METHODS: We randomly assigned inpatients with Covid-19 equally between one of the trial drug regimens that was locally available and open control (up to five options, four active and the local standard of care). The intention-to-treat primary analyses examined in-hospital mortality in the four pairwise comparisons of each trial drug and its control (drug available but patient assigned to the same care without that drug). Rate ratios for death were calculated with stratification according to age and status regarding mechanical ventilation at trial entry.
RESULTS: At 405 hospitals in 30 countries, 11,330 adults underwent randomization; 2750 were assigned to receive remdesivir, 954 to hydroxychloroquine, 1411 to lopinavir (without interferon), 2063 to interferon (including 651 to interferon plus lopinavir), and 4088 to no trial drug. Adherence was 94 to 96% midway through treatment, with 2 to 6% crossover. In total, 1253 deaths were reported (median day of death, day 8; interquartile range, 4 to 14). The Kaplan-Meier 28-day mortality was 11.8% (39.0% if the patient was already receiving ventilation at randomization and 9.5% otherwise). Death occurred in 301 of 2743 patients receiving remdesivir and in 303 of 2708 receiving its control (rate ratio, 0.95; 95% confidence interval [CI], 0.81 to 1.11; P = 0.50), in 104 of 947 patients receiving hydroxychloroquine and in 84 of 906 receiving its control (rate ratio, 1.19; 95% CI, 0.89 to 1.59; P = 0.23), in 148 of 1399 patients receiving lopinavir and in 146 of 1372 receiving its control (rate ratio, 1.00; 95% CI, 0.79 to 1.25; P = 0.97), and in 243 of 2050 patients receiving interferon and in 216 of 2050 receiving its control (rate ratio, 1.16; 95% CI, 0.96 to 1.39; P = 0.11). No drug definitely reduced mortality, overall or in any subgroup, or reduced initiation of ventilation or hospitalization duration.
CONCLUSIONS: These remdesivir, hydroxychloroquine, lopinavir, and interferon regimens had little or no effect on hospitalized patients with Covid-19, as indicated by overall mortality, initiation of ventilation, and duration of hospital stay. (Funded by the World Health Organization; ISRCTN Registry number, ISRCTN83971151; ClinicalTrials.gov number, NCT04315948.).
METHODS: A pilot study was conducted in four primary healthcare (PHC) centers in Malaysia. The model's key features included on-site HCV ribonucleic acid (RNA) testing using a shared GeneXpert® system; noninvasive biomarkers for cirrhosis diagnosis; and extended care to PWID referred from nearby PHC centers and outreach programs. The feasibility assessment focused on three aspects of the model: demand (i.e., uptake of HCV RNA testing and treatment), implementation (i.e., achievement of each step in the HCV care cascade), and practicality (i.e., ability to identify PWID with HCV and expedite treatment initiation despite resource constraints).
RESULTS: A total of 199 anti-HCV-positive PWID were recruited. They demonstrated high demand for HCV care, with a 100% uptake of HCV RNA testing and 97.4% uptake of direct-acting antiviral treatment. The rates of HCV RNA positivity (78.4%) and sustained virologic response (92.2%) were comparable to standard practice, indicating the successful implementation of the model. The model was also practical, as it covered non-opioid-substitution-therapy-receiving individuals and enabled same-day treatment in 71.1% of the participants.
CONCLUSIONS: The modified same-day test-and-treat model is feasible in improving HCV care for rural PWID. The study finding suggests its potential for wider adoption in HCV care for hard-to-reach populations.
METHODS: This study aimed to conduct a 5-year budget impact analysis of the proposed stratified treatment cascade for HCV treatment in Malaysia. A disease progression model that was developed based on model-predicted HCV epidemiology data was used for the analysis, where all HCV patients in scenario A were treated with SOF/DAC for all disease stages while in scenario B, SOF/DAC was used only for non-cirrhotic patients and SOF/VEL was used for the cirrhotic patients. Healthcare costs associated with DAA therapy and disease stage monitoring were included to estimate the downstream cost implications.
RESULTS: The stratified treatment cascade with 109 in Scenario B was found to be cost-saving compared to Scenario A. The cumulative savings for the stratified treatment cascade was USD 1.4 million over 5 years.
DISCUSSION: A stratified treatment cascade with SOF/VEL was expected to be cost-saving and can result in a budget impact reduction in overall healthcare expenditure in Malaysia.
METHODS: The pharmacology module consisted of a pharmacokinetic distribution of oseltamivir carboxylate daily area under the concentration-time curve at steady state (simulated for 75 mg and 150 mg twice daily regimens for 5 days) and a pharmacodynamic distribution of viral shedding duration obtained from phase II influenza inoculation data. The epidemiological module comprised a susceptible, exposed, infected, recovered (SEIR) model to which drug effect on the basic reproductive number (R0 ), a measure of transmissibility, was linked by reduction of viral shedding duration. The number of infected patients per population of 100 000 susceptible individuals was simulated for a series of pandemic scenarios, varying oseltamivir dose, R0 (1.9 vs. 2.7), and drug uptake (25%, 50%, and 80%). The number of infected patients for each scenario was entered into the health economics module, a decision analytic model populated with branch probabilities, disease utility, costs of hospitalized patients developing complications, and case-fatality rates. Change in quality-adjusted life years was determined relative to base case.
RESULTS: Oseltamivir 75 mg relative to no treatment reduced the median number of infected patients, increased change in quality-adjusted life years by deaths averted, and was cost-saving under all scenarios; 150 mg relative to 75 mg was not cost effective in low transmissibility scenarios but was cost saving in high transmissibility scenarios.
CONCLUSION: This methodological study demonstrates proof of concept that the disciplines of pharmacology, disease epidemiology and health economics can be linked in a single quantitative framework.