Adjuvant Treatment Following Irradical Resection of Stage I-III Non-small Cell Lung Cancer: A Population-based Study

Irradical (R1-2) resection for non-small cell lung cancer (NSCLC) is associated with a dismal prognosis. Adjuvant treatment attempts to improve survival outcomes, but evidence on the optimal strategy is limited. The purpose of this study was to compare overall survival (OS) between different adjuvant treatment strategies in these patients. Out of 8,528 patients with newly diagnosed NSCLC from 2015-2018, those with an R1-2 resection were identified from the Netherlands Cancer Registry. First, OS was compared between adjuvant treatment groups 'no therapy', 'radiotherapy (RT) only', 'chemotherapy only', and 'chemo- and radiotherapy (CRT)' using multinomial propensity score-weighted Cox regression analysis. Second, three 1:1 propensity score-matched sets were created for chemotherapy vs no chemotherapy, RT only vs no therapy, and CRT vs chemotherapy only. Kaplan-Meier and Cox regression analyses for OS were performed in each set. With a median follow-up of 23 months, 427 patients were selected. In the weighted regression analysis, compared to no adjuvant therapy, chemotherapy and CRT were associated with improved OS (HR 0.41, 95%CI: 0.22-0.76; and HR 0.55, 95%CI: 0.37-0.81, respectively), whereas RT was not (HR 1.04, 95%CI: 0.73-1.50). In the matched sets, OS was improved after chemotherapy (+/- RT) compared to no chemotherapy (HR 0.47, 95%CI: 0.32-0.69). No OS difference was observed between matched groups of RT only vs no adjuvant therapy (HR 1.13, 95%CI: 0.74-1.72), nor for CRT vs chemotherapy only (HR 1.37, 95%CI: 0.70-2.71). Adjuvant chemotherapy, but not radiotherapy, improves survival after an R1-2 resection in stage I-III NSCLC

Healthcare consumption of patients with left ventricular assist device: real-world data

BACKGROUND: A left ventricular assist device (LVAD) is a life-saving but intensive therapy for patients with end-stage heart failure. We evaluated the healthcare consumption in a cohort of LVAD patients in our centre over 6 years. METHODS: All patients with a primary LVAD implantation at the University Medical Centre Utrecht in Utrecht, the Netherlands from 2016 through 2021 were included in this analysis. Subsequent hospital stay, outpatient clinic visits, emergency department visits and readmissions were recorded. RESULTS: During the investigated period, 226 LVADs were implanted, ranging from 32 in 2016 to 45 in 2020. Most LVADs were implanted in patients aged 40-60 years, while they were supported by or sliding on inotropes (Interagency Registry for Mechanically Assisted Circulatory Support class 2 or 3). Around the time of LVAD implantation, the median total hospital stay was 41 days. As the size of the LVAD cohort increased over time, the total annual number of outpatient clinic visits also increased, from 124 in 2016 to 812 in 2021 (p = 0.003). The numbers of emergency department visits and readmissions significantly increased in the 6‑year period as well, with a total number of 553 emergency department visits and 614 readmissions. Over the years, the annual number of outpatient clinic visits decreased by 1 per patient-year follow-up, while the annual numbers of emergency department visits and readmissions per patient-year remained stable. CONCLUSION: The number of patients supported by an LVAD has grown steadily over the last years, requiring a more specialised healthcare in this particular population

Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD

Accurate non-invasive biomarkers to diagnose metabolic dysfunction-associated steatotic liver disease (MASLD)-related fibrosis are urgently needed. This study applies a translational approach to develop a blood-based biomarker panel for fibrosis detection in MASLD. A molecular gene expression signature identified from a diet-induced MASLD mouse model (LDLr−/−.Leiden) is translated into human blood-based biomarkers based on liver biopsy transcriptomic profiles and protein levels in MASLD patient serum samples. The resulting biomarker panel consists of IGFBP7, SSc5D and Sema4D. LightGBM modeling using this panel demonstrates high accuracy in predicting MASLD fibrosis stage (F0/F1: AUC = 0.82; F2: AUC = 0.89; F3/F4: AUC = 0.87), which is replicated in an independent validation cohort. The overall accuracy of the model outperforms predictions by the existing markers Fib-4, APRI and FibroScan. In conclusion, here we show a disease mechanism-related blood-based biomarker panel with three biomarkers which is able to identify MASLD patients with mild or advanced hepatic fibrosis with high accuracy.</p

Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD

Accurate non-invasive biomarkers to diagnose metabolic dysfunction-associated steatotic liver disease (MASLD)-related fibrosis are urgently needed. This study applies a translational approach to develop a blood-based biomarker panel for fibrosis detection in MASLD. A molecular gene expression signature identified from a diet-induced MASLD mouse model (LDLr−/−.Leiden) is translated into human blood-based biomarkers based on liver biopsy transcriptomic profiles and protein levels in MASLD patient serum samples. The resulting biomarker panel consists of IGFBP7, SSc5D and Sema4D. LightGBM modeling using this panel demonstrates high accuracy in predicting MASLD fibrosis stage (F0/F1: AUC = 0.82; F2: AUC = 0.89; F3/F4: AUC = 0.87), which is replicated in an independent validation cohort. The overall accuracy of the model outperforms predictions by the existing markers Fib-4, APRI and FibroScan. In conclusion, here we show a disease mechanism-related blood-based biomarker panel with three biomarkers which is able to identify MASLD patients with mild or advanced hepatic fibrosis with high accuracy.</p

Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data

BACKGROUND: Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non–poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints. RESULTS: We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA–minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG–positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq. CONCLUSION: By using the full potential of non–poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects

Endosonography With or Without Confirmatory Mediastinoscopy for Resectable Lung Cancer:A Randomized Clinical Trial

PURPOSE:Resectable non-small-cell lung cancer (NSCLC) with a high probability of mediastinal nodal involvement requires mediastinal staging by endosonography and, in the absence of nodal metastases, confirmatory mediastinoscopy according to current guidelines. However, randomized data regarding immediate lung tumor resection after systematic endosonography versus additional confirmatory mediastinoscopy before resection are lacking.METHODS:Patients with (suspected) resectable NSCLC and an indication for mediastinal staging after negative systematic endosonography were randomly assigned to immediate lung tumor resection or confirmatory mediastinoscopy followed by tumor resection. The primary outcome in this noninferiority trial (noninferiority margin of 8% that previously showed to not compromise survival, Pnoninferior &lt;.0250) was the presence of unforeseen N2 disease after tumor resection with lymph node dissection. Secondary outcomes were 30-day major morbidity and mortality.RESULTS:Between July 17, 2017, and October 5, 2020, 360 patients were randomly assigned, 178 to immediate lung tumor resection (seven dropouts) and 182 to confirmatory mediastinoscopy first (seven dropouts before and six after mediastinoscopy). Mediastinoscopy detected metastases in 8.0% (14/175; 95% CI, 4.8 to 13.0) of patients. Unforeseen N2 rate after immediate resection (8.8%) was noninferior compared with mediastinoscopy first (7.7%) in both intention-to-treat (Δ, 1.03%; UL 95% CIΔ, 7.2%; Pnoninferior =.0144) and per-protocol analyses (Δ, 0.83%; UL 95% CIΔ, 7.3%; Pnoninferior =.0157). Major morbidity and 30-day mortality was 12.9% after immediate resection versus 15.4% after mediastinoscopy first (P =.4940).CONCLUSION:On the basis of our chosen noninferiority margin in the rate of unforeseen N2, confirmatory mediastinoscopy after negative systematic endosonography can be omitted in patients with resectable NSCLC and an indication for mediastinal staging.</p

