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Budesonide for COVID-19: real-time meta analysis of 8 studies
Covid Analysis, August 11, 2022, DRAFT
https://c19budesonide.com/meta.html
0 0.5 1 1.5+ All studies 39% 8 9,951 Improvement, Studies, Patients Relative Risk Mortality 38% 6 2,786 Ventilation 6% 1 1,560 ICU admission 52% 1 1,550 Recovery 43% 2 1,995 Cases 33% 1 7,019 RCTs 38% 4 1,856 RCT mortality 15% 3 1,710 Peer-reviewed 37% 6 1,984 Prophylaxis 41% 2 7,019 Early 82% 1 146 Late 34% 5 2,786 Budesonide for COVID-19 c19budesonide.com Aug 2022 Favorsbudesonide Favorscontrol
Statistically significant improvement is seen for mortality. 5 studies from 5 independent teams in 5 different countries show statistically significant improvements in isolation (3 for the most serious outcome).
Meta analysis using the most serious outcome reported shows 39% [23‑52%] improvement. Results are similar for Randomized Controlled Trials and similar for peer-reviewed studies. Early treatment is more effective than late treatment.
0 0.5 1 1.5+ All studies 39% 8 9,951 Improvement, Studies, Patients Relative Risk Mortality 38% 6 2,786 Ventilation 6% 1 1,560 ICU admission 52% 1 1,550 Recovery 43% 2 1,995 Cases 33% 1 7,019 RCTs 38% 4 1,856 RCT mortality 15% 3 1,710 Peer-reviewed 37% 6 1,984 Prophylaxis 41% 2 7,019 Early 82% 1 146 Late 34% 5 2,786 Budesonide for COVID-19 c19budesonide.com Aug 2022 Favorsbudesonide Favorscontrol
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. None of the budesonide studies show zero events in the treatment arm. Multiple treatments are typically used in combination, and other treatments may be more effective.
No treatment, vaccine, or intervention is 100% available and effective for all variants. All practical, effective, and safe means should be used. Denying the efficacy of treatments increases mortality, morbidity, collateral damage, and endemic risk.
All data to reproduce this paper and sources are in the appendix.
Highlights
Budesonide reduces risk for COVID-19 with very high confidence for mortality and in pooled analysis, low confidence for ICU admission and cases, and very low confidence for recovery.
We show traditional outcome specific analyses and combined evidence from all studies, incorporating treatment delay, a primary confounding factor in COVID-19 studies.
Real-time updates and corrections, transparent analysis with all results in the same format, consistent protocol for 43 treatments.
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramakrish.. (RCT) 82% 0.18 [0.04-0.79] hosp./ER 2/73 11/73 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.023 Early treatment 82% 0.18 [0.04-0.79] 2/73 11/73 82% improvement Ramlall (ICU) 71% 0.29 [0.11-0.78] death 33 (n) 915 (n) Intubated patients Improvement, RR [CI] Treatment Control Yu (RCT) 39% 0.61 [0.22-1.67] death 6/787 10/799 Al Sulaiman (ICU) 32% 0.68 [0.41-1.13] death 30/64 31/64 ICU patients MP 80%​1 Alsultan (RCT) -7% 1.07 [0.42-2.71] death 5/14 7/21 Agustí (RCT) -23% 1.23 [0.08-19.0] death 1/40 1/49 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0066 Late treatment 34% 0.66 [0.49-0.89] 42/938 49/1,848 34% improvement Lee 33% 0.67 [0.42-1.08] cases 19/1,674 95/5,345 Improvement, RR [CI] Treatment Control Monserrat V.. (PSM) 49% 0.51 [0.28-0.90] death n/a n/a Tau​2 = 0.00, I​2 = 0.0%, p = 0.0045 Prophylaxis 41% 0.59 [0.41-0.85] 19/1,674 95/5,345 41% improvement All studies 39% 0.61 [0.48-0.77] 63/2,685 155/7,266 39% improvement 8 budesonide COVID-19 studies c19budesonide.com Aug 2022 Tau​2 = 0.01, I​2 = 5.2%, p < 0.0001 Effect extraction pre-specified, see appendix 1 MP: multiple medications, percentage budesonide shown Favors budesonide Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramakrish.. (RCT) 82% hosp./ER Improvement Relative Risk [CI] Tau​2 = 0.00, I​2 = 0.0%, p = 0.023 Early treatment 82% 82% improvement Ramlall (ICU) 71% death Intubated patients Yu (RCT) 39% death Al Sulaiman (ICU) 32% death ICU patients MP 80%​1 Alsultan (RCT) -7% death Agustí (RCT) -23% death Tau​2 = 0.00, I​2 = 0.0%, p = 0.0066 Late treatment 34% 34% improvement Lee 33% case Monserrat V.. (PSM) 49% death Tau​2 = 0.00, I​2 = 0.0%, p = 0.0045 Prophylaxis 41% 41% improvement All studies 39% 39% improvement 8 budesonide COVID-19 studies c19budesonide.com Aug 2022 Tau​2 = 0.01, I​2 = 5.2%, p < 0.0001 Protocol pre-specified/rotate for details1 MP: multiple medications, percentage budesonide shown Favors budesonide Favors control
Figure 1. A. Random effects meta-analysis. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix. B. Scatter plot showing the distribution of effects reported in studies. C. History of all reported effects (chronological within treatment stages).
