Diabetes Prevention in the Vitamin D and Omega-3 Trial
Phase: PHASE3
Conditions: Type 2 Diabetes
Sponsor: Brigham and Women's Hospital

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Cover Page 
 
Study Title: 
Study of Vitamin D and Omega-3 Supplementation for Preventing Diabetes 
 
Sponsor: 
National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health 
 
Study Identifier(s): 
• 
ClinicalTrials.gov Identifier (NCT Number): NCT01633177 
• 
Protocol ID: 0308112690000 
 
 
Document: 
Statistical Analysis Plan 
 
 
 
Date (Submission to NIH):  
November 20, 2009 
 
 

A. SPECIFIC AIMS 
Emerging evidence suggests favorable effects of both vitamin D and marine omega-3 fatty acids on 
glucose homeostasis. Optimal vitamin D intake is essential for insulin secretion and action8-17, and omega-3 
fatty acids may reduce diabetes risk as a result of favorable effects on insulin sensitivity, endothelial function, 
chronic inflammation, or other metabolic abnormalities18-25. Although the metabolic effects of vitamin D and 
omega-3 fatty acids show considerable promise for the primary prevention of type 2 diabetes (T2D), there are 
no completed, ongoing, or planned randomized clinical trials of vitamin D or omega-3 supplements that include 
T2D as a primary outcome in a general population.  
We thus propose to utilize an NIH-funded randomized trial (1 U01 CA138962) to test the hypothesis that 
vitamin D and omega-3 supplementation will reduce the risk of T2D. We will further assess whether and to 
what extent vitamin D or omega-3 supplementation will improve insulin sensitivity and pancreatic b-cell function 
in a subsample of the trial cohort. The VITamin D and OmegA-3 TriaL (VITAL) is a randomized, double-blind, 
placebo-controlled trial specifically designed to evaluate the benefits and risks of vitamin D3 (2,000 IU/day) and 
marine omega-3 fatty acid (eicosapentaenoic acid [EPA] + docosahexaenoic acid [DHA], 1g/day) supplements 
in the primary prevention of cancer and cardiovascular disease (CVD). The VITAL trial will aim to enroll 20,000 
men and women (aged ≥55 and ≥55 years, respectively). The planned treatment duration is 5 years after a 
1.5-year recruitment period. Thus, the VITAL trial offers us a unique opportunity to examine diabetes 
prevention in a large trial of vitamin D and omega-3 supplementation. The current proposal seeks funds to 
implement an inexpensive and efficient strategy to validate self-reported incident T2D cases in the entire trial 
population and to collect pre- and post-intervention measures of glucose, insulin, and hemoglobin A1c (HbA1c) 
in a subset of participants. Two methods of diabetes case validation are proposed. First, we plan to collect 
detailed information about diagnostic glucose testing and anti-diabetic medication use from medical records 
and/or supplementary questionnaires completed by the participant’s physician. Second, to complement our 
diabetes ascertainment process, we will also plan to retrieve additional data on diabetes diagnoses and 
hypoglycemic medications by linking the participants with the Centers for Medicare and Medicaid Services 
(CMS) database. In addition to evaluating whether the study interventions impact the onset of clinical diabetes, 
we propose to collect pre- and post-intervention measures of glucose, insulin, and HbA1c in a subset of the 
participants to reliably assess whether vitamin D or omega-3 supplementation alters insulin and glucose 
homeostasis. We plan to recruit 1,000 participants without prior clinical diabetes at four Clinical and 
Translational Science Center (CTSC) sites across the US (Boston, Chicago, San Francisco, and Houston) 
within the national CTSC network. A standard 2-hour oral glucose tolerance test (OGTT) and HbA1c 
measurements will be performed during the CTSC visits at baseline and at 2-year post-randomization 
(matched for season by month).  
 
Primary Aims:  
1. To test whether vitamin D3 and/or EPA+DHA supplementation reduces the risk of T2D among all 
initially non-diabetic participants in the VITAL trial.  
2. To test whether vitamin D3 and/or EPA+DHA supplementation improves insulin sensitivity and b-cell 
function in a subset of 1,000 non-diabetic participants receiving OGTT at baseline and 2-year post-
randomization.   
Secondary Aims:  
1. To test whether vitamin D3 and/or EPA+DHA supplementation lowers HbA1c, fasting glucose and 
insulin, as well as other surrogate indices of insulin sensitivity and b-cell function as determined by the 
homeostasis model assessment (HOMA-IR and HOMA-%B, respectively) in our substudy.  
2. To test whether vitamin D3 and EPA+DHA supplementation exerts synergistic or additive effects on the 
risk of T2D among all initially non-diabetic participants in the VITAL trial.  
3. To test whether vitamin D3 and EPA+DHA supplementation exerts synergistic or additive effects on 
insulin sensitivity and b-cell function as assessed by OGTT in our substudy.  
 
For the above main effect estimates, we will further explore whether the effect of vitamin D3 or EPA+DHA 
supplementation varies by (1) age, (2) sex, (3) baseline intakes of these nutrients, (4) baseline levels of 
25(OH)D (for vitamin D3), (5) race/skin pigmentation (for vitamin D3), (6) geographic region (for vitamin D3), and 
(7) BMI (for vitamin D3). 
 

D. RESEARCH DESIGN AND METHODS 
D.1.  The Study Population of all Non-diabetic Participants in the VITAL Trial  
D.1.1. Participant recruitment in the VITAL trial  
The VITamin D and OmegA-3 TriaL (VITAL) is an NIH-supported (1 U01 CA138962), randomized, 
double-blind, placebo-controlled trial of the benefits and risks of vitamin D (vitamin D3 [cholecalciferol], 2,000 
IU/d) and omega-3 fatty acids (1 g/d; EPA to DHA ratio, 1:1) in the primary prevention of cancer and CVD. The 
VITAL trial will be conducted among 20,000 apparently healthy participants—10,000 men aged ≥60 and 10,000 
women aged ≥65, ages at which rates of chronic disease increase substantially. Enrollment of racial/ethnic 
minority groups proportionate to the total minority population was a high priority of the VITAL. The VITAL was 
designed to recruit 20,000 men and women with at least 25% representing minority groups at the end of the 
recruitment period. Individuals will be eligible if they have no history of cancer (except non-melanoma skin 
cancer) or CVD (including myocardial infarction [MI], stroke, transient ischemic attack [TIA], angina pectoris, 
coronary artery bypass graft [CABG], or percutaneous coronary intervention [PCI]). Recruitment for the VITAL 
will begin in 2010 and end in 2012. Based on the pilot results, we will be able to identify approximately 40,000 
willing and eligible participants to enter the run-in, with at least 25% underrepresented minorities; 20,000 of 
these will be randomized into the trial, with the same proportion minority. Specifically, of the 20,000 randomized 
participants, we anticipate the ethnic distribution to be 1,400 (7.5%) Hispanic and 18,600 (93%) non-Hispanic; 
with regard to race, we anticipate 5,000 (25%) African-American, 500 (2.5%) Asian, 400 (2%) American Indian, 
80 (0.4%) Pacific Islander, and 14,020 (70.1%) white individuals. Participants will be randomized only if they: 
(1) demonstrate good compliance in pill taking, defined as taking at least two-thirds of the study pills during the 
run-in; (2) express willingness to continue in the trial; (3) report no new history of cancer (except non-
melanoma skin cancer), MI, stroke, TIA, angina pectoris, CABG, PCI, kidney stones, hypercalcemia, 
sarcoidosis, or other serious illness during the run-in; and (4) demonstrate continued willingness to limit 
supplemental vitamin D intake to ≤800 IU/d and to forgo the use of fish oil supplements.  
 
