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This is a single center, parallel-arm randomized controlled pilot study that aims to examine the feasibility and acceptability of the glucose-guided eating (GGE) mobile app and intervention in two populations at risk of chronic disease (postmenopausal women with prediabetes and AYA cancer survivors).
The primary objectives of the study are to (1) test the feasibility and acceptability of the GGE intervention and companion GGE mobile app and (2) quantify the preliminary effect of GGE on 12-week changes in insulin resistance (IR) and body weight.
The secondary objectives of the study are to (1) collect preliminary data on hypothesized mechanisms linking GGE to IR and (2) explore the durability of intervention effects on 24-week changes in body weight.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| GGE with CGM | Experimental | Participants randomized to the Glucose-Guided Intervention will be trained to align their mealtimes with a personalized glucose threshold monitored using continuous glucose monitoring (CGM) and the GGE study app. |
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| CGM only | Active Comparator | Participants randomized to the control arm will only wear a CGM. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Glucose-Guided Eating with CGM | Behavioral | The GGE intervention consist of up to four weeks of training to learn to eat when glucose levels are at or below their usual fasting level. Specifically, participants following GGE will self-monitor their glucose levels with an unblinded CGM while using a mobile app (GGE app) that will provide feedback on whether or not to eat. At desired mealtimes participants will enter their current glucose level, rate their perceived hunger, and label the type of hunger they are experiencing (physical, emotional, sensory and practical). Participants following GGE will be instructed by the app to eat when two conditions are met: (a) the desire to eat arises and (b) their glucose levels are at or below a personalized threshold. During the training period, participants are meant to associate feelings of perceived hunger with fasting glucose levels (i.e., physical hunger). After the training period, participants continue to follow GGE without CGM or use of the app. |
| Measure | Description | Time Frame |
|---|---|---|
| Population-specific accrual | Population-specific accrual will reflect rates of study enrollment and will be defined as number of participants consented to the number of individuals who are determined to be eligible. | Week 0 |
| Population-specific retention rates | Population-specific retention rates will reflect the proportion of enrolled participants who complete the study. | Week 12 |
| GGE app usability | The app usability will be assessed using the 10-item System Usability Scale. SUS scores have a range of 0 to 100 with 100 representing greatest usability. | Week 12 |
| GGE intervention acceptability | GGE intervention acceptability will be assessed with a study specific survey (collected from participants randomized to the GGE intervention only). | Week 12 |
| GGE adherence | GGE adherence will be quantified as percent of reported eating events occurring at or below personalized glucose thresholds/personalized average fasting glucose levels that is collected using the GGE app (collected from participants randomized to the GGE intervention only-during use of the GGE app only). | Weeks 1-4 |
| Measure | Description | Time Frame |
|---|---|---|
| Changes in body weight | Changes in body weight will be measured using calibrated digital scales (measured in kilograms). | Weeks 0-12 and Weeks 12-24 |
| Changes in insulin resistance (HOMA-IR) | Changes in insulin resistance will be measured as homeostatic model assessment for insulin resistance (HOMA-IR). It will be computed from fasting insulin and fasting glucose (fasting insulin (microU/L) x fasting glucose (nmol/L)/22.5). |
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Inclusion Criteria:
All:
Self-reported height and weight that is consistent with a BMI ≥ 27 kg/m2
Willing to use a continuous glucose monitor
Own smartphone that is compatible with Dexcom CGM.
Willingness to commute to GUMC for in-person study visits
No active cancer (except for nonmelanoma skin cancer)
Less than 5 lbs. weight change in previous 3 months
Proficient in speaking and reading English
Postmenopausal women with pre-diabetes:
Age 18 years and older
Diagnosed as having prediabetes.
HbA1c (within 3 months) between 5.7% and 6.4%
Postmenopausal (defined as reporting no menstrual period for ≥1 year or a reported history of a total abdominal hysterectomy with oophorectomy)
AYA cancer survivors:
Current age 21-39 years
Previously diagnosed with cancer, with all cancer-related diagnosis chemotherapy and/or radiation completed at least 6 months previously
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Princess M Georges | Contact | 2026872117 | pg763@georgetown.edu | |
| Megan Roy | Contact | mr1839@georgetown.edu |
| Name | Affiliation | Role |
|---|---|---|
| Susan M Schembre | Georgetown's Lombardi Comprehensive Cancer Center | Principal Investigator |
| Nina Kadan-Lottick | Georgetown's Lombardi Comprehensive Cancer Center | Principal Investigator |
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| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34960058 | Background | Schembre SM, Jospe MR, Giles ED, Sears DD, Liao Y, Basen-Engquist KM, Thomson CA. A Low-Glucose Eating Pattern Improves Biomarkers of Postmenopausal Breast Cancer Risk: An Exploratory Secondary Analysis of a Randomized Feasibility Trial. Nutrients. 2021 Dec 16;13(12):4508. doi: 10.3390/nu13124508. | |
| 34893531 | Background |
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The investigators intend to publish the protocol in a manuscript and share the IPD through an appropriate free access data repository.
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Within 1 year of study completion.
Shared IPD will be available via freely accessible data registry.
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| ID | Term |
|---|---|
| D011236 | Prediabetic State |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| ID | Term |
|---|---|
| D000095583 | Continuous Glucose Monitoring |
| ID | Term |
|---|---|
| D001774 | Blood Chemical Analysis |
| D019963 | Clinical Chemistry Tests |
| D019411 | Clinical Laboratory Techniques |
| D019937 | Diagnostic Techniques and Procedures |
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| CGM only | Other | Comparator participants will use unblinded CGM for up to 4 weeks without the use of the GGE app or any other dietary recommendations. |
|
| Weeks 1-12 |
| Changes in glycemic variability | Changes in glycemic variability will be assessed from CGM data using the freely accessible EasyGV software available from the University of Oxford (https://www.phc.ox.ac.uk/research/resources/easygv). | Weeks 1-12 |
| Changes in oxidative stress | Changes in oxidative stress will be measured as 8-isoprostane from spot urine. | Weeks 1-12 |
| Changes in the soluble receptor for advanced glycation end-products (sRAGE) | Changes the sRAGE was measured in serum by ELISA. | Weeks 1-12 |
| Schembre SM, Jospe MR, Bedrick EJ, Li L, Brewster AM, Levy E, Dirba DD, Campbell M, Taylor RW, Basen-Engquist KM. Hunger Training as a Self-regulation Strategy in a Comprehensive Weight Loss Program for Breast Cancer Prevention: A Randomized Feasibility Study. Cancer Prev Res (Phila). 2022 Mar 1;15(3):193-201. doi: 10.1158/1940-6207.CAPR-21-0298. |
| D004700 | Endocrine System Diseases |
| D003933 | Diagnosis |
| D003940 | Diagnostic Techniques, Endocrine |
| D008991 | Monitoring, Physiologic |
| D008919 | Investigative Techniques |