REVIEW

Annals of Internal Medicine

Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes
A Systematic Review and Meta-analysis of Individual Participant Data From
3 Randomized Clinical Trials
Anastassios G. Pittas, MD, MS; Tetsuya Kawahara, MD, PhD; Rolf Jorde, MD, PhD; Bess Dawson-Hughes, MD;
Ellen M. Vickery, MS; Edith Angellotti, MD; Jason Nelson, MPH; Thomas A. Trikalinos, MD; and Ethan M. Balk, MD, MPH

Background: The role of vitamin D in people who are at risk
for type 2 diabetes remains unclear.

Purpose: To evaluate whether administration of vitamin D
decreases risk for diabetes among people with prediabetes.

Data Sources: PubMed, Embase, and ClinicalTrials.gov fromdatabase inception through 9 December 2022.
Study Selection: Eligible trials that were speciﬁcally designed
and conducted to test the effects of oral vitamin D versus placebo on new-onset diabetes in adults with prediabetes.
Data Extraction: The primary outcome was time to eventfor new-onset diabetes. Secondary outcomes were regression
to normal glucose regulation and adverse events. Prespeciﬁed
analyses (both unadjusted and adjusted for key baseline variables) were conducted according to the intention-to-treat principle.
Data Synthesis: Three randomized trials were included,
which tested cholecalciferol, 20 000 IU (500 mcg) weekly;cholecalciferol, 4000 IU (100 mcg) daily; or eldecalcitol, 0.75
mcg daily, versus matching placebos. Trials were at low riskof bias. Vitamin D reduced risk for diabetes by 15% (hazard
ratio, 0.85 [95% CI, 0.75 to 0.96]) in adjusted analyses, witha 3-year absolute risk reduction of 3.3% (CI, 0.6% to 6.0%).
The effect of vitamin D did not differ in prespeciﬁed subgroups.

Observational studies provide strong and consistent
support for an inverse association between blood
25-hydroxyvitamin D level and risk for type 2 diabetes(1). However, the question of whether vitamin D decreases
risk for new-onset diabetes remains unanswered. In trials
that were speciﬁcally designed to test the hypothesis thatvitamin D reduces the rate of progression to diabetes inpeople with prediabetes (2–4), the risk for developing
diabetes was consistently lower in the group assigned
to vitamin D than in the placebo group; however, theobserved differences were not statistically signiﬁcant,and the reported relative risk reductions (10% to 13%)were smaller than each trial was powered to detect(25% to 36%).
Two meta-analyses of aggregate data from trials thatassessed the effect of vitamin D on diabetes risk
reported statistically signiﬁcant relative risk reductions of
11% to 12% for new-onset diabetes with vitamin D (5, 6).
Zhang and colleagues synthesized results from 8 trials(total n = 4896; range of sample sizes, 117 to 2423; duration of follow-up, 6 months to 5 years) in persons withprediabetes (6). Three of the included trials had low riskof bias (2–4), and the rest had either unclear or high riskof bias. Barbarawi and colleagues synthesized resultsfrom 9 trials (total n = 43 559; range of sample sizes, 109 to
33 951; duration of follow-up, 1 to 7 years) that reported on

Among participants assigned to the vitamin D group who maintained an intratrial mean serum 25-hydroxyvitamin D level of atleast 125 nmol/L (≥50 ng/mL) compared with 50 to 74 nmol/L(20 to 29 ng/mL) during follow-up, cholecalciferol reduced riskfor diabetes by 76% (hazard ratio, 0.24 [CI, 0.16 to 0.36]), with a
3-year absolute risk reduction of 18.1% (CI, 11.7% to 24.6%).
Vitamin D increased the likelihood of regression to normal
glucose regulation by 30% (rate ratio, 1.30 [CI, 1.16 to 1.46]).
There was no evidence of difference in the rate ratios for adverse
events (kidney stones: 1.17 [CI, 0.69 to 1.99]; hypercalcemia: 2.34
[CI, 0.83 to 6.66]; hypercalciuria: 1.65 [CI, 0.83 to 3.28]; death:0.85 [CI, 0.31 to 2.36]).

Limitations: Studies of people with prediabetes do not
apply to the general population. Trials may not have been
powered for safety outcomes.
Conclusion: In adults with prediabetes, vitamin D was effective in decreasing risk for diabetes.
Primary Funding Source: None. (PROSPERO: CRD42020163522)

Ann Intern Med. 2023;176:355-363. doi:10.7326/M22-3018
Annals.org
For author, article, and disclosure information, see end of text.
This article was published at Annals.org on 7 February 2023.

the effect of taking vitamin D for at least 1 year on newonset diabetes (5). This meta-analysis included 2 trials(total n = 38 780) that were conducted for nondiabetes
outcomes (fracture reduction) in persons with average diabetes risk and reported data on new-onset diabetes inpost hoc analyses (7, 8). Data from 1 large vitamin D anddiabetes prevention trial that was included in both metaanalyses were derived from an abstract (4). Overall, bothmeta-analyses included trials that had relatively shortdurations for assessment of diabetes risk (for example, ≤1year), had high risk of bias (for example, open-label trials),or were not speciﬁcally designed and conducted forprimary prevention of type 2 diabetes, potentially undermining the validity of the results. In contrast, a metaanalysis based on individual participant data (IPD) can
See also:
Editorial comment. . . . . . . . . . . . . . . . . . . . . . . . . . . 415
Summary for Patients . . . . . . . . . . . . . . . . . . . . . . . . I-22
Web-OnlySupplement
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Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes

more precisely deﬁne participant cohorts, standardize covariate deﬁnitions, and harmonize analyses to attenuate methodological heterogeneity and can pursue more elaborate
analyses to better explain participant-level treatment effectmodiﬁers and better address clinically relevant questions to
inform practice recommendations (9–13).
We conducted a systematic review of the publishedliterature and performed an IPD meta-analysis of randomized, placebo-controlled diabetes prevention trials ofvitamin D among adults with prediabetes. We sought toassess whether vitamin D decreases risk for new-onset
diabetes, whether the effect differs across prespeciﬁed
subgroups, whether vitamin D promotes regression tonormal glucose regulation, and whether it has adverse
effects in this population.

method experts. We obtained deidentiﬁed data sets ofrelevant study variables from each trial (Supplement
Methods 2, available at Annals.org). The data analyst(J.N.) and at least 1 other member of the research team,in collaboration with each individual principal investigator, assessed the integrity of the data by performing internal and external consistency checks with publishedresults. Databases were harmonized with uniﬁed coding
and by converting variable units to standard units.

