Kooperativer Bibliotheksverbund

In: Journal of Instrumentation, IOP Publishing, Vol. 17, No. 01 ( 2022-01-01), p. P01013-

Abstract: The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector. It consists of 4088 silicon strip sensor modules. During Run 2 (2015–2018) the Large Hadron Collider delivered an integrated luminosity of 156 fb -1 to the ATLAS experiment at a centre-of-mass proton-proton collision energy of 13 TeV. The instantaneous luminosity and pile-up conditions were far in excess of those assumed in the original design of the SCT detector. Due to improvements to the data acquisition system, the SCT operated stably throughout Run 2. It was available for 99.9% of the integrated luminosity and achieved a data-quality efficiency of 99.85%. Detailed studies have been made of the leakage current in SCT modules and the evolution of the full depletion voltage, which are used to study the impact of radiation damage to the modules.

Type of Medium: Online Resource

ISSN: 1748-0221

URL: Article

DOI: 10.1088/1748-0221/17/01/P01013

Language: Unknown

Publisher: IOP Publishing

Publication Date: 2022

detail.hit.zdb_id: 2235672-1

In: Journal of Instrumentation, IOP Publishing, Vol. 17, No. 03 ( 2022-03-01), p. P03014-

Abstract: Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.

Type of Medium: Online Resource

ISSN: 1748-0221

URL: Article

DOI: 10.1088/1748-0221/17/03/P03014

Language: Unknown

Publisher: IOP Publishing

Publication Date: 2022

detail.hit.zdb_id: 2235672-1

In: GeroScience, Springer Science and Business Media LLC, Vol. 44, No. 3 ( 2022-06), p. 1641-1655

Abstract: Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Type of Medium: Online Resource

ISSN: 2509-2715 , 2509-2723

URL: Article

DOI: 10.1007/s11357-022-00547-x

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2022

detail.hit.zdb_id: 2886418-9

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 4337-4337

Abstract: PD-L1 immunohistochemistry (IHC) is routinely used to predict the clinical response to immune checkpoint inhibitors (ICIs); however, multiple assays and antibodies have been used. This study aimed to evaluate the potential of targeted transcriptome and artificial intelligence (AI) to determine PD-L1 RNA expression levels and predict the ICI response compared to traditional IHC. RNA from 396 solid tumors samples was sequenced using next-generation sequencing (NGS) with a targeted 1408-gene panel. RNA expression and PD-L1 IHC were assessed across a broad range of PD-L1 expression levels. The geometric mean naïve Bayesian (GMNB) classifier was used to predict the PD-L1 status. PD-L1 RNA levels assessed by NGS demonstrated robust linearity across high and low expression ranges, and those assessed using NGS and IHC (Tumor cells (TC), Tumor Proportion Score (TPS) and tumor-infiltrating immune cells (ICs) were highly correlated (Tables 1). RNA sequencing provided in-depth information on the tumor microenvironment and immune response, including CD19, CD22, CD8A, CTLA4, and PD-L2 expression status. Sub-analyses showed a sustained correlation of mRNA expression with IHC (TPS and ICs) across different solid tumor types. Machine learning showed high accuracy in predicting PD-L1 status, with the area under the curve varying between 0.988 and 0.920. Targeted transcriptome sequencing combined with AI is highly useful for predicting PD-L1 status. Measuring PD-L1 mRNA expression by NGS is comparable to measuring PD-L1 expression by IHC for predicting ICI response. RNA expression has the added advantages of being amenable to standardization and avoidance of interpretation bias, along with an in-depth evaluation of the tumor microenvironment. Correlation between PD-L1 expression levels and PD-L1 IHC results IHC test results Variable Cases (N) Mean Median Range Lower Quartile Upper Quartile 10th Percentile 90th Percentile Std. Dev. TC & lt;1% CD274 223.00 4.49 2.97 0.00 - 25.99 1.79 5.73 1.07 9.16 4.32 TC & gt;1% CD274 90.00 14.87 10.11 0.62 - 77.53 4.60 18.62 2.95 32.35 15.75 TC & lt;10% CD274 267.00 5.17 3.36 0.00 - 72.72 1.94 6.43 1.14 10.71 6.14 TC & gt;10% CD274 46.00 20.81 14.03 2.90 - 77.53 8.67 26.32 4.21 51.02 17.33 IC & lt;1% CD274 133.00 3.95 2.66 0.00 - 25.99 1.71 4.03 0.99 7.95 4.56 IC & gt;1% CD274 129.00 9.38 5.43 0.29 - 77.53 3.21 10.31 1.74 19.05 12.13 IC & lt;10% CD274 226.00 5.69 3.03 0.00 - 72.72 1.92 6.09 1.15 12.25 8.24 IC & gt;10% CD274 36.00 12.50 8.52 0.29 - 77.53 4.72 13.80 4.18 31.83 13.95 TPS & lt;1% CD274 143.00 3.36 2.35 0.00 - 25.99 1.41 3.58 0.53 7.40 3.87 TPS & gt;1% CD274 207.00 10.19 5.63 0.29 - 133.81 3.03 11.65 1.74 22.25 14.74 TPS & lt;10% CD274 252.00 4.25 2.87 0.00 - 72.72 1.74 4.96 0.92 8.70 5.81 TPS & gt;10% CD274 98.00 15.50 9.67 0.29 - 133.81 4.91 18.74 2.90 31.87 18.57 TPS & lt;30% CD274 319.00 5.35 3.32 0.00 - 72.72 1.94 6.43 1.06 12.00 6.48 TPS & gt;30% CD274 31.00 28.50 18.62 2.90 - 133.81 11.47 35.94 6.67 52.69 27.31 Citation Format: Ahmad Charifa, Alfonso Lam, Hong Zhang, Andrew Ip, Andrew Pecora, Stanley Waintraub, Deena Graham, Donna McNamara, Martin Gutierrez, Andrew Jennis, Ipsa Sharma, Jeffrey Estella, Wanlong Ma, Andre Goy, Maher Albitar. Predicting PD-L1 status in solid tumors using transcriptomic data and artificial intelligence algorithms. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4337.

