Supplementary materials: The cost-effectiveness of real-time continuous glucose monitoring versus intermittently scanned continuous glucose monitoring in individuals with insulin-treated Type 2 diabetes mellitus in Canada
Bibliographic record
Abstract
<b>These are peer-reviewed supplementary materials for the article</b><b> </b><b>'</b><b>The cost-effectiveness of real-time </b><b>continuous glucose monitoring versus </b><b>intermittently scanned continuous glucose </b><b>monitoring in individuals with </b><b>insulin-treated Type 2 diabetes mellitus in </b><b>Canada</b><b>'</b><b> </b><b>published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><br><b>Appendix 1:</b> ECHO-T2DM Description<b>Supplementary figure 1: </b>ECHO-T2DM simplified flow diagram<b>Appendix 2: </b>Validation of ECHO-T2DM<b>Appendix Table 1: </b>ECHO-T2DM Cross-Validation Results=<b>Appendix Table 1:</b> ECHO-T2DM Cross-Validation Results<b>Appendix Table </b><b>2</b><b>: </b>ECHO-T2DM External Validation<b>ECHO-T2DM AdViSHE Assessment</b><b>Part B: </b>Input Data Validation<b>Part C:</b> Validation of the Computerized Model<b>Part D: </b>Operational Validation<b>Part E: </b>Other Validation Techniques<b>Appendix 3:</b> Detailed Input Data<b>Appendix Table 3: </b>Comparison of DIAMOND T2D and REPLACE<b>Appendix Table 4:</b> Unit Costs for Micro- and Macrovascular Complications (Inflated to 2023 CAD)<b>Appendix Table 5: </b>QALY Disutility Weights<b>Appendix 4:</b> Detailed Results<b>Appendix Table 6:</b> Rates for First Event (Per 100 Patient-Years)<b>Appendix Table 7:</b> Base Case Sources of QALY Disutility<b>Appendix Table 8:</b> Results of Sensitivity Analysis Comparing rtCGM with isCGM in patients with T2DM<b>Appendix Figure 2:</b> Estimated HbA1c Trajectory<b>Appendix Figure 3:</b> Estimated Survival<b>Appendix Figure 4: </b>Model Convergence<b>Appendix 5:</b> Checklist of Reporting Model Input in Diabetes Health Economics Studies and CHEERS Checklist<b>References</b><b>Consolidated Health Economic Evaluation Reporting Standard (CHEERS) 2022 Checklist</b><b>Aim:</b> Continuous glucose monitoring (CGM) supports glycemic control and reduces diabetes complications. CGM systems include intermittently scanned CGM (is-CGM) and real-time CGM (rt-CGM). While rt-CGM may provide better outcomes than is-CGM, it costs more upfront and its cost-effectiveness in Canada has not been established. We assessed the cost-effectiveness of rt-CGM versus is-CGM in people with insulin-treated Type 2 diabetes mellitus (T2DM) from a Canadian healthcare payer perspective. <b>Materials </b><b>& methods: </b>We used the ECHO-T2DM microsimulation model to estimate incremental lifetime health outcomes and costs of rt-CGM versus is-CGM. Clinical inputs came from an indirect treatment comparison; cost and utility data were drawn from published sources. Sensitivity analyses tested robustness. <b>Results: </b>Rt-CGM was more effective and less costly than is-CGM, yielding 0.346 additional quality-adjusted life-years and CAD 2237 in savings over 30 years. Benefits stemmed primarily from better glycemic control and fewer complications, reductions in glycemic events, and reduced fear of hypoglycemia. Although rt-CGM incurred CAD 3867 higher acquisition costs, these were more than offset by avoided complications. Deterministic analysis showed dominance in 14 of 18 scenarios, and cost-effectiveness in the remaining four. Uncertainty analysis showed rt-CGM had an ICER below CAD 50,000 in 98% of simulations. <b>Discussion:</b> Rt-CGM is potentially a cost-saving alternative to is-CGM among people with insulin-treated T2DM in Canada. This finding was strengthened by rigorous sensitivity analysis. Study strengths include use of a validated microsimulation model and adoption of conservative assumptions. Limitations include absence of head-to-head trial evidence and indirect use of time in and out of range. <b>Conclusion:</b> Rt-CGM is a potentially cost-saving option for managing insulin-treated T2DM in Canada, with implications for clinical practice and reimbursement policy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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 teacher head, 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".