METHODS

Outcomes
The primary outcome was time to new-onset diabetes
as deﬁned in each trial based on predeﬁned glycemic criteria or a diagnosis of diabetes outside the study (Supplement
Methods 3, available at Annals.org). Glycemic cutoffs for diabetes diagnosis in each trial followed the American Diabetes
Association or World Health Organization guidelines. The
secondary outcome of regression to normal glucose regulation was met if both blood glucose criteria (fasting glucose
level and glucose level 2 hours after a 75-g oral glucose
load) were in the normal range at the last study visit(Supplement Methods 4, available at Annals.org). Safety
outcomes included intervention-speciﬁc adverse eventsof interest (kidney stones, hypercalcemia, and hypercalciuria) and death from any cause (Supplement Methods
5, available at Annals.org).

This meta-analysis was conducted according to guidelines from the National Academy of Sciences (14) andfollowed the prespeciﬁed analysis plan outlined in the protocol, which was prospectively registered at PROSPERO(CRD42020163522). The study is reported according to
the PRISMA-IPD (Preferred Reporting Items for a Systematic
review and Meta-analysis of IPD) statement (15).
Data Sources and Searches
We searched Medline (via PubMed), Embase, andClinicalTrials.gov from database inception through 9
December 2022, with no restrictions on language or
publication date. The search strategy is provided in
Supplement Methods 1 (available at Annals.org).
Study Selection
We conducted a systematic review of the published literature and performed an IPD meta-analysis of randomized, placebo-controlled trials that were speciﬁcally designed andconducted to test whether vitamin D decreases diabetes risk
among adults with prediabetes (who are at risk for type 2 diabetes). Eligible trials 1) were randomized, double-blinded,and placebo-controlled; 2) included only adults (aged ≥18
years) with prediabetes as deﬁned by each trial's adaptationof standard glycemic criteria for prediabetes; 3) evaluatedoral vitamin D in any formulation (for example, ergocalciferol[vitamin D2], cholecalciferol [vitamin D3], or eldecalcitol [a synthetic analogue of calcitriol]); 4) had new-onset diabetes as
the primary outcome; and 5) had an intervention duration ofat least 2 years (to allow time for the exposure to have aneffect and for outcomes to develop and be captured duringfollow-up). We excluded 1) studies whose target populations
were pregnant or lactating women, hospitalized patients(including those in long-term care facilities), patients with endstage renal disease, patients with known diabetes (any type),or patients with HIV infection; 2) studies in which the intervention included other supplements or ingredients (for example,
calcium or yogurt); and 3) studies that included any amountof vitamin D in the comparator.
Data Extraction and Quality Assessment
We established a consortium that included the principal investigator from each eligible trial and subject andRisk-of-Bias Assessment
The methodological quality of each trial was assessedusing the revised Cochrane risk-of-bias tool (16). Risk of bias
was independently assessed by 2 researchers (E.A. and
E.M.B.), with discrepancies resolved by a third reviewer(A.G.P. or T.A.T.). All included trials had ethics approval.

Laboratory Testing
The trials measured serum 25-hydroxyvitamin D byliquid chromatography–tandem mass spectrometry withcalibrators that are traceable to the National Institute ofStandards and Technology (17). Details are provided in
Supplement Methods 6 (available at Annals.org).
Data Synthesis and Analysis
All analyses were prespeciﬁed in the protocol. The
intention-to-treat analysis compared all participants randomly assigned to vitamin D versus placebo, regardlessof adherence to the trial protocol, to estimate the average treatment assignment effect, which can be interpreted as the treatment effect of a policy for vitamin D(18). We also conducted secondary analyses that censored follow-up when a participant stopped taking thetrial pills, started using a diabetes or weight loss medication, or took vitamin D supplements at doses above
1000 IU/d outside the trial. The secondary analysis provides a trial product estimand, which measures an averagetreatment effect during treatment and before introductionof a “rescue” or “ancillary” medication (diabetes or weightloss medications, or high-dose vitamin D supplements
outside the study) (Supplement Methods 7, available atAnnals.org) (18).
After ﬁnding no evidence that the proportional hazards assumption was violated, we estimated the hazard

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Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes

ratio of new-onset diabetes between the groups with
Cox proportional hazards models that were stratiﬁed bytrial and included group assignment (vitamin D vs. placebo) as the main predictor variable. Follow-up time was
the time from randomization until the occurrence of diabetes, death, withdrawal, or the last follow-up encounter
where the participant did not have diabetes. Additionalmodels were adjusted for key variables that were preselected by the author group as the most relevant baselinecharacteristics associated with the primary outcome(age, gender, body mass index [BMI], race, and hemoglobin A1c level) (19, 20). We report all results as unadjusted
intention-to-treat analyses (most conservative) unless statedotherwise. For example, for the outcome of regression tonormal glucose regulation, we present only the secondary
analyses because intention-to-treat analyses would be misleading (for example, when participants began use of diabetes or weight loss medications).
Among trials that administered cholecalciferol, an inactive form of vitamin D that requires activation to 25-hydroxyvitamin D, we conducted an analysis using publishedmethods (21) to examine whether the intratrial cumulative
mean blood 25-hydroxyvitamin D level (measured annuallyin each trial to account for its seasonal variability) predicted
the development of diabetes (after adjustment for baseline
age, gender, BMI, race, and hemoglobin A1c level) and toassess whether achieving a higher intratrial mean blood 25hydroxyvitamin D level among participants assigned to vitamin D versus placebo affected risk for diabetes differentially. Trials that used other forms of vitamin D (such as
eldecalcitol) that do not change blood 25-hydroxyvitaminD level were not included in this analysis.
The variability of the effect of vitamin D on new-onset
diabetes was assessed by each trial and in prespeciﬁed
subgroups based on the following key baseline variables:
serum 25-hydroxyvitamin D level, age, gender, BMI, selfdeﬁned race, glycemic risk (meeting 2 or 3 prediabetes criteria), and total calcium intake from supplements. To test
whether overweight or obesity (which are associated withdecreased vitamin D bioactivation to 25-hydroxyvitamin D
by CYP2R1) modiﬁed the effect of cholecalciferol, we
performed BMI-based subgroup analyses using datafrom trials that administered cholecalciferol. Each subgroup analysis included a test for interaction, and effectmodiﬁcation was claimed if the test reached statisticalsigniﬁcance.
Rate ratios for regression to normal glucose regulationand for prespeciﬁed adverse events (kidney stones, hypercalcemia, hypercalciuria, and death from any cause) werecompared between groups using Poisson regression.
Results are presented as means and 95% CIs. Statisticalanalyses were conducted using SAS, version 9.4 (SASInstitute). No adjustments were made for multiple
comparisons.
Role of the Funding Source
The funding agencies of the included trials had norole in the design of the study; collection, analysis, synthesis, or interpretation of the data; writing of the report;
or the decision to submit the manuscript for publication.
Annals.org

