Efficiently allocating scarce resources for chronic and progressive diseases such as type 2 diabetes mellitus (T2DM) is challenged by limited time and resources and an unusual degree of decision-making uncertainty (e.g., clinical and economic implications that extend far beyond trial durations, patient heterogeneity, evolving practice patterns, and practice patterns that differ between trials and ordinary use). |
To extrapolate trial data to longer decision-making time horizons, economic modeling is routinely used. While economic models of T2DM would ideally be user friendly, transparent, fast, and accurate (i.e., good external validity), the complexity of T2DM generally requires comprehensive (including parallel sets of complications and sophisticated treatment-switching algorithms) to ensure good predictive accuracy. Established T2DM models are generally slow and relatively opaque, which imposes an additional demand on economic stakeholders for case-specific expertise to evaluate the suitability of manufacturer-submitted models and in some cases to run the models with tight deadlines. |
To address a need that some economic stakeholders have for greater user friendliness and faster run times, the IHE Diabetes Cohort Model was constructed using the cohort rather than the micro-simulation approach. A well-known limitation of cohort modeling, however, is an inability to adequately model patient heterogeneity (at least not without a health state explosion) and a potential for biased cost-effectiveness estimates. |
In exercises designed to evaluate the potential magnitude of bias of the IHE Diabetes Cohort Model, we compared results generated for a set of simulation scenarios with those of a micro-simulation model (Economic and Health Outcomes Model of T2DM), chosen because the structures are otherwise generally similar and because it was possible to harmonize the models even more to minimize between-model simulation differences. We found systematic differences in simulated costs and quality-adjusted life-years, but little evidence of systematic differences in the incremental costs and quality-adjusted life-years that underlie cost-effectiveness metrics or in incremental cost-effectiveness ratios and net monetary benefits themselves. |
1 Introduction
2 Objective
3 Methods
3.1 The Models
Type | IHE-DCM | ECHO-T2DM | Method of standardization |
---|---|---|---|
Unit of observation | Cohort model | Microsimulation | N/A |
Cycle length | 1 year | 1 year, but foot submodule operates in monthly cycles | N/A |
Health states | |||
Macrovascular | IHD, MI, stroke, CHF | IHD, MI, stroke, CHF | N/A |
Neuropathy | Symptomatic neuropathy, PVD, LEA | symptomatic neuropathy, PVD, foot ulcer, LEA | Exclude costs and QALYs for foot ulcer |
Retinopathy | BDR, PDR, ME, blindness | BDR, PDR, ME, blindness | |
Kidney disease | Micro- and macroalbuminuria, ESRD | CKD stages 1–5, ESRD | Exclude costs and QALYs for micro-and macroalbuminuria as well as for CKD stages 1–5 |
Risk predictions | |||
Macrovascular | Second event for MI and stroke in UKPDS 82 [36] evaluated within simulation only | UKPDS 82 [36] is used in this application | |
Neuropathy | N/A | ||
Retinopathy | Transition probabilities from Eastman et al. [31] with a power function for HbA1c and SBP | Deactivate the link between SBP and PDR in ECHO-T2DM | |
Kidney disease | Transition probabilities from Eastman et al. [31] with a power function for HbA1c | Apply linear decline of eGFR in IHE-DCM estimated from the CDC CKD model [47] to approximate eGFR decline in ECHO-T2DM | |