D.1.2. Treatment, compliance, and follow-up procedures  
Active vitamin D3 (2,000 IU [50 µg] per pill) and matching inert placebo will be provided by Pharmavite 
LLC. Active fish oil (1 g per soft-gel capsule, EPA to DHA ratio, 1:1) and matching inert placebo will be 
provided by Ocean Nutrition. With regard to follow-up, at 6 months and each anniversary date of 
randomization, participants will be mailed a follow-up questionnaire and a re-supply of bottles or calendar 
packs. The yearly follow-up questionnaire will include items on compliance with randomized treatments, use of 
non-trial supplements of vitamin D and fish oil, development of major illnesses, dietary intakes of vitamin D and 
fish, and updated risk factors related to cancer and CVD. Our primary measure of compliance will be the self-
reported information provided on the yearly follow-up questionnaires, which will ask about adherence to the 
pill-taking regimen. Because VITAL participants will reside throughout the U.S., it will not be possible to obtain 
blood samples for a validity study on all, or even a random sample of, participants. Thus, as in our previous 
trials, each year we will visit unannounced 50 New England-area participants, to request an on-the-spot blood 
sample to be analyzed for 25(OH)D and EPA+DHA levels. The distribution of these values will be compared 
between the active and placebo groups, and compared with the questionnaire data on compliance, as a test for 
validity. Non-responders will be mailed a second and third request and will then be telephoned to collect study 
data. At the very least, vital status will be ascertained. In the WHS, we were able to collect morbidity data on 
97% of participants and mortality data on nearly 100%; we anticipate similar rates in VITAL. Information on 
potential side effects of the study agents will be elicited for monitoring by the Data and Safety Monitoring 
Board. For fish oil, these side effects include GI upset (presence or absence of symptoms of peptic ulcer, 
nausea, constipation, diarrhea); bleeding (any GI bleed, GI bleeding requiring transfusion, hematuria, easy 
bruising, epistaxis); skin eruptions; and physician diagnosis of atrial fibrillation or other irregular rhythms. For 
vitamin D, these side effects include GI symptoms as listed above, and physician diagnosis of hypercalcemia 
or kidney stones.  
As indicated in Appendix A, a baseline questionnaire will be completed by all VITAL participants to collect 
detailed information on demographics (age, gender, race/ethnicity, education, occupation, income); medical 
history (cancer, CVD, hypertension, diabetes, hypercholesterolemia, renal disease, kidney stones, 
hypercalcemia, kidney failure, sarcoidosis, other major illnesses); allergy to fish; current use of supplements 
containing vitamin D or fish oil; current use of other supplements or medications; dietary intake of vitamin D 
and consumption of fish; cancer and vascular risk factors (e.g., smoking, height, weight, BP, cholesterol, 
diabetes, alcohol use, physical activity, and family history of cancer and CVD); and potential effect modifiers of 
the vitamin D component such as skin pigmentation (using the Fitzpatrick scale179, which ranges from ‘always’ 

to ‘never burns’) and sunlight exposure (time spent outdoors, outdoor physical activity, and sunscreen use [zip 
codes will be used to assess latitude and sun strength]). Respondents will also be asked to provide telephone 
number(s) and an e-mail address.  
A validated, self-administered semi-quantitative food frequency questionnaire (FFQ) will also be mailed to 
participants during the run-in. The performance of this FFQ, developed by Walter Willett, MD, DrPH, and 
colleagues, has been validated in many populations that were mainly European Americans180-184 but 
included Hispanic Americans7 and African Americans185. These validation studies comparing the FFQ 
with dietary records or biological measures in blood and adipose tissue have shown that this FFQ is 
an efficient, reliable, and accurate instrument for categorizing individuals according to their intake of 
32 nutrients, including vitamin D and marine omega-3 fats180-184. Participants are asked to estimate their 
average intake over the past year of various foods, beverages, and supplements that contain vitamin D, marine 
omega-3 fats, and other nutrients. Dietary vitamin D intake will be estimated from participants’ reported intakes 
of certain foods, including dairy products, fortified breakfast cereals, fortified juices, dark-meat fish, and cod 
liver oil. Dietary marine omega-3 fat intake will be estimated from intake of dark-meat fish, canned tuna, other 
fish, and seafood. Classifying participants by baseline intake of various nutrients will allow us to evaluate 
whether the study agents’ effects vary by such intake.  
D.1.3. Ascertainment algorithm for identifying incident diabetes:   
On the baseline and subsequent annual questionnaires supported by the parent VITAL trial, we will ask 
all the participants if and when they have ever been diagnosed with T2D. To confirm self-reported diagnosis, 
we seek funding to support retrieval of more detailed information regarding the onset of disease, symptoms, 
diagnostic tests, and hypoglycemic treatment for each incident diabetes case. For each participant who reports 
a diagnosis of diabetes on his/her annual follow-up questionnaire, written permission will be obtained prior to 
contacting his/her healthcare provider. We will contact the participant’s physician for information from medical 
records pertaining to diagnostic glucose values and any antidiabetic treatment. The physician will also be 
mailed a supplementary questionnaire concerning disease onset, symptoms, additional diagnostic tests, and 
hypoglycemic treatment. After all medical records and/or supplementary questionnaires are obtained, a 
study physician, blinded to the randomized treatment assignment, will review the records and make a 
final determination of case status. Confirmation will be based upon American Diabetes Association 
guidelines186 according to presence of: 1) One or more classic symptoms (thirst, polyuria, weight loss, hunger, 
pruritus, or coma) plus fasting plasma glucose (FPG) > 126 mg/dl (7.0 mmol/L) or random PG > 200 mg/dl 
(11.1 mmol/L); or 2) in the absence of symptoms, at least two elevated PG levels on different occasions (FPG 
> 126 mg/dl and/or random PG > 200 mg/dl and/or PG > 200 at > 2 hours on oral glucose tolerance testing); or 
3) treatment with hypoglycemic medication (insulin or oral hypoglycemic agent).  We will not perform glucose 
tolerance testing to screen VITAL participants for T2D at baseline because such an effort would be extremely 
costly and logistically challenging. However, we believe undiagnosed diabetes is likely to be evenly distributed 
in each comparison group as a result of randomization in a large population. Furthermore, any misclassification 
on this basis would only lead to only a slight underestimation of the intervention effect in a prospective setting; 
it should not produce spurious positive results 187.  
D.1.4. Additional information from the Centers for Medicare and Medicaid Services (CMS):  
We also plan to retrieve additional data on the occurrence of any diabetes-related hospitalizations or 
outpatient visits for diabetes, as well as use of oral hypoglycemic agents or insulin, by linking the participants 
with Medicare claims inpatient and outpatient databases from the Centers for Medicaid and Medicare Services 
(CMS). Based on results from our previous validation studies and our extensive experience, we believe that 
combined information from annual self-administered questionnaires and medical information provided by 
physicians through medical record of diagnostic glucose testing or antidiabetic medication, coupled with 
additional information from the CMS linkage inpatient and outpatient databases, will be a highly reliable and 
cost-effective approach to identify T2D in the cohort. The utilization of the CMS linkage database for 
diabetes diagnostic information will be independently supported by the funding from the Lung VITAL 
ancillary study (the Principal Investigator, Dr. Diane Gold). 
 