Introduction
We analyze all significant studies concerning the use of budesonide for COVID-19. Search methods, inclusion criteria, effect extraction criteria (more serious outcomes have priority), all individual study data, PRISMA answers, and statistical methods are detailed in Appendix 1. We present random effects meta-analysis results for all studies, for studies within each treatment stage, for individual outcomes, for peer-reviewed studies, for Randomized Controlled Trials (RCTs), and after exclusions.
Figure 2 shows stages of possible treatment for COVID-19. Prophylaxis refers to regularly taking medication before becoming sick, in order to prevent or minimize infection. Early Treatment refers to treatment immediately or soon after symptoms appear, while Late Treatment refers to more delayed treatment.
Figure 2. Treatment stages.
Preclinical Research
2 In Vitro studies support the efficacy of budesonide [Heinen, Konduri].
[Konduri] investigate a novel formulation of budesonide that may be more effective for COVID-19.
Preclinical research is an important part of the development of treatments, however results may be very different in clinical trials. Preclinical results are not used in this paper.
Results
Figure 3 shows a visual overview of the results, with details in Table 1 and Table 2. Figure 4, 5, 6, 7, 8, 9, 10, and 11 show forest plots for a random effects meta-analysis of all studies with pooled effects, mortality results, ventilation, ICU admission, progression, recovery, cases, and peer reviewed studies.
0 0.5 1 1.5+ ALL STUDIES MORTALITY VENTILATION ICU ADMISSION RECOVERY CASES RANDOMIZED CONTROLLED TRIALS RCT MORTALITY PEER-REVIEWED All Prophylaxis Early Late Budesonide for COVID-19 C19BUDESONIDE.COM AUG 2022
Figure 3. Overview of results.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Early treatment 1 1 100% 82% improvement
RR 0.18 [0.04‑0.79]
p = 0.023
Late treatment 3 5 60.0% 34% improvement
RR 0.66 [0.49‑0.89]
p = 0.0066
Prophylaxis 2 2 100% 41% improvement
RR 0.59 [0.41‑0.85]
p = 0.0045
All studies 6 8 75.0% 39% improvement
RR 0.61 [0.48‑0.77]
p < 0.0001
Table 1. Results by treatment stage.
Studies Early treatment Late treatment Prophylaxis PatientsAuthors
All studies 882% [21‑96%]34% [11‑51%]41% [15‑59%] 9,951 130
Peer-reviewed 682% [21‑96%]28% [2‑48%]49% [10‑72%] 1,984 122
Randomized Controlled TrialsRCTs 482% [21‑96%]15% [-64‑56%] 1,856 80
Table 2. Results by treatment stage for all studies and with different exclusions.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramakrish.. (RCT) 82% 0.18 [0.04-0.79] hosp./ER 2/73 11/73 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.023 Early treatment 82% 0.18 [0.04-0.79] 2/73 11/73 82% improvement Ramlall (ICU) 71% 0.29 [0.11-0.78] death 33 (n) 915 (n) Intubated patients Improvement, RR [CI] Treatment Control Yu (RCT) 39% 0.61 [0.22-1.67] death 6/787 10/799 Al Sulaiman (ICU) 32% 0.68 [0.41-1.13] death 30/64 31/64 ICU patients MP 80%​1 Alsultan (RCT) -7% 1.07 [0.42-2.71] death 5/14 7/21 Agustí (RCT) -23% 1.23 [0.08-19.0] death 1/40 1/49 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0066 Late treatment 34% 0.66 [0.49-0.89] 42/938 49/1,848 34% improvement Lee 33% 0.67 [0.42-1.08] cases 19/1,674 95/5,345 Improvement, RR [CI] Treatment Control Monserrat V.. (PSM) 49% 0.51 [0.28-0.90] death n/a n/a Tau​2 = 0.00, I​2 = 0.0%, p = 0.0045 Prophylaxis 41% 0.59 [0.41-0.85] 19/1,674 95/5,345 41% improvement All studies 39% 0.61 [0.48-0.77] 63/2,685 155/7,266 39% improvement 8 budesonide COVID-19 studies c19budesonide.com Aug 2022 Tau​2 = 0.01, I​2 = 5.2%, p < 0.0001 Effect extraction pre-specified, see appendix 1 MP: multiple medications, percentage budesonide shown Favors budesonide Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramakrish.. (RCT) 82% hosp./ER Improvement Relative Risk [CI] Tau​2 = 0.00, I​2 = 0.0%, p = 0.023 Early treatment 82% 82% improvement Ramlall (ICU) 71% death Intubated patients Yu (RCT) 39% death Al Sulaiman (ICU) 32% death ICU patients MP 80%​1 Alsultan (RCT) -7% death Agustí (RCT) -23% death Tau​2 = 0.00, I​2 = 0.0%, p = 0.0066 Late treatment 34% 34% improvement Lee 33% case Monserrat V.. (PSM) 49% death Tau​2 = 0.00, I​2 = 0.0%, p = 0.0045 Prophylaxis 41% 41% improvement All studies 39% 39% improvement 8 budesonide COVID-19 studies c19budesonide.com Aug 2022 Tau​2 = 0.01, I​2 = 5.2%, p < 0.0001 Protocol pre-specified/rotate for details1 MP: multiple medications, percentage budesonide shown Favors budesonide Favors control