RESULTS
Study Selection
The literature searches yielded 3835 citations from
PubMed and Embase and 270 records in ClinicalTrials.
gov. Of these, 44 full-text articles and all 270 ClinicalTrials.
gov records were further screened (Appendix Figure,available at Annals.org). Three trials met the eligibility criteria: the Tromsø study (3), the vitamin D and type 2 diabetes (D2d) study (2), and the Diabetes Prevention withactive Vitamin D (DPVD) study (4). We obtained IPD fromall 3 eligible trials, and all randomly assigned participants
were included in the meta-analysis.
Each study enrolled adults with prediabetes according to trial-speciﬁc criteria that were nearly identicalamong the trials (Supplement Methods 3). Detailed characteristics of each trial are shown in the Supplement Table(available at Annals.org). The Tromsø study randomly
assigned 511 participants recruited during 2008 to 2010
in Norway, the D2d study randomly assigned 2423 participants recruited during 2013 to 2016 in the United States,
and the DPVD study randomly assigned 1256 participants
recruited during 2013 to 2015 in Japan. The intervention
was cholecalciferol (vitamin D3) in the Tromsø (20 000 IU/wk) and D2d (4000 IU/d) studies and eldecalcitol (0.75mcg/d), a synthetic analogue of calcitriol, in the DPVD
study. All 3 trials were assessed as being at low risk of bias
(Supplement Figure 1, available at Annals.org).
All 4190 participants from the 3 trials contributed
data to the meta-analysis. Participants were randomly
assigned to receive vitamin D (n = 2097) or placebo (n =2093) (Table 1). Forty-four percent of participants were
women, 51% self-identiﬁed as White or European, 33%
self-identiﬁed as Asian, and 15% self-identiﬁed as Black.
At baseline, the mean age of participants was 61 years,
mean BMI was 30 kg/m2, and mean serum 25-hydroxyvitamin D level was 63 nmol/L (25 ng/mL).
Primary Analysis
Over a median follow-up of 3.0 years (IQR, 2.0 to 3.2
years), new-onset diabetes occurred in 475 of 2097
(22.7%) participants in the vitamin D group and 524 of
2093 (25.0%) in the placebo group (8.42 and 9.50 events
per 100 person-years, respectively). In the unadjusted
intention-to-treat analysis, the hazard ratio for vitamin D
was 0.88 (95% CI, 0.77 to 0.99) (Figures 1 and 2). After
adjustment for baseline age, gender, BMI, race, and hemoglobin A1c level, the hazard ratio for vitamin D was
0.85 (CI, 0.75 to 0.96). The absolute risk reduction forvitamin D compared with placebo was 3.3% (CI, 0.6% to6.0%), and the number needed to treat was 30.
In the secondary analysis, which censored follow-up
when a participant stopped taking the trial pills, started
using a diabetes or weight loss medication, or took supplemental vitamin D at a dose above 1000 IU/d outside
the trial, the primary outcome occurred in 447 participants in the vitamin D group and 505 in the placebogroup (8.26 and 9.61 events per 100 person-years,
respectively). The unadjusted hazard ratio for vitamin D
was 0.85 (CI, 0.75 to 0.97), and the adjusted hazard ratio
was 0.83 (CI, 0.73 to 0.94) (Figure 1).
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Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes

Table 1. Participant Characteristics at Baseline*
Characteristic

Overall (n = 4190)

Vitamin D (n = 2097)

Placebo (n = 2093)

Mean age (SD), y
Women, n (%)
Race, n (%)†
White/European
Black/African American
Asian
Other
Current smoking, n (%)
Dietary supplement use‡
Vitamin D
Participants taking vitamin D supplements, n (%)
Mean intake from supplements among all participants (SD), IU/d§Mean intake among participants using supplements (SD), IU/dParticipants taking >1000 IU/d, n (%)
Calcium
Participants taking calcium supplements, n (%)
Mean intake from supplements among all participants (SD), mg/d§
Mean intake among participants using supplements (SD), mg/d
Mean body mass index (SD), kg/m2
Body mass index category, n (%)<30 kg/m2
30 to <35 kg/m2≥35 kg/m2
Laboratory values
Mean serum 25-hydroxyvitamin D level (SD)nmol/L
ng/mL
Serum 25-hydroxyvitamin D category, n (%)||<30 nmol/L (<12 ng/mL)
30 to <50 nmol/L (12 to <20 ng/mL)
50 to <75 nmol/L (20 to <30 ng/mL)≥75 nmol/L (≥30 ng/mL)
Mean fasting glucose level (SD)mmol/L
mg/dL
Mean glucose level 2 h after a 75-g oral glucose load (SD)mmol/L
mg/dL
Mean hemoglobin A1c level (SD), %Prediabetes category, n (%)¶
Met all 3 prediabetes glycemic criteria (IGT þ iA1c þ IFG)
Met 1 or 2 prediabetes glycemic criteria
Mean serum calcium level (SD)mmol/L
mg/dL

60.6 (9.5)
1854 (44.2)

60.4 (9.4)
924 (44.1)

60.9 (9.6)
930 (44.4)

2125 (50.7)
616 (14.7)
1388 (33.1)
61 (1.5)260 (8.9)1065 (50.8)301 (14.4)
697 (33.2)
34 (1.6)
133 (9.1)

1060 (50.6)
315 (15.1)
691 (33.0)
27 (1.3)
127 (8.7)

1216 (29.1)
195.8 (340.8)
331.2 (389.3)
3 (0.1)595 (28.4)
192.4 (341.1)
328.9 (392.4)
2 (0.1)621 (29.8)
199.3 (340.5)
333.5 (386.4)
1 (0.0)860 (20.6)
67.8 (158.0)
134.0 (201.3)
29.5 (5.2)

407 (19.4)
64.1 (153.1)
129.5 (197.2)
29.3 (5.3)

453 (21.7)
71.5 (162.8)
138.3 (205.1)
29.6 (5.1)

2365 (56.4)
1119 (26.7)
706 (16.8)

1188 (56.7)
562 (26.8)
347 (16.5)

1177 (56.2)
557 (26.6)
359 (17.2)

63.4 (23.7)
25.4 (9.5)

63.0 (23.7)
25.2 (9.5)

63.7 (23.7)
25.5 (9.5)

224 (5.3)
1019 (24.3)
1726 (41.2)
1218 (29.1)

123 (5.9)510 (24.3)
890 (42.5)
573 (27.3)

101 (4.8)509 (24.3)
836 (40.0)645 (30.8)

6.0 (0.5)
108.7 (8.2)

6.0 (0.5)
108.9 (8.2)

6.0 (0.5)
108.6 (8.2)

8.1 (1.9)
146.0 (33.9)
5.9 (0.2)

8.1 (1.9)
145.8 (34.8)
5.9 (0.2)

8.1 (1.8)
146.1 (33.0)
5.9 (0.2)

2011 (48.0)2179 (52.0)

981 (46.8)1116 (53.2)

1030 (49.2)
1063 (50.8)

2.3 (0.1)
9.2 (0.4)

2.3 (0.1)
9.2 (0.4)

2.3 (0.1)
9.2 (0.4)