D.1.4.1. Linkage to the CMS inpatient and outpatient databases.   
Medicare is a US federal health insurance program that reimburses in-patient costs for most citizens and 
permanent residents aged ≥65 years. On an annual basis, we will obtain identifiable (Medicare) Data Files 
through ResDAC (www.resdac.unm.edu/Index.asp), which is a CMS contractor that provides free assistance to 
academic and non-profit researchers interested in using Medicare or Medicaid data.  The data use agreement 

(DUA) delineates the confidentiality requirements of the Privacy Act and data release policies and procedures. 
Participants can be identified via their social security number and date of birth or through their Medicare ID 
(HIC).  The following data will be obtained: 
i. 
MedPar Inpatient and Skilled Nursing Facility.  This file contains inpatient stay records summarizing all 
services rendered to a beneficiary from the time of admission to facility through discharge.  Each record 
may represent one claim or multiple claims, depending on the length of stay and the amount of inpatient 
services used throughout the stay.  Data include diagnosis and procedure codes, DRG, dates of service, 
reimbursement amount, hospital /SNF provider, and beneficiary demographic information. 
ii. 
Outpatient SAF.  Contains final action claims data from hospital outpatient departments, rural health 
clinics, renal dialysis facilities, outpatient rehabilitation facilities, comprehensive outpatient rehabilitation 
facilities, community mental health centers, and ambulatory surgical centers.  Information includes 
diagnosis and procedures codes, dates of service, reimbursement amount, outpatient provider number, 
revenue center codes, and beneficiary demographics. 
iii. 
Home Health SAF.  Contains final action claims data including the number of visits, type of visit (e.g., 
skilled-nursing care, home health aides, physical therapy), diagnosis, dates of visits, reimbursement 
amount, provider number, and beneficiary demographics.   
iv. 
Carrier SAF.  Contains final action claims data from non-institutional providers, including physicians, 
physician assistants, clinical social workers, and stand-alone ambulatory surgical centers.  Information 
includes diagnosis and procedures, dates of service, reimbursement amount, provider number, and 
demographics. 
v. 
Hospice SAF.  Contains final action claims data including level of hospice are routine (e.g., routine home 
care, inpatient respite care), terminal diagnosis, dates of service, reimbursement amount, provider 
number, and demographics.  
vi. 
Durable Medical Equipment SAF.  Contains final action claims data including diagnosis, services provided, 
dates of service, reimbursement amount, provider number, and demographics. (DME files began in 1994). 
vii. 
Bene ID Conversion File.  This file is needed to link the SSN finder file we will submit with the Medicare 
administrative data from the Research Data Distribution Center (RDDC).  The identifier on Medicare data 
files processed after November 2005 is called the RDDC Beneficiary Identifier (RDDC Bene ID).   
 
In previous studies which diabetes (ICD-9: 250), chronic obstructive pulmonary disease (COPD, ICD-9: 
490-496, except 493), pneumonia (ICD-9:480-487), congestive heart failure (CHF, ICD-9: 428), and myocardial 
infarction (MI), (ICD-9: 410) were examined, disease diagnosis indices have successfully been developed 
using physician claims data; these may be useful in secondary analyses evaluating whether vitamin D reduces 
T2D188. The sensitivity and predictive value of Medicare hospital claims data for major ICD-9-CM diagnoses 
was evaluated by Fisher and colleagues, who compared claims data with the original hospital record data. The 
sensitivity for diabetes diagnosis was excellent: 0.84 (0.81, 0.86); the predictive value was 0.85 (0.83, 0.88)189.  
Dr. Joel Schwartz and Dr. Antonella Zanobetti, consultants to the parent VITAL trial, are investigators at the 
Harvard School of Public Health and have many years of experience working with administrative Medicare 
data to evaluate a wide range of chronic disease outcomes, including diabetes. We will be able to consult with 
them as needed for support and assistance in the use of CMS linkage for the VITAL diabetes grant.  
 
D.1.4.2. CMS data protection and confidentiality.  When we obtain Identifiable (Medicare) Data Files 
through ResDAC (www.resdac.unm.edu/Index.asp), we will carefully adhere to the DUA, the confidentiality 
requirements of the Privacy Act, and data release policies and procedures. The VITAL data coordinating center 
will address the issues regarding ensuring data integrity, security and confidentiality through a System Security 
Plan to the NHLBI. All VITAL coordinating center staff will sign a confidentiality agreement as well as attending 
HIPAA and IT security training.  The CMS data will be securely stored at Division of Preventive Medicine, with 
access to the building controlled by key card, with security personnel monitoring entrance.  The original media 
on which the CMS data are supplied will be stored in a locked cabinet.  Clinical coordinating center passwords 
will be required to conform to our password policy. Logon access to the database will be password protected.  
Individually identifiable or deducible data will not be transmitted by unsecured telecommunications. The data 
will not be physically moved or transmitted from the clinical coordinating center without written approval from 
CMS. At the conclusion of the study, or by the date of retention identified in the DUA, a CMS “Certification of 
Destruction” certifying the proper destruction of all data obtained will be sent to CMS. These data files will be 
obtained through independent funding and will be available to the VITAL parent trial and all VITAL ancillary 
studies. 

