Type 1 DiabetesiOSNCT05476861
Insulin Omission Surrogate (iOS)
An observational study of Type 1 Diabetes, run by Laval University at 1 site in Canada.
Trial summary
Type 1 Diabetes management is requiring and implies numerous lifestyle modifications. Insulin restriction to control weight is a frequent phenomenon, affecting up to 40% of PWT1D. Read more about this study
- Who is it for?
- Ages 14 years and older
- Conditions the study is for
- Type 1 Diabetes
- How many people
- 751 participants
- Where
- 1 siteCanada
- Study dates
- 1 Nov 2022to 10 May 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 14 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: This retrospective study will include data from people living with type I diabetes (adolescents and adults) who participated in the baseline phase of the BETTER registry.
Who may be able to join
- Adolescents and adults living with type 1 diabetes
- Participated in the baseline phase of the BETTER registry
- Completed a 24-hours dietary recall within the BETTER registry (objective 1 only)
- Completed the two key questions on insulin omission in the BETTER registry (objectives 2 and 3 only)
Who cannot join
- Did not participated in the BETTER registry
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Is Insulin Omission a Surrogate Marker of Eating Disorders and Severity of Diabetes-related Distress: an Exploratory Study.
Type 1 Diabetes management is requiring and implies numerous lifestyle modifications. Insulin restriction to control weight is a frequent phenomenon, affecting up to 40% of PWT1D. Broadly, purging or binge eating behaviors are also frequently disordered eating behaviors (DEB) in people living with a Type 1 Diabetes (associated or not with restrictive eating behaviors). In a study on adolescents with T1D, the prevalence of moderate or high level of DEB ranged from 21% to 32%. Moreover, the presence of binge eating behavior seems to be associated with higher anxiety and depression levels.
Omitting insulin for weight control has been associated with the highest rates of retinopathy and nephropathy when compared to other weight control behaviors and to increase the risk of mortality by 3.2 times and decrease life spans from an average of 58 to 44 years at 11-year follow-up. Moreover, insulin misuse may be much more complex behavior than just the need for weight control. These behaviors may also involve increased distress, loss of control, and feelings of regret, guilt, and shame.
Read more
Interestingly, most studies of eating disorders and type 1 diabetes use question regarding insulin omission as a surrogate marker for eating disorders and disordered eating. For instance, the question used in the BETTER registry are: "In the past 12 months, did you intentionally omit insulin injections with the objective of losing weight?" or "In a typical week, how often do you miss an insulin dose?". However, the validity and robustness of such a marker have not been specifically investigated yet.
Our study objectives are : 1) To confirm that participants who reported intentionally omitting insulin had significantly more disordered eating behavior (based on the review of food records available); 2) To compare the prevalence and the severity of physical and mental health comorbidities (e.g., diabetes micro and macrovascular complications, glycated hemoglobin levels, current and past psychiatric disorders, distress related to diabetes) in people living with diabetes having or not declared to intentionally omit insulin; 3) To establish, using machine learning techniques, the main factors associated with intentional insulin omission behavior, taking into account biological, anthropometric and psychometric factors.
Read the detailed description
Our main hypotheses:
- that people living with Type 1 diabetes who report intentional insulin omission will have a higher risk of disordered eating behaviors and diabetes-related comorbidities;
- that it will be possible to establish different predictors of intentional insulin omissions behaviors by using machine learning techniques.
Statistical Analysis:
The normality of the data distribution will be checked for each value using a graphical analysis of the distribution and a Kolmogorov-Smirnov test before parametric tests are performed. A description of the characteristics of the participants included in this study will be performed. Continuous variables will be presented by the mean and standard deviation for normal distributions, median and range for others. Categorical variables will be presented by the number and percentage of each modality. The level of significance of the tests must be equal or lower than 0.05. The risk of alpha error is set at 0.05, with Bonferroni correction if necessary.
- Objective 1 - 24-hour dietary recall: Macronutrients composition and repartition (in the day), as well as the serving sizes of the food intake will be calculated using the Canadian Food Guide 2007 or the Canadian Nutrient File.
- Objective 2 - Prevalence and severity of diabetes and its comorbidities: Both groups, having or not intentionally omit insulin, will be compared using conventional statistical analyses.
- Objective 3 - Predictive modeling: Based on a previous published methodology (Iceta et al., 2021), the first step will be to reduce entropy in the dataset using a ranking procedure (the Fast Correlation-Based Filter, FCBF) to identify the most discriminating predictor between the two class-labeled datasets (with and without insulin omission). Only items with an FCBF score > 0.1 will be retained for the subsequent steps of the data-mining analysis. The second step of the data-mining analysis will aim at selecting the most relevant predictive algorithm for intentional insulin omission. Performances of different predictive algorithms will be tested and compared: logistic regression, artificial neural networks, naive Bayes classification, decision trees, AdaBoost meta-algorithm, CN2 rule inducer algorithm, SVM algorithm, k-nearest neighbors' algorithm and stochastic gradient algorithm. These artificial intelligence algorithms will be cross-validated (ten times in a row) with a randomized learning sample, renewed ten times and representing 66% of the study population. The validation sample will be represented by the other 33% of the population. The predictive algorithm with the best precision and F1 score will be considered as the best valuable algorithm.
