Lived Experience of Advanced Hybrid Closed-Loop Versus Hybrid Closed-Loop: Patient-Reported Outcomes and Perspectives

Abstract

This article reports on the lived experience of Medtronic advanced hybrid closed-loop (AHCL) in comparison to first generation hybrid closed-loop (HCL) in a randomized, open-label, two-period crossover trial. Patient-reported outcome (PROs) measures were administered before randomization and at the end of each study period in 113 adolescents and young adults with type 1 diabetes. Glucose monitoring satisfaction subscales for emotional burden and behavioral burden improved significantly (P < 0.01) over time with use of AHCL versus HCL and co-occurred with glycemic improvements (reduced percent time above 180 mg/dL during the day and no change in % time less than 54 mg/dL across 24 h) and greater time in Auto Mode. PROs, including distress, technology attitudes, and hypoglycemia confidence, were not different. AHCL use was associated with improved glucose monitoring satisfaction. Satisfaction was greater in those participants who had more appreciable glycemic benefit and stayed in Auto Mode more often.

Clinical Trial Registration number: NCT03040414.

Introduction

Patient-reported outcomes (PROs) offer insight into the lived experience of people with type 1 diabetes using diabetes devices to manage the disease and its daily demands. Typically obtained through questionnaires or interviews, popular PROs measure quality of life¹ and diabetes-specific experiences such as emotional distress² and fear of hypoglycemia.³ In general, the lived experience of using present-day diabetes devices is positive,^4,5 yet, people with type 1 diabetes exhibit varying attitudes and beliefs about using closed-loop systems to automate insulin delivery.⁶ The real-world use of closed-loop is still in its infancy in terms of uptake and availability of multiple approved systems^7,8; understanding the lived experience offers both potential users and prescribers opportunity for more informed decision-making.

In a recent publication,⁹ the Medtronic advanced hybrid closed-loop (AHCL) system was compared to Medtronic commercial 670G hybrid closed-loop (HCL). The AHCL system has several algorithm modifications, including two setpoints (100 and 120 mg/dL) and MD-Logic enhancements.¹⁰ The Medtronic AHCL system demonstrated enhanced efficacy and safety over the commercially available system.⁹ We hypothesized that when compared to 670G HCL, AHCL would be associated with improved PROs.

Materials and Methods

Data were obtained from this randomized, open-label, two-period crossover trial conducted at seven endocrinology practices (four in the United States, one each in Slovenia, Germany, and Israel). Participants were enrolled after completing informed consent/assent based on an IRB-approved protocol (available at https://public.jaeb.org/datasets). Participants remained in the study for ∼28 weeks, including 2–4 weeks of start-up/run-in for device naive participants and two 12-week periods of closed-loop use. Randomization occurred after completion of run-in and resulted in using HCL first, then AHCL, or AHCL then HCL. The primary outcomes were (a) % time >180 mg/dL from 0600 to 2359 h (daytime) and (b) % time <54 mg/dL over 24 h. More detail about the investigational system and study requirements are published elsewhere.⁹ The trial is registered with Clinicaltrials.gov. An independent Data and Safety Monitoring Board provided trial oversight.

Patient population

Participants with duration of type 1 diabetes >1 year, aged 14–29 years, using either an insulin pump or multiple daily injections, and with hemoglobin A1c (HbA1c) between 7% and 11% were included.

Patient-reported outcomes

Previously validated patient-reported outcomes (PROs) were completed at baseline (before randomization), at the end of period 1 (∼12 weeks), and end of period 2 (∼24 weeks). PROs surveys were previously validated in adult samples with type 1 diabetes and tested in adolescents with type 1 diabetes in nonvalidation studies^6,11; all performed appropriately and as expected. PROs surveys were administered in the clinical site's preferred language. If a validated translation did not already exist, the surveys were translated, and back translated, before administration. Languages were English, Hebrew, Slovenian, and German.

