.7% and 54.8%, respectively. Older age (>50 years) and HLH were associated with shorter PFS and OS in multivariate analysis (PFS: hazard ratio [HR], 14.01; 95% confidence interval [CI], 2.34-83.97; and HR, 5.78; 95% CI, 2.35-14.23; OS: HR, 12.41; 95% CI, 1.65-93.53; and HR, 6.09; 95% CI, 2.42-15.30, respectively). Finally, using a control cohort of 425 EBV− DLBCL-NOS, EBV positivity was associated with a shorter OS outcome within patients >50 years (5-year OS, 53% [95% CI, 38.2-74] vs 60.8% [95% CI, 55.4-69.3], P = .038), but not in younger patients

What is driving HTA decision-making? Evidence from cancer drug reimbursement decisions from 6 European countries

Background Decisions on the reimbursement of the same cancer drugs are different across European countries, but empirical work on the reasons behind these differences has been scarce. The main objective of this paper is to make a methodological contribution to existing research, specifically by outlining the systematic process of analysis to address such questions and determining the factors that might lead to different drug reimbursement decisions, and to explore its application in the field of oncology. Methods Reimbursement decisions on cancer drugs in six European countries (Belgium, England, Poland, Portugal, Scotland, and Sweden) between 2006 and 2014 were included in the study. A taxonomy was developed, comprising two groups of variables (system-level and product-specific) and an econometric model was specified (multilevel mixed-effects ordered probit). Results Only one in six evaluations in the sample reach the same reimbursement recommendation. Most health system variables were not determinants of a higher or lower probability of a positive reimbursement recommendation. However, the probability of reimbursement was higher when a drug was considered cost-effective by NICE/SMC and when there was a financial Managed Entry Agreement. This work also demonstrated a possible econometric approach for analysing differences in reimbursement decisions and contributes a structured approach for collecting and preparing data for such analyses. Conclusions Drug reimbursement decisions can be analysed in detail along a set of factors that are related to each decision. This information is essential, not only for understanding why a particular drug is accepted in one country and not in another but also when trying to implement a new HTA system or reform an existing one. This analysis provides policy makers and stakeholders with a model that enables a better understanding of the factors that drive HTA decisions and is adaptable to answer similar questions. Moreover, the data collection limitations encountered and described in this work shed light on the need for greater accessibility and transparency in HTA systems and regarding HTA outcomes.This research was funded under the European 7th Framework Programme with Advance-HTA (no305,983). The results presented reflect the author’s views. The EC is not liable for any use of the information communicated