Figure 4. Random effects meta-analysis for all studies with pooled effects. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramlall (ICU) 71% 0.29 [0.11-0.78] 33 (n) 915 (n) Intubated patients Improvement, RR [CI] Treatment Control Yu (RCT) 39% 0.61 [0.22-1.67] 6/787 10/799 Al Sulaiman (ICU) 32% 0.68 [0.41-1.13] 30/64 31/64 ICU patients MP 80%​1 Alsultan (RCT) -7% 1.07 [0.42-2.71] 5/14 7/21 Agustí (RCT) -23% 1.23 [0.08-19.0] 1/40 1/49 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0066 Late treatment 34% 0.66 [0.49-0.89] 42/938 49/1,848 34% improvement Monserrat V.. (PSM) 49% 0.51 [0.28-0.90] n/a n/a Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.013 Prophylaxis 49% 0.51 [0.28-0.90] 49% improvement All studies 38% 0.62 [0.47-0.80] 42/938 49/1,848 38% improvement 6 budesonide COVID-19 mortality results c19budesonide.com Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.00036 1 MP: multiple medications, percentage budesonide shown Favors budesonide Favors control
Figure 5. Random effects meta-analysis for mortality results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Yu (RCT) 6% 0.94 [0.44-1.98] 13/776 14/784 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.88 Late treatment 6% 0.94 [0.44-1.98] 13/776 14/784 6% improvement All studies 6% 0.94 [0.44-1.99] 13/776 14/784 6% improvement 1 budesonide COVID-19 mechanical ventilation result c19budesonide.com Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.88 Favors budesonide Favors control
Figure 6. Random effects meta-analysis for ventilation.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Yu (RCT) 52% 0.48 [0.23-1.01] 10/771 21/779 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.054 Late treatment 52% 0.48 [0.23-1.01] 10/771 21/779 52% improvement All studies 52% 0.48 [0.23-1.01] 10/771 21/779 52% improvement 1 budesonide COVID-19 ICU result c19budesonide.com Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.054 Favors budesonide Favors control
Figure 7. Random effects meta-analysis for ICU admission.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Agustí (RCT) 39% 0.61 [0.12-3.17] 2/40 4/49 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.57 Late treatment 39% 0.61 [0.12-3.17] 2/40 4/49 39% improvement All studies 39% 0.61 [0.12-3.17] 2/40 4/49 39% improvement 1 budesonide COVID-19 progression result c19budesonide.com Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.57 Favors budesonide Favors control
Figure 8. Random effects meta-analysis for progression.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramakrish.. (RCT) 67% 0.33 [0.15-0.72] no recov. 7/70 21/69 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.0057 Early treatment 67% 0.33 [0.15-0.72] 7/70 21/69 67% improvement Yu (RCT) 17% 0.83 [0.74-0.93] recov. time 787 (n) 1,069 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.0012 Late treatment 17% 0.83 [0.74-0.93] 0/787 0/1,069 17% improvement All studies 43% 0.57 [0.23-1.38] 7/857 21/1,138 43% improvement 2 budesonide COVID-19 recovery results c19budesonide.com Aug 2022 Tau​2 = 0.34, I​2 = 80.6%, p = 0.21 Favors budesonide Favors control
Figure 9. Random effects meta-analysis for recovery.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lee 33% 0.67 [0.42-1.08] cases 19/1,674 95/5,345 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.11 Prophylaxis 33% 0.67 [0.42-1.08] 19/1,674 95/5,345 33% improvement All studies 33% 0.67 [0.41-1.10] 19/1,674 95/5,345 33% improvement 1 budesonide COVID-19 case result c19budesonide.com Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.11 Favors budesonide Favors control
