Towards a Health Economic Simulation Model of Type 2 Diabetes in Sweden
Bibliographic record
Abstract
The aim of this thesis was to provide part of the data required in updating/developing computer simulation models (CSMs) for type 2 diabetes mellitus (T2DM) using data obtained from routine clinical practice in Sweden. In paper I, evolution of five biomarkers (i.e., HbA1c, systolic blood pressure, BMI, LDL and total to HDL cholesterol ratio) over time was estimated using data on 5,043 newly diagnosed T2DM patients from the Swedish National Diabetes Register (NDR) and a dynamic panel data framework. The results indicated that difference between individuals with high and low biomarker values at the baseline was diminishing over time. In paper II, we estimated and validated the risk equations for the first and second major macrovascular events after diagnosis during the five years of follow up using the data on 29,034 T2DM patients from the NDR. We used the Weibull proportional hazard regression to estimate these equations. We found within- and between-event heterogeneities in associations between explanatory variables and the risk of experiencing an event. Validation analysis indicated that all equations had reasonable predictive accuracy in the test sample. In paper III, health utility weights associated with several T2DM-related complications were estimated using survey data on the Swedish version of EuroQol (EQ-5D) instrument among 1,757 T2DM patients collected by the NDR in 2008. The results indicated that history of kidney disorders (–0.114) and stroke (–0.111) had the highest negative effects on the UK EQ-5D index score. Using the UK and Swedish tariffs resulted in discrepant estimates, possibly leading to divergent results from cost–utility analyses. In paper IV, an existing cohort model of T2DM in Sweden was updated using equations from papers II and III, and was used to estimate the lifetime costs and benefits of three second-line treatment alternatives, i.e., GLP-1 agonists, DPP-4 inhibitors, or NPH insulin, as add-on to metformin among T2DM patients in Sweden failing to reach Hba1c ≤ 7% with metformin alone. The results indicated that assuming a willingness to pay of SEK 500,000 per QALY gained in Sweden, treatment strategy with GLP-1 can be considered cost-effective compared to DPP-4 or NPH insulin as second line treatment. The results indicated the importance of developing and refining the equations required in CSMs as new data become available. The data presented in the current thesis are representative of the current clinical practice in Sweden and hence it is suggested that using these data in economic evaluations of T2DM treatment strategies might provide more relevant and accurate results for policy-making in Sweden. (Less)
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".