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1.
Am J Epidemiol ; 190(11): 2405-2419, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1493668

ABSTRACT

Hydroxychloroquine (HCQ) was proposed as an early therapy for coronavirus disease 2019 (COVID-19) after in vitro studies indicated possible benefit. Previous in vivo observational studies have presented conflicting results, though recent randomized clinical trials have reported no benefit from HCQ among patients hospitalized with COVID-19. We examined the effects of HCQ alone and in combination with azithromycin in a hospitalized population of US veterans with COVID-19, using a propensity score-adjusted survival analysis with imputation of missing data. According to electronic health record data from the US Department of Veterans Affairs health care system, 64,055 US Veterans were tested for the virus that causes COVID-19 between March 1, 2020 and April 30, 2020. Of the 7,193 veterans who tested positive, 2,809 were hospitalized, and 657 individuals were prescribed HCQ within the first 48-hours of hospitalization for the treatment of COVID-19. There was no apparent benefit associated with HCQ receipt, alone or in combination with azithromycin, and there was an increased risk of intubation when HCQ was used in combination with azithromycin (hazard ratio = 1.55; 95% confidence interval: 1.07, 2.24). In conclusion, we assessed the effectiveness of HCQ with or without azithromycin in treatment of patients hospitalized with COVID-19, using a national sample of the US veteran population. Using rigorous study design and analytic methods to reduce confounding and bias, we found no evidence of a survival benefit from the administration of HCQ.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Azithromycin/therapeutic use , COVID-19/drug therapy , Hospitalization/statistics & numerical data , Hydroxychloroquine/therapeutic use , Veterans/statistics & numerical data , Aged , Aged, 80 and over , Anti-Bacterial Agents/adverse effects , Azithromycin/adverse effects , COVID-19/mortality , Drug Therapy, Combination , Female , Humans , Hydroxychloroquine/adverse effects , Intention to Treat Analysis , Machine Learning , Male , Middle Aged , Pharmacoepidemiology , Retrospective Studies , SARS-CoV-2 , Treatment Outcome , United States/epidemiology
2.
J Infect Dis ; 224(6): 967-975, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1429245

ABSTRACT

BACKGROUND: Early convalescent plasma transfusion may reduce mortality in patients with nonsevere coronavirus disease 2019 (COVID-19). METHODS: This study emulates a (hypothetical) target trial using observational data from a cohort of US veterans admitted to a Department of Veterans Affairs (VA) facility between 1 May and 17 November 2020 with nonsevere COVID-19. The intervention was convalescent plasma initiated within 2 days of eligibility. Thirty-day mortality was compared using cumulative incidence curves, risk differences, and hazard ratios estimated from pooled logistic models with inverse probability weighting to adjust for confounding. RESULTS: Of 11 269 eligible person-trials contributed by 4755 patients, 402 trials were assigned to the convalescent plasma group. Forty and 671 deaths occurred within the plasma and nonplasma groups, respectively. The estimated 30-day mortality risk was 6.5% (95% confidence interval [CI], 4.0%-9.7%) in the plasma group and 6.2% (95% CI, 5.6%-7.0%) in the nonplasma group. The associated risk difference was 0.30% (95% CI, -2.30% to 3.60%) and the hazard ratio was 1.04 (95% CI, .64-1.62). CONCLUSIONS: Our target trial emulation estimated no meaningful differences in 30-day mortality between nonsevere COVID-19 patients treated and untreated with convalescent plasma. Clinical Trials Registration. NCT04545047.


Subject(s)
Blood Component Transfusion , COVID-19/mortality , COVID-19/therapy , Immunization, Passive , Plasma , Adult , Aged , Aged, 80 and over , Female , Hospitalization , Humans , Male , Middle Aged , Treatment Outcome , United States/epidemiology , Veterans , Young Adult
3.
Am J Epidemiol ; 190(11): 2405-2419, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1393147