Diabetes distress

All participants completed the Diabetes Distress Scale (DDS),² a widely used, 17-item scale of diabetes-related emotional distress. The DDS includes items on more immediate frustrations with daily management as well as worries about long-term complications. The type 1 diabetes specific (T1-DDS) was considered but ultimately DDS was used given more validation data in this age range. Higher scores indicate greater diabetes distress. In this sample, reliability was high on the total scale (Cronbach's alpha = 0.93) and ranged from 0.77 to 0.82 on the subscales.

Hypoglycemia confidence

The Hypoglycemia Confidence Scale¹² measures the degree to which people with diabetes feel able to stay safe from hypoglycemia-related problems. They respond to eight situations (e.g., when driving, when exercising) and higher scores indicate greater confidence. Reliability was high on this scale (Cronbach's alpha = 0.83).

Glucose monitoring satisfaction

The Glucose Monitoring Satisfaction Survey¹³ evaluates satisfaction with glucose monitoring and results. Items focus on ease of use, hassle, and perceived accuracy of monitoring devices. Higher scores on this 15-item scale indicate greater satisfaction. Reliability of the total score was high (Cronbach's alpha = 0.91) and subscales ranged from 0.77 to 0.86.

Technology attitudes

Attitudes about diabetes-specific technology were assessed¹⁴ with this five-item survey. Higher scores indicated more positive attitudes about devices and technology. Reliability of this scale was acceptable (Cronbach's alpha = 0.79).

Glycemic metrics

Continuous glucose monitoring (CGM) with the Medtronic Guardian 3 sensor was used to obtain the primary outcomes calculated over 84 days starting with the time Auto Mode in each system was initiated. A minimum of 72 h of CGM data were prespecified to be required for a participant's data in that period to be included in the analyses.

Analytic plan

Statistical analyses were performed on an intention-to-treat basis, and all participants were included in these analyses of PROs. Repeated measures least squares regression models with an unstructured covariance structure were fit to compare PROs between the two intervention arms adjusting for period, prestudy MiniMed 670G system use, and HbA1c at randomization as fixed effects. Missing data were handled by means of direct likelihood analyses and not imputed for any analyses; there were minimal missing PROs responses. Post hoc correlational analyses were examined to determine if change in glycemic outcomes and Auto Mode use were associated with change in PROs. All P-values are two-tailed. Analyses were performed using SAS 9.4.

Results

There were 113 participants randomized and analyzed. Mean age of participants was 19 ± 4 years, median type 1 diabetes duration of 12 years, and mean HbA1c at screening of 8.1% ± 0.8%. The sample included more females (62%) than males and only 8% identified as racial or ethnic minorities. At enrollment, 20% were using multiple daily injections, 62% were using CGM, and 13% were using 670G in Auto Mode. More extensive demographic and clinical characteristics were reported in primary outcomes article.⁹

Patient-reported outcomes

Repeated measures analyses were run on all PROs and glucose satisfaction changed significantly across time periods (P = 0.003). There were two satisfaction subscales that changed and showed superiority of AHCL: emotional burden and behavioral burden (P < 0.01). None of the other PROs changed significantly (see Table 1).

Table 1.