Mortality | UKPDS 82 [36] used for both models | ||
Baseline patient characteristics | Includes mean values for a wide range of demographics, biomarkers, and clinical history inputs | Includes mean (SD) values for a wide range of demographics, biomarkers, and clinical history inputs with an option to include correlation between biomarkers | SD included in ECHO-T2DM but baseline biomarkers were assumed to be uncorrelated |
Efficacy data and AEs for intervention and comparator | First year change applied at initiation of the treatment for wide range of biomarkers AE risk applied as an annual event rate | First year change applied at initiation of the treatment for wide range of biomarkers AE risk applied as an annual event rate | N/A |
Insulin rescue medication | Applied in same way as intervention and comparator treatment | Supports insulin rescue with a fixed dose working in a similar way as the treatment profile for intervention and comparator. Supports flexible dose with adjusted effects | Use fixed dose insulin rescue in ECHO-T2DM |
Biomarker value progression | Annual linear change | Annual linear change supported for all biomarkers, additionally supports the non-linear evolution equations for HbA1c change sourced from UKPDS 68. eGFR decline dependent on current eGFR level and albuminuria status based on the CDC CKD model | Apply linear change for HbA1c and estimate a linear decline for IHE-DCM based on the CDC CKD model [47] |
Other disease management (ACE inhibitors, statins) | Supports anti-hypertensive, anti-dyslipidemia, and weight management drugs | Supports anti-hypertensive, anti-dyslipidemia, and weight management drugs with associated RRs for events (e.g., stroke) associated with use of ACE inhibitors and statins | No treatment for other disease management is included |
Costs and QALYs | |||
Treatment costs | Annual cost applied for all treatment arms | Annual cost applied for all treatment arms | N/A |
Unit costs for complications | Apply event cost in year of the event and an annual cost for each event. Possible to assign separately event costs for first and second MI, stroke, and LEA | Apply first-year cost and subsequent annual follow-up cost. Support possibility to assign non-fatal and fatal event costs separately | Assign same unit costs for fatal, non-fatal, first and second events |
QoL | Disutility applied for current health state(s) and demographics deducted from base utility level. Support disutility for first and subsequent events for MI and stroke | Disutility approach applied with disutility for current health state(s) and demographics deducted from base utility level | Assign same disutility for first and second events in IHE-DCM |
3.2 Reference Case
Parameter | Reference case (male and female individuals separately) | Expanded Reference case | Early disease (hypothetical) | Late disease (hypothetical) | |||
---|---|---|---|---|---|---|---|
Mean/% | Mean/% | SD | Mean/% | SD | Mean/% | SD | |
Demographics | |||||||
Age (years) | 66.00 | 66.00 | 6.00 | 50.00 | 6.00 | 75.00 | 6.00 |
Male (%) | – | 50.0 | – | 50.0 | – | 50.0 | – |
Disease duration (years)a | 8.00 | 8.00 | – | 2.50 | – | 15.00 | – |
Ethnicity/race (%) | |||||||
African Americans | 1.9 | 1.9 | – | 1.9 | – | 1.9 | – |
Caucasian | 98.1 | 0.0 | – | 0.0 | – | 0.0 | – |
Clinical indicators | |||||||
Atrial fibrillation (%) | 0.0 | 0.0 | – | 0.0 | – | 0.0 | – |
Smokers (%) | 0.0 | 0.0 | – | 0.0 | – | 0.0 | – |