D2d = vitamin D and type 2 diabetes study; DPVD = Diabetes Prevention with active Vitamin D study; iA1c = impaired A1c; IFG = impaired fasting
glucose; IGT = impaired glucose tolerance.
* The individual participant data meta-analysis cohort comprises all participants from the 3 included trials (the Tromsø study [n = 511], the D2dstudy [n = 2423], and the DPVD study [n = 1256]). Percentages may not sum to 100 because of rounding. The P value for all statistical comparisons
between the vitamin D and placebo groups was greater than 0.05 except for serum 25-hydroxyvitamin D level (P = 0.044).
† Race was reported by participants. “Other” includes American Indian or Alaska Native, Native Hawaiian or other Paciﬁc Islander, or other race (allfrom the D2d study). Asian includes Asian American (n = 130 from the D2d study); Asian, not speciﬁed (n = 2 from the Tromsø study); or Japanese(n = 1256 from the DPVD study).
‡ Data on vitamin D and calcium intake are derived from a question about consumption of dietary supplements, including multivitamins.
§ Value shown is among all participants, regardless of whether they reported use of supplements.
|| Based on 2011 Institute of Medicine Dietary Reference Intakes for Calcium and Vitamin D.
¶ Deﬁnitions are from the 2010 American Diabetes Association Standards of Care guidelines. IFG is deﬁned as fasting glucose level of 100 to
125 mg/dL (5.6 to 6.9 mmol/L). IGT is deﬁned as 2-hour postload glucose level after a 75-g oral glucose load of 140 to 199 mg/dL (7.8 to 11.0
mmol/L). iA1c is deﬁned as hemoglobin A1c level of 5.7% to 6.4%.

Subgroup Analyses
The effect of vitamin D on new-onset diabetes did not
differ by baseline age, gender, BMI, race, glycemic risk, or
total calcium intake from supplements (Supplement
Figure 2, available at Annals.org). Among the 224 participants with a baseline serum 25-hydroxyvitamin D level
less than 30 nmol/L (<12 ng/mL), the hazard ratio in thevitamin D group was 0.58 (CI, 0.35 to 0.97) (Supplement
Figure 2).
When we examined data from the 2 trials (Tromsøand D2d [2, 3]) that administered cholecalciferol, which
requires activation to 25-hydroxyvitamin D in the liverand elsewhere by CYP2R1, there was a signiﬁcant interaction by baseline BMI. Supplementation with cholecalciferol

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Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes

reduced risk for diabetes in participants with a baseline BMI
below the median of 31.3 kg/m2 but not in those with a
BMI at or above the median (hazard ratios, 0.74 [CI, 0.60
to 0.90] and 1.01 [CI, 0.84 to 1.22], respectively; P forinteraction = 0.023) (Supplement Figure 3, available atAnnals.org). In contrast, in the trial that used eldecalcitol,an active analogue of vitamin D that does not requirehydroxylation by CYP2R1, there was no effect modiﬁcation by baseline BMI (P for interaction = 0.82).
Intratrial 25-Hydroxyvitamin D Level andDiabetes Risk
In the 2 trials that administered cholecalciferol(Tromsø and D2d [2, 3]), there was a statistically signiﬁcantinteraction between intratrial cumulative mean serum 25hydroxyvitamin D level and treatment assignment (cholecalciferol or placebo) on risk for diabetes (P < 0.001);
therefore, we present results by treatment (cholecalciferol
vs. placebo). Among participants assigned to cholecalciferol, the hazard ratios for diabetes among those who
maintained intratrial mean serum 25-hydroxyvitamin Dlevels of 100 to 124 nmol/L (40 to 50 ng/mL) (n = 400) and
125 nmol/L or higher (≥50 ng/mL) (n = 472) during followup were 0.38 (CI, 0.27 to 0.55) and 0.24 (CI, 0.16 to 0.36),
respectively, compared with participants who maintainedlevels of 50 to 74 nmol/L (20 to 29 ng/mL) (n = 114)
(Figure 3). Absolute risk reductions at 3 years were 11.4%(CI, 4.6% to 18.3%) and 18.1% (CI, 11.7% to 24.6%),
respectively. Among participants assigned to placebo,
the hazard ratios for diabetes by intratrial cumulative
mean serum 25-hydroxyvitamin D group were not statistically signiﬁcant (Figure 3).
Regression to Normal Glucose Regulation
At the last study visit, 271 of 1881 participants(14.4%) in the vitamin D group had experienced regression to normal glucose regulation compared with 209 of
1889 (11.1%) in the placebo group. The rate ratio for
regression to normal glucose regulation in the vitamin Dgroup compared with placebo at the last visit was 1.30

(CI, 1.16 to 1.46) (Supplement Figure 4, available atAnnals.org).
SafetyThe frequency of the prespeciﬁed adverse events ofinterest (kidney stones, hypercalcemia, and hypercalciuria) was low. Rate ratios were 1.17 (CI, 0.69 to 1.99) for
kidney stones, 2.34 (CI, 0.83 to 6.66) for hypercalcemia,
and 1.65 (CI, 0.83 to 3.28) for hypercalciuria (Table 2).
Seven participants (0.3%) in the vitamin D group and 8(0.4%) in the placebo group died (rate ratio, 0.85 [CI,0.31 to 2.36]).

DISCUSSION
This IPD meta-analysis of 3 randomized, doubleblinded, placebo-controlled trials speciﬁcally designed
for diabetes prevention found that vitamin D in people
with prediabetes was beneﬁcial in decreasing risk for diabetes and increasing the likelihood of regression to normal glucose regulation, with no offsetting safety signals.
Among participants treated with cholecalciferol, achieving and sustaining higher serum 25-hydroxyvitamin Dlevels conferred progressively lower risk for diabetes.
The individual trials included in this meta-analysis,
which were powered to detect diabetes risk reductions
no lower than 25%, reported nearly identical, non–statistically signiﬁcant risk reductions of 10% (Tromsø), 12%(D2d), and 13% (DPVD) (2–4). When we combined IPD,
vitamin D reduced risk for diabetes by 12% and 15% in
the unadjusted and adjusted intention-to-treat analyses,
respectively, a beneﬁt that the original trials were underpowered to detect. We found no statistically signiﬁcanteffect modiﬁcation in any subgroup deﬁned by key baseline characteristics. Although the degree of relative
reduction in risk for diabetes with vitamin D is small(15%) compared with other diabetes prevention strategies (58% with intensive lifestyle modiﬁcation and 31%
with metformin in the Diabetes Prevention Program
study) (22), the 3-year absolute risk reduction was 3.3%,

Figure 1. Effect of vitamin D on new-onset diabetes among adults with prediabetes.
Population

Vitamin D

Placebo

Events/Rate per 100
Participants, n/N Person-Years

Events/Rate per 100
Participants, n/N Person-Years

Hazard Ratio(95%CI)

All participants, intention-to-treat analysis
Unadjusted
475/2097
Adjusted

8.42

524/2093

9.50

0.88 (0.77–0.99)
0.85 (0.75–0.96)