Figure 10. Random effects meta-analysis for cases.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramakrish.. (RCT) 82% 0.18 [0.04-0.79] hosp./ER 2/73 11/73 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.023 Early treatment 82% 0.18 [0.04-0.79] 2/73 11/73 82% improvement Yu (RCT) 39% 0.61 [0.22-1.67] death 6/787 10/799 Improvement, RR [CI] Treatment Control Al Sulaiman (ICU) 32% 0.68 [0.41-1.13] death 30/64 31/64 ICU patients MP 80%​1 Alsultan (RCT) -7% 1.07 [0.42-2.71] death 5/14 7/21 Agustí (RCT) -23% 1.23 [0.08-19.0] death 1/40 1/49 Tau​2 = 0.00, I​2 = 0.0%, p = 0.039 Late treatment 28% 0.72 [0.52-0.98] 42/905 49/933 28% improvement Monserrat V.. (PSM) 49% 0.51 [0.28-0.90] death n/a n/a Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.013 Prophylaxis 49% 0.51 [0.28-0.90] 49% improvement All studies 37% 0.63 [0.48-0.82] 44/978 60/1,006 37% improvement 6 budesonide COVID-19 peer reviewed trials c19budesonide.com Aug 2022 Tau​2 = 0.00, I​2 = 0.1%, p = 0.00071 Effect extraction pre-specified, see appendix 1 MP: multiple medications, percentage budesonide shown Favors budesonide Favors control
Figure 11. Random effects meta-analysis for peer reviewed studies. [Zeraatkar] analyze 356 COVID-19 trials, finding no significant evidence that peer-reviewed studies are more trustworthy. They also show extremely slow review times during a pandemic. Authors recommend using preprint evidence, with appropriate checks for potential falsified data, which provides higher certainty much earlier. Effect extraction is pre-specified, using the most serious outcome reported, see the appendix for details.
Randomized Controlled Trials (RCTs)
Figure 12 shows the distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results. Figure 13 and 14 show forest plots for a random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. Table 3 summarizes the results.
RCTs help to make study groups more similar, however they are subject to many biases, including age bias, treatment delay bias, severity of illness bias, regulation bias, recruitment bias, trial design bias, followup time bias, selective reporting bias, fraud bias, hidden agenda bias, vested interest bias, publication bias, and publication delay bias [Jadad], all of which have been observed with COVID-19 RCTs.
RCTs have a bias against finding an effect for interventions that are widely available — patients that believe they need the intervention are more likely to decline participation and take the intervention. This is illustrated with the extreme example of an RCT showing no significant differences for use of a parachute when jumping from a plane [Yeh]. RCTs for budesonide are more likely to enroll low-risk participants that do not need treatment to recover, making the results less applicable to clinical practice. This bias is likely to be greater for widely known treatments. Note that this bias does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable.
Evidence shows that non-RCT trials can also provide reliable results. [Concato] find that well-designed observational studies do not systematically overestimate the magnitude of the effects of treatment compared to RCTs. [Anglemyer] summarized reviews comparing RCTs to observational studies and found little evidence for significant differences in effect estimates. [Lee] shows that only 14% of the guidelines of the Infectious Diseases Society of America were based on RCTs. Evaluation of studies relies on an understanding of the study and potential biases. Limitations in an RCT can outweigh the benefits, for example excessive dosages, excessive treatment delays, or Internet survey bias could have a greater effect on results. Ethical issues may also prevent running RCTs for known effective treatments. For more on issues with RCTs see [Deaton, Nichol].
In summary, we need to evaluate each trial on its own merits. RCTs for a given medication and disease may be more reliable, however they may also be less reliable. For example, consider trials for an off-patent medication, very high conflict of interest trials may be more likely to be RCTs (and more likely to be large trials that dominate meta analyses).
