https://vdmeta.com/
•Random effects meta-analysis of the
20 vitamin D COVID-19 treatment studies to date
shows an estimated reduction of
62% in the effect measured, RR
0.38
[0.27-0.53].
95% of the studies to date report
positive effects (12 of
20 are statistically significant in isolation).
There is significant heterogeneity in studies, however this overview
highlights that all treatment studies show positive effects, with the
exception of one very late stage cholecalciferol study.
•Sufficiency studies show a strong
association between vitamin D sufficiency and outcomes. Meta-analysis of the
50 sufficiency studies shows an estimated reduction
of 53%, RR
0.47
[0.40-0.55].
•All data to reproduce this paper and
the sources are in the appendix.
Show forest plot for: |
Treatment studies |
Sufficiency studies |
Treatment with exclusions |
Treatment mortality |
Treatment cases |
Treatment viral- |
Improvement | Studies | Authors | Patients | |
All treatment studies | 62% [47‑73%] | 20 | 206 | 14,808 |
Treatment mortality results | 69% [49‑81%] | 11 | 102 | 2,647 |
All sufficiency studies | 53% [45‑60%] | 50 | 407 | 11,766 |
Figure 1. A. Random effects
meta-analysis of treatment studies. Simplified dosages are shown for
comparison, these are the total dose in the first five days for treatment, and
the monthly dose for prophylaxis. Calcifediol treatment is indicated with (c).
For full details see the appendix. B. Scatter plot showing the
distribution of effects reported in serum level analysis (sufficiency) studies
and treatment studies (the vertical lines and shaded boxes show the median and
interquartile range). C and D. Chronological history of all reported
effects for treatment studies and sufficiency studies. The 2 studies reporting
negative effects both have very low statistical significance.
Introduction
We analyze all significant studies regarding vitamin D and
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 studies analyzing outcomes based on
sufficiency, for all treatment studies, for mortality results only, and for
treatment studies within each treatment stage.
Vitamin D.
Vitamin D undergoes two
conversion steps before reaching the biologically active form as shown in
Figure 2. The first step is conversion to calcidiol, or 25(OH)D, in
the liver. The second is conversion to calcitriol, or 1,25(OH)2D, which occurs
in the kidneys, the immune system, and elsewhere. Calcitriol is the active,
steroid-hormone form of vitamin D, which binds with vitamin D receptors found
in most cells in the body. Vitamin D was first identified in relation to bone
health, but is now known to have multiple functions, including an important
role in the immune system [Martens]. There is a significant delay
involved in the conversion from cholecalciferol, therefore calcidiol
(calcifediol) may be preferable for treatment.Figure 2. Simplified view of vitamin D sources and conversion.
Sufficiency.
Many vitamin D studies
analyze outcomes based on serum vitamin D levels which may be maintained via
sun exposure, diet, or supplementation. We refer to these studies as
sufficiency studies, as they typically present outcomes based on vitamin D
sufficiency. These studies do not establish a causal link between vitamin D
and outcomes. In general, low vitamin D levels are correlated with many other
factors that may influence COVID-19 susceptibility and severity. Therefore,
beneficial effects found in these studies may be due to factors other than
vitamin D. On the other hand, if vitamin D is causally linked to the observed
benefits, it is possible that adjustments for correlated factors could obscure
this relationship. For these reasons, we analyze sufficiency studies
separately from treatment studies. We include all sufficiency studies that
provide a comparison between groups having sufficient and insufficient
levels.Treatment.
For studies regarding
treatment with vitamin D, we distinguish three stages as shown in
Figure 3. Pre-Exposure Prophylaxis (PrEP) refers to
regularly taking vitamin D before being infected. Early Treatment
refers to treatment immediately or soon after symptoms appear, while Late
Treatment refers to more delayed treatment.Figure 3. Treatment stages.
Results
Figure 1 shows the
effects reported in sufficiency studies and treatment studies.
Figure 4 and 5 show results by treatment stage.
Figure 6 shows a
forest plot for random effects meta-analysis of sufficiency studies, while
Figure 7, 8, 9, and 10 show forest plots for all treatment
studies with pooled effects, and for studies reporting mortality,
case results, and viral clearance results only.
Table 1 summarizes the results.
Study type | Number of studies reporting positive results | Total number of studies | Percentage of studies reporting positive results | Random effects meta-analysis results |
Analysis of outcomes based on sufficiency | 45 | 50 | 90.0% |
53% improvement RR 0.47 [0.40‑0.55] p < 0.0001 |
Early treatment | 3 | 3 | 100% |
90% improvement RR 0.10 [0.03‑0.36] p = 0.00039 |
Late treatment | 8 | 9 | 88.9% |
58% improvement RR 0.42 [0.28‑0.63] p < 0.0001 |
Pre‑Exposure Prophylaxis | 8 | 8 | 100% |
46% improvement RR 0.54 [0.38‑0.77] p = 0.00072 |
All treatment studies | 19 | 20 | 95.0% |
62% improvement RR 0.38 [0.27‑0.53] p < 0.0001 |
Table 1. Results.
Figure 4. Results by treatment stage.
Figure 5. Results by treatment stage.
Figure 6. Random effects meta-analysis for sufficiency studies.
Figure 7. Random effects meta-analysis for treatment studies.
Figure 8. Random effects meta-analysis for
mortality results only.
Figure 9. Random effects meta-analysis for
COVID-19 case results only.
Figure 10. Random effects meta-analysis for
viral clearance results only.
Exclusions
To avoid bias in the selection of studies, we include all
studies in the main analysis. Here we show the results after excluding studies
with critical issues.
[Murai] is a very late stage study (mean 10 days from
symptom onset, with 90% on oxygen at baseline), with poorly matched arms in
terms of ethnicity, diabetes, and baseline ventilation, all of which favor the
control group. Further, this study uses cholecalciferol, which may be
especially poorly suited for such a late stage.
The studies excluded are as follows, and the resulting forest
plot is shown in Figure 11.
[Murai], very late stage, >50% on oxygen/ventilation at baseline.