Real-Time Continuous Glucose Monitoring to Aid Weight Loss in Prediabetes
Phase: NA
Conditions: Weight Loss, PreDiabetes
Sponsor: Stanford University

March 19, 2019 
Real-Time Continuous Glucose Monitoring to Aid Weight Loss in Prediabetes 
IRB Protocol Number: 49402 
NCT Number: 03844646 
 
Table of Contents 
STUDY OVERVIEW ......................................................................................................................................... 3 
KEY STUDY PERSONNEL ................................................................................................................................. 4 
FUNDING SOURCES ....................................................................................................................................... 4 
Study Protocol ............................................................................................................................................... 5 
1. 
BACKGROUND ................................................................................................................................... 5 
2. 
STUDY AIMS ...................................................................................................................................... 6 
3. 
STUDY DESIGN ................................................................................................................................... 7 
3.1 Sample Size ..................................................................................................................................... 7 
3.2 Study Population ............................................................................................................................. 7 
3.3 Study Location ................................................................................................................................. 7 
3.4 Study Duration ................................................................................................................................ 7 
3.5 Randomization ................................................................................................................................ 7 
4. 
STUDY PROCEDURES ......................................................................................................................... 8 
4.1 Study Design .................................................................................................................................... 8 
4.2 Recruitment .................................................................................................................................... 8 
4.3 Intervention .................................................................................................................................... 8 
5. 
STATISTICAL CONSIDERATION .......................................................................................................... 9 
5.1 Statistical Basis for Sample Size ...................................................................................................... 9 
5.2 Statistical Plan ................................................................................................................................. 9 
REFERENCES ................................................................................................................................................ 10 
APPENDIX .................................................................................................................................................... 12 
A. Inclusion/exclusion criteria ................................................................................................................. 12 
B. Questionnaire ..................................................................................................................................... 12 
C. Outcome Measurement Methods ...................................................................................................... 13 
 

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STUDY OVERVIEW 
Study Title 
Real-Time Continuous Glucose Monitoring to Aid Weight Loss in Prediabetes 
Abbreviations 
Real-Time Continuous Glucose Monitoring (RT-CGM) 
 
Study Aims and Outcome Measures 
RT-CGM has revolutionized the treatment of patients on intensive insulin therapy and its 
utility can also be harnessed to help individuals with prediabetes make healthful lifestyle 
changes. Successful weight loss requires adherence to lower calories, regular exercise, 
and self-monitoring. This proposal will test the hypothesis that RT-CGM will facilitate all 
of these components for successful weight loss by functioning as a continuous self-
monitor and guiding healthful food choices and physical activity. 
 
AIM #1:  Compare weight loss.  
Intermittent RT-CGM use will augment dietitian-guided weight loss in individuals with 
prediabetes. 
 
AIM #2:  Compare physical activity.  
Intermittent RT-CGM use will increase physical activity compared with dietitian support 
only. 
 
Other measures will include glucose indices (fasting glucose, A1c).  
 
Study Population 
We aim to enroll 50 participants who are overweight/obese with prediabetes. Please 
see APPENDIX A for more detailed inclusion/exclusion criteria. 
 
Design 
This will be a randomized, parallel-group, pilot study of intermittent RT-CGM with 
dietitian support versus dietitian support only. 
 
 
 
Duration 
We anticipate that the entire study will take 24 months through data analysis. Each 
eligible candidate who voluntarily consents to participate in the study will be active on 
the study for a total of 4 months.  

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KEY STUDY PERSONNEL 
Co-Principal Investigator 
Sun Kim, MD MS 
Associate Professor of Medicine, Division of Endocrinology, Stanford University 
 
Co-Principal Investigator 
Christopher D. Gardner, PhD 
Rehnborg Farquhar Professor of Medicine, Stanford University 
 
Study Dietitian 
Leah Groppo 
 
Study Coordinator 
Pending 
 
 
FUNDING SOURCES 
 
Stanford Diabetes Research Center Pilot and Feasibility Grants Program 
 
 

