Investigating Novel Predictions of Hypoglycemia Occurrence in Real-world Models (iNPHORM)

• ClinicalTrials.gov Identifier: NCT04219514
• Recruitment Status: Completed
• First Posted: January 7, 2020
• Last Update Posted: April 13, 2021
• Sponsor: Stewart Harris
• Collaborator: Sanofi
• Information provided by (Responsible Party): Stewart Harris, Western University, Canada

Study Description

Brief Summary:

Hypoglycemia is the most common diabetes-related adverse event. However, it is often under-reported to healthcare providers by patients and simultaneously, not often asked about by healthcare providers. As a result, little is known about how often hypoglycemia occurs and consequently, which individuals with diabetes will experience such events. The aims of this study are to determine the real- world occurrence of hypoglycemia and develop/validate real-world risk prediction models for hypoglycemia. These risk prediction models will generate a risk score that indicates an individual's risk for hypoglycemia given their socio-demographic, clinical, and/or behaviour-related characteristics. They can be used to promote clinician awareness around patients' hypoglycemia risks, guide point- of-care and patient decision-making with regard to treatment changes, inform the development and conduct of population-based interventions, and lead to tailored, cost-effective management strategies.

Condition or disease
Hypoglycemia; Diabetes Mellitus, Type 2; Diabetes Mellitus, Type 1

Detailed Description:

The overarching purpose of the proposed investigation is to develop and validate three real-world risk prediction models for: 1) severe hypoglycemia, 2) non-severe daytime hypoglycemia, and 3) non-severe nighttime hypoglycemia, that are applicable to the general population with diabetes (Type 1 and Type 2). These prediction models, which will produce risk scores, will be generated using long-term, prospective data on the frequency and multidimensional risk factors of real-world hypoglycemia. Self-reported hypoglycemia data - a pragmatic and significant patient-important outcome in the clinical management of diabetes - will collected in a non-clinical setting as they are crucial to determining the true distributional burden of events and impactful avenues for prevention, especially given the known epidemiological challenges of existent data collection strategies (e.g., via RCT- or registry-based designs). The use of real-world data will also enhance the generalizability and thus, clinical value of hypoglycemia risk prediction models.

The study will employ an ambidirectional (one-year retrospective and one-year prospective) observational cohort design such that multiple exposures (i.e., risk factors) will be collected and evaluated in relation to the occurrence of an outcome (hypoglycemia events). Participants will be enrolled into a prospective, observational cohort referred to as the 'Diabetes iNPHORM Community'. Data will be collected through online questionnaires administered at baseline (to collect retrospective data) and each month of the one-year prospective period. A pilot test will be conducted prior to the enrollment of participants into the Diabetes iNPHORM Community. The purpose of this pilot test is to test the usability of the online question platform, flow and format of the questionnaires, and the readability of the questions.

Participants will be recruited into the pilot test and the observational cohort of the study from a pre-existing online panel representative of the general public that has been developed and managed by Ipsos Interactive Services (IIS), a global leader in survey conduct. All individuals in the pre-existing online panel provided profile information and consented to be approached by IIS and its subsidiary partners to complete surveys. For this study, individuals approached to participate in the pilot tests will not subsequently be invited to participate in the observational cohort.

Study Design

• Study Type: Observational
• Actual Enrollment: 1206 participants
• Observational Model: Cohort
• Time Perspective: Other
• Official Title: Investigating Novel Predictions of Hypoglycemia Occurrence in Real-world Models
• Actual Study Start Date: February 10, 2020
• Actual Primary Completion Date: March 30, 2021
• Actual Study Completion Date: March 30, 2021

Groups and Cohorts

Outcome Measures

Primary Outcome Measures :

1. Incidence proportions and densities of severe hypoglycemia, non-severe daytime hypoglycemia, and non-severe nighttime hypoglycemia [ Time Frame: Up to 12 months prospectively ]
   Self-reported through questionnaires
2. Risk scores for severe hypoglycemia, non-severe daytime hypoglycemia, non-severe nighttime hypoglycemia [ Time Frame: Up to 12 months prospectively ]

   Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-World Models (iNPHORM) Hypoglycemia Risk Score:

   Risk scores using the probabilities (0-100%) from our validated multivariable prediction models will be calculated to reflect the degree of risk due to the candidate variables (low to high risk scores will denote low to high risks of hypoglycemia occurrence, respectively). Any selected ranges of predicted probabilities used as boundaries for risk stratification will be justified. Details relevant to the calculation of subject-specific risks will be reported, including the intercepts and betas from the logistic regression models and nomograms.

