Technological Advances in Glucose Management in Older Adults (TANGO)

This is a study to assess the effectiveness of CGM (Continuous Glucose Monitor), enhanced by a diabetes management platform (DMP), collectively called enhanced CGM (eCGM), in the care of older patients with T1D. The DMP includes an automated data transfer from CGM, insulin-delivery devices, and activity tracker to a clinical decision support system (CDS) that provides dosing adjustment recommendations based on that data to the healthcare team. In addition, the DMP includes on-demand education for patients and caregivers, and an interface for communication between providers, patients, and their caregivers.

Study Overview

• Status: Completed
• Conditions: Hypoglycemia; Type 1 Diabetes Mellitus; Older Adults
• Intervention / Treatment: Other: eCGM (enhanced CGM)

Detailed Description

Hypoglycemia is a major and often devastating complication of T1D in the elderly. CGM has been shown to reduce the risk for hypoglycemia in adults with T1D including some more functional patients over 65 years old. However, the Medicare population is heterogeneous and may have age-related clinical and functional impairments that can impact self-care. These patients will require additional targeted guidance and support to fully realize the potential benefits of CGM. To address these age-specific barriers which could limit the effective use of CGM, in our planned RCT (Specific Aim 1) the use of CGM will be coupled with the DMP (Diabetes Management Platform), a tablet-based technology platform ( termed enhanced CGM (eCGM)). The CGM, insulin delivery, and activity data uploaded from the DMP will be analyzed by the clinical decision support system (CDS), which will provide insulin dosing recommendations to the study physicians, who will then accept or reject changes in therapy. The use of the DMP is expected to help the less technologically proficient Medicare patients to derive benefit from CGM. Specific Aim 2 will involve extensive mixed methods research (including semi-structured interviews of patients and caregivers) directed at making an in-depth assessment of barriers to the use of diabetes technology in older adults. This investigation will provide the evidence-base for future improvements in both the technology and clinical approach to the training of older adults and their caregivers. Specific Aim 3 will involve a cost-effectiveness analysis of the technology system (CGM with DMP = enhanced CGM [eCGM]) used in the trial as well as quality of life measures, providing a foundation for decision-making on coverage.

• Study Type: Interventional
• Enrollment (Actual): 168
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Massachusetts
    • Boston, Massachusetts, United States, 02215
      • Joslin Diabetes Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 65 years and older (Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Patients with age ≥ 65 years
• Community-living
• Clinical diagnosis of T1D
• On multiple insulin injections (≥3 injection/s day) or insulin pump.

Exclusion Criteria:

• Use of real-time CGM in past 2 years
• A1c > 10% (since individuals with very poor glycemic control usually have barriers to optimal self-care that preclude effective use of technology)
• Use of insulin pump that cannot be uploaded for CDS
• Unable or unwilling to perform task needed for study participation during the run-in period
• Severe vision or hearing impairment that could interfere with study tasks
• Need to use acetaminophen on regular basis (since can interfere with CGM accuracy)
• Living in an institutional setting (e.g. group homes, nursing homes)
• Terminal diseases with life expectancy < 1 year (e.g. malignancy)
• Severe comorbidities that prevent completing outcome measurements (e.g. severe dementia, severe vision impairment, severe functional disabilities, inability to perform basic activities of daily living)
• Alcohol or other drug abuse
• Conditions that impact wear of CGM (e.g. CHF with edema, skin conditions); and
• End stage renal insufficiency (eGFR<30), or on dialysis (since impact of fluid shift on sensor lag not clearly understood).

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Intervention; The intervention group will use eCGM (CGM with Diabetes Management Platform(DMP)) and an activity meter. The DMP will be pre-loaded with geriatric-specific education material, weblink to online education and surveys. The CGM, insulin delivery, and activity data uploaded from the DMP will be analyzed by the clinical decision support system (CDS), which will provide insulin dosing recommendations to the study physicians, who will then accept or reject changes in therapy. The DMP can also be configured to route the insulin regimen change approved by the study physician to the designated care providers of the patient. Blue-tooth unabled insulin pens will also provide additional data to verify if the patient is taking recommended insulin doses.	Other: eCGM (enhanced CGM); Glucose (CGM and Bluetooth BG meter), insulin (pump or Bluetooth insulin pen) and activity data will be automatically uploaded via the subjects' tablet computers, and analyzed by the CDS. The CDS will, if indicated generate adjustable insulin dosing recommendations that will compensate for different insulin requirements following high vs low activity days. The recommendations of the CDS will be used by the clinical team in their therapeutic decision-making about insulin dosing adjustments at the scheduled study follow up visits and the remote visits between these in-person visits. In addition, study staff will provide recommendations regarding hypoglycemic warning symptoms, causes, and appropriateness of treatment.
No Intervention: Attention Control; The attention control group will receive an android tablet pre-loaded with activity monitor devices, education material, and weblink to online education and surveys. However, the data will not be analyzed by CDS. An independent physician and a study staff member- only caring for the control group subjects will review the insulin and glucose data at in-person and remote study visits and make appropriate dosing adjustments based on self monitoring glucose levels

