| 1. |
- Jin, Ying-Hui, et al.
(författare)
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Chemoprophylaxis, diagnosis, treatments, and discharge management of COVID-19 : An evidence-based clinical practice guideline (updated version)
- 2020
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Ingår i: Military Medical Research. - : Springer Science and Business Media LLC. - 2054-9369. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, coronavirus disease 2019 (COVID-19), affecting more than seventeen million people around the world. Diagnosis and treatment guidelines for clinicians caring for patients are needed. In the early stage, we have issued "A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version)"; now there are many direct evidences emerged and may change some of previous recommendations and it is ripe for develop an evidence-based guideline. We formed a working group of clinical experts and methodologists. The steering group members proposed 29 questions that are relevant to the management of COVID-19 covering the following areas: chemoprophylaxis, diagnosis, treatments, and discharge management. We searched the literature for direct evidence on the management of COVID-19, and assessed its certainty generated recommendations using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Recommendations were either strong or weak, or in the form of ungraded consensus-based statement. Finally, we issued 34 statements. Among them, 6 were strong recommendations for, 14 were weak recommendations for, 3 were weak recommendations against and 11 were ungraded consensus-based statement. They covered topics of chemoprophylaxis (including agents and Traditional Chinese Medicine (TCM) agents), diagnosis (including clinical manifestations, reverse transcription-polymerase chain reaction (RT-PCR), respiratory tract specimens, IgM and IgG antibody tests, chest computed tomography, chest x-ray, and CT features of asymptomatic infections), treatments (including lopinavir-ritonavir, umifenovir, favipiravir, interferon, remdesivir, combination of antiviral drugs, hydroxychloroquine/chloroquine, interleukin-6 inhibitors, interleukin-1 inhibitors, glucocorticoid, qingfei paidu decoction, lianhua qingwen granules/capsules, convalescent plasma, lung transplantation, invasive or noninvasive ventilation, and extracorporeal membrane oxygenation (ECMO)), and discharge management (including discharge criteria and management plan in patients whose RT-PCR retesting shows SARS-CoV-2 positive after discharge). We also created two figures of these recommendations for the implementation purpose. We hope these recommendations can help support healthcare workers caring for COVID-19 patients.
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| 2. |
- Ji, Xinyu, et al.
(författare)
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Epigenetic–smoking interaction reveals histologically heterogeneous effects of TRIM27 DNA methylation on overall survival among early-stage NSCLC patients
- 2020
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Ingår i: Molecular Oncology. - : Wiley. - 1574-7891 .- 1878-0261. ; 14:11, s. 2759-2774
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Tidskriftsartikel (refereegranskat)abstract
- Tripartite motif containing 27 (TRIM27) is highly expressed in lung cancer, including non-small-cell lung cancer (NSCLC). Here, we profiled DNA methylation of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tumours from 613 early-stage NSCLC patients and evaluated associations between CpG methylation of TRIM27 and overall survival. Significant CpG probes were confirmed in 617 samples from The Cancer Genome Atlas. The methylation of the CpG probe cg05293407TRIM27 was significantly associated with overall survival in patients with LUSC (HR = 1.65, 95% CI: 1.30–2.09, P = 4.52 × 10−5), but not in patients with LUAD (HR = 1.08, 95% CI: 0.87–1.33, P = 0.493). As incidence of LUSC is associated with higher smoking intensity compared to LUAD, we investigated whether smoking intensity impacted on the prognostic effect of cg05293407TRIM27 methylation in NSCLC. LUSC patients had a higher average pack-year of smoking (37.49LUAD vs 54.79LUSC, P = 1.03 × 10−19) and included a higher proportion of current smokers than LUAD patients (28.24%LUAD vs 34.09%LUSC, P = 0.037). cg05293407TRIM27 was significantly associated with overall survival only in NSCLC patients with medium–high pack-year of smoking (HR = 1.58, 95% CI: 1.26–1.96, P = 5.25 × 10−5). We conclude that cg05293407TRIM27 methylation is a potential predictor of LUSC prognosis, and smoking intensity may impact on its prognostic value across the various types of NSCLC.
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| 3. |
- Zhang, Ruyang, et al.
(författare)
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Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects
- 2020
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Ingår i: Chest. - : Elsevier BV. - 0012-3692. ; 158:2, s. 808-819
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Tidskriftsartikel (refereegranskat)abstract
- Background: DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions. Research Question: Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis? Study Design and Methods: Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated. Results: Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10–17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10–18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC3 year, 0.88 [95% CI, 0.83-0.93]; and AUC5 year, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively. Interpretation: The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.
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