Figure 12. The distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Ramakrish.. (RCT) 82% 0.18 [0.04-0.79] hosp./ER 2/73 11/73 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.023 Early treatment 82% 0.18 [0.04-0.79] 2/73 11/73 82% improvement Yu (RCT) 39% 0.61 [0.22-1.67] death 6/787 10/799 Improvement, RR [CI] Treatment Control Alsultan (RCT) -7% 1.07 [0.42-2.71] death 5/14 7/21 Agustí (RCT) -23% 1.23 [0.08-19.0] death 1/40 1/49 Tau​2 = 0.00, I​2 = 0.0%, p = 0.63 Late treatment 15% 0.85 [0.44-1.64] 12/841 18/869 15% improvement All studies 38% 0.62 [0.29-1.33] 14/914 29/942 38% improvement 4 budesonide COVID-19 Randomized Controlled Trials c19budesonide.com Aug 2022 Tau​2 = 0.17, I​2 = 28.9%, p = 0.22 Effect extraction pre-specified(most serious outcome, see appendix) Favors budesonide Favors control
Figure 13. Random effects meta-analysis for all Randomized Controlled Trials. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Yu (RCT) 39% 0.61 [0.22-1.67] 6/787 10/799 Improvement, RR [CI] Treatment Control Alsultan (RCT) -7% 1.07 [0.42-2.71] 5/14 7/21 Agustí (RCT) -23% 1.23 [0.08-19.0] 1/40 1/49 Tau​2 = 0.00, I​2 = 0.0%, p = 0.63 Late treatment 15% 0.85 [0.44-1.64] 12/841 18/869 15% improvement All studies 15% 0.85 [0.44-1.64] 12/841 18/869 15% improvement 3 budesonide COVID-19 RCT mortality results c19budesonide.com Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.63 Favors budesonide Favors control
Figure 14. Random effects meta-analysis for RCT mortality results.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Randomized Controlled Trials 2 4 50.0% 38% improvement
RR 0.62 [0.29‑1.33]
p = 0.22
RCT mortality results 1 3 33.3% 15% improvement
RR 0.85 [0.44‑1.64]
p = 0.63
Table 3. Randomized Controlled Trial results.
Heterogeneity
Heterogeneity in COVID-19 studies arises from many factors including:
Treatment delay.
The time between infection or the onset of symptoms and treatment may critically affect how well a treatment works. For example an antiviral may be very effective when used early but may not be effective in late stage disease, and may even be harmful. Oseltamivir, for example, is generally only considered effective for influenza when used within 0-36 or 0-48 hours [McLean, Treanor]. Figure 15 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 43 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
Figure 15. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 43 treatments. Early treatment is critical.
Patient demographics.
Details of the patient population including age and comorbidities may critically affect how well a treatment works. For example, many COVID-19 studies with relatively young low-comorbidity patients show all patients recovering quickly with or without treatment. In such cases, there is little room for an effective treatment to improve results (as in [López-Medina]).
Effect measured.
Efficacy may differ significantly depending on the effect measured, for example a treatment may be very effective at reducing mortality, but less effective at minimizing cases or hospitalization. Or a treatment may have no effect on viral clearance while still being effective at reducing mortality.
Variants.
There are many different variants of SARS-CoV-2 and efficacy may depend critically on the distribution of variants encountered by the patients in a study. For example, the Gamma variant shows significantly different characteristics [Faria, Karita, Nonaka, Zavascki]. Different mechanisms of action may be more or less effective depending on variants, for example the viral entry process for the omicron variant has moved towards TMPRSS2-independent fusion, suggesting that TMPRSS2 inhibitors may be less effective [Peacock, Willett].
Regimen.
Effectiveness may depend strongly on the dosage and treatment regimen.
Other treatments.
The use of other treatments may significantly affect outcomes, including anything from supplements, other medications, or other kinds of treatment such as prone positioning.
Medication quality.
The quality of medications may vary significantly between manufacturers and production batches, which may significantly affect efficacy and safety. [Williams] analyze ivermectin from 11 different sources, showing highly variable antiparasitic efficacy across different manufacturers. [Xu] analyze a treatment from two different manufacturers, showing 9 different impurities, with significantly different concentrations for each manufacturer.
Meta analysis.
The distribution of studies will alter the outcome of a meta analysis. Consider a simplified example where everything is equal except for the treatment delay, and effectiveness decreases to zero or below with increasing delay. If there are many studies using very late treatment, the outcome may be negative, even though the treatment may be very effective when used earlier.
In general, by combining heterogeneous studies, as all meta analyses do, we run the risk of obscuring an effect by including studies where the treatment is less effective, not effective, or harmful.
When including studies where a treatment is less effective we expect the estimated effect size to be lower than that for the optimal case. We do not a priori expect that pooling all studies will create a positive result for an effective treatment. Looking at all studies is valuable for providing an overview of all research, important to avoid cherry-picking, and informative when a positive result is found despite combining less-optimal situations. However, the resulting estimate does not apply to specific cases such as early treatment in high-risk populations. While we present pooled results for all studies, we also present individual outcome and treatment time analyses, which are more relevant for specific use cases.
Discussion
Publication bias.