ABSTRACT

Hydroxychloroquine (HCQ) was proposed as an early therapy for coronavirus disease 2019 (COVID-19) after in vitro studies indicated possible benefit. Previous in vivo observational studies have presented conflicting results, though recent randomized clinical trials have reported no benefit from HCQ among patients hospitalized with COVID-19. We examined the effects of HCQ alone and in combination with azithromycin in a hospitalized population of US veterans with COVID-19, using a propensity score-adjusted survival analysis with imputation of missing data. According to electronic health record data from the US Department of Veterans Affairs health care system, 64,055 US Veterans were tested for the virus that causes COVID-19 between March 1, 2020 and April 30, 2020. Of the 7,193 veterans who tested positive, 2,809 were hospitalized, and 657 individuals were prescribed HCQ within the first 48-hours of hospitalization for the treatment of COVID-19. There was no apparent benefit associated with HCQ receipt, alone or in combination with azithromycin, and there was an increased risk of intubation when HCQ was used in combination with azithromycin (hazard ratio = 1.55; 95% confidence interval: 1.07, 2.24). In conclusion, we assessed the effectiveness of HCQ with or without azithromycin in treatment of patients hospitalized with COVID-19, using a national sample of the US veteran population. Using rigorous study design and analytic methods to reduce confounding and bias, we found no evidence of a survival benefit from the administration of HCQ.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Azithromycin/therapeutic use , COVID-19/drug therapy , Hospitalization/statistics & numerical data , Hydroxychloroquine/therapeutic use , Veterans/statistics & numerical data , Aged , Aged, 80 and over , Anti-Bacterial Agents/adverse effects , Azithromycin/adverse effects , COVID-19/mortality , Drug Therapy, Combination , Female , Humans , Hydroxychloroquine/adverse effects , Intention to Treat Analysis , Machine Learning , Male , Middle Aged , Pharmacoepidemiology , Retrospective Studies , SARS-CoV-2 , Treatment Outcome , United States/epidemiology
4.
Trials ; 22(1): 431, 2021 Jul 05.
Article in English | MEDLINE | ID: covidwho-1298059

ABSTRACT

BACKGROUND: Therapeutic targeting of host-cell factors required for SARS-CoV-2 entry is an alternative strategy to ameliorate COVID-19 severity. SARS-CoV-2 entry into lung epithelium requires the TMPRSS2 cell surface protease. Pre-clinical and correlative data in humans suggest that anti-androgenic therapies can reduce the expression of TMPRSS2 on lung epithelium. Accordingly, we hypothesize that therapeutic targeting of androgen receptor signaling via degarelix, a luteinizing hormone-releasing hormone (LHRH) antagonist, will suppress COVID-19 infection and ameliorate symptom severity. METHODS: This is a randomized phase 2, placebo-controlled, double-blind clinical trial in 198 patients to compare efficacy of degarelix plus best supportive care versus placebo plus best supportive care on improving the clinical outcomes of male Veterans who have been hospitalized due to COVID-19. Enrolled patients must have documented infection with SARS-CoV-2 based on a positive reverse transcriptase polymerase chain reaction result performed on a nasopharyngeal swab and have a severity of illness of level 3-5 (hospitalized but not requiring invasive mechanical ventilation). Patients stratified by age, history of hypertension, and severity are centrally randomized 2:1 (degarelix: placebo). The composite primary endpoint is mortality, ongoing need for hospitalization, or requirement for mechanical ventilation at 15 after randomization. Important secondary endpoints include time to clinical improvement, inpatient mortality, length of hospitalization, duration of mechanical ventilation, time to achieve a normal temperature, and the maximum severity of COVID-19 illness. Exploratory analyses aim to assess the association of cytokines, viral load, and various comorbidities with outcome. In addition, TMPRSS2 expression in target tissue and development of anti-viral antibodies will also be investigated. DISCUSSION: In this trial, we repurpose the FDA approved LHRH antagonist degarelix, commonly used for prostate cancer, to suppress TMPRSS2, a host cell surface protease required for SARS-CoV-2 cell entry. The objective is to determine if temporary androgen suppression with a single dose of degarelix improves the clinical outcomes of patients hospitalized due to COVID-19. TRIAL REGISTRATION: ClinicalTrials.gov NCT04397718. Registered on May 21, 2020.


Subject(s)
COVID-19 , Veterans , Clinical Trials, Phase II as Topic , Hospitalization , Humans , Male , Multicenter Studies as Topic , Oligopeptides , Randomized Controlled Trials as Topic , SARS-CoV-2 , Treatment Outcome
5.
PLoS One ; 16(5): e0251651, 2021.
Article in English | MEDLINE | ID: covidwho-1226903

ABSTRACT

BACKGROUND: The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death. METHODS AND RESULTS: We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality. CONCLUSIONS: Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted.