Patient-Reported Outcomes Scores

	BaselineN = 113	End of period 1		End of period 2		P ^a
	BaselineN = 113	AHCLN = 55	670GN = 57	AHCLN = 56	670GN = 55	P ^a
DDS total score mean ± SD	1.68 ± 0.72	1.65 ± 0.68	1.62 ± 0.71	1.63 ± 0.82	1.55 ± 0.56	0.36
Emotional burden subscale total score mean ± SD	1.80 ± 0.80	1.75 ± 0.73	1.70 ± 0.70	1.67 ± 0.87	1.64 ± 0.62	0.44
Physician related distress subscale total score mean ± SD	1.32 ± 0.53	1.34 ± 0.61	1.33 ± 0.73	1.44 ± 0.93	1.26 ± 0.38	0.29
Regimen related distress subscale total score mean ± SD	1.80 ± 0.79	1.73 ± 0.74	1.69 ± 0.75	1.70 ± 0.79	1.65 ± 0.68	0.48
Interpersonal distress subscale total score mean ± SD	1.79 ± 1.00	1.78 ± 0.92	1.75 ± 0.97	1.68 ± 0.90	1.64 ± 0.78	0.44
Glucose monitoring satisfaction survey mean score mean ± SD	2.76 ± 0.52	2.89 ± 0.54	2.63 ± 0.58	2.70 ± 0.54	2.67 ± 0.69	0.003
Openness subscale mean score mean ± SD	3.57 ± 0.83	3.90 ± 0.72	3.53 ± 0.78	3.57 ± 0.85	3.68 ± 0.93	0.06
Emotional burden subscale mean score mean ± SD	1.99 ± 0.80	1.89 ± 0.83	1.91 ± 0.72	1.80 ± 0.64	2.17 ± 0.95	0.008
Behavioral burden subscale mean score mean ± SD	1.78 ± 0.68	1.85 ± 0.84	2.09 ± 0.75	1.89 ± 0.67	2.17 ± 0.97	<0.001
Trust subscale mean score mean ± SD	4.18 ± 0.79	4.17 ± 0.91	4.23 ± 0.70	4.30 ± 0.66	4.02 ± 1.05	0.29
Hypoglycemia confidence survey mean score mean ± SD	3.46 ± 0.44	3.51 ± 0.39	3.52 ± 0.56	3.57 ± 0.45	3.53 ± 0.39	0.75
Diabetes technology attitudes survey mean ± SD	22.18 ± 2.54	22.40 ± 3.10	22.33 ± 3.00	22.71 ± 2.77	22.11 ± 3.68	0.29

Based on a repeated measures least squares regression model adjusting for period, prestudy 670G system use, and HbA1c at randomization as fixed effects. The model includes three time points: (1) baseline, (2) period 1 outcome, and (3) period 2 outcome. Nominal (uncorrected) P-values were adjusted for multiple comparisons using the Two Stage Benjamini-Hochberg adaptive false discovery rate procedure.

AHCL, advanced hybrid closed loop; DDS, Diabetes Distress Scale; HbA1c, hemoglobin A1c; SD, standard deviation.

Change over time relative to glycemic change

The glycemic outcomes of percent time >180 mg/dL during the day, percent time <54 mg/dL across 24 h, and percent time in Auto Mode were examined alongside changes on the satisfaction measure. Spearman correlations showed significant associations with AHCL on percent time >180 md/dL (rho = −0.23) and percent time <54 mg/dL (rho = −0.24), indicating that satisfaction increased as less time was spent in hyperglycemia and hypoglycemia. As time in Auto Mode increased, so did satisfaction (rho = 0.32).

Discussion

Our data demonstrate that AHCL use led not only to glycemic improvements⁹ but also to improved satisfaction with glucose monitoring and results. Further, those who experienced greater improvements (e.g., larger decrease in percent time >180 mg/dL during the day and less time <54 mg/dL across 24 h) experienced greater satisfaction. Likewise, more time in Auto Mode was associated with greater glucose satisfaction. While all PROs scales used in this study are equally valid and constructed in similar manners, baseline scores on technology attitudes and hypoglycemia confidence were already high, thus there was little room for improvement due to ceiling effects. This may be a result of the high percentage of participants on insulin pumps (80%), and nearly two-thirds were already using CGM. Future analyses are planned to explore subgroup differences (e.g., MDI vs. pump) on glycemic and PROs outcomes. Finally, diabetes distress is typically a sensitive PRO that often changes over time with treatment, whether it is focused on behavioral or emotional aspects of diabetes, or both.^15,16 In this analysis, distress did not change, but subscales of the satisfaction measure that did change were behavioral burden and emotional burden. It may be that these items were more sensitive to the positive glycemic changes experienced by those in the study.

Another common method to obtain PROs is focus groups or semistructured interviews, which were not conducted in this study. Potential benefits of exploring experiences through focus groups are better understanding of the subtleties of survey responses, as well as participant discussion that fuels new ideas not captured on surveys. Future studies of closed-loop systems should use this methodology to complement the questionnaire findings.

Conclusions

The results are encouraging and suggest benefit beyond safety and efficacy, and with more sustained time in Auto Mode, there was higher satisfaction with glucose monitoring and results. While this analysis did not focus on the order of these changes, they do occur in parallel, reinforcing the notion that facilitating improvement in both areas—glycemic and lived experiences—can and should be achievable outcomes for adolescents and young adults with type 1 diabetes.

