The Benefits and Risks of Receiving Investigational Solid Tumor Drugs in Randomized Trials : A Systematic Review and Meta-analysis.

BACKGROUND: Many patients participate in cancer trials to access new therapies. The extent to which new treatments produce clinical benefit for trial participants is unclear. PURPOSE: To estimate the progression-free survival (PFS) and overall survival (OS) advantage of assignment to experimental groups in randomized trials for 6 solid tumors. DATA SOURCES: ClinicalTrials.gov was searched for trials of investigational drugs with results posted between 2017 and 2021. STUDY SELECTION: Investigational drugs were defined as those not yet having full approval from the U.S. Food and Drug Administration for the study indication. Trials were included if they were randomized and tested drugs or biologics. DATA EXTRACTION: Data extraction was completed by 2 independent reviewers. Data were pooled using a random-effects model. DATA SYNTHESIS: The sample included 128 trials comprising 141 comparisons of a new drug and a comparator. These comparisons included 47 050 patients. The pooled hazard ratio for PFS was 0.80 (95% CI, 0.75 to 0.85), indicating statistically significant benefit for patients in experimental groups. This corresponded to a median PFS advantage of 1.25 months (CI, 0.80 to 1.68 months). The pooled hazard ratio for OS was 0.92 (CI, 0.88 to 0.95), corresponding to a survival gain of 1.18 months (CI, 0.72 to 1.71 months). The absolute risk for a serious adverse event for comparator group patients was 29.56% (CI, 26.64% to 32.65%), with an increase in risk of 7.40% (CI, 5.66% to 9.14%) for patients in experimental groups. LIMITATIONS: Trials in this sample were heterogeneous. Comparator group interventions were assumed to reflect standard of care. CONCLUSION: Assignment to experimental groups produces statistically significant survival gains. However, the absolute survival gain is small, and toxicity is statistically significantly greater. The findings of this review provide reassuring evidence that patients are not meaningfully disadvantaged by assignment to comparator groups. PRIMARY FUNDING SOURCE: Canadian Institutes of Health Research.

Identification of difficult laryngoscopy using an optimized hybrid architecture.

BACKGROUND: Identification of difficult laryngoscopy is a frequent demand in cervical spondylosis clinical surgery. This work aims to develop a hybrid architecture for identifying difficult laryngoscopy based on new indexes. METHODS: Initially, two new indexes for identifying difficult laryngoscopy are proposed, and their efficacy for predicting difficult laryngoscopy is compared to that of two conventional indexes. Second, a hybrid adaptive architecture with convolutional layers, spatial extraction, and a vision transformer is proposed for predicting difficult laryngoscopy. The proposed adaptive hybrid architecture is then optimized by determining the optimal location for extracting spatial information. RESULTS: The test accuracy of four indexes using simple model is 0.8320. The test accuracy of optimized hybrid architecture using four indexes is 0.8482. CONCLUSION: The newly proposed two indexes, the angle between the lower margins of the second and sixth cervical spines and the vertical direction, are validated to be effective for recognizing difficult laryngoscopy. In addition, the optimized hybrid architecture employing four indexes demonstrates improved efficacy in detecting difficult laryngoscopy. TRIAL REGISTRATION: Ethics permission for this research was obtained from the Medical Scientific Research Ethics Committee of Peking University Third Hospital (IRB00006761-2015021) on 30 March 2015. A well-informed agreement has been received from all participants. Patients were enrolled in this research at the Chinese Clinical Trial Registry ( http://www.chictr.org.cn , identifier: ChiCTR-ROC-16008598) on 6 June 2016.

metamedian: An R package for meta-analyzing studies reporting medians.

When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to incorporate primary studies reporting sample medians in meta-analysis, yet there are currently no comprehensive software tools implementing these methods. In this paper, we present the metamedian R package, a freely available and open-source software tool for meta-analyzing primary studies that report sample medians. We summarize the main features of the software and illustrate its application through real data examples involving risk factors for a severe course of COVID-19.

Wildfire exposure and academic performance in Brazil: A causal inference approach for spatiotemporal data.

