Individuals with type 1 diabetes of minoritized race-ethnicities and low-socioeconomic status (SES) do not access nor use automated insulin delivery (AID) technology at equal rates compared to their non-Hispanic White (NHW) and high SES counterparts. Using four AID trials (n=292), we ran linear mixed models to compare glycemic outcomes using race/ethnicity, education, and income. These trials overrepresented NHW (83%), high-income (91%), and highly educated (86%) populations. By education, participants with 180 mg/dL: 46.2% vs. 34.5% (p<0.001). These differences disappeared following AID use. By race/ethnicity and income groups, there were no differences in baseline glycemic control. While baseline glycemic control tended to be worse for underrepresented populations, AID glycemic efficacy was approximately equivalent. These results suggest improving accessibility to AID could equalize glycemic outcome disparities

Bisio, Alessandro

García-Tirado, José

Gonder-Frederick, Linda

Hall, Megan

Villard, Orianne

English

Bern Open Repository and Information System (BORIS)

source: https://doi.org/10.48350/184064 | downloaded: 7.8.2023 Page 1 of 8 Diabetes Technology and Therapeutics © Mary Ann Liebert, Inc. DOI: 10.1089/dia.2023.0197 1 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery1 José García-Tirado§†*, PhD, Orianne Villard§‡*, PhD, Megan Hall§†, BA,  Alessandro Bisio††, MD, Linda Gonder-Frederick, PhD §⁋. § Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.  † Department of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland. ‡ Department of Endocrinology, Diabetes, and Nutrition, Montpellier University Hospital, Montpellier, France.   † Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.   †† Novo Nordisk   ⁋ Department of Psychiatry, University of Virginia, Charlottesville, VA, USA.   * J.G-T. and O.V. contributed equally to the realization of this work.  Corresponding author: Linda Gonder-Frederick, Ph.D. Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA, lag3g@uvahealth.org.                                                               1 Initial reports of this analysis were presented by Megan Hall at the conference for Advanced Technologies & Treatments for Diabetes that took place in Barcelona, Spain, from April 27-30, 2022. Downloaded by University of Bern from www.liebertpub.com at 06/26/23. For personal use only. Page 2 of 8    2 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. Dear Editor, Individuals with type 1 diabetes (T1D) of minoritized racial/ethnic groups and low socioeconomic status (SES) access and use advanced diabetes technology at lower rates compared to non-Hispanic White (NHW) and high SES populations, 1 which has been associated with worse glycemic outcomes.2 In addition to lower technology use, individuals of minoritized racial/ethnic groups, especially non-Hispanic Black and Hispanic groups, are vastly underrepresented in diabetes technology clinical trials. Our research center, which has conducted multiple major clinical trials of automated insulin delivery (AID) technology3,4 recently performed a self-assessment study to determine the extent of underrepresentation of diverse populations in our studies and to compare differences in glycemic outcomes across race/ethnicity, education, and income. The study included adult (> 21 years) data from four major AID trials (n=292) which collected household income (without information on household size) and education using $25k brackets and categories, respectively. Within this limitation, and given the skewed distribution of participants’ income and education levels, we defined annual household income as “higher” if  ≥$50,000 (average household income in Charlottesville, VA) and education as “higher” if greater than/equal to a bachelor’s degree – these groups representing approximately 62% and 33% of the U.S. population, respectively.5 Representation and glycemic outcomes of minoritized racial-ethnic groups were compared to those of NHW participants. Glycemic outcomes included HbA1c, time-in-range (TIR - 70 to 180 mg/dL), time-below-range (TBR - <70 mg/dL), and time-above-range (TAR - >180 mg/dL). Linear mixed regression models compared glycemic outcomes for variables distributed normally while adjusting for age, study, previous CGM and pump use and corresponding baseline outcomes. We reported mean±SD and median with interquartile ranges for normal distributions and skewed distributions, respectively. Paralleling current literature, our trials overrepresented the NHW (83%), higher-income (91%), and higher-educated (86%) populations (Table 1). The percentages of minoritized racial/ethnic identities included in the study participants were 6% Hispanic, 3% Asian, 2% Black, and 6% multi-racial. Comparing baseline and final glycemic outcomes for NHW versus all minoritized racial/ethnic groups, there were no significant differences (Table 1A). For education, there were