All participants, secondary analysis
Unadjusted
Adjusted

8.26

505/2093

9.61

0.85 (0.75–0.97)
0.83 (0.73–0.94)

447/2097

0.70

0.80

0.90

1.0

1.1

Secondary analyses censored follow-up when a participant stopped taking the trial pills, started using a diabetes or weight loss medication, or took
vitamin D supplements at a dose above 1000 IU/d outside the study.
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Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes

Figure 2. Incidence curves for new-onset diabetes among
adults with prediabetes: intention-to-treat analysis.
1.0

PlaceboVitamin D

Cumulative Hazard of Diabetes

0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
0

6

12

30

42

48

At risk, nVitamin D 2097 2040 1908 1745 1527 1298 1105 429
Placebo2093 2032 1900 1714 1488 1239 1050 397

281
255

18

24

36

Months Since Randomizationtranslating to a number of persons with prediabetes
needed to treat of 30 (compared with 7 with intensive
lifestyle modiﬁcation and 14 with metformin in the
Diabetes Prevention Program study). Extrapolating to
the more than 374 million adults worldwide who haveprediabetes suggests that inexpensive vitamin D supplementation could delay the development of diabetes in more than 10 million people.
In participants treated with cholecalciferol (Tromsø andD2d), those who maintained higher intratrial serum 25hydroxyvitamin D levels had lower risk for diabetes, withthe greatest risk reduction (76%) occurring at intratrial serum 25-hydroxyvitamin D levels of 125 nmol/L or higher
compared with those who maintained an intratrial mean
serum 25-hydroxyvitamin D level of 50 to 74 nmol/L. Theseﬁndings conﬁrm results from the D2d study, which used
identical methods (21), and are consistent with reports
from aggregate meta-analyses that higher cholecalciferol
doses were more effective than lower doses in reducing diabetes risk (5). These results from the present study arealso consistent with results from longitudinal observational
studies that have reported a larger decrease in diabetes
risk for participants who have blood 25-hydroxyvitamin Dlevels above 125 nmol/L (1, 23).
These results suggest that the blood 25-hydroxyvitamin D level needed to optimally reduce diabetes
risk may be near and possibly above the range of 125
to 150 nmol/L (50 to 60 ng/mL) that the 2011 Instituteof Medicine Committee to Review Dietary Reference
Intakes for Calcium and Vitamin D provided as therange corresponding to the tolerable upper intake
level (UL) of 4000 IU/d for vitamin D (24). The reportstated that this UL is purposefully conservative because of
the unavailability of adequate safety data. A carefully

designed and monitored trial of treatment to a 25hydroxyvitamin D target is needed to test our ﬁndingthat higher levels are required to optimize reduction in diabetes risk. Such a “treat-to-target” trial would also provide important evidence related to the UL for vitamin D.
Clinically relevant adverse events, such as kidneystones, hypercalcemia, and hypercalciuria, were reported
in each of the 3 included trials. These events were rare
(1.3% for kidney stones, 0.4% for hypercalcemia, and
0.8% for hypercalciuria), and, in the combined analysis,
there were no statistically signiﬁcant differences between
the vitamin D and placebo groups. Detailed analyses fromthe D2d study showed that cholecalciferol at 4000 IU/d
was well tolerated and overall adverse events were lessfrequent in the vitamin D group compared with placebo(25). However, trials are not designed or powered to evaluate safety, especially because they exclude people
who may be at risk for adverse events. Although IPD
meta-analyses improve the power to detect differencesin adverse events, they cannot fully assess safety (26–28). Observational studies can provide clinically useful
information on safety. Longitudinal observational studies that have reported on blood 25-hydroxyvitamin Dlevel and diabetes risk have not reported adverse outcomes with higher levels of 25-hydroxyvitamin D. However,the beneﬁt and safety of vitamin D are population-speciﬁc,and the balance of beneﬁt and safety requires constantassessment as evidence evolves.
The vitamin D formulations in the eligible trials were
not identical because of differences in clinical practice
between Europe and the United States (cholecalciferol
was tested in Tromsø and D2d) and Japan (eldecalcitol
was tested in DPVD), which informed the selection ofvitamin D for each trial. Eldecalcitol is a synthetic analogue of calcitriol (1,25-dihydroxyvitamin D), which is theactive form of vitamin D that binds directly to the vitamin
D receptor and is used for prevention and treatment of
osteoporosis in Japan (4). Cholecalciferol requires a 2step hydroxylation process to be converted to calcitriol.
Pooling results from these 3 trials is appropriate because
the physiologic effects of cholecalciferol and eldecalcitol
would not be expected to vary given that the ﬁnal product of the vitamin D biosynthetic pathway for cholecalciferol is calcitriol. This is supported by the remarkably
similar relative risk reduction for new-onset diabetes
reported in each trial individually (10% to 13%).
There is evidence that obesity represses vitamin D
bioactivation by CYP2R1 (29, 30), leading to reduced
production of 25-hydroxyvitamin D, and that weight loss
upregulates CYP2R1 expression (30). When we examined data from the 2 trials that administered cholecalciferol (2, 3), which requires activation ﬁrst by CYP2R1 andsubsequently by CYP27B1, there was an interaction by
BMI such that participants with baseline BMI below themedian (31.3 kg/m2) had a 26% lower risk for diabetes
with cholecalciferol versus placebo, whereas among participants with a BMI at or above the median, there did
not seem to be an effect. In contrast, in the DPVD trial,
which used an active analogue of vitamin D that does not
require hydroxylation by CYP2R1 or CYP27B1 (4), there
was no effect modiﬁcation by baseline BMI. Taken

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Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes

Figure 3. Effect of cholecalciferol on new-onset diabetes among adults with prediabetes according to intratrial cumulative mean
serum 25-hydroxyvitamin D level.
Events/
Hazard Ratio (95% CI)
Participants, n/N
Cholecalciferol<50 nmol/L
50–74 nmol/L
75–99 nmol/L
100–124 nmol/L≥125 nmol/L

8/25
50/114110/316
94/40078/472

1.18 (0.55 – 2.54)
1.00 (reference)
0.64 (0.45–0.90)
0.38 (0.27–0.55)
0.24 (0.16–0.36)

Placebo<50 nmol/L
50–74 nmol/L
75–99 nmol/L
100–124 nmol/L≥125 nmol/L

95/283
144/500
123/423
20/101
5/24

1.29 (0.98–1.69)
1.00 (reference)
1.07 (0.84–1.37)
0.68 (0.42–1.11)
0.70 (0.28–1.71)
0.10

0.25

0.50

1.0

1.5 2.0

3.0

Analyses censored follow-up when a participant stopped taking the trial pills, started using a diabetes or weight loss medication, or took vitamin
D supplements at a dose above 1000 IU/d outside the study. Details are provided in Supplement Methods 7 (available at Annals.org).