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Study Protocol
1. BACKGROUND
The heart of diabetes prevention is lifestyle changes and weight reduction. The pivotal 
Diabetes Prevention Program (DPP) study clearly demonstrated that weight loss of 7% and 
moderate physical activity reduced the incidence of type 2 diabetes (DM2) in individuals 
with prediabetes.1 In addition, lifestyle changes were superior to early initiation of 
metformin, a glucose-lowering medication. While benefits of lifestyle changes are 
undeniable, successful interventions are lacking to help individuals with prediabetes make 
and sustain lifestyle changes leading to significant weight loss. Currently, DPP-modelled 
“real-life” interventions show an average weight loss of 4% and show drop-out rates as high 
as 50%.2  
The goal of this proposal is to test the hypothesis that real-time continuous glucose 
monitoring (RT-CGM) will facilitate weight loss in overweight/obese individuals with 
prediabetes. Although controversy exists regarding optimal diets and interventions for 
weight loss, there is consensus that the following components are generally needed to lose 
weight:3 1) reduction in energy intake, 2) participation in physical activity and 
3) incorporation of self-monitoring (e.g., food tracking). We hypothesize that 
RT-CGM will help the user achieve all of these components and lose weight. 
Unlike other health trackers which relies on user input, RT-CGM provides 
continuous monitoring and instantaneous feedback on glucose levels which 
reflect user food choices and physical activity. A small sensor is inserted 
below the skin and into the interstitial fluid. The sensor measures glucose 
from 40 to 400mg/dL every 5 minutes and transmits the data wirelessly to a 
display such as a smart phone (Fig. 1). Eating generally increases and 
exercise decreases glucose concentrations. As individuals with prediabetes 
have some degree of insulin secretory dysfunction and hyperglycemia, 
certain food choices (high in carbohydrate content, added sugars, and 
calories) may increase glucose more than other healthful choices. Thus, RT-
CGM can monitor when eating is occurring and also can provide feedback on 
the effect of food choices to adversely increase glucose. Furthermore, it can 
also reflect the beneficial effects of exercise to lower glucose. Thus, coupled 
with education, we hypothesize that RT-CGM can be used as a self-
monitoring device to motivate healthful food choices and physical activity that 
maintain lower glucose and aid weight loss.  
RT-CGM is an existing technology that is being underutilized. There has 
been little direct examination of RT-CGM as a behavior modification and 
weight loss tool in individuals with prediabetes. CGMs currently are indicated 
for patients treated with intensive insulin therapy such as those with type 1 
diabetes.4 Use of CGM in individuals with type 1 diabetes has been 
consistently shown to improve glucose control.5,6 In limited studies in patients with DM2, 
use of CGM also has been successfully used to motivate behavioral change and weight 
loss.7 The potential benefits of CGM also are suggested by studies of activity monitors in 
the general population.8 Collectively, those individuals most adherent with tracking food, 
activity and weight show the greatest weight loss.9 With this understanding, RT-CGM may 
function as the ultimate self-monitoring device as instantaneous glucose changes will reflect 
effects of food choices and physical activity.
Fig 1. 
Glucose 
readings from 
RT-CGM
displayed on a 
smart phone 
can be used to 
motivate food 
choices and 
physical 

6 
 
 
The goal of this proposal is to assess whether RT-CGM will augment dietitian-guided 
weight loss and influence food choices and physical activity in overweight/obese 
patients with prediabetes. In essence, we will be evaluating whether CGM can function as 
the ideal self-monitoring device. 
 
Study Rationale 
Currently, over a third of adults qualify for the diagnosis of prediabetes,10 and 5-10% of 
those with prediabetes progress to DM2 every year.1,11 Lifestyle changes and weight loss 
significantly delay the progression to DM2.1 However, weight loss remains challenging and 
newer tools are desperately needed to help overweight/obese individuals with prediabetes 
change lifestyle and lose weight. 
 
RT-CGM has revolutionized the treatment of patients on intensive insulin therapy and its 
utility can also be harnessed to help individuals with prediabetes make healthful lifestyle 
changes. Successful weight loss requires adherence to lower calories, regular exercise, and 
self-monitoring.3 This proposal will test the hypothesis that RT-CGM will facilitate all of 
these components for successful weight loss by functioning as a continuous self-
monitor and guiding healthful food choices and physical activity. 
 
Overweight/obese patients with prediabetes will be randomized to intermittent RT-CGM with 
dietitian support (n=25) versus dietitian support only (n=25). The CGM group will wear the 
RT-CGM for 10 days at baseline, months 1 and 2. The baseline RT-CGM will be the 
“learning phase” to teach effects of usual food intake and activity on glucose levels. The 
subsequent CGM trials will be used to enforce healthful eating and at least 150-min of 
moderate intensity exercise to maintain normal peak glucose less than 140 mg/dL 
(“enforcement phase”).  
 
2. STUDY AIMS 
 
If any of the primary or secondary outcome measures are changed, study staff must update 
clinicaltrials.gov.  
 
The primary objective will be to determine whether intermittent use of a RT-CGM will 
facilitate weight loss in individuals who are overweight/obese with prediabetes.  
 
2.1. Primary Outcome Measure 
AIM #1:  Compare weight loss.  
Intermittent RT-CGM use will augment dietitian-guided weight loss in individuals with 
prediabetes. 
 
