Table 2:
Regression equations of the best model in the utilization indicator of “DDDs” in each of the parenteral anti-diabetes drugs and classifications (insulins)
| DDDs for Total Insulins - Regression Analysis | |||
|---|---|---|---|
| Drug Name | Regression Type | Regression Equation | R2 |
| Insulin (beef) | Polynomial | y = 52091x2 - 709873x + 2E+06 | R2 = 0.7928 |
| Insulin aspart | Polynomial | y = 194885x2 + 3E+06x − 6E+06 | R2 = 0.9688 |
| Insulin glargine | Polynomial | y = 149075x2 + 2E+06x − 4E+06 | R2 = 0.9786 |
| Insulin (human) | Polynomial | y = −81.161x2 + 1403.6x − 2241.7 | R2 = 0.7005 |
| Combinations Insulin | Linear | y = −551827x + 3E+07 | R2 = 0.2367 |
| Insulin detemir | Polynomial | y = 33237x2 − 170685x + 155513 | R2 = 0.817 |
| Insulin glulisine (Pen) | Polynomial | y = 22100x2 − 63183x + 850.45 | R2 = 0.8801 |
| Insulin glulisine (Vial) | Linear | y = 634458x + 9E+06 | R2 = 0.6795 |
| Total Insulins | Power | y = 3E+07x0.5057 | R2 = 0.8087 |
| DDDs for Total Insulin Classifications - Regression Analysis | |||
|---|---|---|---|
| Drug Name | Regression Type | Regression Equation | R2 |
| Short-Acting Insulin (Vials) | Polynomial | y = −23613x2 + 129796x + 4E+07 | R2 = 0.0071 |
| Rapid-Acting Insulin (Vials) | Polynomial | y = −81.161x2 + 1403.6x - 2241.7 | R2 = 0.7005 |
| Rapid-Acting Insulin (Pens) | Polynomial | y = 216985x2 + 3E+06x − 6E+06 | R2 = 0.969 |
| Long-Acting Insulin (Vials/Pens) | Polynomial | y = 182313x2 + 2E+06x − 4E+06 | R2 = 0.9796 |
| Total Insulins | Polynomial | y = 375603x2 + 5E+06x + 3E+07 | R2 = 0.9446 |