Secondary Outcome Measures :

1. Exploratory causal estimates of different treatment regimens and hypoglycemia rates [ Time Frame: Up to 12 months prospectively ]
   Derived from data captured through questionnaires

Eligibility Criteria

• Ages Eligible for Study: 18 Years to 90 Years (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No
• Sampling Method: Non-Probability Sample

Study Population

Participants will be recruited into the pilot test and the observational cohort of the study from a pre-existing online panel representative of the general public developed and managed by Ipsos Interactive Services (IIS), a global leader in survey conduct. Within the USA, IIS and its subsidiary partners manage a nationwide panel of 65,000+ people with diabetes (~10,000 with T1DM and ~58,000 with T2DM); this panel will serve as the sampling frame for the current investigation. All individuals in the pre-existing online panel provided profile information and consented to be approached by IIS and its subsidiary partners to complete surveys. For this study, individuals approached to participate in the pilot tests will not subsequently be invited to participate in the observational cohort.

Criteria

Inclusion Criteria:

• Self-reported diagnosis of T1DM or T2DM
• Use of insulin and/or secretagogues for at least one year at the time of enrolment
• Living in the United States of America for at least one year at the time of enrolment

Exclusion Criteria:

• Unable to read and understand English
• Currently pregnant or pregnant within the previous year
• Currently participating in an interventional clinical trial or research study

Contacts and Locations

Locations

United States, New York

Ipsos

New York, New York, United States, 10010

Sponsors and Collaborators

Stewart Harris

Sanofi

Investigators

• Principal Investigator: Stewart Harris, MD MPH; Western University
• Principal Investigator: Alexandria Ratzki-Leewing, PhD(c) MSc; Western University

More Information

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):

Ratzki-Leewing A, Black JE, Ryan BL, Harris SB. Real-world risk factors of confirmed or probable COVID-19 in Americans with diabetes: A prospective, community-based study (iNPHORM). Endocrinol Diabetes Metab. 2022 Jul;5(4):e342. doi: 10.1002/edm2.342. Epub 2022 May 29.

Ratzki-Leewing A, Ryan BL, Zou G, Webster-Bogaert S, Black JE, Stirling K, Timcevska K, Khan N, Buchenberger JD, Harris SB. Predicting Real-world Hypoglycemia Risk in American Adults With Type 1 or 2 Diabetes Mellitus Prescribed Insulin and/or Secretagogues: Protocol for a Prospective, 12-Wave Internet-Based Panel Survey With Email Support (the iNPHORM [Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-world Models] Study). JMIR Res Protoc. 2022 Feb 11;11(2):e33726. doi: 10.2196/33726.

Ratzki-Leewing AA, Ryan BL, Buchenberger JD, Dickens JW, Black JE, Harris SB. COVID-19 hinterland: surveilling the self-reported impacts of the pandemic on diabetes management in the USA (cross-sectional results of the iNPHORM study). BMJ Open. 2021 Sep 2;11(9):e049782. doi: 10.1136/bmjopen-2021-049782.

• Responsible Party: Stewart Harris, Professor, Western University, Canada
• ClinicalTrials.gov Identifier: NCT04219514
• Other Study ID Numbers: 112986
• First Posted: January 7, 2020
• Last Update Posted: April 13, 2021
• Last Verified: April 2021

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No

• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Stewart Harris, Western University, Canada:

hypoglycemia; diabetes mellitus

Additional relevant MeSH terms:

Diabetes Mellitus; Diabetes Mellitus, Type 2; Hypoglycemia; Diabetes Mellitus, Type 1; Glucose Metabolism Disorders; Metabolic Diseases; Endocrine System Diseases; Autoimmune Diseases; Immune System Diseases