Type of Medium: Online Resource

ISSN: 1538-7445

URL: Article

DOI: 10.1158/1538-7445.AM2023-4337

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2023

detail.hit.zdb_id: 2036785-5

detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: PLOS ONE, Public Library of Science (PLoS), Vol. 16, No. 7 ( 2021-7-30), p. e0255228-

Abstract: The development of a prognostic mortality risk model for hospitalized COVID-19 patients may facilitate patient treatment planning, comparisons of therapeutic strategies, and public health preparations. Methods We retrospectively reviewed the electronic health records of patients hospitalized within a 13-hospital New Jersey USA network between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2, with follow-up through May 29, 2020. With death or hospital discharge by day 40 as the primary endpoint, we used univariate followed by stepwise multivariate proportional hazard models to develop a risk score on one-half the data set, validated on the remainder, and converted the risk score into a patient-level predictive probability of 40-day mortality based on the combined dataset. Results The study population consisted of 3123 hospitalized COVID-19 patients; median age 63 years; 60% were men; 42% had 〉 3 coexisting conditions. 713 (23%) patients died within 40 days of hospitalization for COVID-19. From 22 potential candidate factors 6 were found to be independent predictors of mortality and were included in the risk score model: age, respiratory rate ≥25/minute upon hospital presentation, oxygenation 〈 94% on hospital presentation, and pre-hospital comorbidities of hypertension, coronary artery disease, or chronic renal disease. The risk score was highly prognostic of mortality in a training set and confirmatory set yielding in the combined dataset a hazard ratio of 1.80 (95% CI, 1.72, 1.87) for one unit increases. Using observed mortality within 20 equally sized bins of risk scores, a predictive model for an individual’s 40-day risk of mortality was generated as -14.258 + 13.460*RS + 1.585*(RS–2.524)^2–0.403*(RS–2.524)^3. An online calculator of this 40-day COVID-19 mortality risk score is available at www.HackensackMeridianHealth.org/CovidRS . Conclusions A risk score using six variables is able to prognosticate mortality within 40-days of hospitalization for COVID-19. Trial registration Clinicaltrials.gov Identifier: NCT04347993 .

Type of Medium: Online Resource

ISSN: 1932-6203

URL: Article

URL: Article

URL: Article

URL: Article

URL: Article

URL: Article

URL: Article

URL: Article

DOI: 10.1371/journal.pone.0255228

DOI: 10.1371/journal.pone.0255228.g001

DOI: 10.1371/journal.pone.0255228.g002

DOI: 10.1371/journal.pone.0255228.g003

DOI: 10.1371/journal.pone.0255228.g004

DOI: 10.1371/journal.pone.0255228.t001

DOI: 10.1371/journal.pone.0255228.t002

DOI: 10.1371/journal.pone.0255228.t003

Language: English

Publisher: Public Library of Science (PLoS)

Publication Date: 2021

detail.hit.zdb_id: 2267670-3

In: Blood, American Society of Hematology, Vol. 138, No. Supplement 1 ( 2021-11-05), p. 2892-2892