HbA1c (%) | 7.50 | 8.00 | 1.50 | 8.00 | 1.50 | 8.00 | 1.50 |
SBP (mmHg) | 145.00 | 145.00 | 22.00 | 135.00 | 22.00 | 155.00 | 22.00 |
BMI (kg/m2) | 28.00 | 28.00 | 5.00 | 27.00 | 5.00 | 30.00 | 5.00 |
WBC (*106) | 7.00 | 7.00 | 1.90 | 7.00 | 1.90 | 7.00 | 1.90 |
HR (beat/minute) | 79.00 | 79.00 | 12.00 | 79.00 | 12.00 | 79.00 | 12.00 |
Total cholesterol (mg/dL)b | 200.77 | 200.77 | 1.20 | 190.00 | 46.33 | 210.00 | 46.33 |
LDL cholesterol (mg/dL)b | 115.83 | 115.83 | 39.77 | 110.00 | 39.77 | 130.00 | 39.77 |
HDL cholesterol (mg/dL)b | 50.19 | 50.19 | 15.44 | 50.19 | 15.44 | 50.19 | 15.44 |
Triglycerides (mg/dL)c | 176.99 | 176.99 | 1.50 | 176.99 | 132.74 | 176.99 | 132.74 |
eGFR (mL/min/1.73 m2) | 70.00 | 70.00 | 15.00 | 80.00 | 15.00 | 60.00 | 15.00 |
Co-morbidities (%) | |||||||
Microalbuminuria | – | 25.6 | – | 10.3 | – | 30.0 | – |
Macroalbuminuria | – | 3.6 | – | 1.9 | – | 20.0 | – |
IHD (not including MI) | – | 6.1 | – | 0.0 | – | 12.0 | – |
MI | – | 12.0 | – | 2.0 | – | 25.0 | – |
CHF | – | 6.1 | – | 0.0 | – | 10.0 | – |
Stroke | – | 9.2 | – | 1.4 | – | 20.0 | – |
Reference Case | Expanded Reference Case | |||||
---|---|---|---|---|---|---|
Treatment | Intervention | Control | Intervention | Control | ||
Mean (SE) change from baseline | Mean | Mean | Mean | SE | Mean | SE |
HbA1c, % | − 1 | 0 | − 1 | 0.05 | − 0.5 | 0.05 |
SBP, mmHg | − 10 | 0 | − 10 | 1.5 | 0 | 0 |
LDL cholesterol, mg/dL | − 19.305 | 0 | − 19.305 | 1.5 | 0 | 0 |
BMI, kg/m2 | − 1 | 0 | − 1 | 0.05 | 0 | 0 |
eGFR | 0 | 0 | 0 | 0 | − 5 | 1.000 |
Rates of adverse events (per P-Y of exposure): | ||||||
Non-severe hypoglycemia | 0 | 0 | 0.5 | 0 | 1 | 0 |
Severe hypoglycemia | 0 | 0 | 0 | 0 | 0 | 0 |
Correspondinga HbA1c, % | 7.5 | 7.5 | 7.5 | 0 | 7.5 | 0 |
Drifts | ||||||
HbA1c, % | 0 | 0 | 0.14 | 0 | 0.14 | 0 |
SBP, mmHg | 0 | 0 | 0.3 | 0 | 0.3 | 0 |
Total cholesterol, mg/dL | 0 | 0 | 0 | 0 | 0 | 0 |
LDL cholesterol, mg/dL | 0 | 0 | 0 | 0 | 0 | 0 |
HDL cholesterol, mg/dL | 0 | 0 | 0 | 0 | 0 | 0 |
Triglycerides, mg/dL | 0 | 0 | 0 | 0 | 0 | 0 |
BMI, kg/m2 | 0 | 0 | 0 | 0 | 0 | 0 |
eGFR (ECHO-T2DM) | 0 | 0 | ||||
eGFR (IHE-DCM) | 0 | 0 | − 2.43 | 0 | − 2.43 | 0 |
Treatment costs (CAN$) | ||||||
Drug | 2500 | 1000 | 2500 | 0 | 1000 | 0 |
3.3 Expanded Reference Case
# | Description | Change in parameter(s) | Base case |
---|---|---|---|
Base case | Expanded MH reference Challenge | – | – |
1 | Higher HbA1c target | HbA1c target of 8.5% | HbA1c target 8.0% |
2 | Higher HbA1c drift for comparator | HbA1c drift higher for comparator (0.24%) | 0.14% for both arms |
3 | Treatment intensification | Intensification after year 3 (both arms) | HbA1c target 8.0% |
4 | Model applied “as intended” | Flexible insulin dose (ECHO-T2DM) | Fixed insulin dose (both models) |
All unit costs/QALYs (both models) | Zero costs/QALYs for foot ulcer, CKD stages, and micro- and macroalbuminuria | ||
5 | No PSA (second-order uncertainty) | PSA inactive for both models | PSA active |
6 | Early disease patients | More favorable age, disease duration, biomarkers (SBP, TC, LDL, BMI, eGFR), and micro- and macrovascular disease histories at baseline | ADVANCE baseline patient characteristics [50] |
7 | Late disease patients | Less favorable age; disease duration; SBP, TC, LDL, BMI, and eGFR biomarkers; and more patients with micro- and macrovascular disease at baseline | ADVANCE baseline patient characteristics [50] |
8 | Alternative QALY decrements for key outcomes | QALY weights sourced from CODE-2 [51]: MI (-0.028), stroke (-0.115), CHF (-0.028), IHD (-0.028), ESRD (-0.175), and LEA (-0.272) | CADTH recommended disutility weights |
