Table 2.
Input Parameters and Data Sources used in the Markov Model for Crohn’s Disease.
| Parameters | Value | Data Source |
|---|---|---|
| Patients’ characteristics | ||
| Age, years | 36.1 | Sandborn 20137 |
| Females, % | 53 | Sandborn 20137 |
| Weight, kg | 69.8 | Sandborn 20137 |
| Transition probabilities (per cycle) | ||
| Treatment efficacy | ||
| First-line treatment | ||
| Induction phase | ||
| Remission | ||
| Infliximab | 0.5454 | Calculations based on Singh 201835 |
| Adalimumab | 0.4359 | Calculations based on Singh 201835 |
| Vedolizumab | 0.3536 | Calculations based on Singh 201835 |
| Response | ||
| Infliximab | 0.3480 | Calculations based on Singh 201835 |
| Adalimumab | 0.0291 | Calculations based on Singh 201835 |
| Vedolizumab | 0.0424 | Calculations based on Singh 201835 |
| Maintenance phase | ||
| Remission | ||
| Infliximab | 0.4649 | Calculations based on Singh 201835 |
| Adalimumab | 0.5731 | Calculations based on Singh 201835 |
| Vedolizumab | 0.4134 | Calculations based on Singh 201835 |
| Response | ||
| Infliximab | 0.4029 | Calculations based on Singh 201835 |
| Adalimumab | 0.0470 | Calculations based on Singh 201835 |
| Vedolizumab | 0.0639 | Calculations based on Singh 201835 |
| Subsequent lines | ||
| Induction phase | ||
| Remission | ||
| Infliximab | 0.1160 | Assumption: to be same as least efficacious drug |
| Adalimumab | 0.2344 | Calculations based on Singh 201835 |
| Vedolizumab | 0.1160 | Calculations based on Singh 201835 |
| Response | ||
| Infliximab | 0.2077 | Assumption: to be same as least efficacious drug |
| Adalimumab | 0.1591 | Calculations based on Singh 201835 |
| Vedolizumab | 0.2077 | Calculations based on Singh 201835 |
| Maintenance phase | ||
| Remission | ||
| Infliximab | 0.1389 | Assumption: to be same as least efficacious drug |
| Adalimumab | 0.3367 | Calculations based on Singh 201835 |
| Vedolizumab | 0.1389 | Calculations based on Singh 201835 |
| Response | ||
| Infliximab | 0.2519 | Assumption: to be same as least efficacious drug |
| Adalimumab | 0.2032 | Calculations based on Singh 201835 |
| Vedolizumab | 0.2519 | Calculations based on Singh 201835 |
| Discontinuation of treatment from real-world evidence | ||
| First-line treatment | ||
| Infliximab | 0.0326 | Calculation based on Chen 201927 |
| Adalimumab | 0.0637 | Calculation based on Chen 201927 |
| Vedolizumab | 0.0387 | Calculation based on Helwig 202128 |
| Subsequent lines | ||
| Infliximab | 0.0490 | Calculation based on Helwig 202029 |
| Adalimumab | 0.0446 | Calculation based on Helwig 202029 |
| Vedolizumab | 0.0401 | Calculation based on Helwig 202029 |
| Outcomes after surgery | ||
| Remission | 0.5268 | Silverstein 199936 |
| Probability of active disease after surgery | 0.4732 | Calculations based on Silverstein 199936 |
| Probability of disease recurrence | 0.0350 | Blackhouse 201237 |
| Safety | ||
| Serious infection probabilities (per cycle) | ||
| Infliximab | 0.0063 | Calculations based on Hanauer 200238 |
| Adalimumab | 0.0042 | Calculations based on Colombel 200739 |
| Vedolizumab | 0.0087 | Calculations based on Sandborn 20137 |
| Mortality | ||
| Standardized mortality ratio—UK | 1.2600 | King 202031 |
| Standardized mortality ratio—France | 1.3900 | Duricova 201040 |
| Perioperative mortality | 0.0000 | Assumption (included in SMR) |
| Utility | ||
| Active disease | 0.4 | Lindsay 200841 |
| Remission | 0.83 | Lindsay 200841 |
| Response | 0.55 | Lindsay 200841 |
| Surgery | 0.4 | Assumption: same as utility for active disease |
| Remission after surgery | 0.67 | Lindsay 200841 |
| Active disease (SoC) | 0.4 | Assumption: same as utility for active disease |
| Disutility | ||
| Serious infections | 0.07 | Worbes-Cerezo 201934 |
Abbreviations: SMR, standardized mortality ratio; SoC, standard of care.