 
 
D.2. Our Substudy with Data Collection at Baseline and after 2-Year Follow-up  
D.2.1. Clinical and Translational Science Centers (CTSC) subcohort in VITAL  
The main purpose of our 2-year substudy among 1,000 participants is to obtain detailed clinical 
assessments of glycemic status, insulin sensitivity and secretion in order to understand whether 
vitamin D or omega-3 fatty acid supplementation compared with placebo results in discernable 
changes in intermediate phenotypes of glucose and insulin homeostasis over a 2 year period. Such 
data will shed light on the physiologic mechanisms by which either or both supplements reduce T2D 
incidence, as well as identifying potential risks.     
This will be accomplished by establishing a Clinical and Translational Science Center (CTSC) subcohort 
of 1,000 VITAL subjects who live in four racially and ethnically diverse large metropolitan areas – Boston, 
Chicago, San Francisco, and Houston – and agree to additionally participate in a series of ancillary studies, 
including this proposal on T2D.  These CTSC sites among four major metropolitan areas also provide good 
geographic and racial/ethnic diversity (please refer to Section O for letters of support and collaboration from 
the Principal Investigators of the CTSCs in Boston, Chicago, San Francisco, and Houston). These CTSC sites 
are part of a funded, high-priority NIH program for translational research that streamlines and facilitates the 
translation of research findings into tangible health benefits through established infrastructure for space, 
experienced staff, dedicated equipment and administrative support for the clinical visits for VITAL and other 
clinical research studies. Most of the staff time and faculty collaborations will be funded independently. Staff at 
each of the CTSCs will be trained in the standardized protocol for the VITAL CTSC component and will 
undergo regular site visits to evaluate compliance with the protocol and to identify any quality assurance 
problems.  
Each of the 4 participating CTSCs has a project director and additional staff to carry out the 
protocol that may include recruitment coordinators, physicians, nurses, data collectors, and others. 
The project director will be appointed among local clinicians by the CTSC Director at each site and will 
have broad oversight for our ancillary studies, inter-institutional collaborations, and will bear ultimate 
responsibility for the operations of the substudy (Three of four CTSC project directors have been 
appointed and their letters of support are provided in Appendix C). The project director at each of the 
four CTSC will be responsible for monitoring each of the proposed ancillary studies, supervising the 
staff at the CTSC who will be conducting the various evaluations, and interfacing with the Project 
Coordinator and Principal Investigator in Boston. They will oversee the implementation of the CTSC 
protocol (including the oral glucose tolerance testing [OGTT]) at each site. The Principal Investigator of 
this ancillary study will oversee the entire ancillary project and will coordinate each project director of 
4 CTSCs by producing and modifying standard protocols or operating procedures, monitoring the 
recruitment, reviewing and approving requests for data access and database proposals, monitoring 
human protection, confidentiality, and security procedures, scheduling regular meetings, and creating 
opportunities to enhance collaboration within and across CTSCs. Under the supervision of the 
Principal Investigator, the Project Coordinator will work closely with four project directors and other 
CTSC staff to ensure that the work is completed in an accurate and timely fashion. To maximize the 
consistency and quality control in the performance of the parent and ancillary studies across the 
CTSCs, staff at each site will be trained in the protocol for the VITAL CTSC component and will 
undergo regular site visits to evaluate compliance with the protocol and to identify any quality 
assurance problems. Data collected for this study will comply with the standardized protocol 
established by the ancillary study. Our project coordinator will provide research and administrative 
support as needed by the Principal Investigator and research team. He/she will work with CTSC staff 
from 4 sites to collect the data in a consistent manner, and to conduct site visits to ensure compliance.  
As potentially willing and eligible participants are enrolled into VITAL, we will identify 1,000 participants 
without previously diagnosed T2D who are eligible respondents to the VITAL questionnaires in the greater 
metropolitan areas of Boston, Chicago, San Francisco, and Houston, and also agree to participate in ancillary 
studies (funded through other grants) that will make use of CTSCs for clinical examinations and blood 
collections. Approximately 250 participants will be recruited at each of 4 CTSC sites. In addition to prespecified 
inclusion criteria in the VITAL trial, all eligible participants should be in generally good health, mobile, and able 
to give complete informed consent. A copy of the consent form will be sent home and all participants will 
provide written informed consent. At both the baseline and 2-year follow-up CTSC clinical visits, several 
standard clinical assessments will be performed, including height, weight, waist/hip circumference, and blood 

