Table 3. Comparison of the RMSE of the 5 Models at Forecasting MD, PSD, and IOP for All Patients in the Ocular Hypertension Treatment Study at 12, 24, 36, 48, and 60 Months.
| Months Ahead by Metric | RMSE (% Improvement)a,b | ||||
|---|---|---|---|---|---|
| KF-OHTNc | KF-HTG | PM | LR1 | LR2 | |
| MD | |||||
| 12 | 1.44 (18.8) | 1.48 (16.4) | 1.52 (14.3) | 1.77 | 1.76 (0.7) |
| 24 | 1.64 (32.2) | 1.64 (32.3) | 1.70 (29.7) | 2.42 | 2.43 (–0.3) |
| 36 | 1.59 (47.1) | 1.60 (46.7) | 1.67 (44.5) | 3.00 | 3.01 (–0.4) |
| 48 | 1.61 (55.5) | 1.64 (54.6) | 1.76 (51.4) | 3.62 | 3.63 (–0.4) |
| 60 | 1.72 (59.7) | 1.85 (56.7) | 1.89 (55.8) | 4.27 | 4.28 (–0.4) |
| PSD | |||||
| 12 | 0.73 (14.7) | 0.71 (17.0) | 0.68 (19.6) | 0.85 | 0.86 (–1.5) |
| 24 | 0.80 (28.3) | 0.81 (28.0) | 0.76 (32.2) | 1.12 | 1.13 (–0.7) |
| 36 | 0.84 (39.3) | 0.97 (29.8) | 0.81 (41.2) | 1.38 | 1.38 (0.2) |
| 48 | 0.93 (45.0) | 1.19 (29.7) | 0.90 (46.5) | 1.69 | 1.69 (0.1) |
| 60 | 1.04 (48.5) | 1.48 (26.4) | 1.00 (50.2) | 2.01 | 2.00 (0.6) |
| IOP | |||||
| 12 | 2.33 (26.6) | 2.67 (15.8) | 2.48 (21.7) | 3.17 | 3.15 (0.5) |
| 24 | 2.67 (40.4) | 2.83 (36.7) | 2.72 (39.2) | 4.47 | 4.45 (0.6) |
| 36 | 3.02 (46.7) | 2.99 (47.1) | 3.02 (46.7) | 5.66 | 5.60 (1.0) |
| 48 | 3.23 (53.0) | 3.36 (51.1) | 3.54 (48.5) | 6.88 | 6.83 (0.8) |
| 60 | 3.42 (58.5) | 4.08 (50.6) | 4.56 (44.8) | 8.25 | 8.14 (1.4) |
Abbreviations: IOP, intraocular pressure; KF-OHTN, Kalman filter built using a sample of patients with ocular hypertension from the Ocular Hypertension Treatment Study; KF-HTG, KF built using a sample of patients with high-tension glaucoma; LR, linear regression model; MD, mean deviation; PM, personalized mean model; PSD, pattern standard deviation; RMSE, root-mean-square error.
The RMSE values closer to 0 indicate estimations closer to the actual values obtained in the trial.
Percentage improvement is measured with respect to the LR1 model and computed as (RMSELR1 − RMSEM)/(RMSELR1) × 100, where RMSEM is the RMSE belonging to the KF-OHTN, KF-HTG, PM, or LR2 model. Positive percentage improvement values indicate improved performance compared with the LR1 model.
The RMSE was estimated using leave-1-out cross-validation.