As the frequency and intensity of wildfires are projected to globally amplify due to climate change, there is a growing need to quantify the impact of exposure to wildfires in vulnerable populations such as adolescents. In our study, we applied rigorous causal inference methods to estimate the effect of wildfire exposure on the academic performance of high school students in Brazil between 2009 and 2015. Using longitudinal data from 8,183 high schools across 1,571 municipalities in Brazil, we estimated that the average performance in most academic subjects decreases under interventions that increase wildfire exposure, e.g., a decrease of 1.8 % (p = 0.01) in the natural sciences when increasing the wildfire density from 0.0035 wildfires/km2 (first quantile in the sample) to 0.0222 wildfires/km2 (third quartile). Furthermore, these effects considerably worsened over time. Our findings highlight the adverse impact of wildfires on educational outcomes.

Evaluating Model Specification When Using the Parametric G-Formula in the Presence of Censoring.

The noniterative conditional expectation (NICE) parametric g-formula can be used to estimate the causal effect of sustained treatment strategies. In addition to identifiability conditions, the validity of the NICE parametric g-formula generally requires the correct specification of models for time-varying outcomes, treatments, and confounders at each follow-up time point. An informal approach for evaluating model specification is to compare the observed distributions of the outcome, treatments, and confounders with their parametric g-formula estimates under the "natural course." In the presence of loss to follow-up, however, the observed and natural-course risks can differ even if the identifiability conditions of the parametric g-formula hold and there is no model misspecification. Here, we describe 2 approaches for evaluating model specification when using the parametric g-formula in the presence of censoring: 1) comparing factual risks estimated by the g-formula with nonparametric Kaplan-Meier estimates and 2) comparing natural-course risks estimated by inverse probability weighting with those estimated by the g-formula. We also describe how to correctly compute natural-course estimates of time-varying covariate means when using a computationally efficient g-formula algorithm. We evaluate the proposed methods via simulation and implement them to estimate the effects of dietary interventions in 2 cohort studies.

Standard error estimation in meta-analysis of studies reporting medians.

We consider the setting of an aggregate data meta-analysis of a continuous outcome of interest. When the distribution of the outcome is skewed, it is often the case that some primary studies report the sample mean and standard deviation of the outcome and other studies report the sample median along with the first and third quartiles and/or minimum and maximum values. To perform meta-analysis in this context, a number of approaches have recently been developed to impute the sample mean and standard deviation from studies reporting medians. Then, standard meta-analytic approaches with inverse-variance weighting are applied based on the (imputed) study-specific sample means and standard deviations. In this article, we illustrate how this common practice can severely underestimate the within-study standard errors, which results in poor coverage for the pooled mean in common effect meta-analyses and overestimation of between-study heterogeneity in random effects meta-analyses. We propose a straightforward bootstrap approach to estimate the standard errors of the imputed sample means. Our simulation study illustrates how the proposed approach can improve the estimation of the within-study standard errors and consequently improve coverage for the pooled mean in common effect meta-analyses and estimation of between-study heterogeneity in random effects meta-analyses. Moreover, we apply the proposed approach in a meta-analysis to identify risk factors of a severe course of COVID-19.

Impact of molecular diagnostic tests on diagnostic and treatment delays in tuberculosis: a systematic review and meta-analysis.

BACKGROUND: Countries with high TB burden have expanded access to molecular diagnostic tests. However, their impact on reducing delays in TB diagnosis and treatment has not been assessed. Our primary aim was to summarize the quantitative evidence on the impact of nucleic acid amplification tests (NAAT) on diagnostic and treatment delays compared to that of the standard of care for drug-sensitive and drug-resistant tuberculosis (DS-TB and DR-TB). METHODS: We searched MEDLINE, EMBASE, Web of Science, and the Global Health databases (from their inception to October 12, 2020) and extracted time delay data for each test. We then analysed the diagnostic and treatment initiation delay separately for DS-TB and DR-TB by comparing smear vs Xpert for DS-TB and culture drug sensitivity testing (DST) vs line probe assay (LPA) for DR-TB. We conducted random effects meta-analyses of differences of the medians to quantify the difference in diagnostic and treatment initiation delay, and we investigated heterogeneity in effect estimates based on the period the test was used in, empiric treatment rate, HIV prevalence, healthcare level, and study design. We also evaluated methodological differences in assessing time delays. RESULTS: A total of 45 studies were included in this review (DS = 26; DR = 20). We found considerable heterogeneity in the definition and reporting of time delays across the studies. For DS-TB, the use of Xpert reduced diagnostic delay by 1.79 days (95% CI - 0.27 to 3.85) and treatment initiation delay by 2.55 days (95% CI 0.54-4.56) in comparison to sputum microscopy. For DR-TB, use of LPAs reduced diagnostic delay by 40.09 days (95% CI 26.82-53.37) and treatment initiation delay by 45.32 days (95% CI 30.27-60.37) in comparison to any culture DST methods. CONCLUSIONS: Our findings indicate that the use of World Health Organization recommended diagnostics for TB reduced delays in diagnosing and initiating TB treatment. Future studies evaluating performance and impact of diagnostics should consider reporting time delay estimates based on the standardized reporting framework.

