The goal of this observational study is to validate medico-administrative algorithms that classify diabetes phenotypes (Type 1, Type 2, and Latent Autoimmune Diabetes in Adults - LADA) in a population-based cohort in Quebec, including children, adolescents, and young adults up to 40 years old with diagnosed diabetes. The main questions it aims to answer are:
Can these algorithms accurately distinguish between Type 1, Type 2, and LADA across different age groups? What is the prevalence and incidence of each diabetes phenotype in Quebec? Participants will have their medical and administrative data analyzed, including data on medication usage and healthcare visits, to validate the accuracy of the algorithms. The study will involve comparing these algorithm-based classifications with clinical diagnoses or self-reported data to ensure reliability.
Individuals diagnosed with Type 1, Type 2, or Latent Autoimmune Diabetes in Adults (LADA) based on clinical or self-reported data.
Participants diagnosed between 1997 and 2024.
Residents of Quebec with available medico-administrative records from 1997 to 2024.
Non-residents of Quebec during the study period.
The study population consists of individuals diagnosed with Type 1, Type 2, or LADA diabetes, as well as other diabetes-related phenotypes, within the province of Quebec. The population includes children, adolescents, and young adults up to 40 years of age at the time of diagnosis. The cohort is drawn from a comprehensive dataset of medical, self-reported, and medico-administrative records spanning from 1997 to 2024. This diverse population allows for a robust validation of the diabetes classification algorithms across different age groups and phenotypes, providing valuable insights into the epidemiology of diabetes in Quebec.
Cohort
Retrospective
no intervention
Other interventionno intervention. this is observational study.
Diagnostic Accuracy Measures (Percentages)
The primary outcome measure is the accuracy of the medico-administrative algorithms in correctly classifying participants into one of the following diabetes phenotypes: Type 1, Type 2, LADA, or Other Phenotypes, compared to clinical or self-reported diagnoses. 1.1. Diagnostic Accuracy Measures (Percentages) * Sensitivity (Se) * Specificity (Sp) * Positive Predictive Value (PPV) * Negative Predictive Value (NPV) All reported as proportions or percentages. These indicators will not be aggregated into a single value, but will be presented separately to respect their distinct units of measurement.
Classification Counts (Number of Cases)
The primary outcome measure is the accuracy of the medico-administrative algorithms in correctly classifying participants into one of the following diabetes phenotypes: Type 1, Type 2, LADA, or Other Phenotypes, compared to clinical or self-reported diagnoses. 1.2. Classification Counts (Number of Cases) * True Positives (TP) * True Negatives (TN) * False Positives (FP) * False Negatives (FN) All reported as counts of participants. These indicators will not be aggregated into a single value, but will be presented separately to respect their distinct units of measurement.
Likelihood Ratios (Unitless)
The primary outcome measure is the accuracy of the medico-administrative algorithms in correctly classifying participants into one of the following diabetes phenotypes: Type 1, Type 2, LADA, or Other Phenotypes, compared to clinical or self-reported diagnoses. 1.3. Likelihood Ratios (Unitless) * Positive Likelihood Ratio (LR+) * Negative Likelihood Ratio (LR-) Reported as unitless ratios. These indicators will not be aggregated into a single value, but will be presented separately to respect their distinct units of measurement.
Prevalence of Each Diabetes Phenotype (Proportion/Percentage)
Prevalences of each diabetes phenotype (Type 1, Type 2, LADA, and Other Phenotypes) within the study population : Determines the proportion of individuals who have each specific diabetes phenotype (Type 1, Type 2, LADA, or Other Phenotypes) at a given point in time (Reported as a percentage or proportion). Unit of Measure: Proportion or percentage of the study population. These calculations will provide insights into the distribution and emergence of different diabetes phenotypes within the Quebec population from 1997 to 2024, allowing for a better understanding of disease patterns and informing public health strategies and resource allocation. These indicators will not be aggregated into a single value, but will be presented separately to respect their distinct units of measurement.
Incidence of Each Diabetes Phenotype
Incidences of each diabetes phenotype (Type 1, Type 2, LADA, and Other Phenotypes) within the study population: Incidence (I): Calculates the rate at which new cases of each diabetes phenotype occur in the study population over the defined period (Reported as a rate or proportion). Unit of Measure: Rate of new cases (e.g., per 1,000 person-years) or proportion (cases/total population). These calculations will provide insights into the distribution and emergence of different diabetes phenotypes within the Quebec population from 1997 to 2024, allowing for a better understanding of disease patterns and informing public health strategies and resource allocation. These indicators will not be aggregated into a single value, but will be presented separately to respect their distinct units of measurement.
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Universite du Quebec en Outaouais
Lead sponsor
McGill University
Collaborator
Centre de Recherche du Centre Hospitalier de l'Université de Montréal
Collaborator
University Hospital, Angers
Collaborator
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