Subject(s)
COVID-19/epidemiology , Veterans Health , Age Factors , Aged , Aged, 80 and over , Body Mass Index , COVID-19/mortality , Disease Progression , Female , Hospitalization , Humans , Intensive Care Units , Longitudinal Studies , Male , Middle Aged , Risk Factors , SARS-CoV-2/isolation & purification , Sex Factors , United States/epidemiology , Veterans
6.
Nat Med ; 27(4): 668-676, 2021 04.
Article in English | MEDLINE | ID: covidwho-1174686

ABSTRACT

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.


Subject(s)
COVID-19/genetics , Drug Repositioning , Mendelian Randomization Analysis/methods , SARS-CoV-2 , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/physiology , COVID-19/drug therapy , Genome-Wide Association Study , Humans , Interleukin-10 Receptor beta Subunit/genetics , Interleukin-10 Receptor beta Subunit/physiology , Quantitative Trait Loci , Receptor, Interferon alpha-beta/genetics , Receptor, Interferon alpha-beta/physiology
8.
PLoS One ; 15(11): e0241825, 2020.
Article in English | MEDLINE | ID: covidwho-919031

ABSTRACT

BACKGROUND: Available COVID-19 mortality indices are limited to acute inpatient data. Using nationwide medical administrative data available prior to SARS-CoV-2 infection from the US Veterans Health Administration (VA), we developed the VA COVID-19 (VACO) 30-day mortality index and validated the index in two independent, prospective samples. METHODS AND FINDINGS: We reviewed SARS-CoV-2 testing results within the VA between February 8 and August 18, 2020. The sample was split into a development cohort (test positive between March 2 and April 15, 2020), an early validation cohort (test positive between April 16 and May 18, 2020), and a late validation cohort (test positive between May 19 and July 19, 2020). Our logistic regression model in the development cohort considered demographics (age, sex, race/ethnicity), and pre-existing medical conditions and the Charlson Comorbidity Index (CCI) derived from ICD-10 diagnosis codes. Weights were fixed to create the VACO Index that was then validated by comparing area under receiver operating characteristic curves (AUC) in the early and late validation cohorts and among important validation cohort subgroups defined by sex, race/ethnicity, and geographic region. We also evaluated calibration curves and the range of predictions generated within age categories. 13,323 individuals tested positive for SARS-CoV-2 (median age: 63 years; 91% male; 42% non-Hispanic Black). We observed 480/3,681 (13%) deaths in development, 253/2,151 (12%) deaths in the early validation cohort, and 403/7,491 (5%) deaths in the late validation cohort. Age, multimorbidity described with CCI, and a history of myocardial infarction or peripheral vascular disease were independently associated with mortality-no other individual comorbid diagnosis provided additional information. The VACO Index discriminated mortality in development (AUC = 0.79, 95% CI: 0.77-0.81), and in early (AUC = 0.81 95% CI: 0.78-0.83) and late (AUC = 0.84, 95% CI: 0.78-0.86) validation. The VACO Index allows personalized estimates of 30-day mortality after COVID-19 infection. For example, among those aged 60-64 years, overall mortality was estimated at 9% (95% CI: 6-11%). The Index further discriminated risk in this age stratum from 4% (95% CI: 3-7%) to 21% (95% CI: 12-31%), depending on sex and comorbid disease. CONCLUSION: Prior to infection, demographics and comorbid conditions can discriminate COVID-19 mortality risk overall and within age strata. The VACO Index reproducibly identified individuals at substantial risk of COVID-19 mortality who might consider continuing social distancing, despite relaxed state and local guidelines.


Subject(s)
Coronavirus Infections/mortality , Pneumonia, Viral/mortality , Adult , Age Factors , Aged , Aged, 80 and over , Area Under Curve , Betacoronavirus/isolation & purification , COVID-19 , Comorbidity , Coronavirus Infections/pathology , Coronavirus Infections/virology , Databases, Factual , Female , Humans , Logistic Models , Male , Middle Aged , Pandemics , Pneumonia, Viral/pathology , Pneumonia, Viral/virology , ROC Curve , Risk Factors , SARS-CoV-2 , Veterans Health , Young Adult
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