together, these results suggest that the effect of vitamin
D on diabetes risk is mediated via its conversion to 25hydroxyvitamin D by CYP2R1—which is primarily expressedin the liver but also in multiple other tissues, including inpancreatic b cells (31)—and subsequently to 1,25-dihydroxyvitamin D by CYP27B1 in the kidney and pancreatic b
cells and other tissues (32). This can explain why cholecalciferol seems to work in leaner people with prediabetes with
intact CYP2R1 bioactivity but less well in those with overweight or obesity who are unable to fully convert vitamin D
to 25-hydroxyvitamin D, thereby reducing the exposure of
the pancreatic b cell to the beneﬁcial effects of the fully
activated vitamin D molecule.
Beyond delaying progression to diabetes, regression
to normal glucose regulation is also important because
euglycemia is associated with a lower prevalence of microvascular disease, nephropathy, and retinopathy compared with prediabetes, primarily due to lower glycemic
exposure over time (33). At the last study visit, participants

assigned to vitamin D were 30% more likely than those in
the placebo group to have had regression to normal glucose regulation. Hence, when evaluating the overall beneﬁt of vitamin D in prediabetes, the higher likelihood ofregression to normal glucose regulation should be added
to the lower risk for progression to diabetes.
This IPD meta-analysis has several strengths. In contrast
to aggregate data meta-analysis, an IPD meta-analysis increases the statistical power to detect beneﬁts and risks
and, through data harmonization, improves the precisionof results and allows additional, thorough, and more
appropriate analyses, including analyses to establish therobustness of results in important subgroups (9–12). The
key strength of our meta-analysis lies in the homogeneityand high quality of the included clinical trials, all of whichwere randomized, double-blinded, placebo-controlled,
and at low risk of bias. Most important, and in contrast toother meta-analyses in this area (5, 6), the eligible trials
in this meta-analysis were speciﬁcally designed and conducted

Table 2. Occurrence of Prespeciﬁed Adverse Events*
Event

Kidney stone (self-reported)
Within-study laboratory
evaluation
Hypercalcemia
Hypercalciuria
Death due to any cause

Vitamin D (n = 2097; 5643 Person-Years)

Placebo (n = 2093; 5514 Person-Years)

Incidence
Rate Ratio
for Vitamin D vs.
Placebo (95% CI)

Events,n

Events per
100 Person-Years

ParticipantsWith ≥1 Event, nEvents,n

Events per
100 Person-Years

ParticipantsWith ≥1 Event,
n

30

0.53

29

25

0.45

24

1.17 (0.69–1.99)

12
22
7

0.21
0.39
0.12

12
22
7

5
13
8

0.09
0.23
0.15

5
13
8

2.34 (0.83–6.66)
1.65 (0.83–3.28)
0.85 (0.31–2.36)

D2d = vitamin D and type 2 diabetes study; DPVD = Diabetes Prevention with active Vitamin D study.
* Kidney stone was a prespeciﬁed adverse event of interest in all trials; it was based on self-report and conﬁrmed by review of medical records.
Hypercalcemia was a prespeciﬁed adverse event of interest in all trials; it was based on trial-speciﬁc serum calcium thresholds (uncorrected for albumin) and required conﬁrmation by repeated measurement. Hypercalciuria was a prespeciﬁed adverse event of interest in 2 trials (D2d and DPVD); it
was based on trial-speciﬁc urine calcium–creatinine thresholds and required conﬁrmation by repeated measurement. In the Tromsø study, participants were not assessed for hypercalciuria in real time, but primary urine calcium–creatinine data were available. To incorporate the Tromsø study
data in the individual participant data meta-analysis, we used the D2d study criterion for hypercalciuria (yes/no), deﬁned as a fasting morning urine
calcium–creatinine ratio (mg/dL  mg/dL) above 0.375. Further details on deﬁnitions of adverse events are provided in Supplement Methods 5(available at Annals.org).
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Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes

for diabetes prevention, used modern deﬁnitions of prediabetes (which were nearly identical within trials) to deﬁne thestudy populations that were at risk for diabetes, had adequate
long-term follow-up, and ascertained the primary outcomeof new-onset diabetes using nearly identical prespeciﬁed
glycemic criteria.
The search strategy excluded diabetes prevention trials
with vitamin D that targeted children, pregnant or lactating
women, hospitalized patients, and patients with end-stage
renal disease or HIV at enrollment. Therefore, our results
may not apply to these populations because the pathophysiology of diabetes and rates of progression to diabetes
may differ. The studied population included people at highrisk for type 2 diabetes, so the results do not apply to thegeneral healthy population and should not be extrapolated
to those who are at average risk for type 2, type 1, or othertypes of diabetes (such as monogenic diabetes).
This IPD meta-analysis of vitamin D trials, speciﬁcallydesigned and conducted for diabetes prevention, overcame limitations of meta-analyses that used aggregate
data from heterogeneous studies and provides evidence
supporting the use of vitamin D in people with prediabetes to reduce their risk for progression to type 2 diabetes.
From Division of Endocrinology, Diabetes and Metabolism, Tufts
Medical Center, Boston, Massachusetts (A.G.P., E.M.V., J.N.);
Department of Internal Medicine, Kokura Medical Association
Health Testing Center, Kitakyushu, Japan (T.K.); Institute of Clinical
Medicine, UiT The Arctic University of Norway, Tromsø, Norway(R.J.); Division of Endocrinology, Diabetes and Metabolism, Tufts
Medical Center, and Jean Mayer USDA Human Nutrition ResearchCenter on Aging at Tufts University, Boston, Massachusetts (B.D.);
Takeda Pharmaceuticals, Cambridge, Massachusetts (E.A.); andCenter for Evidence Synthesis in Health, Brown University School of
Public Health, Providence, Rhode Island (T.A.T., E.M.B.).
Note: Dr. Pittas, Ms. Vickery, and Mr. Nelson had full access toall of the data in the study, and all authors had responsibility forthe decision to submit the manuscript for publication.
Disclaimer: The views expressed in this article are those of theauthors and do not necessarily represent the views of the
National Institutes of Health or any other funding agency.
Acknowledgment: The authors thank the investigators, staff,
and trial participants for their outstanding dedication and commitment to the individual trials that contributed data to thismeta-analysis.
Financial Support: Dr. Pittas receives funding from the National
Institutes of Health (U01DK098245) to conduct the D2d study and is
supported in part by generous donations to the Tupper Research
Fund at Tufts Medical Center, Boston, Massachusetts. Dr. Jorde hasreceived grants from the Novo Nordisk Foundation (R195-A16126),
the Northern Norway Regional Health Authority (6856/SFP102912), and the Research Council of Norway (184766). Dr. DawsonHughes receives funding from the National Institutes of Health(U01DK098245) and from the U.S. Department of Agriculture underagreement #58-1950-7-707. Dr. Angellotti was afﬁliated with theDivision of Endocrinology, Diabetes and Metabolism, Tufts Medical

Center (Boston, Massachusetts), while contributing to this work. The
DPVD study received a restricted grant from Kitakyushu Medical
Association.
Disclosures: Disclosures can be viewed at www.acponline.org/
authors/icmje/ConﬂictOfInterestForms.do?msNum=M22-3018.
Reproducible Research Statement: Study protocol: Available on
PROSPERO (CRD42020163522). Statistical code: Available fromMs. Vickery (e-mail, evickery@tuftsmedicalcenter.org). Data set:
Sharing of data used in this analysis is at the discretion of theprincipal investigators of the individual trials.
Corresponding Author: Anastassios G. Pittas, MD, MS, Division
of Endocrinology, Diabetes and Metabolism, Tufts Medical
Center, 800 Washington Street, Box 268, Boston, MA 02111;
e-mail, apittas@tuftsmedicalcenter.org.