Pacific Biosciences Fusion and Long Isoform Pipeline for Cancer Transcriptome-Based Resolution of Isoform Complexity.

Genomic profiling using short-read sequencing has utility in detecting disease-associated variation in both DNA and RNA. However, given the frequent occurrence of structural variation in cancer, molecular profiling using long-read sequencing improves the resolution of such events. For example, the Pacific Biosciences long-read RNA-sequencing (Iso-Seq) transcriptome protocol provides full-length isoform characterization, discernment of allelic phasing, and isoform discovery, and identifies expressed fusion partners. The Pacific Biosciences Fusion and Long Isoform Pipeline (PB_FLIP) incorporates a suite of RNA-sequencing software analysis tools and scripts to identify expressed fusion partners and isoforms. In addition, sequencing of a commercial reference (Spike-In RNA Variants) with known isoform complexity was performed and demonstrated high recall of the Iso-Seq and PB_FLIP workflow to benchmark our protocol and analysis performance. This study describes the utility of Iso-Seq and PB_FLIP analysis in improving deconvolution of complex structural variants and isoform detection within an institutional pediatric and adolescent/young adult translational cancer research cohort. The exemplar case studies demonstrate that Iso-Seq and PB_FLIP discover novel expressed fusion partners, resolve complex intragenic alterations, and discriminate between allele-specific expression profiles.

Detection of brain somatic variation in epilepsy-associated developmental lesions.

OBJECTIVE: Epilepsy-associated developmental lesions, including malformations of cortical development and low-grade developmental tumors, represent a major cause of drug-resistant seizures requiring surgical intervention in children. Brain-restricted somatic mosaicism has been implicated in the genetic etiology of these lesions; however, many contributory genes remain unidentified. METHODS: We enrolled 50 children who were undergoing epilepsy surgery into a translational research study. Resected tissue was divided for clinical neuropathologic evaluation and genomic analysis. We performed exome and RNA sequencing to identify somatic variation and we confirmed our findings using high-depth targeted DNA sequencing. RESULTS: We uncovered candidate disease-causing somatic variation affecting 28 patients (56%), as well as candidate germline variants affecting 4 patients (8%). In agreement with previous studies, we identified somatic variation affecting solute carrier family 35 member A2 (SLC35A2) and mechanistic target of rapamycin kinase (MTOR) pathway genes in patients with focal cortical dysplasia. Somatic gains of chromosome 1q were detected in 30% (3 of 10) of patients with Type I focal cortical dysplasia (FCD)s. Somatic variation in mitogen-activated protein kinase (MAPK) pathway genes (i.e., fibroblast growth factor receptor 1 [FGFR1], FGFR2, B-raf proto-oncogene, serine/threonine kinase [BRAF], and KRAS proto-oncogene, GTPase [KRAS]) was associated with low-grade epilepsy-associated developmental tumors. RNA sequencing enabled the detection of somatic structural variation that would have otherwise been missed, and which accounted for more than one-half of epilepsy-associated tumor diagnoses. Sampling across multiple anatomic regions revealed that somatic variant allele fractions vary widely within epileptogenic tissue. Finally, we identified putative disease-causing variants in genes not yet associated with focal cortical dysplasia. SIGNIFICANCE: These results further elucidate the genetic basis of structural brain abnormalities leading to focal epilepsy in children and point to new candidate disease genes.

Accuracy of rapid point-of-care antigen-based diagnostics for SARS-CoV-2: An updated systematic review and meta-analysis with meta-regression analyzing influencing factors.