2.2. Secondary Outcome Measure 
AIM #2:  Compare physical activity.  
Intermittent RT-CGM use will increase physical activity compared with dietitian support 
only. 
 
Other measures will include glucose indices (fasting glucose, A1c).  

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3. STUDY DESIGN 
 
3.1 Sample Size 
We aim to have 50 total participants in this study.  
 
3.2 Study Population 
We aim to enroll 50 participants who are overweight/obese with prediabetes. Please 
see APPENDIX A for more detailed inclusion/exclusion criteria. 
 
3.3 Study Location 
Participants will be recruited from the San Francisco Bay Area. The research study 
office is located near the Stanford Hospital and Clinics at 300 Pasteur Drive, Stanford, 
CA 94305.  
 
Blood draws will occur in the Boswell Clinic Laboratory at 300 Pasteur Drive, Level 1, 
A12, Stanford, CA  94305.  
 
3.4 Study Duration 
We anticipate that the entire study will take 24 months through data analysis. 
 
Months 1-3 
-Prepare IRB and study protocols 
 
Months 4-14 
-Recruit 5 individuals per month 
 
Months 14-18 
-Last group of participants completes protocol 
 
Months 18-24 
-Data cleaning 
-Data analysis 
 
3.5 Randomization 
Eligible participants will be consented for the study and have baseline measurements 
before being randomized to either the RT-CGM versus dietitian only group. Participants 
will be randomized according to a computerized random number generator.  
 
 
 

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4. STUDY PROCEDURES 
 
4.1 Study Design 
This will be a randomized, parallel-group, pilot study of intermittent RT-CGM with dietitian 
support versus dietitian support only. We will randomize 50 individuals who are 
overweight/obese (BMI 25-40 kg/m2) with prediabetes. A registered dietitian will meet with 
all volunteers monthly for 3 months and advise on a hypocaloric diet (500 kcal/day deficit) 
and physical activity (150 minutes per week). (See Fig 2).  
4.2 Recruitment 
Preliminary recruitment strategies will include: 
- 
Recruitment through the Endocrinology Clinic. 
- 
Targeted mass mailings from existing study participants lists (individuals who 
expressed interest in participating in future studies) and other email lists, 
currently over 10,000 emails. 
 
Pace of recruitment will be monitored throughout the study. Since the recruitment 
timeline can be difficult to predict, if the pace is significantly slower than anticipated, the 
Primary Investigators may decide to alter the budget, timeline, and/or elements of study 
design (e.g., alter enrollment target, increase budget, reduce elements of data 
generation) accordingly.  
4.3 Intervention 
Participants will be randomized 1:1 to either the CGM group with dietitian support or 
Dietitian-only group (See Fig 2). At baseline, patients in the CGM group will wear a 
Dexcom RT-CGM for 10 days and be advised to keep a food and activity log for 7 days 
(This will be the “learning phase”). They will then meet with a registered dietitian to 
review CGM and food/activity log and be advised on a 500 kcal deficit diet and 150 
min/week physical-activity goal. They will also be advised to target postprandial glucose 
less than 140 mg/dL. They again will wear CGM for 10 days followed by dietitian 
consultation at months 1 and 2 (“enforcement phase”). 
Volunteers randomized to Dietitian-only group will meet with a dietitian at baseline, months 
1 and 2. They will also be advised to keep a food and activity log for 7 days prior to meeting 
with the dietitian. They also will be advised on a 500 kcal deficit diet and 150 min/week 
physical-activity goal. 

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5. STATISTICAL CONSIDERATION 
  
5.1 Statistical Basis for Sample Size 
The primary endpoint will be amount of weight lost in RT-CGM vs Dietitian-only group. 
Based on a previous weight-loss study of overweight/obese individuals with prediabetes,16 
with 50 participants, we anticipate detecting a within group difference in weight of 1.8 kg 
and between group difference of 8kg with 80% power and type 1 error of 0.05. Drop out of 
20% will results in effect sizes of 2 and 9kg, respectively.  
5.2 Statistical Plan 
In progress.  
 