- Conditions
- Type 1 Diabetes
- Keywords
- Diabetes, Insulin Omission, Eating behaviors, Mental Health, Physical comorbidities of diabetes
- Medical subject headings
- Diabetes Mellitus, Type 1, Diabetes Mellitus, Feeding Behavior, Psychological Well-Being
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Having omit insulin | Patients with type 1 diabetes who responded to the BETTER survey that they intentionally forgot their insulin. | |
| Not intentionally omit insulin | Patients with type 1 diabetes who responded to the BETTER survey that they did not intentionally omit their insulin, but they did omit it. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Insulin omission
"In the past 12 months, did you intentionally omit insulin injections with the objective of losing weight?" "In a typical week, how often do you miss an insulin dose?"
Measured: Baseline
Secondary outcomes (14)
Demographic data
Measured: Baseline
Diabetes history
Measured: Baseline
Current treatment for diabetes
If any.
Measured: Baseline
Total daily dose of insulin
In units.
Measured: Baseline
Complications of diabetes
Like hypoglycemia, diabetic ketoacidosis (DKA), micro- and macro-vascular.
Measured: Baseline
Comorbidities
Including celiac disease.
Measured: Baseline
Medication
The medication that is being taken for depression, if any.
Measured: Baseline
Depression Scale (PHQ-9)
The Patient Health Questionnaire (9 items).
Measured: Baseline
Dietary intake : 24 hours recalls
Macronutrients per meal total per day.
Measured: Baseline
Dietary intake : all food items in each meal
Including portions and macronutrients.
Measured: Baseline
Type of diet
If any.
Measured: Baseline
Number of meals
Per day.
Measured: Baseline
Body Mass Index (BMI)
Weight and height will be combined to report BMI in kg/m^2.
Measured: Baseline
Waist circumference
In cm.
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Jul 2022
- Study start1 Nov 2022
- Primary completion10 May 2023
- Study completion10 May 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Type 1 DiabetesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 751 participants (actual)
Sponsor and investigators
- Lead sponsor
- Laval University
- Sponsor type
- University, hospital or other
- Collaborators
- McGill University, Institut de Recherches Cliniques de Montreal
- Responsible party
- Principal investigator, Sylvain Iceta, Laval University
- Investigators
- Sylvain Iceta, MD, PhD, Principal investigator, Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05476861
- Sponsor's protocol ID
- 2023-3876, 22239
- Acronym
- iOS
- Status last verified
- May 2023
- First submitted
- 25 Jul 2022
- Last updated
- 12 May 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 12 May 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Is Insulin Omission a Surrogate Marker of Eating Disorders and Severity of Diabetes-related Distress: an Exploratory Study.
- ClinicalTrials.gov ID
- NCT05476861
- Acronym / sponsor ID
- iOS / 2023-3876, 22239
- Conditions
- Type 1 Diabetes
- Keywords
- Diabetes, Insulin Omission, Eating behaviors, Mental Health, Physical comorbidities of diabetes
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 751 participants (actual)
- Lead sponsor
- Laval UniversityUniversity, hospital or other
- Collaborators
- McGill University, Institut de Recherches Cliniques de Montreal
- Study start
- 1 Nov 2022 (actual)
- Primary completion
- 10 May 2023 (actual)
- Study completion
- 10 May 2023 (actual)
- First posted
- 27 Jul 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Type 1 Diabetes management is requiring and implies numerous lifestyle modifications. Insulin restriction to control weight is a frequent phenomenon, affecting up to 40% of PWT1D. Broadly, purging or binge eating behaviors are also frequently disordered eating behaviors (DEB) in people living with a Type 1 Diabetes (associated or not with restrictive eating behaviors). In a study on adolescents with T1D, the prevalence of moderate or high level of DEB ranged from 21% to 32%. Moreover, the presence of binge eating behavior seems to be associated with higher anxiety and depression levels.
Omitting insulin for weight control has been associated with the highest rates of retinopathy and nephropathy when compared to other weight control behaviors and to increase the risk of mortality by 3.2 times and decrease life spans from an average of 58 to 44 years at 11-year follow-up. Moreover, insulin misuse may be much more complex behavior than just the need for weight control. These behaviors may also involve increased distress, loss of control, and feelings of regret, guilt, and shame.
Interestingly, most studies of eating disorders and type 1 diabetes use question regarding insulin omission as a surrogate marker for eating disorders and disordered eating. For instance, the question used in the BETTER registry are: "In the past 12 months, did you intentionally omit insulin injections with the objective of losing weight?" or "In a typical week, how often do you miss an insulin dose?". However, the validity and robustness of such a marker have not been specifically investigated yet.