Abstract: Introduction: Acute graft-vs.-host disease (aGVHD) remains a major diagnostic and clinical problem in patients after allogenic hematopoietic stem cell transplant (HSCT). Finding biomarkers that play a role in aGVHD not only helps in predicting and diagnosing aGVHD, but might help in developing prophylaxis and therapeutic approaches. Using Next Generation Sequencing (NGS) and targeted RNA sequencing along with a machine learning approach to predict, we investigated the potential of discovering new biomarkers that can predict aGVHD. Methods: RNA extracted from bone marrow aspiration samples collected around day 90 post HSCT from 46 patients were sequenced using 1408 targeted genes. cDNA was first generated, then adapters were ligated. The coding regions of the expressed genes were captured from this library using sequence-specific probes to create the final library. Sequencing was performed using an Illumina NextSeq 550 platform. Ten million reads per sample in a single run were required. Read length was 2 × 150 bp. Expression profile was generated using Cufflinks. A machine learning system is developed to predict the GVHD cases and to discover the relevant genes. A subset of genes relevant to GVHD is automatically selected for the classification system, based on a k-fold cross-validation procedure (with k=10). For an individual gene, a Naïve Bayesian classifier was constructed on the training of k-1 subsets and tested on the other testing subset. To eliminate the underflow problem commonly associated with the standard Naïve Bayesian classifiers, we applied Geometric Mean Naïve Bayesian (GMNB) as the classifier to predict GVHD. The processes of gene selection and GVHD classification are applied iteratively to obtain an optimal classification system and a subset of genes relevant to GVHD. Results: The analyzed bone marrow samples included patients transplanted for aplastic anemia (#1), acute lymphoblastic leukemia (#9), acute myeloid leukemia (#16), mixed phenotype acute leukemia (#1), myelodysplastic syndrome (#10), chronic myelomonocytic leukemia (#5), and myeloproliferative neoplasm (#4). Of the 46 patients, 30 (65%) had a diagnosis of aGVHD (grade 2-4). The GMNB modified Bayesian model selected 7 genes as top classifiers. These top classifier genes included Class II Major Histocompatibility gene (CIITA), B-cell markers genes (CD19 and CD22), early T-cell related gene (TCL1A), hematopoietic-specific transcription factor (IKZF3), a gene involved in protein-protein interaction, and a gene involved in DNA helicase nucleotide excision repair (ERCC3). When these 7 genes were used in GMNB-modified classifier with 10-fold cross validation to predict aGVHD, the model classified 28 of the 30 positive cases accurately and 14 of the 16 negative cases accurately. The sensitivity was 93% (95% CI, 76%-99%). The specificity was 87.5% (95% CI: 60%-97%). The positive predictive value (PPV) was 93% (95% CI: 76%-99%) and the negative predictive value (NPV) was 87.5% (95% CI: 60%-98%). Conclusion: While most biomarker discovery has been focused on inflammatory cytokines, chemokines, and their receptors, our data suggest that hematopoietic proliferation and transcription regulators in bone marrow might provide important information for the diagnosis and prediction of aGVHD. This data suggests that biomarkers related to B-cell, T-cell, and MHC play a role in aGVHD at the bone marrow level. These findings also suggest that targeting these biomarkers in the bone marrow might be a realistic approach for prophylaxis and treatment that needs to be explored. Although further validation is needed, this study suggests that targeted RNA sequencing by NGS combined with machine learning algorithm can be a practical and cost-effective approach for the diagnosis and prediction of aGVHD. Figure 1 Figure 1. Disclosures Pecora: Genetic testing cooperative: Other: equity investor; Genetic testing cooperative: Membership on an entity's Board of Directors or advisory committees. Goy: Rosewell Park: Consultancy; Elsevier's Practice Update Oncology, Intellisphere, LLC(Targeted Oncology): Consultancy; Acerta: Consultancy, Research Funding; Genentech/Hoffman la Roche: Research Funding; Vincerx pharma: Membership on an entity's Board of Directors or advisory committees; Physicians' Education Resource: Consultancy, Other: Meeting/travel support; Vincerx: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Xcenda: Consultancy; Janssen: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; OncLive Peer Exchange: Honoraria; Xcenda: Consultancy, Honoraria; AbbVie/Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; COTA (Cancer Outcome Tracking Analysis): Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Other: Leadership role; Elsevier PracticeUpdate: Oncology: Consultancy, Honoraria; Infinity/Verastem: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol Meyers Squibb: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Honoraria, Other; Genomic Testing Cooperative: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Other: Leadership role; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; Hoffman la Roche: Consultancy; Michael J Hennessey Associates INC: Consultancy; LLC(Targeted Oncology): Consultancy; Medscape: Consultancy; Bristol Meyers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie/Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Honoraria; Constellation: Research Funding; Janssen: Research Funding; Karyopharm: Research Funding; Phamacyclics: Research Funding; Hackensack Meridian Health, Regional Cancer Care Associates/OMI: Current Employment. Rowley: ReAlta Life Sciences: Consultancy.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood-2021-147583