Physical exercise volume, type, and intensity and risk of all-cause mortality and cardiovascular events in patients with cardiovascular disease: a mediation analysis

AIMS: To estimate the relation between physical exercise volume, type, and intensity with all-cause mortality and recurrent vascular events in patients with cardiovascular disease (CVD) and to quantify to what extent traditional cardiovascular risk factors mediate these relations. METHODS AND RESULTS: In the prospective UCC-SMART cohort ( N = 8660), the associations of clinical endpoints and physical exercise volume (metabolic equivalent of task hours per week, METh/wk), type (endurance vs. endurance + resistance), and intensity (moderate vs. vigorous) were estimated using multivariable-adjusted Cox models. The proportion mediated effect (PME) through body mass index, systolic blood pressure, low-density lipoprotein cholesterol, insulin sensitivity, and systemic inflammation was assessed using structural equation models. Sixty-one percent of patients (73% male, age 61 ± 10 years, >70% receiving lipid-lowering and blood pressure-lowering medications) reported that they did not exercise. Over a median follow-up of 9.5 years [interquartile range (IQR) 5.1-14.0], 2256 deaths and 1828 recurrent vascular events occurred. The association between exercise volume had a reverse J-shape with a nadir at 29 (95% CI 24-29) METh/wk, corresponding with a HR 0.56 (95% CI 0.48-0.64) for all-cause mortality and HR 0.63 (95% CI 0.55-0.73) for recurrent vascular events compared with no exercise. Up to 38% (95% CI 24-61) of the association was mediated through the assessed risk factors of which insulin sensitivity (PME up to 12%, 95% CI 5-25) and systemic inflammation (PME up to 18%, 95% CI 9-37) were the most important. CONCLUSION: Regular physical exercise is significantly related with reduced risks of all-cause mortality and recurrent vascular events in patients with CVD. In this population with high rates of lipid-lowering and blood pressure--lowering medication use, exercise benefits were mainly mediated through systemic inflammation and insulin resistance

Effects of copy number variations on brain structure and risk for psychiatric illness: large-scale studies from the ENIGMA working groups on CNVs

