6/21 Late treatment study
et al., Braz J Microbiol, doi:10.1007/s42770-020-00395-x (preprint 6/21) (Peer Reviewed)
No benefit of hydroxychloroquine on SARS-CoV-2 viral load reduction in non-critical hospitalized patients with COVID-19
No benefit of hydroxychloroquine on SARS-CoV-2 viral load reduction in non-critical hospitalized patients with COVID-19
Viral load comparison for 34 HCQ and 32 control patients hospitalized with moderate COVID-19. All patients recovered limiting the room for beneficial effects. While not achieving statistical significance, results show faster recovery with HCQ. The greatest benefit is seen mid-recovery as expected for an effective treatment:Δt7-12: 81% improvement with HCQ
Δt<7: 24% improvement with HCQFor Δt>12, everyone has recovered so there is no room for improvement. Since the HCQ group started slightly higher the improvement is slightly less. Most participants have also dropped out by this test, with only 6 HCQ and 9 control remaining (also suggesting HCQ patients recovered faster).
Effect extraction follows pre-specified rules prioritizing more serious outcomes. For an individual study the most serious outcome may have a smaller number of events and lower statistical signficance, however this provides the strongest evidence for the most serious outcomes when combining the results of many trials.
Δt<7: 24% improvement with HCQFor Δt>12, everyone has recovered so there is no room for improvement. Since the HCQ group started slightly higher the improvement is slightly less. Most participants have also dropped out by this test, with only 6 HCQ and 9 control remaining (also suggesting HCQ patients recovered faster).
Faíco-Filho et al., 6/21/2020, prospective, Brazil, South America, peer-reviewed, median age 58.0, 6 authors.
Δt7-12 ΔCt improvement, 80.8% lower, relative rate 0.19, p = 0.40, treatment 34, control 32.
Δt<7 ΔCt improvement, 24.0% lower, relative rate 0.76, p = 0.36, treatment 34, control 32.
Δt>12 ΔCt improvement, 15.0% higher, relative rate 1.15, p = 0.52, treatment 34, control 32.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. For an individual study the most serious outcome may have a smaller number of events and lower statistical signficance, however this provides the strongest evidence for the most serious outcomes when combining the results of many trials.