Author contributions are available at Annals.org.

References
1. Song Y, Wang L, Pittas AG, et al. Blood 25-hydroxy vitamin D levels and incident type 2 diabetes: a meta-analysis of prospective studies. Diabetes Care. 2013;36:1422-8. [PMID: 23613602] doi:10.2337/
dc12-0962
2. Pittas AG, Dawson-Hughes B, Sheehan P, et al; D2d ResearchGroup. Vitamin D supplementation and prevention of type 2 diabetes. N Engl J Med. 2019;381:520-30. [PMID: 31173679] doi:10.1056/
NEJMoa1900906
3. Jorde R, Sollid ST, Svartberg J, et al. Vitamin D 20,000 IU per
week for ﬁve years does not prevent progression from prediabetes
to diabetes. J Clin Endocrinol Metab. 2016;101:1647-55. [PMID:
26829443] doi:10.1210/jc.2015-4013
4. Kawahara T, Suzuki G, Mizuno S, et al. Effect of active vitamin D
treatment on development of type 2 diabetes: DPVD randomised
controlled trial in Japanese population. BMJ. 2022;377:e066222.
[PMID: 35613725] doi:10.1136/bmj-2021-066222
5. Barbarawi M, Zayed Y, Barbarawi O, et al. Effect of vitamin D supplementation on the incidence of diabetes mellitus. J Clin Endocrinol
Metab. 2020;105. [PMID: 32491181] doi:10.1210/clinem/dgaa335
6. Zhang Y, Tan H, Tang J, et al. Effects of vitamin D supplementation on prevention of type 2 diabetes in patients with prediabetes: asystematic review and meta-analysis. Diabetes Care. 2020;43:16508. [PMID: 33534730] doi:10.2337/dc19-1708
7. de Boer IH, Tinker LF, Connelly S, et al; Women's Health Initiative
Investigators. Calcium plus vitamin D supplementation and the riskof incident diabetes in the Women's Health Initiative. Diabetes Care.
2008;31:701-7. [PMID: 18235052] doi:10.2337/dc07-1829
8. Avenell A, Cook JA, MacLennan GS, et al; RECORD trial group.
Vitamin D supplementation and type 2 diabetes: a substudy of arandomised placebo-controlled trial in older people (RECORD trial,
ISRCTN 51647438). Age Ageing. 2009;38:606-9. [PMID: 19617604]
doi:10.1093/ageing/afp109
9. Riley RD, Lambert PC, Abo-Zaid G. Meta-analysis of individual
participant data: rationale, conduct, and reporting. BMJ. 2010;340:
c221. [PMID: 20139215] doi:10.1136/bmj.c221
10. Debray TP, Moons KG, van Valkenhoef G, et al; GetReal
Methods Review Group. Get real in individual participant data (IPD)
meta-analysis: a review of the methodology. Res Synth Methods.
2015;6:293-309. [PMID: 26287812] doi:10.1002/jrsm.1160
11. Jones AP, Riley RD, Williamson PR, et al. Meta-analysis of individual patient data versus aggregate data from longitudinal clinical

362 Annals of Internal Medicine • Vol. 176 No. 3 • March 2023

Downloaded from https://annals.org by 219.107.53.184 on 04/21/2023.

Annals.org

REVIEW

Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes
trials. Clin Trials. 2009;6:16-27. [PMID: 19254930] doi:10.1177/
1740774508100984
12. Tudur Smith C, Marcucci M, Nolan SJ, et al. Individual participant data meta-analyses compared with meta-analyses based on
aggregate data. Cochrane Database Syst Rev. 2016;9:MR000007.
[PMID: 27595791] doi:10.1002/14651858.MR000007.pub3
13. Barnard ND, Willett WC, Ding EL. The misuse of meta-analysis
in nutrition research. JAMA. 2017;318:1435-6. [PMID: 28975260]
doi:10.1001/jama.2017.12083
14. Eden J, Levit L, Berg A, et al, eds; Institute of Medicine
Committee on Standards for Systematic Reviews of Comparative
Effectiveness Research. Finding What Works in Health Care:
Standards for Systematic Reviews. National Academies Pr. 2011.
[PMID: 24983062] doi:10.17226/13059
15. Tierney JF, Vale C, Riley R, et al. Individual participant data(IPD) meta-analyses of randomised controlled trials: guidance on
their use. PLoS Med. 2015;12:e1001855. [PMID: 26196287] doi:10.1371/
journal.pmed.1001855
16. Higgins JPT, Altman DG, Sterne JAC. Assessing risk of bias inincluded studies. In: Higgins JPT, Green S, eds. Cochrane Handbook
for Systematic Reviews of Interventions. Version 5.1.0 [updated
March 2011]. The Cochrane Collaboration; 2011.
17. Bedner M, Lippa KA, Tai SS. An assessment of 25-hydroxyvitamin D measurements in comparability studies conducted by the
Vitamin D Metabolites Quality Assurance Program. Clin Chim Acta.
2013;426:6-11. [PMID: 23978484] doi:10.1016/j.cca.2013.08.012
18. U.S. Food and Drug Administration. E9(R1) Statistical Principles
for Clinical Trials: Addendum: Estimands and Sensitivity Analysis in
Clinical Trials. Guidance for Industry. May 2021. Accessed at www.
fda.gov/regulatory-information/search-fda-guidance-documents/
e9r1-statistical-principles-clinical-trials-addendum-estimands-andsensitivity-analysis-clinical on 25 November 2022.
19. Hernández AV, Steyerberg EW, Habbema JD. Covariate adjustment in randomized controlled trials with dichotomous outcomesincreases statistical power and reduces sample size requirements. J
Clin Epidemiol. 2004;57:454-60. [PMID: 15196615]
20. Holmberg MJ, Andersen LW. Adjustment for baseline characteristics in randomized clinical trials. JAMA. 2022;328:2155-6. [PMID:
36394881] doi:10.1001/jama.2022.21506
21. Dawson-Hughes B, Staten MA, Knowler WC, et al; D2d ResearchGroup. Intratrial exposure to vitamin D and new-onset diabetes among
adults with prediabetes: a secondary analysis from the vitamin D andtype 2 diabetes (D2d) study. Diabetes Care. 2020;43:2916-22. [PMID:
33020052] doi:10.2337/dc20-1765