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.Funding information: European Union's Horizon2020 Research and Innovation Programme, Grant/Award Number: CoMorMent project; Grant #847776; KG Jebsen Stiftelsen; National Institutes of Health, Grant/Award Number: U54 EB020403; Norges Forskningsråd, Grant/Award Number: #223273; South-Eastern Norway Regional Health Authority, Grant/Award Number: #2020060ACKNOWLEDGMENTS: The ENIGMA Consortium is supported by the NIH Big Data to Knowledge (BD2K) program under consortium grant number U54 EB020403 (PI: Thompson). OAA is supported by the Research Council of Norway, South East Norway Health Authority, KG Jebsen Stiftelsen, EU H2020. C. A. has been funded by the Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/ 024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM; Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds; European Union Seventh Framework Program under grant agreements FP7-4-HEALTH-2009-2.2.1-2-241,909 (Project EU-GEI), FP7- HEALTH-2013-2.2.1-2-603,196 (Project PSYSCAN) and FP7- HEALTH-2013- 2.2.1-2-602,478 (Project METSY); and European Union H2020 Program under the Innovative Medicines Initiative two Joint Undertaking (grant agreement No 115916, Project PRISM, and grant agreement No 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso and Fundación Alicia Koplowitz. R. A-A is funded by a Miguel Servet contract from the Carlos III Health Institute (CP18/00003). G. B. is supported by the Dutch Organization for Health Research and Development ZonMw (grants 91112002 & 91712394). A. S. B. is supported by the Dalglish Family Chair in 22q11.2 Deletion Syndrome, Canadian Institutes of Health Research (CIHR) grants MOP-79518, MOP89066, MOP-97800 and MOP-111238, and NIMH grant number U01 MH101723–01(3/5). C. E. B. is also supported by the National Institute of Mental Health: RO1 MH085953, R01 MH100900 and 1U01MH119736. N. E. B. is granted the KNAW Academy Professor Award (PAH/6635). V. D. C. is supported by NIH R01 MH094524. S. C. is supported by the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3); Helmholtz Initiative and Networking Fund. C. R. K. C. is supported by NIA T32AG058507. E. W. C. C. is supported by the Canadian Institutes of Health Research, Ontario Mental Health Foundation grant MOP-74631 and NIMH grant U01MH101723–01(3/5). S. Ci. has received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3). M. C. C. is supported by the Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. N. A. C. is supported by Agencia Nacional de Investigación y Desarrollo (ANID Chile) PIA ACT192064. GId. Z. is supported by the NHMRC. J. L. D. and D. E. J. L. are supported by the Wellcome Trust. T. B. C. is supported by NICHD grant PO1-HD070454, NIH grant UO1-MH191719, and NIMH grant R01 MH087636-01A1. AMD is supported by U24DA041147. B. D. is supported by the Swiss National Science Foundation (NCCR Synapsy, project grant numbers 32003B_135679, 32003B_159780, 324730_192755 and CRSK3_190185), the Leenaards Foundation and the Roger De Spoelberch Foundation. SE is supported by the NARSAD-Young Investigator Grant “Epigenetic Regulation of Intermediate Phenotypes in Schizophrenia”. B. E. S. is supported by the NIH (NIMH). D. C. G. is supported by NIH grant numbers MH078143, MH083824, AG058464. W. R. K. is supported by NIH/MH R0106824. R. E. G. is supported by NIH/NIMH grant numbers MH087626, MH119737. DMMcD-McG is supported by National Institutes of Mental Health (NIMH), grant numbers MH119737-02; MH191719; and MH087636-01A1. S. E. M. is supported by NHMRC grants APP1103623; APP1158127; APP1172917. TM is supported by Research Council of Norway - grant number 273345. D. G. M. is supported by the National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London and S (European Autism Interventions)/EU AIMS-2-TRIALS, a European Innovative Medicines Initiative Joint Undertaking under grant agreements 115300 and 777394. T. N. was supported by Stiftelsen KG Jebsen under grant number SKGJ-MED-021. R. A. O. is supported by NIMH R01 MH090553. S. Y. S. has been funded by the Canadain Institutes of Health Research. M. J. O. is supported by MRC Centre grant MR/L010305/1 and Wellcome Trust grant 100,202/Z/12/Z; Dr. Owen has received research support from Takeda. Z. P. is supported by CIHR, CFI, HSFC. B. G. P. is supported by CIHR FDN 143290 and CAIP Chair. G. M. R. is supported by Fondecyt-Chile #1171014 and ANID-Chile ACT192064. A. Re. was supported by a grant from the Swiss National Science Foundation (31003A_182632). DRR is supported by R01 MH120174 (PI: Roalf). This report represents independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London (to J. J. R). PSS is supported by NHMRC (Australia) program grant 1093083. J. E. S. is supported by NIH K01-ES026840. S. M. S. is supported by the Epilepsy Society. T. J. S. is supported by NIH grants R01MH107108, R01HD042794, and HDU54079125. I. E. S. is supported by South-Eastern Norway Regional Health Authority (#2020060), European Union's Horizon2020 Research and Innovation Programme (CoMorMent project; grant #847776) and the KG Jebsen Foundation (SKGJ-MED-021). V. M. S. is supported by Research Council of Norway (CoE funding scheme, grant number 223273). D. J. S. is supported by the SA MRC. C. K. T. is supported by Research Council of Norway (#230345, #288083, #223273) and South-Eastern Norway Regional Health Authority (#2019069, #2021070, #500189). D. T.