Investigating Novel Predictions of Hypoglycemia Occurrence in Real-world Models (iNPHORM)
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|ClinicalTrials.gov Identifier: NCT04219514|
Recruitment Status : Completed
First Posted : January 7, 2020
Last Update Posted : April 13, 2021
|Condition or disease|
|Hypoglycemia Diabetes Mellitus, Type 2 Diabetes Mellitus, Type 1|
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 Type :||Observational|
|Actual Enrollment :||1206 participants|
|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|
- 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
- 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.
- Exploratory causal estimates of different treatment regimens and hypoglycemia rates [ Time Frame: Up to 12 months prospectively ]Derived from data captured through questionnaires
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04219514
|United States, New York|
|New York, New York, United States, 10010|
|Principal Investigator:||Stewart Harris, MD MPH||Western University|
|Principal Investigator:||Alexandria Ratzki-Leewing, PhD(c) MSc||Western University|