BACKGROUND: Comprehensive information about the accuracy of antigen rapid diagnostic tests (Ag-RDTs) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is essential to guide public health decision makers in choosing the best tests and testing policies. In August 2021, we published a systematic review and meta-analysis about the accuracy of Ag-RDTs. We now update this work and analyze the factors influencing test sensitivity in further detail. METHODS AND FINDINGS: We registered the review on PROSPERO (registration number: CRD42020225140). We systematically searched preprint and peer-reviewed databases for publications evaluating the accuracy of Ag-RDTs for SARS-CoV-2 until August 31, 2021. Descriptive analyses of all studies were performed, and when more than 4 studies were available, a random-effects meta-analysis was used to estimate pooled sensitivity and specificity with reverse transcription polymerase chain reaction (RT-PCR) testing as a reference. To evaluate factors influencing test sensitivity, we performed 3 different analyses using multivariable mixed-effects meta-regression models. We included 194 studies with 221,878 Ag-RDTs performed. Overall, the pooled estimates of Ag-RDT sensitivity and specificity were 72.0% (95% confidence interval [CI] 69.8 to 74.2) and 98.9% (95% CI 98.6 to 99.1). When manufacturer instructions were followed, sensitivity increased to 76.3% (95% CI 73.7 to 78.7). Sensitivity was markedly better on samples with lower RT-PCR cycle threshold (Ct) values (97.9% [95% CI 96.9 to 98.9] and 90.6% [95% CI 88.3 to 93.0] for Ct-values <20 and <25, compared to 54.4% [95% CI 47.3 to 61.5] and 18.7% [95% CI 13.9 to 23.4] for Ct-values ≥25 and ≥30) and was estimated to increase by 2.9 percentage points (95% CI 1.7 to 4.0) for every unit decrease in mean Ct-value when adjusting for testing procedure and patients' symptom status. Concordantly, we found the mean Ct-value to be lower for true positive (22.2 [95% CI 21.5 to 22.8]) compared to false negative (30.4 [95% CI 29.7 to 31.1]) results. Testing in the first week from symptom onset resulted in substantially higher sensitivity (81.9% [95% CI 77.7 to 85.5]) compared to testing after 1 week (51.8%, 95% CI 41.5 to 61.9). Similarly, sensitivity was higher in symptomatic (76.2% [95% CI 73.3 to 78.9]) compared to asymptomatic (56.8% [95% CI 50.9 to 62.4]) persons. However, both effects were mainly driven by the Ct-value of the sample. With regards to sample type, highest sensitivity was found for nasopharyngeal (NP) and combined NP/oropharyngeal samples (70.8% [95% CI 68.3 to 73.2]), as well as in anterior nasal/mid-turbinate samples (77.3% [95% CI 73.0 to 81.0]). Our analysis was limited by the included studies' heterogeneity in viral load assessment and sample origination. CONCLUSIONS: Ag-RDTs detect most of the individuals infected with SARS-CoV-2, and almost all (>90%) when high viral loads are present. With viral load, as estimated by Ct-value, being the most influential factor on their sensitivity, they are especially useful to detect persons with high viral load who are most likely to transmit the virus. To further quantify the effects of other factors influencing test sensitivity, standardization of clinical accuracy studies and access to patient level Ct-values and duration of symptoms are needed.

Effectiveness and safety of intrauterine insemination vs. assisted reproductive technology: emulating a target trial using an observational database of administrative claims.

OBJECTIVE: To compare the effectiveness and safety of 1 cycle of assisted reproductive technology (ART) vs. 3 cycles of intrauterine insemination (IUI). DESIGN: Target trial emulation using observational data. SETTING: A healthcare claims database (2011-2015). PATIENT(S): The patients were 29,021 women aged 18-45 years with an infertility diagnosis and no history of IUI or ART within the past 12 months. INTERVENTION(S): One ART cycle immediately, with no more cycles of ART or IUI within the next 4 months; or 1 IUI cycle immediately, with 2 additional consecutive cycles of IUI within the next 4 months unless pregnancy occurred. MAIN OUTCOME MEASURE(S): Live births, multiple births, congenital malformations, preterm births, small-for-gestational-age newborns, large-for-gestational-age newborns, admission to neonatal intensive care unit (NICU), gestational diabetes, preeclampsia, and gestational hypertension. RESULT(S): The probability of live birth was 27.3% for ART and 26.3% for IUI. The observational analogue of per-protocol risk difference (95% confidence interval) for ART compared with IUI was 1.0% (-0.1%, 2.2%) for live births, 4.3% (3.7%, 4.9%) for multiple births, 3.4% (2.8%, 4.0%) for preterm births, 1.5% (0.9%, 2.1%) for NICU admissions, and 0.6% (0.2%, 1.0%) for gestational diabetes. The risk differences for the other outcomes were <0.5%. The results of the 2 strategies were similar in women ≤40 years, but in women >40 years the probability of live birth was greater for ART (14.4%) than for IUI (7.4%). CONCLUSION(S): Compared with 3 cycles of IUI, 1 cycle of ART was estimated to have a similar probability of live birth but slightly higher risks of multiple gestations, preterm births, and NICU admissions.