pressure.  Participants will be compensated for their time and travel. This CTSC subcohort is expected to have 
the same racial/ethnic composition as the overall VITAL cohort and will be randomized equally into the 4 
treatment groups (1000 overall; 250 participants in each of the 4 groups: vitamin D alone, omega-3 alone, both 
agents, or both placebos).  
These 1,000 participants will also have blood drawn at baseline and after 2 years of follow-up (matched 
by season, by month). During the CTSC visit, blood will be drawn, centrifuged and processed locally, and the 
plasma, serum, red blood cells, and buffy coats (including multiple vials of EDTA, heparin, and citrate plasma, 
and one vial each for EDTA red blood cells, EDTA buffy coat, and citrate buffy coat) will be frozen and stored 
temporarily at the CTSC laboratory. At regular intervals, the CTSC will send overnight shipments of all frozen 
samples to the blood laboratory at the Division of Preventive Medicine, Brigham and Women’s Hospital for 
storage in liquid nitrogen freezers. Each freezer has a back-up power system connected to an electronic alarm 
that has protected stored samples from inadvertent thawing or warming for nearly 20 years. This resource will 
also be extremely valuable for future studies to explore other genetic and biochemical hypotheses in this well-
characterized cohort. A nested case-control or case-cohort approach can be used, enabling the study of many 
promising biochemical and genetic markers (e.g., VDR polymorphisms) as potential predictors of disease risk 
and modifiers of intervention effects at very low incremental cost. 
D.2.2. Assessment of glucose and insulin homeostasis  
We propose to perform an oral glucose (75 g) tolerance test (OGTT) (2 hours) to accurately screen for 
T2D in our subsample of 1,000 participants at study entry and after randomization. Our aims in this effort will 
be to: 1) obtain more accurate assessment of insulin and glucose homeostasis using OGTT; and 2) assess the 
effect of vitamin D and omega-3 supplementation on objective measures of insulin sensitivity and insulin 
secretion by OGTT, plasma HbA1c levels, and HOMA-IR and HOMA-%B. This approach represents an 
extremely cost-effective trial considering its size and potential to answer critical questions. Participants in this 
subset will be stratified by randomized assignments in a manner that will provide important information for 
objective estimates of insulin sensitivity and secretion. The data collected in this subset will complement the 
data collected in the entire trial by providing more important information on the individual effects of vitamin D 
and omega-3 fatty acids in intermediate metabolic phenotypes.  
Following standardized protocol, an OGTT using an oral dose of 75 g glucose will be performed in the 
morning at the same time for each participant after an overnight fast. Blood samples will be taken at baseline (-
5 minutes) and after 30, 60, and 120 minutes for measurements of glucose and insulin. Diabetes will be 
defined according to the 2003 criteria of the American Diabetes Association186: a plasma glucose value of ³ 
126 mg/dL (7 mmol/L) in the fasting state or a 2-hour postprandial glucose ³ 200 mg/dl (11.1 mmol/L) after 
taking a 75-g oral glucose load. The following parameters will be measured: (1) Insulin sensitivity and b-cell 
function. Insulin sensitivity will be estimated using the whole-body insulin sensitivity index (ISI) derived from the 
OGTT as proposed by Matsuda and DeFronzo190. Insulin secretion will be estimated using the insulinogenic 
index, which is a commonly used index of b-cell function defined as the ratio of the increment of plasma insulin 
(µIU/ml) to that of plasma glucose 30 min (mmol/ml) after glucose loading.  (2) Glucose tolerance or glycemic 
status. In addition to fasting glucose and insulin levels, HbA1c will be monitored to reflect recent average 
glycemia during the previous 2 to 3 months and to assess its changes in response to the assigned 
interventions.  (3) Other indices of glucose and insulin homeostasis. The fasting plasma glucose and insulin 
levels and their derived HOMA-IR and HOMA-B will be analyzed as a secondary variable. HOMA-IR will be 
computed as follows: fasting insulin (µIU/ml)´ fasting glucose (mmol/ml) /22.5 and HOMA-%B will be 
calculated using the following formula: 20 ´ fasting insulin (µIU/ml)/ fasting glucose (mmol/ml)-3.5. Glucose will 
be measured enzymatically on the Hitachi 911 analyzer using Roche Diagnostics reagents (Indianapolis, IN). 
Insulin will be measured by an ultra-sensitive ELISA assay from ALPCO Diagnostics (Windham, NH).  HbA1c 
will be measured using turbidometric immunoinhibition, classically using whole blood hemolysates (Boehringer 
Manheim). We will store all the samples collected at baseline and 2-year follow-up for batching at the 
blood laboratory at the Division of Preventive Medicine, Brigham and Women’s Hospital in Boston, MA. 
To minimize biases due to intra- and inter-assay variability across CTSCs and/or over time, no assays 
including OGTT will be done by the Central Lab, the Biochemistry Laboratory of Dr. Nader Rifai at 
Children’s Hospital in Boston (MA), until the end of follow-up for this substudy.  
 
D.2.3. Measurements of plasma 25(OH)D levels:   

As part of the parent VITAL grant (NIH 1 U01 CA138962), plasma levels of 25(OH)D will be assayed and 
available for our proposal in 2000 paired blood samples (baseline and 2 year follow-up).  Plasma 25(OH)D will 
be measured by Dr. Bruce Hollis at the Medical University of South Carolina.  Circulating 25(OH)D will 
determined by radioimmunoassay, which uses reagents from the DiaSorin Corporation (Stillwater, NM), 
recognizes and quantitates 25(OH)D2 and 25(OH)D3 equally.  This assay has been in widespread clinical use 
for nearly 20 years, and has also been employed for research use in numerous research studies.  In Dr. Hollis’ 
laboratory, the intra- and inter-assay coefficients of variation are <10% for 25(OH)D191-193. 
Despite the widespread use of this radioimmunoassay, we are cognizant that there are multiple other 
measurement techniques currently employed around the world, and that there is substantial intra- and 
interassay variation in reporting of 25(OH)D levels among these techniques (i.e., laboratory drift over time plus 
lack of agreement among different techniques).  As a consequence, the VITAL study will purchase and utilize 
Standard Reference Material (SRM) for 25(OH)D2 and 25(OH)D3 measurements (SRM 972); these samples 
will soon be available from the National Institute of Standards and Technology (NIST).  Dr. Hollis will report his 
assay performance based on this SRM, and we will incorporate the results in all appropriate manuscripts.  In 
addition, the VITAL study will participate in the Office of Dietary Supplements (ODS) funded NST quality 
assurance program for measurement of 25(OH)D2 and 25(OH)D3 using human blood samples. Use of SRM 
972 will enhance the interpretability and validity of our study, and participation in the quality assurance program 
will enhance the overall performance of our lab over time. 
D.3. Trial Data Management and Monitoring 
For the main VITAL study of 20,000 participants, our computing system, which was developed and fine-
tuned in our previous trials, will track each participant’s stage and level of participation in VITAL by 
automatically generating letters, questionnaires, and phone call reminders at the appropriate times. 
Questionnaire data will be optically scanned into the computer using TELEform and Alchemy (Cardiff Software) 
programs that have been successfully used for our other mail-based clinical trials (WHS, PHS). Out-of-range, 
internally inconsistent, and unclear data are reviewed by a verifier who corrects misread variables. Forms that 
cannot be scanned, and name and address changes, are entered using traditional double-entry procedures. All 
data undergo additional within-form and across-time checks to verify accuracy. The database will be 
maintained on a UNIX server. All data files will be backed up nightly, ensuring at least two current copies at all 
times. Each month, a set of data files will be taken off-site for long-term storage. 
The Principal Investigator will be responsible for the observance of all conditions of use and for 
establishment and maintenance of appropriate administrative, technical and physical security 
safeguards to prevent unauthorized use and to protect the confidentiality of the data. To maintain 
confidentiality, we will substitute codes for participant identifiers, remove face sheets containing 
patient demographic information, properly dispose of participant identifying documents, limit access 
to identified data and store research records in locked cabinets. All participant samples obtained will 
be maintained in the Division of Preventive Medicine at Brigham and Women’s Hospital. Information 
obtained from the results of our study, if published, will be presented collectively and without 
participant identifiers. In addition, our project programmer will analyze the data and create summary-
level reports for each CTSC site to inform the Principal Investigator of the results of the project. Data 
reports will also be produced to comply with the requirements of the grant. For the CTSC subcohort of 
1,000 VITAL participants, study personnel at each CTSC site will collect the data from the proposed clinical 
visits using optically scannable forms.  These forms will be optically scanned at each CTSC site and sent to the 
Division of Preventive Medicine for additional reviews, verification, and data checks to identify out-of-range 
values and maximize accuracy. All the blood samples collected at baseline and 2-year follow-up for the 
substudy will be stored for batching until the end of follow-up. If available, the testing results including 
OGTT will be reported to local health care providers. The investigators will refer participants to their 
primary care physicians when diabetes is diagnosed or when test results require follow-up.  
With regard to the risks of the study agents, information on potential side effects discussed above will be 
elicited on each follow-up questionnaire for monitoring by the Data and Safety Monitoring Board.  We will 
compare the incidence of potential side effects in the active versus placebo groups for each agent, including 
the incidence of kidney stones with vitamin D assignment and the incidence of GI symptoms, skin 
abnormalities, and bleeding with fish oil assignment. The potential risk of disclosure of confidential information 
is guarded against by maintaining completed questionnaires and blood test results in locked files accessible by 
authorized personnel only. Endpoint and health-related questionnaire data will be stored in separate files from 
the processing data and will be accessible only to approved investigators and programmers. In these files, 