differences in baseline HbA1c in those with low compared to Downloaded by University of Bern from www.liebertpub.com at 06/26/23. For personal use only. Page 3 of 8    3 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. those with high (p<0.001) education levels, as well as for TIR (p<0.001) and TAR (p<0.001). Post-AID, these differences disappeared for HbA1c (p=0.113), marginally improved for TIR (p=0.054) but did not improve significantly for TBR and TAR (Table 1B). For income,  baseline TBR was higher for participants with low versus high incomes (p=0.028). However, this difference resolved after AID use (Table 1C). Failure to find differences between race/ethnicity groups in baseline and post-AID glycemic metrics may have been due to the small sample size and higher income/education levels of our minoritized racial/ethnic participants. Possibly due to this small and skewed sample of racial/ethnic minority groups, baseline and post-trial glycemic status were more highly associated with income and education than race/ethnicity. However, we recognize that our analysis could not sufficiently address systemic racism, provider bias, and medical mistrust, which contribute to underrepresentation and worse glycemic outcomes among minoritized racial/ethnic groups.6 Moreover, baseline glycemic differences associated with level of education were not completely eradicated with AID use. Despite these limitations, this self-assessment clearly identified underrepresentation and glycemic disparities in clinical trials at our research center. This was highly beneficial, resulting in the implementation of strategies to increase the diversity in our clinical trial population, which included outreach to more diverse groups through purposive sampling approaches, community outreach events, and collaboration with public health leadership. We also are making strides to remove potential financial barriers to study participation via increased transportation/study-related funding. We encourage other diabetes research groups to conduct similar self-assessments which can lead to implementation of strategies to begin to rectify the problem of underrepresentation In addition, our findings suggest that improving accessibility to AID may help to equalize disparities in glycemic outcome associated with SES factors such as income, and that it is important for clinical trials to include participants who represent, not only racial/ethnic diversity, but also underrepresented SES backgrounds. Author Disclosure Statement J.G-T. reports receiving industry research support and royalties from Dexcom through his institution. No other competing financial interests exist for the remaining authors. Downloaded by University of Bern from www.liebertpub.com at 06/26/23. For personal use only. Page 4 of 8    4 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. Authors’ Contributions J.G-T. was involved in verifying and analyzing the data and writing and editing the article. O.V. was involved in verifying and analyzing the data, performing the statistical analyses, and writing and editing the article. M.H. was involved in verifying and analyzing the data and writing and editing the article. A.B. was involved in verifying and analyzing the data and writing and editing the article. L.F-G. was involved in verifying and analyzing the data and writing and editing the article.  Acknowledgement The authors thank the study volunteers and the research staff at the University of Virginia Center for Diabetes Technology.    Downloaded by University of Bern from www.liebertpub.com at 06/26/23. For personal use only. Page 5 of 8    5 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. References 1. Kanbour S, Jones M, Abusamaan MS, et al. Racial Disparities in Access and Use of Diabetes Technology Among Adult Patients With Type 1 Diabetes in a U.S. Academic Medical Center. Diabetes Care. 2023;46(1): 56–64, doi: 10.2337/dc22-1055 2. Fantasia KL, Wirunsawanya K, Lee C, et al. Racial Disparities in Diabetes Technology Use and Outcomes in Type 1 Diabetes in a Safety-Net Hospital. J Diabetes Sci Technol 2021;1–8, doi:10.1177/1932296821995810  3. Brown SA, Kovatchev BP, Raghinaru D, et al. Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes. N Engl J Med. 2019 Oct 31;381(18):1707–17; doi: 10.1056/NEJMoa1907863 4. Kovatchev BP, Kollar L, Anderson SM, et al. Evening and overnight closed-loop control versus 24/7 continuous closed-loop control for type 1 diabetes: a randomised crossover trial. Lancet. 2020 Feb;2(2):e64–73, doi: 10.1016/S2589-7500(19)30218-3 5. U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates. “S1901 Income in the Past 12 Months (in 2019 inflation-adjusted dollars).” “S1501 Educational Attainment.” 2019; doi: 10.1001/jama.2014.3201 6. Agarwal S, Schechter C, Gonzalez J, Long JA. Racial-Ethnic Disparities in Diabetes Technology use Among Young Adults with Type 1 Diabetes. Diabetes Technol Ther. 2021 Apr;23(4):306–313; doi: 10.1089/dia.2020.0338.     