Trial Outcomes & Findings for Precision Diets for Diabetes Prevention (NCT NCT03919877)

NCT ID: NCT03919877

Last Updated: 2026-05-22

Results Overview

Change in glycemic control measured from baseline through all phases of study, stratified according food type and metabolic sub-type. Glycemic control is derived from continuous glucose monitor (CGM) data and expressed in milligrams/deciliter.

Recruitment status

COMPLETED

Study phase

Target enrollment

115 participants

Primary outcome timeframe

Assessed at a meal (2 to 6 weeks after baseline), starting just prior eating, for a period of 3 hours

Results posted on

2026-05-22

Participant Flow

Participant milestones

Participant milestones
Measure	Optimizing Diet for Glycemic Control Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.
Overall Study STARTED	115
Overall Study COMPLETED	97
Overall Study NOT COMPLETED	18

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Precision Diets for Diabetes Prevention

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	Optimizing Diet for Glycemic Control n=115 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.
Age, Categorical <=18 years	0 Participants n=2 Participants
Age, Categorical Between 18 and 65 years	100 Participants n=2 Participants
Age, Categorical >=65 years	15 Participants n=2 Participants
Age, Continuous	54 years STANDARD_DEVIATION 12.7 • n=2 Participants
Sex: Female, Male Female	64 Participants n=2 Participants
Sex: Female, Male Male	51 Participants n=2 Participants
Ethnicity (NIH/OMB) Hispanic or Latino	4 Participants n=2 Participants
Ethnicity (NIH/OMB) Not Hispanic or Latino	100 Participants n=2 Participants
Ethnicity (NIH/OMB) Unknown or Not Reported	11 Participants n=2 Participants
Race (NIH/OMB) American Indian or Alaska Native	1 Participants n=2 Participants
Race (NIH/OMB) Asian	30 Participants n=2 Participants
Race (NIH/OMB) Native Hawaiian or Other Pacific Islander	0 Participants n=2 Participants
Race (NIH/OMB) Black or African American	0 Participants n=2 Participants
Race (NIH/OMB) White	69 Participants n=2 Participants
Race (NIH/OMB) More than one race	4 Participants n=2 Participants
Race (NIH/OMB) Unknown or Not Reported	11 Participants n=2 Participants
Region of Enrollment United States	115 Participants n=2 Participants

PRIMARY outcome

Timeframe: Assessed at a meal (2 to 6 weeks after baseline), starting just prior eating, for a period of 3 hours

Population: Participants with all metabolic testing results, omics, CGM, and meal data

Outcome measures

Outcome measures
Measure	Insulin-sensitive - Potato n=14 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-resistant - Potato n=16 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-sensitive - Pasta n=12 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-resistant - Pasta n=16 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.
Change in Glycemic Control as Measured by Change Blood Sugar Values Baseline	88.9 mg/dL Standard Error 2.98	95.4 mg/dL Standard Error 9.07	90.8 mg/dL Standard Error 2.04	96.7 mg/dL Standard Error 3.13
Change in Glycemic Control as Measured by Change Blood Sugar Values Change at Peak	74.5 mg/dL Standard Error 6.06	41.7 mg/dL Standard Error 5.23	59.5 mg/dL Standard Error 6.43	39.2 mg/dL Standard Error 4.85

PRIMARY outcome

Timeframe: Baseline (Day 1)

Population: Participants who had OGTT performed

Classify metabolic subphenotype in individuals without diabetes using a machine learning algorithm applied to the glucose time-series response generated by a 16-point (blood draws) oral glucose tolerance testing (OGTT) done in the clinical research center and at home (using CGM). Participants were categorized as insulin sensitive (IS) if teady state plasma glucose (SSPG) was \<120 mg dl-1 and insulin resistant (IR) if their SSPG was ≥120 mg dl-1. For this analysis, disposition index (DI) \< 1.58 indicates dysfunctional β-cell function, whereas DI ≥ 1.58 indicates normal β-cell function.

Outcome measures

Outcome measures
Measure	Insulin-sensitive - Potato n=56 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-resistant - Potato Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-sensitive - Pasta Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-resistant - Pasta Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.
Area Under the Receiver Operating Characteristic (ROC) Curve - Classification of Metabolic Subphenotype Beta cell function	0.875 Proportion of accurate classifications Interval 0.842 to 0.908	—	—	—
Area Under the Receiver Operating Characteristic (ROC) Curve - Classification of Metabolic Subphenotype Muscle insulin resistance	0.951 Proportion of accurate classifications Interval 0.934 to 0.968	—	—	—
Area Under the Receiver Operating Characteristic (ROC) Curve - Classification of Metabolic Subphenotype Incretin Effect	0.877 Proportion of accurate classifications Interval 0.851 to 0.903	—	—	—

SECONDARY outcome

Timeframe: Assessed at a meal (2 to 6 weeks after baseline), starting just prior eating, for a period of 3 hours

Population: Participants with all metabolic testing results, omics, CGM, and meal data

Measured from baseline through all phases of study, from continuous glucose monitor (CGM) data, and stratified according food type and metabolic sub-type.

Outcome measures

Outcome measures
Measure	Insulin-sensitive - Potato n=14 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-resistant - Potato n=16 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-sensitive - Pasta n=12 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.	Insulin-resistant - Pasta n=16 Participants Participants underwent metabolic testing, then ate a variety of foods to assess their impact on blood sugars.
Change in Area Under the Curve (AUC) of Blood Glucose Level	5175 mg*min/dL Standard Deviation 532	3000 mg*min/dL Standard Deviation 591	4076 mg*min/dL Standard Deviation 594	2379 mg*min/dL Standard Deviation 333

Adverse Events

Optimizing Diet for Glycemic Control

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Adverse event data not reported

Additional Information

Michael Snyder, Ph.D.

Stanford University

Phone: (650) 723-4668

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place