participants are identified only by study ID. Each dataset will require documentation. Documentation provides 
information about the methodology and procedures used to collect the data, details about codes, definitions of 
variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by 
scientific area, study design, the type of data collected, and characteristics of the dataset. The data will be 
available only to authorized staff members. Our existing computer and security systems, which balance these 
considerations, will be used in VITAL. In addition, employees involved with the proposed study will be asked to 
sign a form agreeing not to disclose any information to which they might have access, regardless of their 
personal perception about its confidentiality. Each employee of the study with human subject contact 
participates in an institutional (Brigham and Women’s Hospital) human subjects educational program, which 
consists of reviewing regulatory and informational documents pertaining to human subjects research; passing 
a test on ethical principles and regulations governing human subjects research; and signing a statement of 
commitment to the protection of human subjects.  Finally, all such employees are required to participate in 
HIPAA training.  
D.4. Statistical Analysis 
D.4.1. Primary analysis plan for all incident T2D in the parent trial  
All analyses will be conducted with SAS version 9 (SAS Institute, Cary, NC), and a 2-sided test with a 
significance level of a=0.05 (p<0.05) will be used. Analyses of treatment effects will be based on the intent-to-
treat principle. All prevalent T2D cases at baseline will be excluded. The first analysis will compare baseline 
characteristics by randomized treatment assignment to ensure that balance is achieved by the randomization. 
Baseline characteristics will be compared by randomized groups using 2-sample t tests for continuous 
variables and c2 statistics for categorical variables. Characteristics to be examined include known diabetes risk 
factors, including age; gender; race/ethnicity; BMI; smoking; alcohol use; physical activity; medical conditions 
such as hypertension, hyperlipidemia, and family history of diabetes mellitus; and baseline vitamin D and 
omega-3 fatty acid intakes as assessed by dietary questionnaires of all participants. The large sample size, as 
well as successful balance of known potential confounders, will provide assurance that unmeasured or 
unknown potential confounders will also be equally distributed across randomized treatment groups. 
The primary aim is to compare the main effects of intention-to-treat with vitamin D and with fish oil on the 
incidence of T2D. Kaplan-Meier survival curves will be used to estimate the overall cumulative incidence over 
time for each active treatment group and its corresponding placebo group. The log-rank test will be computed 
to compare the curves. We will then use the Cox proportional hazards model to allow for variable follow-up 
lengths and will estimate the hazard ratio for each intervention using indicators for treatment exposure194, 
controlling for age and gender. To test the proportionality assumption (i.e., that of non-changing hazards ratios 
over time), we will include an interaction term for treatment with the logarithm of time in the Cox models. 
Beyond the primary analyses, we will examine effect modification by two randomized interventions, sex, and 
race. Similar analyses will be conducted in subgroups stratified by sex and race (Whites and Non-Whites). We 
also have a prior interest in the effects of the vitamin D intervention within groups defined by race/ethnicity, 
sunlight exposure, geographic regions, and BMI. In addition, we will evaluate effect modification by vitamin D, 
long-chain polyunsaturated fatty acids, calcium and phosphorus intakes from the FFQ (as these nutrients affect 
vitamin D bioavailability41), as well as other baseline risk factors for T2D. We will formally assess the statistical 
significance of effect modification using interaction terms between subgroup indicators and randomized 
assignment, testing for trend when subgroup categories are ordinal. We will also test interactions of the 2 
agents using interaction terms in the Cox model.  
Multiple sensitivity analyses will be carried out according to compliance. Participants will be censored if 
and when they stop taking at least two-thirds of their study pills, report taking outside supplements containing 
study agents, or are missing compliance information. Considering latency period for diabetes prevention, we 
will also subdivide the period of risk into years 1 and 2 combined and year 3 onward combined. We will 
examine whether treatment effects vary over time and duration of treatment by examining survival plots and 
interactions with time as described above in the test for non-proportional hazards. To further safeguard the 
health of the study participants, all the test results including OGTT in the subset study will be reported 
to local health care providers. Because intervention approaches provided by physicians among 
diabetes patients or pre-diabetic individuals (i.e. IFG or IGT) will possibly dilute the effect estimates 
from the primary intention to treat analysis in the entire trial, future secondary analyses by excluding 
the substudy samples (5%) will be performed.  
 

D.4.2. Analysis plan for longitudinal changes in intermediate phenotypes in our subset study 
For all continuous measurements (e.g. HbA1c, OGTT parameters) at one time point (pre-randomization 
and post-randomization), we will first examine the distributions and use transformations to achieve normality 
when necessary. We will compare baseline values to ensure balance by randomized treatment assignment, 
both overall and by CTSC site. The intraclass correlation coefficient will be calculated to determine the 
association between two separate measurements for each parameter over time in each intervention group for 
descriptive purposes.  
The primary analysis in our proposed substudy is to determine the effects of randomized vitamin D or 
omega-3 treatments on the changes in surrogate measures of glucose tolerance, insulin sensitivity and insulin 
secretion between baseline and the end of 2-year intervention period. These continuous measurements will be 
examined by analysis of covariance, including terms for baseline value, treatment, and CTSC site. For each 
continuous primary outcome (surrogate indices of insulin sensitivity and secretion and HbA1c levels), we will 
use a linear mixed-effects model for these repeated measures over time, including two measurements for each 
outcome as the dependent variables, with random intercepts and slopes as a function of time and fixed effects 
for CTSC sites, treatment, time, and interaction between time and treatment, accounting for the correlation 
among repeated measures in the same participant. Within the mixed model, we will estimate 95% CIs and P 
values for the two main intervention effects (vitamin D versus placebo and omega-3 fatty acids versus placebo) 
for changes in those indices between baseline and 2 years of follow up within each group.  
With multiplicative interaction terms, we will study whether treatment effects differ by the other 
intervention or across subgroups. These prespecified analyses will be performed for age (<75 and ≥75 years), 
sex, race (Whites or non-Whites), BMI (<25 and ≥25 kg/m2), baseline levels of 25(OH)D, and baseline intake of 
dietary long-chain omega-3 fatty acids (above and below the median). Additional analyses will be performed 
with adjustment for age and BMI at baseline and sex and race. For continuous secondary outcomes (HOMA-
IR, HOMA-B and fasting glucose and insulin levels), we will use the same procedures as in the primary 
analysis. The regression parameters in our linear mixed-effects models will be estimated with the Proc Mixed 
program of the SAS software package (version 9, SAS Institute, Cary, N.C.). Testing will be two-sided and 
conducted with a 5% type I error rate.  
In addition, to increase power, we will analyze the change in measures from baseline to follow-up 
conditioning on the baseline value. Because of the randomization, this is unlikely to be affected by regression 
to the mean, and should provide a more powerful analysis, depending on the correlation of the measures over 
time195. We will use linear regression analysis to adjust for any imbalance in key variables at baseline, and to 
adjust for study site in the CTSC data. If follow-up to the 2-year evaluation is less than complete, we will 
conduct sensitivity analyses to estimate the effect under intention-to-treat. For example, we will impute the 
mean change in effect found in the placebo group, adding a random error to allow for within-person variation. 
We will use multiple imputation to correct the error term196, 197. While this should drive the estimated treatment 
effect closer to the null, those who do not appear for follow-up visits are less likely to be continuing to take 
study agents.   
 