 
 

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REFERENCES 
1.  
Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the Incidence of Type 2 
Diabetes With Lifestyle Intervention or Metformin. English J [Internet] 2002;346(6):393–
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bmed/11832527%5Cnhttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC13
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real-world settings that were modeled on the diabetes prevention program? Health Aff 
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Ramage S, Farmer A, Apps Eccles K, McCargar L. Healthy strategies for successful 
weight loss and weight maintenance: a systematic review. Appl Physiol Nutr Metab 
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American Diabetes Association AD. 6. Glycemic Targets: Standards of Medical Care in 
Diabetes-2018. Diabetes Care [Internet] 2018;41(Suppl 1):S55–64. Available from: 
http://www.ncbi.nlm.nih.gov/pubmed/29222377 
5.  
Tamborlane W V, Beck RW, Bode BW, et al. Continuous glucose monitoring and 
intensive treatment of type 1 diabetes. N Engl J Med 2008;359(14):1464–76.  
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Beck RW, Riddlesworth T, Ruedy K, et al. Effect of Continuous Glucose Monitoring on 
Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections. Jama [Internet] 
2017;317(4):371. Available from: 
http://jama.jamanetwork.com/article.aspx?doi=10.1001/jama.2016.19975 
7.  
Ehrhardt N, Al Zaghal E. Behavior Modification in Prediabetes and Diabetes: Potential 
Use of Real-Time Continuous Glucose Monitoring. J Diabetes Sci Technol [Internet] 
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http://journals.sagepub.com/doi/10.1177/1932296818790994 
8.  
Lewis ZH, Lyons EJ, Jarvis JM, Baillargeon J. Using an electronic activity monitor system 
as an intervention modality: A systematic review Health behavior, health promotion and 
society. BMC Public Health [Internet] 2015;15(1). Available from: 
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Pourzanjani A, Quisel T, Foschini L. Adherent use of digital health trackers is associated 
with weight loss. PLoS One 2016;11(4):1–14.  
10.  
Menke A, Casagrande S, Cowie CC. Contributions of A1c, fasting plasma glucose, and 2-
hour plasma glucose to prediabetes prevalence: NHANES 2011–2014. Ann Epidemiol 
[Internet] 2018;1–7. Available from: https://doi.org/10.1016/j.annepidem.2018.07.012 
11.  
Tabák AG, Herder C, Kivimäki M. Prediabetes : A high-risk state for developing diabetes 

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Progression from prediabetes to diabetes Reversion to normoglycaemia Risk prediction. 
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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3891203/ 
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Schauer PR, Burguera B, Ikramuddin S, et al. Effect of Laparoscopic Roux-En Y Gastric 
Bypass on Type 2 Diabetes Mellitus. Trans . Meet Am Surg Assoc [Internet] 
2003;121(4):160–78. Available from: 
http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00153307-
200301210-00017 
13.  
Care D, Suppl SS. Classification and diagnosis of diabetes: Standards of medical care in 
Diabetesd2018. Diabetes Care 2018;41(January):S13–27.  
14.  
Pittas AG, Dawson-Hughes B, Sheehan PR, et al. Rationale and design of the vitamin D 
and type 2 diabetes (D2d) study: A diabetes prevention trial. Diabetes Care 
2014;37(12):3227–34.  
15.  
Gardner CD, Trepanowski JF, Gobbo LCD, et al. Effect of low-fat VS low-carbohydrate 
diet on 12-month weight loss in overweight adults and the association with genotype 
pattern or insulin secretion the DIETFITS randomized clinical trial. JAMA - J Am Med 
Assoc 2018;319(7):667–79.  
16.  
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Overweight and Obese Older Individuals With Prediabetes. Diabetes Care 
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APPENDIX 
A. Inclusion/exclusion criteria 
 
Inclusion Criteria 
 
Comments 
Age ≥ 18 years 
Overweight/obese BMI 25-40 kg/m2, or ≥23 if Asian 
Prediabetes fasting glucose of 100-125 mg/dL and/or 
A1c 5.7-6.4% 
 
Exclusion Criteria 
 
Age <18 years 
BMI >40 kg/m2 
Medications Taking medications known to affect 
glucose (e.g., anti-hyperglycemic) or 
weight (e.g., weight-loss medicaitons) 
Physical limitation Cannot ambulate 
Planning pregnancy Women pregnant currently or planning to 
become pregnant during the course of the 
study and/or breastfeeding 
 
 
 
Anti-hyperglycemic medications  
 
Metformin 
 
Other 
Weight-loss medications  
 
phentermine 
 
Saxenda (liraglutide) 
 
Contrave (naltrexone/bupropion) 
 
Belviq (lorcaserin) 
 
Qsymia (phentermine/topiramate) 
 
Xenical (orlistat) 
 
B. Questionnaire 
The following questionnaire will be conducted at baseline and at the end-of-study: 
- IPAQ (International Physical Activity Questionnaire) – to assess physical activity in last 7 days 
at 6 time points.  
CL, C., & AL, M. (2003). International physical activity questionnaire: 12-country reliability and 
validity. Medicine & Science in Sports & Exercise, 35(8), 1381-1395. 
 

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C. Outcome Measurement Methods 
Anthropometrics.  
Glucose indices (fasting glucose, HbA1c). 
RT-CGM. Dexcom G6 CGM 
Questionnaire data related to physical activity.