Expanding the clinical phenotype of FGFR1 internal tandem duplication.

Closed spinal dysraphism (SD) is a type of neural tube defect originating during early embryonic development whereby the neural tissue of the spinal defect remains covered by skin, often coinciding with markers of cutaneous stigmata. It is hypothesized that these events are caused by multifactorial processes, including genetic and environmental causes. We present an infant with a unique congenital midline lesion associated with a closed SD. Through comprehensive molecular profiling of the intraspinal lesion and contiguous skin lesion, an internal tandem duplication (ITD) of the kinase domain of the fibroblast growth factor receptor 1 (FGFR1) gene was found. This ITD variant is somatic mosaic in nature as supported by a diminished variant allele frequency in the lesional tissue and by its absence in peripheral blood. FGFR1 ITD results in constitutive activation of the receptor tyrosine kinase to promote cell growth, differentiation, and survival through RAS/MAPK signaling. Identification of FGFR1 ITD outside of central nervous system tumors is exceedingly rare, and this report broadens the phenotypic spectrum of somatic mosaic FGFR1-related disease.

A deletion in the N gene of SARS-CoV-2 may reduce test sensitivity for detection of SARS-CoV-2.

One SARS-CoV-2-positive sample demonstrated impaired detection of the N1 target by RT-PCR using US CDC primer/probe sets. A 3 nucleotide deletion was discovered that overlaps the forward primer binding site. This finding underscores the importance of continued SARS-CoV-2 mutation surveillance and assessment of the impact on diagnostic test performance.

Revisiting the g-null Paradox.

The (noniterative conditional expectation) parametric g-formula is an approach to estimating causal effects of sustained treatment strategies from observational data. An often-cited limitation of the parametric g-formula is the g-null paradox: a phenomenon in which model misspecification in the parametric g-formula is guaranteed in some settings consistent with the conditions that motivate its use (i.e., when identifiability conditions hold and measured time-varying confounders are affected by past treatment). Many users of the parametric g-formula acknowledge the g-null paradox as a limitation when reporting results but still require clarity on its meaning and implications. Here, we revisit the g-null paradox to clarify its role in causal inference studies. In doing so, we present analytic examples and a simulation-based illustration of the bias of parametric g-formula estimates under the conditions associated with this paradox. Our results highlight the importance of avoiding overly parsimonious models for the components of the g-formula when using this method.

Long-read whole genome sequencing reveals HOXD13 alterations in synpolydactyly.

Synpolydactyly 1, also called syndactyly type II (SDTY2), is a genetic limb malformation characterized by polydactyly with syndactyly involving the webbing of the third and fourth fingers, and the fourth and fifth toes. It is caused by heterozygous alterations in HOXD13 with incomplete penetrance and phenotypic variability. In our study, a five-generation family with an SPD phenotype was enrolled in our Rare Disease Genomics Protocol. A comprehensive examination of three generations using Illumina short-read whole-genome sequencing (WGS) did not identify any causative variants. Subsequent WGS using Pacific Biosciences (PacBio) long-read HiFi Circular Consensus Sequencing (CCS) revealed a heterozygous 27-bp duplication in the polyalanine tract of HOXD13. Sanger sequencing of all available family members confirmed that the variant segregates with affected individuals. Reanalysis of an unrelated family with a similar SPD phenotype uncovered a 21-bp (7-alanine) duplication in the same region of HOXD13. Although ExpansionHunter identified these events in most individuals in a retrospective analysis, low sequence coverage due to high GC content in the HOXD13 polyalanine tract makes detection of these events challenging. Our findings highlight the value of long-read WGS in elucidating the molecular etiology of congenital limb malformation disorders.

Biomarkers That Correlate with Active Pulmonary Tuberculosis Treatment Response: a Systematic Review and Meta-analysis.

