Preventing type 2 diabetes using combination therapy: design and methods of the CAnadian Normoglycaemia Outcomes Evaluation (CANOE) trial
Bibliographic record
Abstract
Several studies have demonstrated that type 2 diabetes mellitus (DM) can be prevented/delayed in subjects with impaired glucose tolerance (IGT) by using pharmacologic agents and/or lifestyle interventions. However, a number of challenges remain, including the translation of lifestyle programmes to the general population and the need to achieve greater risk reductions by using pharmacologic approaches. IGT, like DM, is characterized by insulin resistance, beta-cell dysfunction and increased hepatic glucose production. We believe that the use of combination diabetes therapy would be a particularly effective diabetes prevention strategy. In this context, we initiated the Canadian Normoglycemia Outcomes Evaluation (CANOE) study, a moderately sized, randomized, double-blind, controlled trial. The primary objective of CANOE is to determine whether treatment with metformin plus rosiglitazone, in addition to a healthy living lifestyle programme, will prevent the development of DM. The secondary objective of CANOE is to determine whether this treatment approach will improve cardiovascular risk factors associated with IGT. A total of 200 patients will be recruited in Toronto and London, Ontario, and followed for an average of 4 years (range 3-5 years). Active treatment with metformin (500 mg) plus rosiglitazone (2 mg), administered as one capsule twice daily, will be compared to matched placebo. Subjects will be eligible for randomization if they have IGT and are between the ages of 30-75 years. The primary outcome will be the development of new-onset DM, diagnosed by either two fasting plasma glucose values of >or=7 mmol/l or one positive oral glucose tolerance test with a 2-h plasma glucose value of >11.0 mmol/l during the active drug phase of the trial. With a sample size of 100 participants per group, we will be able to detect a relative risk reduction of 45%, with a two-sided log-rank test with a significance level of 0.05 and 80% power, assuming that the median time to progression is 8 years in the control group and that participants will be recruited over 2 years and followed for an average of 4 years. In conclusion, the CANOE study will determine whether combination pharmacological therapy combined with a lifestyle intervention programme can significantly modify the development of diabetes in high-risk Canadians.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".