Downloaded by University of Bern from www.liebertpub.com at 06/26/23. For personal use only. Page 6 of 8    6 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. Table 1. Baseline and final glycemic metrics for race/ethnicity, education, and income groups. A. Minoritized Racial/Ethnic participants (MRE) Non-Hispanic White participants (NHW) Baseline  Final     Baseline Final Mean adjusted treatment difference (Baseline-Final), [95%CI] p-value Baseline Final Mean adjusted treatment difference (Baseline-Final), [95%CI] p-value Mean adjusted treatment difference (MRE - NHW), [95%CI] p-value Mean adjusted treatment difference (MRE - NHW), [95%CI] p-value N 49  49        240  239                    HbA1c (%) 7.56 ± 0.15  7.26 ± 0.15  -0.30 [ -0.55 to -0.04]  0.022  7.37 ± 0.07  7.06 ± 0.07  -0.31 [ -0.43 to -0.20]  <.001  0.19 [ -0.13 to 0.50]  0.246  0.20 [ -0.12 to 0.52]  0.218  TIR 70-180 (%) 56.77 ± 2.47  67.26 ± 2.47  10.49 [ 6.96 to 14.02]  <.001  59.45 ± 1.11  69.33 ± 1.13  9.88 [ 8.23 to 11.53]  <.001  -2.68 [ -8.00 to 2.65]  0.324  -2.07 [ -7.42 to 3.28]  0.447  TBR 70 3.92 ± 0.50  1.99 ± 0.50  -1.94 [ -2.86 to -1.02]  <.001  3.93 ± 0.22  1.76 ± 0.23  -2.16 [ -2.59 to -1.73]  <.001  0.00 [ -1.08 to 1.07]  0.996  0.22 [ -0.86 to 1.31]  0.688  TAR 180 39.29 ± 2.61  30.77 ± 2.61  -8.51 [ -12.24 to -4.79]  <.001  36.64 ± 1.17  28.91 ± 1.20  -7.73 [ -9.47 to -5.99]  <.001  2.64 [ -2.97 to 8.25]  0.355  1.86 [ -3.77 to 7.49]  0.517   Downloaded by University of Bern from www.liebertpub.com at 06/26/23. For personal use only. Page 7 of 8    7 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. B.  < Bachelor’s degree participants   ≥ Bachelor’s degree participants Baseline  Final     Baseline  Final  Mean adjusted treatment difference (Baseline-Final), [95%CI]  p-value  Baseline  Final  Mean adjusted treatment difference (Baseline-Final), [95%CI]  p-value  Mean adjusted treatment difference (<Bachelor -  ≥ Bachelor), [95%CI]  p-value  Mean adjusted treatment difference  (< Bachelor -  ≥ Bachelor), [95%CI]  p-value  N 34  34        208  208                    HbA1c (%) 7.83 ± 0.16  7.29 ± 0.16  -0.54 [ -0.76 to -0.31]  <.001  7.25 ± 0.07  7.02 ± 0.07  -0.23 [ -0.33 to -0.13]  <.001  0.58 [ 0.25 to 0.92]  <.001  0.27 [ -0.07 to 0.61]  0.113  TIR 70-180 (%) 50.07 ± 2.75  64.37 ± 2.75  14.30 [ 10.22 to 18.37]  <.001  61.18 ± 1.22  70.18 ± 1.22  9.00 [ 7.19 to 10.81]  <.001  -11.10 [ -17.01 to -5.19]  <.001  -5.81 [ -11.72 to 0.11]  0.054  TBR 70 3.70 ± 0.61  1.78 ± 0.61  -1.92 [ -3.02 to -0.82]  <.001  4.31 ± 0.27  1.92 ± 0.27  -2.39 [ -2.88 to -1.91]  <.001  -0.61 [ -1.92 to 0.70]  0.358  -0.14 [ -1.45 to 1.17]  0.836  TAR 180 46.19 ± 2.91  33.74 ± 2.91  -12.44 [ -16.75 to -8.14]  <.001  34.49 ± 1.29  27.91 ± 1.29  -6.58 [ -8.50 to -4.67]  <.001  11.70 [ 5.43 to 17.96]  <.001  5.84 [ -0.43 to 12.10]  0.068      Downloaded by University of Bern from www.liebertpub.com at 06/26/23. For personal use only. Page 8 of 8    8 Diabetes Technology and Therapeutics Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery (DOI: 10.1089/dia.2023.0197) This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. C.  Low-income participants (<$50k)   High-income participants  (≥$50k)  Baseline  Final     Baseline  Final  Mean adjusted treatment difference (Baseline-Final), [95%CI]  p-value  Baseline  Final  Mean adjusted treatment difference (Baseline-Final), [95%CI]  p-value  Mean adjusted treatment difference (<$50k - ≥$50k), [95%CI]  p-value  Mean adjusted treatment difference (<$50k - ≥$50k), [95%CI]  p-value  N 19  19        184  184                    HbA1c (%) 7.53 ± 0.20  7.03 ± 0.20  -0.49 [ -0.78 to -0.21]  <.001  7.33 ± 0.08  7.06 ± 0.08  -0.27 [ -0.38 to -0.16]  <.001  0.19 [ -0.23 to 0.61]  0.366  -0.03 [ -0.45 to 0.39]  0.892  TIR 70-180 (%) 57.38 ± 3.69  66.00 ± 3.69  8.63 [ 3.41 to 13.84]  0.001  58.86 ± 1.39  69.38 ± 1.39  10.52 [ 8.56 to 12.49]  <.001  -1.48 [ -9.24 to 6.27]  0.707  -3.38 [ -11.13 to 4.37]  0.391  TBR 70 5.42 ± 0.74  1.86 ± 0.74  -3.56 [ -4.89 to -2.23]  <.001  3.68 ± 0.28  1.87 ± 0.28  -1.81 [ -2.31 to -1.31]  <.001  1.74 [ 0.19 to 3.29]  0.028  -0.01 [ -1.56 to 1.54]  0.993  TAR 180 37.19 ± 3.87  32.00 ± 3.87  -5.19 [ -10.68 to 0.30]  0.064  37.46 ± 1.46  28.76 ± 1.46  -8.70 [ -10.76 to -6.63]  <.001  -0.27 [ -8.41 to 7.86]  0.947  3.24 [ -4.90 to 11.37]  0.434  TIR 70-180 means percentage of time-in-range 70 to 180 mg/dl, TBR percentage of time-below-range (less than 70 mg/dl) and TAR percentage of time-above-range (greater than 180 mg/dl).  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Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery.

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Underrepresentation of Diverse Populations and Glycemic Outcomes in Major Clinical Trials of Automated Insulin Delivery.

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