Language: English

Publisher: American Society of Hematology

Publication Date: 2021

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 138, No. Supplement 1 ( 2021-11-05), p. 3463-3463

Abstract: Introduction: Cytogenetic analysis is important for stratifying patients with various myeloid neoplasms. It has been reported that whole-genome sequencing can be used as an alternative to cytogenetic analysis in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). With the increasing use of liquid biopsy in the diagnosis and monitoring of patients with various types of neoplasms, we explored the potential of using liquid biopsy and next generation sequencing (NGS) in detecting chromosomal structural abnormalities or copy number variation (CNV) in patients with myeloid neoplasms. For practical approach and for capturing single nucleotide variants (SNV) and to achieve enough depth in sequencing, we used targeted sequencing for determining the chromosomal structural abnormalities in cell-free DNA (cfDNA) in patients with myeloid neoplasms. Methods: Peripheral blood plasma samples from 144 patients with myeloid neoplasms were used to extract cfDNA for NGS testing. This included 49 patients with MDS, 31 with AML, and 64 patients with myeloproliferative neoplasms (MPN). The median age was 68.5 (range: 24-96); 56 (39%) were female. cfDNA was sequenced using 275 gene panel. The panel uses single primer extension (SPE) approach with UMI. Sequencing depth was increased to more than 1000X (after removing duplicates). CNVkit software was used for analyzing and visualizing copy number variations. All samples were confirmed to be diagnostic by showing mutations in diagnostic genes with variant allele frequency & gt;20% or by showing diagnostic chromosomal structural abnormalities (e.g., 5q deletion in MDS, 5q- syndrome). Cytogenetic data on 35 corresponding bone marrow samples (18 AML and 17 MDS) were available for comparison. Results: Of the 144 samples, 47 (33%) showed chromosomal structural abnormalities. In the AML group, 20 of 31 (65%) showed cytogenetic abnormalities by cfDNA testing. Of these positive AML patients, 18 (90%) (58% of total AML) had poor-risk cytogenetics. Therefore, the AML patients with normal cytogenetics or cytogenetic abnormalities other than high-risk constituted 42% of total AML patients. Of the MDS group, 11 of 49 MDS patients (22%) showed cytogenetic abnormalities by cfDNA testing, 6 of whom (54.5%) had high-risk cytogenetics. Overall, 12% of all MDS had poor-risk cytogenetics by cfDNA testing. In the MPN group, 16 of 64 (25%) showed cytogenetic abnormalities, 2 of which (12.5%) had 7q deletion (3% of all MPN); the rest (87.5%) of cytogenetic-positive MPN (22% of total MPN) had other abnormalities including 20q-, +8, 12q, 17p-, 11q-, trisomy 9, trisomy 21 and others. To compare chromosomal abnormalities as detected by cfDNA NGS testing with conventional cytogenetic analysis of corresponding bone marrow samples, we classified cytogenetic findings based on risk stratification into either intermediate-risk or poor-risk. Of the 36 cases, there was 100% concordance between cfDNA data and cytogenetic data when findings were grouped based on risk classification. Two of the conventional cytogenetic samples showed no metaphases while one showed intermediate-risk abnormalities by cfDNA NGS analysis and the second showed poor-risk cytogenetic abnormalities by cfDNA NGS analysis. These 36 cases included 16 cases with normal cytogenetics. Simple abnormalities such as 5q-, 7q-, +8 were called in identical fashion, but some other abnormalities such as derivative chromosome and marker chromosome were resolved or interpreted differently by the cfDNA NGS analysis. The NGS panel design used in this study does not cover fusion genes or chromosomal translocation, and chromosomal translocations were missed at this time. Conclusions: This data shows that liquid biopsy using and targeted NGS is reliable in detecting chromosomal structural abnormalities in myeloid neoplasms and potentially can replace the need for conventional cytogenetic testing. While the current study was not designed to detect chromosomal translocations, a small, targeted panel of 275 genes is adequate for standard risk classification of myeloid neoplasms into intermediate or high-risk. Considering that in the same test complete mutation profiling can also be achieved along with chromosomal structural analysis, liquid biopsy in myeloid neoplasms might be considered as an efficient replacement to bone marrow biopsy in patients with myeloid neoplasms when fusion genes are not expected. Figure 1 Figure 1. Disclosures Goy: Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Infinity/Verastem: Research Funding; COTA (Cancer Outcome Tracking Analysis): Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Other: Leadership role; OncLive Peer Exchange: Honoraria; Bristol Meyers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Vincerx: Honoraria, Membership on an entity's Board of Directors or advisory committees; Elsevier PracticeUpdate: Oncology: Consultancy, Honoraria; AbbVie/Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Vincerx pharma: Membership on an entity's Board of Directors or advisory committees; LLC(Targeted Oncology): Consultancy; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Xcenda: Consultancy, Honoraria; Gilead: Membership on an entity's Board of Directors or advisory committees; Acerta: Consultancy, Research Funding; Rosewell Park: Consultancy; Janssen: Membership on an entity's Board of Directors or advisory committees; Elsevier's Practice Update Oncology, Intellisphere, LLC(Targeted Oncology): Consultancy; AbbVie/Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; MorphoSys: Honoraria, Other; Incyte: Honoraria; Novartis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyers Squibb: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genomic Testing Cooperative: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Other: Leadership role; Celgene: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech/Hoffman la Roche: Research Funding; Janssen: Research Funding; Karyopharm: Research Funding; Michael J Hennessey Associates INC: Consultancy; Hoffman la Roche: Consultancy; Physicians' Education Resource: Consultancy, Other: Meeting/travel support; Medscape: Consultancy; Phamacyclics: Research Funding; Constellation: Research Funding; Xcenda: Consultancy; Hackensack Meridian Health, Regional Cancer Care Associates/OMI: Current Employment. Pecora: Genetic testing cooperative: Other: equity investor; Genetic testing cooperative: Membership on an entity's Board of Directors or advisory committees. Koprivnikar: Bristol Myers Squibb: Speakers Bureau. McCloskey: BMS: Honoraria, Speakers Bureau; COTA: Other: Equity Ownership; Takeda: Consultancy, Speakers Bureau; Pfizer: Consultancy; Novartis: Consultancy; Jazz: Consultancy, Speakers Bureau; Incyte: Speakers Bureau; Amgen: Speakers Bureau.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood-2021-148164