D.5. 
Power Calculations  
We calculated the power of our primary trial and substudy separately by using a Stata program 
developed by Royston and Babiker for multi-arm clinical trial designs198, 199. The power computation is based 
on the log-rank test and is performed according to the asymptotic distribution of the log-rank test statistic, 
adjusted appropriately for the design features such as arbitrary time-to-event distribution, nonproportional 
hazards, non-uniform rates of patient entry, loss to follow-up, and treatment changes from allocated treatment 
198. This approach was performed using Intercooled Stata version 8.2 (Stata Corporation, College Station, TX).  
D.5.1. Type 2 diabetes risk in the trial. Based on the age-specific rates of prevalence and incidence of T2D 
in the U.S. general population (non-
Hispanic whites and African 
Americans), we calculated the power 
to detect a clinically meaningful 10-
40% reduction in the incidence of T2D 
among the participants without self-
reported T2D at baseline. Assuming 
that the prevalence of T2D for the U.S. 
elderly population (³60 years) is 
Table 3. Power for effects of a single agent on incident T2D in the parent VITAL trial 
with 10,000 men aged≥60 and 10,000 women aged≥65 with 5 years of follow-up 
RR† 
Total  
Women 
Men 
White 
Minority 
16,770 ‡ 
9,210 ‡ 
9,270 ‡ 
14,100 ‡ 
4,305 ‡ 
0.90 
79.4% 
42.2% 
42.4% 
58.8% 
22.5% 
0.85 
98.8% 
76.5% 
76.8% 
91.3% 
45.0% 
0.80 
>99.9% 
95.3% 
95.4% 
99.4% 
69.9% 
0.75 
>99.9% 
99.6% 
99.6% 
>99.9% 
88.3% 
0.70 
>99.9% 
>99.9% 
>99.9% 
>99.9% 
97.0% 
0.65 
>99.9% 
>99.9% 
>99.9% 
>99.9% 
99.5% 
0.60 
>99.9% 
>99.9% 
>99.9% 
>99.9% 
>99.9% 
†Expected RR; ‡ Expected total number of non-diabetic participants.  
 

16.0%31, we will have approximately 4,200 participants for each randomized treatment. With an annual 
incidence rate of T2D of 2.7% for the U.S. elderly population (³60 years)32 and a significance level of 5% for a 
2-sided test, we will have about 80% power to detect a 10% reduction in T2D during 5 years of treatment and 
follow-up (allowing for a 80% compliance rate in each arm) (Table 3).  As expected, power to explore the sex-
specific or ethnic-specific effects in the cohort will be lower due to decreasing sample sizes. We would have 
enough power to detect a 15-20% risk reduction for women and men, separately. Since 25% of the total 
population will be non-white minority group, we would have 80% power to detect a risk reduction of 
approximately 25% in this group.   
If both agents are effective in preventing T2D but act independently, power would be reduced slightly due 
to a somewhat smaller overall number of events. If 
the agents interact, however, power will be affected 
to the extent of the interaction. By assuming a 2-
sided a level at 0.05, we calculated power over a 
range of one single agent effect from 0.80 to 0.75, 
and the ratio of RRs for interaction ranging from 
1.00 (only an additive effect) to 0.70 (with an 
additional 30% reduction).  As shown in Table 4, 
using the total samples of non-diabetic participants 
(n=4,200 participants for each randomized 
treatment given approximately 16% prevalent T2D 
in the U.S. elderly population)31, we will have 
enough power (>80%) to detect important 
interactions with a ratio of RR ≤0.90. Should the 
agents act synergistically, power would increase, as 
illustrated in Table 4 for main effects for the outcome of T2D.  
D.5.2. Continuous outcomes in the substudy. To compute statistical power for changes in each of 
continuous outcomes collected in the subset study, we must obtain the expected mean difference and its 
standard deviation based on previous clinical randomized trials which ascertained the effect of fish oil 
supplements (DHA and EPA) and vitamin D3 on glucose and/or insulin homeostasis.  Given numerous small-
scale trials of fish oil supplementation, we focused on the pooled weighted mean differences or net mean 
differences from previous meta-analyses rather than individual trials.  We identified 4 meta-analyses of 
randomized trials of fish oil supplements on glycemic biomarkers in which 15 or 21 randomized trials were 
included with trial durations of 2 to 52 weeks (Table 2)124, 126, 158, 159.  We also identified 4 randomized trials with 
a total of 1,560 non-diabetic participants and durations from 6 weeks to 7 years (median=24 months) that 
specifically examined vitamin D3 supplementation (doses ranged from 400 to 8,572 IU/day; the median 
dose=2000 IU) (Table 1)67, 68, 92, 93.  These previous clinical trials or meta-analysis of randomized trials provided 
sufficient information to compute the standard deviations of the outcome change for at least one of main 
outcomes.  Based on the respective median values (to avoid unstable outliers), we finally assumed standard 
deviations of 2.28 for ISI, 12.0 for IGI, 0.72 for HbA1c, 0.32 for HOMA-IR, and 16 for HOMA-B, respectively.  
Therefore, to 
calculate power, the 
following 
assumptions were 
made:  (1) a 2x2 
factorial trial in 
1,000 participants 
without T2D at 
baseline; (2) 
independent and 
equal allocation of 
participants to each 
treatment; (3) an estimated 13% undiagnosed T2D identified by OGTT; and (4) a dropout rate of 20%. Using 
these estimates, a total of 700 non-diabetic participants will provide us sufficient power to detect various 
changes in these intermediate measures between baseline and after 2 years of follow-up by interventions. As 
noted in Table 5, overall, we will have adequate power (>80%) to detect the expected 2-year changes in our 
Table 4. Power for interaction effects on incident T2D in the VITAL trial 
of 10,000 men aged ≥60 and 10,000 women aged ≥65 with 5-year 
follow-up 
RR 
Single agent† 
Interaction
† 
RR  
Both 
agents 
Power 
Main Effect    
Interaction 
0.90 
1.0 
0.81 
73.3% 
 