-G. was supported by the Instituto de Salud Carlos III (PI14/00639 and PI14/00918) and Fundación Instituto de Investigación Marqués de Valdecilla (NCT0235832 and NCT02534363). Dvd. M. is supported by Research Council of Norway #276082. F. V. R. is supported by the Michael Smith Foundation for Health Research Scholar Award. deCODE genetics has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreements' no. 115008 (NEWMEDS) and no. 115300 (EUAIMS), of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union's Seventh Framework Programme (EU-FP7/ 2007–2013). L. T. W. is supported by Research Council of Norway, European Research Council. The IDIVAL neuroimage unit is supported by Instituto de Salud Carlos III PI020499, research funding SCIII-INT13/0014, MICINN research funding SAF2010-20840-C02- 02, SAF2013-46292-R. The TOP/NORMENT study are supported by the Research Council of Norway (#223273). The GOBS study data collection was supported in part by the National Institutes of Health (NIH) grants: R01 MH078143, R01 MH078111, and R01 MH083824 with work conducted in part in facilities constructed under the support of NIH grant number C06 RR020547. The Sydney Memory and Ageing Study has been funded by three National Health & Medical Research Council (NHMRC) Program Grants (ID No. ID350833, ID568969, and APP1093083). We thank the participants and their informants for their time and generosity in contributing to this research. We also acknowledge the MAS research team: https://cheba.unsw.edu.au/researchprojects/sydney-memory-and-ageing-study. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/ project/older-australian-twins-study) to this study. The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Aging Well, Aging Productively Program (ID No. 401162); NHMRC Project (seed) Grants (ID No. 1024224 and 1025243); NHMRC Project Grants (ID No. 1045325 and 1085606); and NHMRC Program Grants (ID No. 568969 and 1093083). We thank the participants for their time and generosity in contributing to this research. This research was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research Excellence Grant (ID No. 1079102) from the National Health and Medical Research Council. The NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the KG Jebsen Foundation, the Research Council of Norway, to S. L. H., V. M. S., A. J. L., and T. E. The authors thank Dr. Eike Wehling for recruiting participants in Bergen, and Professor Jonn-Terje Geitung and Haraldplass Deaconess Hospital for access to the MRI facility. Additional support by RCN grants 177458/V50 and 231286/F20. The Betula study was supported by a Wallenberg Scholar Grant (KAW). The HUNT Study is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU—Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. Research for the GAP cohort was supported by the Department of Health via the National Institute for Health Research (NIHR) Specialist Biomedical Research Center for Mental Health award to South London and Maudsley NHS Foundation Trust (SLaM) and the Institute of Psychiatry at King's College London, London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. S.J. is supported by Calcul Quebec (http:// www.calculquebec.ca), Compute Canada (http://www.computecanada. ca), the Brain Canada Multi investigator research initiative (MIRI), the Institute of Data Valorization (Canada First Research Excellence Fund), CHIR, Canada Research Chairs and the Jeanne et Jean Louis Levesque Foundation. The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO), MW904-61-193 (de Geus & Boomsma), MaGWnr: 400-07-080 (van 't Ent), MagW 480-04-004 (Boomsma), NWO/SPI 56-464-14,192 (Boomsma), the European Research Council, ERC-230374 (Boomsma), and Amsterdam Neuroscience. Funding for genotyping was obtained from the National Institutes of Health (NIMH U24 MH068457-06; Grand Opportunity grants 1RC2 MH089951, and 1RC2 MH089995); the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Boomsma), 51.02.060 (Hilleke Hulshoff Pol), 668.772 (Boomsma & Hulshoff Pol); NWO/SPI 56-464-14192 (Boomsma), the European Research Council (ERC230374) (Boomsma), High Potential Grant Utrecht University (Hulshoff Pol), NWO Brain and Cognition 433-09-220 (Hulshoff Pol). SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide SNP typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The ENIGMA-22q11.2 Deletion Syndrome Working Group wishes to acknowledge our dear colleague Dr. Clodagh Murphy, who sadly passed away in April 2020. Open access funding enabled and organized by Projekt DEAL