Annals.org

22. Knowler WC, Barrett-Connor E, Fowler SE, et al; Diabetes
Prevention Program Research Group. Reduction in the incidence oftype 2 diabetes with lifestyle intervention or metformin. N Engl J
Med. 2002;346:393-403. [PMID: 11832527]
23. Pittas AG, Sun Q, Manson JE, et al. Plasma 25-hydroxyvitamin
D concentration and risk of incident type 2 diabetes in women.
Diabetes Care. 2010;33:2021-3. [PMID: 20805275] doi:10.2337/
dc10-0790
24. Ross AC, Taylor CL, Yaktine AL, et al, eds; Institute of Medicine(US) Committee to Review Dietary Reference Intakes for Vitamin D
and Calcium. Dietary Reference Intakes for Calcium and Vitamin D.
National Academies Pr; 2011. doi:10.17226/13050
25. Johnson KC, Pittas AG, Margolis KL, et al; D2d research group.
Safety and tolerability of high-dose daily vitamin D3 supplementation in the vitamin D and type 2 diabetes (D2d) study—a randomized
trial in persons with prediabetes. Eur J Clin Nutr. 2022;76:1117-24.
[PMID: 35140313] doi:10.1038/s41430-022-01068-8
26. Qureshi R, Mayo-Wilson E, Rittiphairoj T, et al. Harms in Systematic
Reviews Paper 3: Given the same data sources, systematic reviews ofgabapentin have different results for harms. J Clin Epidemiol. 2022;143:
224-41. [PMID: 34742790] doi:10.1016/j.jclinepi.2021.10.025
27. Qureshi R, Mayo-Wilson E, Rittiphairoj T, et al. Harms in Systematic
Reviews Paper 2: Methods used to assess harms are neglected in systematic reviews of gabapentin. J Clin Epidemiol. 2022;143:212-23.
[PMID: 34742789] doi:10.1016/j.jclinepi.2021.10.024
28. Qureshi R, Mayo-Wilson E, Li T. Harms in Systematic Reviews Paper
1: An introduction to research on harms. J Clin Epidemiol. 2022;143:
186-96. [PMID: 34742788] doi:10.1016/j.jclinepi.2021.10.023
29. Roizen JD, Long C, Casella A, et al. Obesity decreases hepatic
25-hydroxylase activity causing low serum 25-hydroxyvitamin D.
J Bone Miner Res. 2019;34:1068-73. [PMID: 30790351] doi:10.1002/
jbmr.3686
30. Elkhwanky MS, Kummu O, Piltonen TT, et al. Obesity represses
CYP2R1, the vitamin D 25-hydroxylase, in the liver and extrahepatic
tissues. JBMR Plus. 2020;4:e10397. [PMID: 33210060] doi:10.1002/
jbm4.10397
31. The Human Protein Atlas. CYP2R1. Accessed at www.proteinatlas.
org/ENSG00000186104-CYP2R1/tissue/pancreas on 3 January 2023.
32. The Human Protein Atlas. CYP27B1. Accessed at www.proteinatlas.
org/ENSG00000111012-CYP27B1/tissue/pancreas on 3 January 2023.
33. Perreault L, Pan Q, Schroeder EB, et al; Diabetes Prevention
Program Research Group. Regression from prediabetes to normal
glucose regulation and prevalence of microvascular disease in the
Diabetes Prevention Program Outcomes Study (DPPOS). Diabetes
Care. 2019;42:1809-15. [PMID: 31320445] doi:10.2337/dc19-0244

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Author Contributions: Conception and design: A.G. Pittas, R.
Jorde, B. Dawson-Hughes, E.M. Vickery, E. Angellotti, E.M. Balk.
Analysis and interpretation of the data: A.G. Pittas, B. DawsonHughes, J. Nelson, T.A. Trikalinos, E.M. Balk.
Drafting of the article: A.G. Pittas, E.M. Vickery, J. Nelson, E.M.
Balk.
Critical revision for important intellectual content: A.G. Pittas, T.
Kawahara, R. Jorde, B. Dawson-Hughes, E.M. Vickery, J. Nelson,
T.A. Trikalinos, E.M. Balk.
Final approval of the article: A.G. Pittas, T. Kawahara, R. Jorde,
B. Dawson-Hughes, E.M. Vickery, E. Angellotti, J. Nelson, T.A.
Trikalinos, E.M. Balk.
Provision of study materials or patients: A.G. Pittas, T.
Kawahara, R. Jorde.
Statistical expertise: J. Nelson, T.A. Trikalinos, E.M. Balk.
Administrative, technical, or logistic support: A.G. Pittas, E.M.
Vickery.
Collection and assembly of data: A.G. Pittas, T. Kawahara, R.
Jorde, E.M. Vickery, E. Angellotti, J. Nelson, E.M. Balk.

Analyzed data Available data Obtaining data Eligibility Screening Identification

Appendix Figure. PRISMA-IPD (Preferred Reporting Items for a Systematic review and Meta-analysis of IPD) ﬂow diagram.
Articles identified via literature searches (n = 3835)
PubMed: 1670
Embase: 2165
ClinicalTrials.gov records (n = 270)

Additional studies identified via other sources,
including contact with researchers (n = 0)

Citations (n = 3835)
ClinicalTrials.gov records (n = 270)

Full-text articles retrieved (n = 44)
ClinicalTrials.gov records (n = 270)
Excluded (n = 308)*
Studies included (n = 3 [4 articles])ClinicalTrials.gov records included (n = 2)
Eligible studies for which IPD were not sought (n = 0)

Studies for which IPD were provided (n = 3)
Participants for whom data were provided (n = 4190)
Participants for whom no data were provided (n = 0)

Studies for which IPD were not provided (n = 0)

Studies included in analysis (n = 3)
Participants included in analysis (n = 4190)
Participants excluded (n = 0)
Participants for whom no data were provided (n = 0)

IPD = individual participant data.
* For reporting purposes, 1 exclusion reason was chosen for each article or record; however, most excluded studies had multiple reasons for exclusion.
Excluded published articles (n = 40): existing systematic review (n = 18), follow-up <2 years (n = 9), population not people with prediabetes (n = 4), did
not study vitamin D supplementation alone (n = 2), duplicate publication or no unique data (n = 3), not randomized controlled trial (n = 2), not doubleblinded (n = 2). Excluded ClinicalTrials.gov records (n = 268): not prediabetes (n = 132), not randomized controlled trial (n = 64), not double-blinded(n = 22), did not study vitamin D supplementation alone (n = 20), follow-up <2 years (n = 16), not adults (n = 12), no outcome of interest (n = 1), terminated early and no results available (company chose not to report interim results) (n = 1).
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