Data Sharing Statement

Data will be made available on a public website (www.jaeb.org) at a later date.

Study Group Members

Protocol chairs

Protocol Chairs and Co-PI: R.M.B., MD and M.P., MD.

Clinical sites

A listing of the FLAIR sites with participating principal investigator (PI), coinvestigators (CI), subinvestigators (I), primary coordinator (PC), coordinators (C), study nurses (SN), research assistants (RA), project manager (PM), and administrative manager (AM) is included below. The number included in the randomized trial at each site is indicated in parenthesis after the sites' name.

International Diabetes Center (23)

Amy Criego (PI), Richard Bergenstal (PI), Anders Carlson (PI), Thomas Martens (I), Shannon Beasley (I), Mary Johnson (PM), Diane Whipple (PC), Jamie Hyatt (C), Alina Punel (C), Aimee Grieme (C), Lee Ann Thomas (RA), Amy LaFrance (AM), and Caitlin Hasledalen (RA).

Joslin Diabetes Center (19)

Lori Laffel (PI), Elvira Isganaitis (I), Emily Freiner (PC, I), Louise Ambler-Osborn (I), Hannah Desrochers (C), Christine Turcotte (C), Nisha Naik (C), Lindsay Roethke (C), and Margaret Fisher (C).

Schneider Children's Hospital (17)

Revital Nimri (PI), Michal Nevo (I), Rachel Bello (I), Alona Hamou (PC), Orna Hermon (PC), Orit Horesh (SN), Galit Shiovitch Mantzuri (SN), Irit Drotz (SN), Nava Yehiel (SN), and Rachel Naveh (C).

University of Florida (17)

Desmond Schatz (PI), Michael Haller (CI), Anastasia Albanese-O'Neill (CI), Eleni Sheehan (I), Julio Leey (I), Madison Smith (I), Laura Jacobsen (I), Janey Adams (PC), Jennifer Hosford (C), and Loren Whyte (C).

University Medical Centre Ljubljana (16)

Tadej Battelino (PI), Klemen Dovč (I), Nataša Bratina (I), Darja Šmigoc Schweiger (I), Urška Sever (C), Ana Gianini (C), Barbara Murn Berkopec (C), and Brigita Mali (C).

Yale University (11)

Stuart Weinzimer (PI), Kate Weyman (I), Lori Carria (PC), and Melinda Zgorski (C).

Auf der Bult Centre for Children and Adolescents (10)

Thomas Danne (PI), Torben Biester (PI), Thekla von dem Berge (I), Jantje Weiskorn (I), Olga Kordonouri (I), Sarah Biester (PC), Bärbel Aschemeier (C), Kerstin Remus (C), and Nicole Pisarek (C).

Jaeb Center for Health Research Tampa, FL

Judy Sibayan, Roy Beck, Thomas Mouse, Julie Davis, Ryan Bailey, Amanda Hellmann, Nicole Reese, Peter Calhoun, Heidi Strayer, Nathan Cohen, Robert Henderson, Craig Kollman, Jennifer Kennedy, William Woodall, and Israel Mahr

Quality of life investigator

K.K.H., Stanford University.

National Institute of Diabetes, Digestive, and Kidney Diseases

Guillermo Arreaza-Rubin (Project Scientist), Thomas Eggerman (Program Officer), and Neal Green (Project Manager).

Central Laboratory—University of Minnesota Advanced Research and Diagnostic Laboratory

Robert Janicek and Deanna Gabrielson.

