Reply to Burt LA, et al.: Adverse Effects of High-Dose Vitamin D Supplementation on Volumetric Bone Density Are Greater in Females Than Males
Bibliographic record
Abstract
We thank Dr Boucher(1) for her comments on our findings and hope our response provides further clarification. It is important to emphasize that our results are based on exploratory outcomes from our randomized controlled trial, and it is our intention that these results pave the way for additional studies to explore the sex differences in response to high-dose vitamin D supplementation and to confirm that supplementation doses higher than the recommendations are not necessary for bone health in older healthy adults. As stated in the article, a limitation of considering sex differences as an exploratory outcome of the trial was that we may be underpowered to detect time-by-treatment group-by-sex effects over the 3 years. Nevertheless, our findings were statistically significant for females as noted in the article, whereas statistically significant effects were not found for males. The primary aim of this trial was to investigate the effect of vitamin D supplementation on bone density and strength;(2) thus, for the primary outcome, the trial was only powered to examine differences between treatment group (ie, combining males and females) in total bone mineral density (TtBMD) at the tibia or radius, measured using high-resolution peripheral quantitative computed tomography (HR-pQCT). In the event of a statistically significant result, the power of the test is irrelevant. The only variable that we present with a p value for the interaction effect of time-by-treatment group-by-sex that is outside the traditional 0.05 level is cortical bone mineral density (CtBMD) at the radius (p = 0.072),(3) and for this variable power may have been an issue. We presented the treatment effect in graphical form (Fig. 2) and in the text, with 95% confidence intervals,(3) enabling readers to see differences in the estimated treatment effect in males and females and the possible ranges given the sample size. The differences between males and females are smaller for CtBMD at the radius than for other variables, and one could question whether they are clinically relevant. Outlier values were checked but remained in the analyses except for one individual who had a cyst in the radius field of view. The normality of the arithmetic means for each data subgroup is not relevant in this analysis. In general, individual profile plots showed response to vitamin D supplementation was non-linear. No data transformation was needed because this curve can be estimated using a quadratic effect in a multiple linear regression model. Essentially a curved line was fitted for each individual and the regression coefficients for that individual are estimated. These are the "random effects" and are assumed to be normally distributed. Diagnostic residual plots were examined for deviation from this assumption and other assumptions underlying the random effects model. Our study was designed to understand how bone outcomes are affected by high-dose vitamin D supplementation specifically in vitamin D–sufficient individuals as defined by IOM (now National Academy of Medicine) standards. We measured changes in TtBMD and bone strength in healthy individuals without osteoporosis and with 25(OH)D serum from 30 to 125 nmol/L. We agree that participants with low 25(OH)D levels may have responded differently to high-dose vitamin D supplementation, which would need to be explored following a different study design. We have investigated the effect of the baseline serum 25(OH)D and achieved serum 25(OH)D at month 12 on our bone outcomes. We are underpowered to perform a sex-stratified analysis within treatment groups, but we explored the data using a 75 nmol/L threshold at baseline of our pooled cohort.(4) There were 138 participants with baseline 25(OH)D levels of 75 nmol/L or less, and their dose-dependent pattern of bone loss was similar to the full cohort, with greatest loss in the 10,000 IU group. We did not have enough participants (N = 24) to perform stratification based on 25(OH)D <50 nmol/L. Currently, we have not explored the data using tertiles or quintiles.(5) Achieved serum 25(OH)D at 12 months was highly correlated with treatment group, as can be seen clearly in Fig. 4A, B, where there is very little overlap between the three treatment groups at 12 months.(3) Funding for the Calgary Vitamin D Study was provided by Pure North S′Energy Foundation in response to an investigator-initiated research grant proposal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.033 | 0.041 |
| Insufficient payload (model declined to judge) | 0.006 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".