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in duration of hypoglycemia	Minutes per day CGM < 70 mg/dL assessed over 2 weeks CGM use (blinded in the control arm; unblinded in the treatment arm)	change of duration of hypoglycemia(minutes/day) from baseline to 6 months between intervention and control groups

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Fasting and bedtime CGM glucose values per day	Difference from fasting and bedtime CGM glucose values per day	change in glucose values(mg/dl) from baseline to 6 months between intervention and control groups
Severe biochemical hypoglycemia	Incidence of severe biochemical hypoglycemia (defined as CGM below 54mg/dL for > than 20 minutes) assessed over 2 weeks CGM use (blinded in the control arm; unblinded in the treatment arm)	change in severe biochemical hypoglycemia (episodes per day) from baseline to 6 months between intervention and control groups
Severe clinical hypoglycemia	Incidence of clinically severe hypoglycemia (requiring third party assistance or loss of consciousness) measured by clinical history,	change in severe clinical hypoglycemia (episodes per day) from baseline to 6 months between intervention and control groups
Hemoglobin A1C	A1C measured by laboratory test	Change in A1C (%) from baseline to 6 months between intervention and control groups
Cost-effectiveness and cost-utility	cost-effectiveness and cost-utility of using eCGM versus usual care with self-monitoring glucose monitoring by calculating the incremental cost-effectiveness ratios	6 months
Barriers and facilitators of CGM use	Mixed-method approach using semi-structured interviews to assess barriers and facilitators in those participants who fail the pretrial run-in and those who derive benefits from eCGM	6 months

Collaborators and Investigators

• Sponsor: Joslin Diabetes Center
• Collaborators: Beth Israel Deaconess Medical Center; Boston Children's Hospital; RTI International
• Investigators: Principal Investigator: Medha N Munshi, MD, Joslin Diabetes Center

Publications and helpful links

General Publications

• Munshi M, Slyne C, Adam A, Davis D, Michals A, Atakov-Castillo A, Weinger K, Toschi E. Impact of Diabetes Duration on Functional and Clinical Status in Older Adults With Type 1 Diabetes. Diabetes Care. 2022 Mar 1;45(3):754-757. doi: 10.2337/dc21-2000.
• Munshi M, Slyne C, Davis D, Michals A, Sifre K, Dewar R, Atakov-Castillo A, Toschi E. Use of Technology in Older Adults with Type 1 Diabetes: Clinical Characteristics and Glycemic Metrics. Diabetes Technol Ther. 2022 Jan;24(1):1-9. doi: 10.1089/dia.2021.0246.
• Toschi E, Munshi MN. Benefits and Challenges of Diabetes Technology Use in Older Adults. Endocrinol Metab Clin North Am. 2020 Mar;49(1):57-67. doi: 10.1016/j.ecl.2019.10.001. Epub 2019 Nov 18.
• Toschi E, Slyne C, Sifre K, O'Donnell R, Greenberg J, Atakov-Castillo A, Carl S, Munshi M. The Relationship Between CGM-Derived Metrics, A1C, and Risk of Hypoglycemia in Older Adults With Type 1 Diabetes. Diabetes Care. 2020 Oct;43(10):2349-2354. doi: 10.2337/dc20-0016. Epub 2020 May 27.

Study record dates

Study Major Dates

• Study Start (Actual): March 30, 2017
• Primary Completion (Actual): September 1, 2022
• Study Completion (Actual): October 1, 2022

Study Registration Dates

• First Submitted: February 21, 2017
• First Submitted That Met QC Criteria: March 7, 2017
• First Posted (Actual): March 13, 2017

Study Record Updates

• Last Update Posted (Actual): May 12, 2026
• Last Update Submitted That Met QC Criteria: May 7, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: older adults; hypoglycemia; CGM; geriatrics; type 1 diabetes; technology; clinical decision support
• Additional Relevant MeSH Terms: Endocrine System Diseases; Metabolic Diseases; Autoimmune Diseases; Immune System Diseases; Glucose Metabolism Disorders; Diabetes Mellitus; Nutritional and Metabolic Diseases; Hypoglycemia; Diabetes Mellitus, Type 1
• Other Study ID Numbers: CHS #2016-29

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No