Publishing is often biased towards positive results, however evidence suggests that there may be a negative bias for inexpensive treatments for COVID-19. Both negative and positive results are very important for COVID-19, media in many countries prioritizes negative results for inexpensive treatments (inverting the typical incentive for scientists that value media recognition), and there are many reports of difficulty publishing positive results [Boulware, Meeus, Meneguesso]. For budesonide, there is currently not enough data to evaluate publication bias with high confidence.
One method to evaluate bias is to compare prospective vs. retrospective studies. Prospective studies are more likely to be published regardless of the result, while retrospective studies are more likely to exhibit bias. For example, researchers may perform preliminary analysis with minimal effort and the results may influence their decision to continue. Retrospective studies also provide more opportunities for the specifics of data extraction and adjustments to influence results.
100% of retrospective studies report positive effects, compared to 60% of prospective studies, consistent with a bias toward publishing positive results. The median effect size for retrospective studies is 49% improvement, compared to 32% for prospective studies, suggesting a potential bias towards publishing results showing higher efficacy. Figure 16 shows a scatter plot of results for prospective and retrospective studies.
Figure 16. Prospective vs. retrospective studies.
Funnel plot analysis.
Funnel plots have traditionally been used for analyzing publication bias. This is invalid for COVID-19 acute treatment trials — the underlying assumptions are invalid, which we can demonstrate with a simple example. Consider a set of hypothetical perfect trials with no bias. Figure 17 plot A shows a funnel plot for a simulation of 80 perfect trials, with random group sizes, and each patient's outcome randomly sampled (10% control event probability, and a 30% effect size for treatment). Analysis shows no asymmetry (p > 0.05). In plot B, we add a single typical variation in COVID-19 treatment trials — treatment delay. Consider that efficacy varies from 90% for treatment within 24 hours, reducing to 10% when treatment is delayed 3 days. In plot B, each trial's treatment delay is randomly selected. Analysis now shows highly significant asymmetry, p < 0.0001, with six variants of Egger's test all showing p < 0.05 [Egger, Harbord, Macaskill, Moreno, Peters, Rothstein, Rücker, Stanley]. Note that these tests fail even though treatment delay is uniformly distributed. In reality treatment delay is more complex — each trial has a different distribution of delays across patients, and the distribution across trials may be biased (e.g., late treatment trials may be more common). Similarly, many other variations in trials may produce asymmetry, including dose, administration, duration of treatment, differences in SOC, comorbidities, age, variants, and bias in design, implementation, analysis, and reporting.
Figure 17. Example funnel plot analysis for simulated perfect trials.
Conflicts of interest.
Pharmaceutical drug trials often have conflicts of interest whereby sponsors or trial staff have a financial interest in the outcome being positive. Budesonide for COVID-19 lacks this because it is off-patent, has multiple manufacturers, and is very low cost. In contrast, most COVID-19 budesonide trials have been run by physicians on the front lines with the primary goal of finding the best methods to save human lives and minimize the collateral damage caused by COVID-19. While pharmaceutical companies are careful to run trials under optimal conditions (for example, restricting patients to those most likely to benefit, only including patients that can be treated soon after onset when necessary, and ensuring accurate dosing), not all budesonide trials represent the optimal conditions for efficacy.
Early/late vs. mild/moderate/severe.
Some analyses classify treatment based on early/late administration (as we do here), while others distinguish between mild/moderate/severe cases. We note that viral load does not indicate degree of symptoms — for example patients may have a high viral load while being asymptomatic. With regard to treatments that have antiviral properties, timing of treatment is critical — late administration may be less helpful regardless of severity.
Conclusion
Budesonide is an effective treatment for COVID-19. Statistically significant improvement is seen for mortality. 5 studies from 5 independent teams in 5 different countries show statistically significant improvements in isolation (3 for the most serious outcome). Meta analysis using the most serious outcome reported shows 39% [23‑52%] improvement. Results are similar for Randomized Controlled Trials and similar for peer-reviewed studies. Early treatment is more effective than late treatment.
Study Notes
0 0.5 1 1.5 2+ Mortality -23% Improvement Relative Risk Progression 39% c19budesonide.com Agustí et al. NCT04355637 Budesonide RCT LATE TREATMENT Favors budesonide Favors control
[Agustí] Small early-terminated RCT with 40 inhaled budesonide and 49 control patients, showing no significant differences. 400µg/12h via Pulmicort Turbuhaler. TACTIC. NCT04355637.
0 0.5 1 1.5 2+ Mortality 32% Improvement Relative Risk Mortality, D30 47% c19budesonide.com Al Sulaiman et al. Budesonide for COVID-19 ICU Favors budesonide Favors control
[Al Sulaiman] Combined retrospective (Mar-Jun 2020) and prospective (until Mar 2021) study of 954 COVID+ ICU patients in Saudi Arabia, 68 treated with ICS (80% budesonide or budesonide/formoterol, 20% fluticasone/salmeterol), showing lower mortality with treatment, statistically significant for 30-day but not in-hospital mortality.
