Investigating Novel Predictions of Hypoglycemia Occurrence in Real-world Models
Condition: Hypoglycemia; Diabetes Mellitus, Type 2; Diabetes Mellitus, Type 1
MeSH terms: Diabetes Mellitus; Diabetes Mellitus, Type 2; Hypoglycemia; Diabetes Mellitus, Type 1
Study type: Observational

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.
    

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.
    

Observational model: Cohort
Time perspective: Other
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.
      
Keywords: hypoglycemia; diabetes mellitus