9 | Treatment effects | HbA1c lowering only: intervention (-1%) and comparator (-0.5%) | Treatment effects for SBP, LDL, BMI, and eGFR |
10 | Rebound of treatment effects following discontinuation | Full rebound of TE following discontinuation | No rebound in HbA1c |
11 | Discontinuation of treatments | No discontinuation of interventions following intensification to insulin | Discontinuation of interventions following intensification to insulin |
12 | Lower insulin cost | 50% lower (basal CAN$500/year and bolus CAN$800/year) | Cost of fixed-dose basal: CAN$1000/year |
Cost of fixed-dose bolus: CAN$1600/year | |||
13 | Higher treatment costs (intervention) | 50% higher (CAN$3750) | CAN$2500 for intervention in BC |
14 | Lower treatment costs (intervention) | 50% lower (CAN$1250) | CAN$2500 for intervention in BC |
15 | No modeling of CKD | eGFR kept constant over time | eGFR decline in line with the CDC-CKD model [47] |
16 | Deterministic cohort model | PSA inactive for IHE-DCM | PSA active for IHE-DCM |
17 | Female subgroup | 100% female | 50% female/50% male |
18 | Male subgroup | 100% male | 50% female/50% male |
3.4 Analysis
4 Results
4.1 Comparison of Model Implementation
4.2 Reference Case
4.3 Expanded Reference Case
IHE-DCM | ECHO-T2DM | |||||
---|---|---|---|---|---|---|
Intervention | Control | Difference | Intervention | Control | Difference | |
Cost drivers | ||||||
Treatment | 31,473 | 24,186 | 7287 | 29,372 | 21,674 | 7698 |
Non-insulin AHA | – | – | – | 15,040 | 4666 | 10,375 |
Insulin AHA | – | – | – | 14,332 | 17,009 | − 2677 |
MI | 12,384 | 13,152 | − 768 | 12,828 | 13,540 | − 712 |
IHD | 7391 | 7830 | − 439 | 5524 | 5685 | − 161 |
CHF | 9228 | 9659 | − 431 | 7343 | 7282 | 62 |
Stroke | 14,349 | 16,454 | − 2105 | 9391 | 10,025 | − 634 |
PVD | – | – | – | 183 | 165 | 18 |
Retinopathy | 247 | 286 | − 40 | 250 | 264 | − 14 |
CKD | 4051 | 4007 | 44 | 6890 | 8199 | − 1309 |
Neuropathy | – | – | – | 310 | 319 | − 8 |
Amputation | 3716 | 3449 | 267 | |||
Lower extremity diseasea | 5142 | 4972 | 171 | 4209 | 3932 | 277 |
Hypoglycemia | 483 | 655 | − 171 | 602 | 711 | − 109 |
Total costs (95% CI) | 84,266 | 80,547 | 3719 (− 2807; 10,245) | 76,410 | 71,312 | 5098 (− 3162; 9694) |
Disutility drivers | ||||||
MI | 0.097 | 0.099 | − 0.002 | 0.089 | 0.089 | 0.000 |
IHD | 0.081 | 0.086 | − 0.004 | 0.059 | 0.060 | − 0.001 |
CHF | 0.094 | 0.097 | − 0.003 | 0.071 | 0.069 | 0.002 |
Stroke | 0.086 | 0.095 | − 0.009 | 0.077 | 0.078 | − 0.001 |
PVD | – | – | – | 0.090 | 0.081 | 0.009 |
Retinopathy | 0.033 | 0.038 | − 0.005 | 0.034 | 0.037 | − 0.002 |
CKD | 0.040 | 0.040 | 0.000 | 0.083 | 0.098 | − 0.015 |
Neuropathy | – | – | – | 0.025 | 0.025 | − 0.001 |
Amputation event | – | – | – | 0.050 | 0.046 | 0.004 |
Lower extremity disease | 0.201 | 0.192 | 0.009 | – | – | – |
Hypoglycemia | 0.642 | 0.807 | − 0.165 | 0.598 | 0.740 | − 0.142 |
Excess weight | 0.202 | 0.268 | − 0.066 | 0.266 | 0.283 | − 0.017 |
Survivalb | 0.471 | − 0.558 | ||||
Total | 0.671 | 0.722 | ||||
Health outcomes (discounted) | ||||||
LYs (95% CI) | 13.169 | 12.710 | 0.459 (0.096; 0.822) | 11.150 | 10.546 | 0.604 (0.180; 1.033) |
QALYs (95% CI) | 10.966 | 10.295 | 0.671 (− 0.029; 1.371) | 8.978 | 8.256 | 0.722 (0.359; 1.205) |
Survival at end of year 40 | 0.8% | 0.7% | 0.2% | 0.3% | 0.2% | 0.1% |
Net monetary benefits | 29,834 (− 5833; 65,501) | 31,009 (14,562; 55,026) | ||||
Incremental cost per QALY gained | 5542 | 7059 |