0 0.5 1 1.5 2+ Mortality -7% Improvement Relative Risk Hospitalization time 20% no CI c19budesonide.com Alsultan et al. Budesonide for COVID-19 RCT LATE Favors budesonide Favors control
[Alsultan] Small RCT 49 severe condition hospitalized patients in Syria, showing lower mortality with colchicine and shorter hospitalization time with both colchicine and budesonide (all of these not statistically significant).
0 0.5 1 1.5 2+ Case 33% Improvement Relative Risk c19budesonide.com Lee et al. Budesonide for COVID-19 Prophylaxis Favors budesonide Favors control
[Lee (B)] Retrospective 44,968 patients in South Korea, 7,019 on inhaled corticosteroids, showing no statistically significant differences in COVID-19 cases.
0 0.5 1 1.5 2+ Mortality 49% Improvement Relative Risk c19budesonide.com Monserrat Villatoro et al. Budesonide Prophylaxis Favors budesonide Favors control
[Monserrat Villatoro] PSM retrospective 3,712 hospitalized patients in Spain, showing lower mortality with existing use of azithromycin, bemiparine, budesonide-formoterol fumarate, cefuroxime, colchicine, enoxaparin, ipratropium bromide, loratadine, mepyramine theophylline acetate, oral rehydration salts, and salbutamol sulphate, and higher mortality with acetylsalicylic acid, digoxin, folic acid, mirtazapine, linagliptin, enalapril, atorvastatin, and allopurinol.
0 0.5 1 1.5 2+ Hospitalization/ER 82% Improvement Relative Risk Hospitalization/ER (b) 90% Recovery 67% Recovery time 12% no CI c19budesonide.com Ramakrishnan et al. Budesonide for COVID-19 RCT EARLY Favors budesonide Favors control
[Ramakrishnan] RCT with 73 budesonide patients and 73 control patients, showing significantly lower combined risk of an ER visit or hospitalization, and lower risk of no recovery at day 14.
0 0.5 1 1.5 2+ Mortality 71% Improvement Relative Risk c19budesonide.com Ramlall et al. Budesonide for COVID-19 INTUBATED PATIENTS Favors budesonide Favors control
[Ramlall] Retrospective 948 intubated patients, 33 treated with budesonide, showing lower mortality with treatment.
0 0.5 1 1.5 2+ Mortality 39% Improvement Relative Risk Ventilation 6% ICU admission 52% Death/hospitalization 25% Recovery time 17% c19budesonide.com Yu et al. Budesonide for COVID-19 RCT LATE TREATMENT Favors budesonide Favors control
[Yu] Interim results from the PRINCIPLE trial, 1,073 treated with budesonide starting a median of 6 days after symptom onset, showing lower hospitalization/death, and faster recovery with treatment. ISRCTN86534580.
We performed ongoing searches of PubMed, medRxiv, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19budesonide.com. Search terms were budesonide, filtered for papers containing the terms COVID-19 or SARS-CoV-2. Automated searches are performed every few hours with notification of new matches. All studies regarding the use of budesonide for COVID-19 that report a comparison with a control group are included in the main analysis. This is a living analysis and is updated regularly.
We extracted effect sizes and associated data from all studies. If studies report multiple kinds of effects then the most serious outcome is used in pooled analysis, while other outcomes are included in the outcome specific analyses. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO2 is more important than cough. When results provide an odds ratio, we computed the relative risk when possible, or converted to a relative risk according to [Zhang]. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported including propensity score matching (PSM), the PSM results are used. Adjusted primary outcome results have preference over unadjusted results for a more serious outcome when the adjustments significantly alter results. When needed, conversion between reported p-values and confidence intervals followed [Altman, Altman (B)], and Fisher's exact test was used to calculate p-values for event data. If continuity correction for zero values is required, we use the reciprocal of the opposite arm with the sum of the correction factors equal to 1 [Sweeting]. Results are expressed with RR < 1.0 favoring treatment, and using the risk of a negative outcome when applicable (for example, the risk of death rather than the risk of survival). If studies only report relative continuous values such as relative times, the ratio of the time for the treatment group versus the time for the control group is used. Calculations are done in Python (3.9.13) with scipy (1.8.0), pythonmeta (1.26), numpy (1.22.2), statsmodels (0.14.0), and plotly (5.6.0).
Forest plots are computed using PythonMeta [Deng] with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case) and inverse variance weighting. Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor (3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome.
We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.