Language: English

Publisher: American Society of Hematology

Publication Date: 2021

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 140, No. Supplement 1 ( 2022-11-15), p. 11893-11895

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood-2022-169586

Language: English

Publisher: American Society of Hematology

Publication Date: 2022

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: BMC Infectious Diseases, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2021-12)

Abstract: Hydroxychloroquine has not been associated with improved survival among hospitalized COVID-19 patients in the majority of observational studies and similarly was not identified as an effective prophylaxis following exposure in a prospective randomized trial. We aimed to explore the role of hydroxychloroquine therapy in mildly symptomatic patients diagnosed in the outpatient setting. Methods We examined the association between outpatient hydroxychloroquine exposure and the subsequent progression of disease among mildly symptomatic non-hospitalized patients with documented SARS-CoV-2 infection. The primary outcome assessed was requirement of hospitalization. Data was obtained from a retrospective review of electronic health records within a New Jersey USA multi-hospital network. We compared outcomes in patients who received hydroxychloroquine with those who did not applying a multivariable logistic model with propensity matching. Results Among 1274 outpatients with documented SARS-CoV-2 infection 7.6% were prescribed hydroxychloroquine. In a 1067 patient propensity matched cohort, 21.6% with outpatient exposure to hydroxychloroquine were hospitalized, and 31.4% without exposure were hospitalized. In the primary multivariable logistic regression analysis with propensity matching there was an association between exposure to hydroxychloroquine and a decreased rate of hospitalization from COVID-19 (OR 0.53; 95% CI, 0.29, 0.95). Sensitivity analyses revealed similar associations. QTc prolongation events occurred in 2% of patients prescribed hydroxychloroquine with no reported arrhythmia events among those with data available. Conclusions In this retrospective observational study of SARS-CoV-2 infected non-hospitalized patients hydroxychloroquine exposure was associated with a decreased rate of subsequent hospitalization. Additional exploration of hydroxychloroquine in this mildly symptomatic outpatient population is warranted.

Type of Medium: Online Resource

ISSN: 1471-2334

URL: Article

DOI: 10.1186/s12879-021-05773-w

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2021

detail.hit.zdb_id: 2041550-3

In: Journal of Medical Artificial Intelligence, AME Publishing Company, Vol. 5 ( 2022-12), p. 10-10

Type of Medium: Online Resource

ISSN: 2617-2496

URL: Journal

URL: Article

DOI: 10.21037/jmai

DOI: 10.21037/jmai-22-28

Language: Unknown

Publisher: AME Publishing Company

Publication Date: 2022