Current WHO recommendations for monitoring treatment response in adult pulmonary tuberculosis (TB) are sputum smear microscopy and/or culture conversion at the end of the intensive phase of treatment. These methods either have suboptimal accuracy or a long turnaround time. There is a need to identify alternative biomarkers to monitor TB treatment response. We conducted a systematic review of active pulmonary TB treatment monitoring biomarkers. We screened 9,739 articles published between 1 January 2008 and 31 December 2020, of which 77 met the inclusion criteria. When studies quantitatively reported biomarker levels, we meta-analyzed the average fold change in biomarkers from pretreatment to week 8 of treatment. We also performed a meta-analysis pooling the fold change since the previous time point collected. A total of 81 biomarkers were identified from 77 studies. Overall, these studies exhibited extensive heterogeneity with regard to TB treatment monitoring study design and data reporting. Among the biomarkers identified, C-reactive protein (CRP), interleukin-6 (IL-6), interferon gamma-induced protein 10 (IP-10), and tumor necrosis factor alpha (TNF-α) had sufficient data to analyze fold changes. All four biomarker levels decreased during the first 8 weeks of treatment relative to baseline and relative to previous time points collected. Based on limited data available, CRP, IL-6, IP-10, and TNF-α have been identified as biomarkers that should be further explored in the context of TB treatment monitoring. The extensive heterogeneity in TB treatment monitoring study design and reporting is a major barrier to evaluating the performance of novel biomarkers and tools for this use case. Guidance for designing and reporting treatment monitoring studies is urgently needed.

Discovery of clinically relevant fusions in pediatric cancer.

BACKGROUND: Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. RESULTS: Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient's medical record, both known and novel fusions provided medically meaningful information. CONCLUSIONS: The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

Can we predict the severe course of COVID-19 - a systematic review and meta-analysis of indicators of clinical outcome?

BACKGROUND: COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19. METHODS: This systematic review was registered at PROSPERO under CRD42020177154. We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies. RESULTS: Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10 mg/L, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49 U/L, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88 pg/mL, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 to 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73). DISCUSSION: This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors that predict severe COVID-19 outcomes and will inform clinical scores to support early decision-making.

PTEN somatic mutations contribute to spectrum of cerebral overgrowth.

Phosphatase and tensin homologue (PTEN) regulates cell growth and survival through inhibition of the mammalian target of rapamycin (MTOR) signalling pathway. Germline genetic variation of PTEN is associated with autism, macrocephaly and PTEN hamartoma tumour syndromes. The effect of developmental PTEN somatic mutations on nervous system phenotypes is not well understood, although brain somatic mosaicism of MTOR pathway genes is an emerging cause of cortical dysplasia and epilepsy in the paediatric population. Here we report two somatic variants of PTEN affecting a single patient presenting with intractable epilepsy and hemimegalencephaly that varied in clinical severity throughout the left cerebral hemisphere. High-throughput sequencing analysis of affected brain tissue identified two somatic variants in PTEN. The first variant was present in multiple cell lineages throughout the entire hemisphere and associated with mild cerebral overgrowth. The second variant was restricted to posterior brain regions and affected the opposite PTEN allele, resulting in a segmental region of more severe malformation, and the only neurons in which it was found by single-nuclei RNA-sequencing had a unique disease-related expression profile. This study reveals brain mosaicism of PTEN as a disease mechanism of hemimegalencephaly and furthermore demonstrates the varying effects of single- or bi-allelic disruption of PTEN on cortical phenotypes.

Gastroblastoma with a novel EWSR1-CTBP1 fusion presenting in adolescence.

Gastroblastomas are rare tumors with a biphasic epithelioid/spindle cell morphology that typically present in early adulthood and have recurrent MALAT1-GLI1 fusions. We describe an adolescent patient with Wiskott-Aldrich syndrome who presented with a large submucosal gastric tumor with biphasic morphology. Despite histologic features consistent with gastroblastoma, a MALAT1-GLI1 fusion was not found in this patient's tumor; instead, comprehensive molecular profiling identified a novel EWSR1-CTBP1 fusion and no other significant genetic alterations. The tumor also overexpressed NOTCH and FGFR by RNA profiling. The novel fusion and expression profile suggest a role for epithelial-mesenchymal transition in this tumor, with potential implications for the pathogenesis of biphasic gastric tumors such as gastroblastoma.