Our study objectives are : 1) To confirm that participants who reported intentionally omitting insulin had significantly more disordered eating behavior (based on the review of food records available); 2) To compare the prevalence and the severity of physical and mental health comorbidities (e.g., diabetes micro and macrovascular complications, glycated hemoglobin levels, current and past psychiatric disorders, distress related to diabetes) in people living with diabetes having or not declared to intentionally omit insulin; 3) To establish, using machine learning techniques, the main factors associated with intentional insulin omission behavior, taking into account biological, anthropometric and psychometric factors.
Detailed description
Our main hypotheses:
- that people living with Type 1 diabetes who report intentional insulin omission will have a higher risk of disordered eating behaviors and diabetes-related comorbidities;
- that it will be possible to establish different predictors of intentional insulin omissions behaviors by using machine learning techniques.
Statistical Analysis:
The normality of the data distribution will be checked for each value using a graphical analysis of the distribution and a Kolmogorov-Smirnov test before parametric tests are performed. A description of the characteristics of the participants included in this study will be performed. Continuous variables will be presented by the mean and standard deviation for normal distributions, median and range for others. Categorical variables will be presented by the number and percentage of each modality. The level of significance of the tests must be equal or lower than 0.05. The risk of alpha error is set at 0.05, with Bonferroni correction if necessary.
- Objective 1 - 24-hour dietary recall: Macronutrients composition and repartition (in the day), as well as the serving sizes of the food intake will be calculated using the Canadian Food Guide 2007 or the Canadian Nutrient File.
- Objective 2 - Prevalence and severity of diabetes and its comorbidities: Both groups, having or not intentionally omit insulin, will be compared using conventional statistical analyses.
- Objective 3 - Predictive modeling: Based on a previous published methodology (Iceta et al., 2021), the first step will be to reduce entropy in the dataset using a ranking procedure (the Fast Correlation-Based Filter, FCBF) to identify the most discriminating predictor between the two class-labeled datasets (with and without insulin omission). Only items with an FCBF score > 0.1 will be retained for the subsequent steps of the data-mining analysis. The second step of the data-mining analysis will aim at selecting the most relevant predictive algorithm for intentional insulin omission. Performances of different predictive algorithms will be tested and compared: logistic regression, artificial neural networks, naive Bayes classification, decision trees, AdaBoost meta-algorithm, CN2 rule inducer algorithm, SVM algorithm, k-nearest neighbors' algorithm and stochastic gradient algorithm. These artificial intelligence algorithms will be cross-validated (ten times in a row) with a randomized learning sample, renewed ten times and representing 66% of the study population. The validation sample will be represented by the other 33% of the population. The predictive algorithm with the best precision and F1 score will be considered as the best valuable algorithm.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Having omit insulin | – | –Patients with type 1 diabetes who responded to the BETTER survey that they intentionally forgot their insulin. |
| Not intentionally omit insulin | – | –Patients with type 1 diabetes who responded to the BETTER survey that they did not intentionally omit their insulin, but they did omit it. |
Who may qualify
- Ages
- 14 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- This retrospective study will include data from people living with type I diabetes (adolescents and adults) who participated in the baseline phase of the BETTER registry.
Key inclusion criteria (4 listed)
- Adolescents and adults living with type 1 diabetes
- Participated in the baseline phase of the BETTER registry
- Completed a 24-hours dietary recall within the BETTER registry (objective 1 only)
- Completed the two key questions on insulin omission in the BETTER registry (objectives 2 and 3 only)
Key exclusion criteria (1 listed)
- Did not participated in the BETTER registry
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Insulin omission
Time frame: Baseline
"In the past 12 months, did you intentionally omit insulin injections with the objective of losing weight?" "In a typical week, how often do you miss an insulin dose?"
14 secondary outcomes
Demographic data
Time frame: Baseline
Diabetes history
Time frame: Baseline
Current treatment for diabetes
Time frame: Baseline
Total daily dose of insulin
Time frame: Baseline
Complications of diabetes
Time frame: Baseline
Comorbidities
Time frame: Baseline
Medication
Time frame: Baseline
Depression Scale (PHQ-9)
Time frame: Baseline
Dietary intake : 24 hours recalls
Time frame: Baseline
Dietary intake : all food items in each meal
Time frame: Baseline
Type of diet
Time frame: Baseline
Number of meals
Time frame: Baseline
Body Mass Index (BMI)
Time frame: Baseline
Waist circumference
Time frame: Baseline
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 May 2023.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Sylvain Iceta, MD, PhD principal investigator
Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ)
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Type 1 Diabetes, run by Laval University at 1 site in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 12 May 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Insulin omission (time frame: Baseline). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 May 2023.