 
0.9 
0.73 
96.1% 
24.4% 
 
0.8 
0.65 
99.8% 
74.8% 
 
0.7 
0.57 
>99.9% 
98.4% 
0.85 
1.0 
0.72 
97.1% 
 
 
0.9 
0.65 
99.8% 
23.1% 
 
0.8 
0.58 
>99.9% 
71.7% 
 
0.7 
0.51 
>99.9% 
97.7% 
†RR = expected RR, including only compliant participants (assuming 80% 
compliance). Represents the effect among those not assigned to the other 
intervention and assumes the same effect for both agents. The interaction is 
the RR for the combined group divided by the product of risks for the two 
separate groups—i.e., RRint=RRboth/(RR vit D alone* RR fish oil alone). An 
interaction=1 implies additive effects (no interaction). 
Table 5. Power calculation for intervention effects on surrogate measures as continuous outcome variables 
in our subset study of 1000 non-diabetic participants † 
ISI 
Power 
IGI 
Power 
HbA1c  
Power 
HOMA-IR 
Power 
HOMA-B 
Power 
0.15 
41.2% 
1.5 
91.1% 
0.05 
45.0% 
0.05 
98.5% 
2.0 
91.1% 
0.25 
82.6% 
2.5 
>99.9% 
0.10 
95.7% 
0.10 
>99.9% 
2.5 
98.5% 
0.35 
98.2% 
3.5 
>99.9% 
0.15 
>99.9% 
0.15 
>99.9% 
3.0 
99.8% 
0.45 
99.9% 
4.5 
>99.9% 
0.20 
>99.9% 
0.20 
>99.9% 
3.5 
>99.9% 
ISI, Insulin Sensitivity Index (mg/kg/min); IGI, Insulinogenic index for Insulin Secretion (pmol/mmol); HbA1c, 
glycated hemoglobin A1c (%); HOMA-IR, the homeostasis model assessment of insulin resistance; HOMA-B, the 
HOMA of beta-cell function.  
†The expected effects were expressed as the mean difference of the outcome change between baseline and after 
2 years of follow-up (the treatment group versus the placebo group).  

primary outcome measures (ISI, IGI, and HbA1c) and secondary measures (HOMA-IR and HOMA-B), although 
we will not have enough power to detect sex- or ethnicity-specific effects in this subset study.   
D.6. Strengths and Limitations  
This ancillary study will test two very promising nutritional agents (vitamin D and fish oil) for the 
prevention of T2D in an extremely cost-effective fashion—i.e., utilizing the resource provided by the parent 
VITAL trial. Strengths of this ancillary study include the unique resource provided by the parent trial, large 
numbers of participants at high risk for T2D, long follow-up, high-quality covariate data, and exceptional cost-
efficiency.  The dose for each agent was chosen on the basis of an extensive and careful review of available 
evidence, with the goal of optimizing the balance of safety and efficacy. We will develop and implement an 
inexpensive and efficient strategy to validate all self-reported incident T2D cases in the entire trial population 
as a primary outcome and to collect pre- and post-intervention measures of insulin and glucose homeostasis in 
a subset of the participants as secondary outcomes. The proposed study also has some potential limitations.  
Misclassification due to undiagnosed T2D: As a continuous progressive metabolic disorder, T2D often begins 
with years of an asymptomatic state of insulin resistance (including hyperglycemia and compensatory 
hyperinsulinemia) before resulting in an irreversible “exhaustion” of pancreatic b-cells that ultimately leads to 
an irreversible state of T2D.  As in any large-scale epidemiological study, classification will not be perfect and 
will involve some trade-offs. Because the cost for screening 20,000 participants who currently reside in 
different parts of the country would be prohibitively high and the gain in data quality negligible, the strategy we 
propose to assess T2D is a cost-efficient and sufficiently accurate to achieve the outlined scientific goals. We 
believe undiagnosed diabetes is likely to be evenly distributed in each comparison group as a result of 
randomization in a large population. Furthermore, any misclassification on this basis would only lead to an 
underestimation of the intervention effect in a prospective setting; it should not produce spurious positive 
results. We also plan to retrieve additional data on the occurrence of any diabetes-related hospitalizations, and 
use of oral hypoglycemic agents or insulin by linking the participants with Medicare claims data from the CMS 
database. Based on results from our previous validation studies and our extensive experience, we believe that 
combined information from annual self-administered questionnaires and medical information provided by 
physicians through medical record, phone interview, or supplementary questionnaire, coupled with additional 
medical record data from the CMS linkage database, will be a highly reliable and cost-effective approach to 
identify T2D in the cohort and minimize the proportion of undiagnosed cases.  
Fixed doses set by the parent study: The goal of our ancillary study is to complement but not overlap 
or interfere with the primary and secondary objectives of the parent trial. Our proposed diabetes 
research will test only one dose of each agent rather than examining multiple doses to determine the 
dose-response relationship. The dose for each agent was chosen on the basis of an extensive and 
careful review of available evidence, with the goal of optimizing the balance of safety and efficacy. The 
dose of vitamin D (2,000 IU/day) is sufficient to produce optimal plasma concentrations of 25(OH)D but 
below the tolerable upper intake level of vitamin D ingestion in adults. On the basis of pharmacokinetic 
and epidemiologic data, it may be possible to conclude that vitamin D supplementation is effective 
without an additional trial using multiple doses. The proposed intervention of 1 g/d EPA/DHA 
supplement would be expected to have the effect of achieving the purported optimal levels associated 
with health benefits in previous studies but with minimal risks.  
Multiple comparisons: There is a concern of false positive results due to multiple testing especially in 
our proposed subgroup analyses. However, our stratified analyses are essentially fully pre-specified 
based on prior clinical data and are exploratory in nature. Although we do not plan to formally 
implement statistical adjustments for multiple comparisons, we will evaluate any observed effects in 
light of prior human and animal data, as well as the plausibility of the biological mechanisms.  
Generalizability: Because our participants are not a random sample of US adults, we will not generalize our 
findings to the US population without carefully considering lifestyle and genetic characteristics. Because the 
trial population is older, the results may not be generalizable to younger men and women. However, older 
populations have the highest rates of T2D, allowing the trial to be completed in a shorter time period, at greater 
cost efficiency.