We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment (for example based on oxygen status or lung involvement), and treatment started within 5 days of the onset of symptoms. If studies contain a mix of early treatment and late treatment patients, we consider the treatment time of patients contributing most to the events (for example, consider a study where most patients are treated early but late treatment patients are included, and all mortality events were observed with late treatment patients). We note that a shorter time may be preferable. Antivirals are typically only considered effective when used within a shorter timeframe, for example 0-36 or 0-48 hours for oseltamivir, with longer delays not being effective [McLean, Treanor].
A summary of study results is below. Please submit updates and corrections at the bottom of this page.
A summary of study results is below. Please submit updates and corrections at https://c19budesonide.com/meta.html.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Ramakrishnan], 2/8/2021, Randomized Controlled Trial, United Kingdom, peer-reviewed, 24 authors, average treatment delay 3.0 days. risk of hospitalization/ER, 81.8% lower, RR 0.18, p = 0.02, treatment 2 of 73 (2.7%), control 11 of 73 (15.1%), NNT 8.1, ITT.
risk of hospitalization/ER, 90.1% lower, RR 0.10, p = 0.004, treatment 1 of 70 (1.4%), control 10 of 69 (14.5%), NNT 7.7, PP.
risk of no recovery, 67.1% lower, RR 0.33, p = 0.003, treatment 7 of 70 (10.0%), control 21 of 69 (30.4%), NNT 4.9, PP, day 14.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Agustí], 2/10/2022, Randomized Controlled Trial, Spain, peer-reviewed, 21 authors, trial NCT04355637 (history). risk of death, 22.5% higher, RR 1.23, p = 1.00, treatment 1 of 40 (2.5%), control 1 of 49 (2.0%), day 90.
risk of progression, 38.7% lower, RR 0.61, p = 0.69, treatment 2 of 40 (5.0%), control 4 of 49 (8.2%), NNT 32.
[Al Sulaiman], 11/10/2021, prospective, Saudi Arabia, peer-reviewed, 80% of treatment patients used budesonide, mean age 61.4, 24 authors, study period 1 March, 2020 - 31 March, 2021. risk of death, 32.0% lower, HR 0.68, p = 0.13, treatment 30 of 64 (46.9%), control 31 of 64 (48.4%), adjusted per study, in-hospital mortality, propensity score matching, multivariable, Cox proportional hazards.
risk of death, 47.0% lower, HR 0.53, p = 0.03, treatment 25 of 65 (38.5%), control 29 of 65 (44.6%), adjusted per study, propensity score matching, multivariable, Cox proportional hazards, day 30.
[Alsultan], 12/31/2021, Randomized Controlled Trial, Syria, peer-reviewed, 11 authors. risk of death, 7.1% higher, RR 1.07, p = 1.00, treatment 5 of 14 (35.7%), control 7 of 21 (33.3%).
[Ramlall], 10/18/2020, retrospective, USA, preprint, 3 authors. risk of death, 71.0% lower, HR 0.29, p = 0.01, treatment 33, control 915, Cox proportional hazards.
[Yu], 4/12/2021, Randomized Controlled Trial, United Kingdom, peer-reviewed, 24 authors, average treatment delay 6.0 days. risk of death, 39.1% lower, RR 0.61, p = 0.45, treatment 6 of 787 (0.8%), control 10 of 799 (1.3%), NNT 204.
risk of mechanical ventilation, 6.0% lower, RR 0.94, p = 1.00, treatment 13 of 776 (1.7%), control 14 of 784 (1.8%), NNT 905.
risk of ICU admission, 52.0% lower, RR 0.48, p = 0.07, treatment 10 of 771 (1.3%), control 21 of 779 (2.7%), NNT 71.
risk of death/hospitalization, 25.0% lower, RR 0.75, p = 0.96, treatment 72 of 787 (9.1%), control 116 of 1,069 (10.9%), NNT 59, adjusted per study, day 28.
recovery time, 17.4% lower, relative time 0.83, p = 0.001, treatment 787, control 1,069, adjusted per study.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Lee (B)], 9/9/2021, retrospective, South Korea, preprint, 5 authors. risk of case, 32.6% lower, RR 0.67, p = 0.10, treatment 19 of 1,674 (1.1%), control 95 of 5,345 (1.8%), NNT 156, adjusted per study, odds ratio converted to relative risk, multivariate.
[Monserrat Villatoro], 1/8/2022, retrospective, propensity score matching, Spain, peer-reviewed, 18 authors. risk of death, 49.0% lower, OR 0.51, p = 0.01, RR approximated with OR.
Supplementary Data
References
Please send us corrections, updates, or comments. Vaccines and treatments are both valuable and complementary. All practical, effective, and safe means should be used. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. Denying the efficacy of any method increases mortality, morbidity, collateral damage, and the risk of endemic status. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
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