Data and safety monitoring board

Steven H. Belle (Chair), Jessica Castle, Jennifer Green, Laurent Legault, Steven M. Willi, Carol Wysham, and Thomas Eggerman (DSMB Executive Secretary for NIDDK)

Role of the Funder/Sponsor

The role of the Sponsor is specified for each of the following: Design and conduct of the study: There was no involvement from the National Institute of Diabetes and Digestive and Kidney Diseases or Medtronic in the design and conduct of the study. Collection, management, analysis, and interpretation of the data: There was no involvement from the National Institute of Diabetes and Digestive and Kidney Diseases or Medtronic in the collection, management, analysis, and interpretation of the data. Preparation, review, or approval of the article; and decision to submit the article for publication: The National Institute of Diabetes and Digestive and Kidney Diseases and Medtronic were not involved in the writing of the original article draft submitted. The National Institute of Diabetes and Digestive and Kidney Diseases and Medtronic were sent the article for review but any revisions made based on their comments were at the discretion of the authors, and permission for submitting content to journal was not required. There was no approval of the National Institute of Diabetes and Digestive and Kidney Diseases and Medtronic required or obtained for article submission.

Footnotes

Disclaimer

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Authors' Contributions

K.K.H. drafted article. R.J.B. and P.C. performed the statistical analysis. L.M.L., T.D., S.A.W., J.S., D.S., N.B., R.B., A.P., R.N., R.W.B., R.M.B., and M.P., reviewed and edited article.

Acknowledgments

Medtronic MiniMed, Inc., provided the MiniMed 670G and AHCL systems, and infusion sets, used in the study. Medtronic, Inc., provided study CGM devices and sensors.

Author Disclosure Statement

K.K.H. reports grants from Dexcom, personal fees from LifeScan Diabetes Institute and Cercacor, Inc., outside the submitted work. M.P. reports grants from the National Institutes of Health via Health Partners, during the conduct of the study; grants from Insulet, Dexcom, Medtronic, Roche, Eli Lilly, Lexicon, OPKO, and AstraZeneca, grants and personal fees from Novo Nordisk and Sanofi, grants, personal fees, and owning stock from DreaMed Diabetes, personal fees from RSP Systems and Qulab Medical, grants and personal fees from Pfizer, grants and owning stock from Nutriteen Professional and NG Solutions, outside the submitted work. L.M.L. reports grants from the National Institutes of Health during the conduct of the study; personal fees from Sanofi, NovoNordisk, Eli Lilly, Roche, Lifescan, Convatec, Insulogic, Laxmi, Boehringer Ingelheim, Johnson & Johnson, Dexcom, and Insulet, outside the submitted work. D.S. reports grants from the National Institutes of Health, during the conduct of the study; grants from the Leona M. and Harry B. Helmsley Charitable Trust, outside the submitted work. T.D. reports owning stock in DreaMed Ltd. during the conduct of the study; grants and personal fees from AstraZeneca, Dexcom, Boehringer, NovoNordisk, Medtronic, Sanofi, Eli Lilly, and Insulet, outside the submitted work. S.A.W. reports grants from the National Institutes of Health, during the conduct of the study; personal fees from Medtronic, Insulet, Tandem, Eli Lilly, Sanofi, and Zealand, outside the submitted work. R.N. reports grants from National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, nonfinancial support from Medtronic MiniMed, Inc., during the conduct of the study; grants, personal fees, and other from DreaMed Diabetes Ltd., grants and nonfinancial support from Medtronic MiniMed, Inc., nonfinancial support from Dexcom, nonfinancial support from Insulet, grants, and personal fees from Eli Lilly, grants and personal fees from Novonordisk, outside the submitted work. J.S. reports no conflicts of interest. R.J.B. reports no conflicts of interest. P.C. reports personal fees from Dexcom outside the submitted work. R.B. reports grants from the National Institutes of Health, nonfinancial support from Medtronic Minimed, Inc., during the conduct of the study. R. Beck reports grants from National Institutes of Health, nonfinancial support from Medtronic during the conduct of the study; grants, nonfinancial support, and study supplies from Dexcom, consulting fees paid to nonprofit employer from Bigfoot Biomedical, outside the submitted work. R.M.B. reports grants and other from Abbott Diabetes Care, grants and other from Eli Lilly, outside the submitted work. In addition, Dr. M.P. has a patent WO2010097796 issued to DreaMed Diabetes, a patent WO2011039741 issued to DreaMed Diabetes, and a patent WO2019077482 pending.

Funding Information

Research reported in this publication was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number (IUC4DK10861) grant provided to Jaeb Center for Health Research and paid to each of the investigator's institutions.

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