The present work applied time-to-event modeling to quantify the dropout risk as well as the exposure–response relationship between lacosamide plasma concentration and seizure probability, in newly diagnosed patients with focal or generalized tonic–clonic seizures without signs of focal onset (provided they had no history or findings suggestive of idiopathic generalized epilepsy). |
Baseline disease severity expressed as the number of seizures in the previous 3 months was identified as a key predictor of seizure risk in addition to the area under the plasma concentration–time curve of lacosamide. |
Simulations suggested that an initial target dose >200 mg/day could potentially benefit patients with greater disease severity. |
1 Introduction
2 Patients and Methods
2.1 Study Design
2.2 Modeling Strategy and Software
2.3 Pharmacokinetic Modeling
2.4 Dropout Modeling
2.5 Seizure Modeling
2.6 Model Qualification
2.7 Simulations
3 Results
3.1 Data
LCM | CBZ-CR | Total | |
---|---|---|---|
N (%) | 443 (50.2) | 440 (49.8) | 883 (100.0) |
Age (years) | |||
Mean (CV %) | 42.0 (42.6) | 41.8 (41.3) | 41.9 (41.9) |
Median (range) | 40 (16–87) | 41 (16–85) | 40 (16–87) |
IQR | 25.5–55 | 26–55 | 26–55 |
Sex, n (%) | |||
Female | 200 (45.1) | 209 (47.5) | 409 (46.3) |
Male | 243 (54.9) | 231 (52.5) | 474 (53.7) |
Number of seizures in the previous 3 months | |||
Mean (CV %) | 12.4 (319.8) | 10.2 (279.1) | 11.3 (305.3) |
Median (range) | 3 (1–450) | 2 (0–300) | 2 (0–450) |
IQR | 1–6 | 2–5 | 1–6 |
Number of seizures in the previous 3 months (categorical), n (%) | |||
<2 | 122 (27.5) | 105 (23.9) | 227 (25.7) |
2–6 | 216 (48.8) | 238 (54.1) | 454 (51.4) |
7–50 | 80 (18.1) | 80 (18.2) | 160 (18.1) |
>50 | 25 (5.6) | 17 (3.9) | 42 (4.8) |
3.2 Pharmacokinetic Modeling
3.3 Dropout Modeling
Parameter | Description | Estimate | 90% CIa
|
---|---|---|---|
BP1 (day) | Breakpoint 1 | 20 | 18.2–20.9 |
BP2 (day) | Δ(BP2–BP1) | 9.76 | 5.29–11.5 |
BP3 (day) | Δ(BP3–BP2) | 105 | 95.7–140 |
BP4 (day) | Δ(BP4–BP3) | 340 | 251–357 |
λ1 (1/day)b
| Hazard from t = 0 to BP1 | 0.00205 | 0.0014–0.00267 |
λ2 (1/day)b
| Hazard from BP1 to BP2 | 0.00358 | 0.00254–0.00601 |
λ3 (1/day)b
| Hazard from BP2 to BP3 | 0.000946 | 0.000759–0.00123 |
λ4 (1/day)b
| Hazard from BP3 to BP4 | 0.000613 | 0.000456–0.00074 |
λ5 (1/day)b
| Hazard from BP4 to end | 0.00221 | 0.00134–0.00358 |
Coeff_SEX | Effect of sex = female on hazard | 0.238 | 0.0346–0.437 |
HR_SEXb
| Hazard ratio female vs. male | 1.27 | 1.04–1.55 |
Coeff_TYPE | Effect of LCM on hazard | −0.138 | −0.333–0.0399 |
HR_TYPEb
| Hazard ratio LCM vs. CBZ-CR | 0.871 | 0.717–1.04 |
3.4 Seizure Modeling
Parameter | Description | Estimate | 90% CIa
| |
---|---|---|---|---|
λ1 (1/day)b
|
λ for the time to 1st event | 0.000733 | 0.000534 | 0.000957 |
p1 | Weibull shape parameter 1st event | 0.493 | 0.464 | 0.531 |
λ2 (1/day)b
|
λ for the 2nd + event | 0.00889 | 0.00606 | 0.013 |
p2 | Weibull shape parameter 2nd + event | 0.713 | 0.675 | 0.75 |
NSP3M (<2) ~ λ1 | Effect of NSP3M <2 on ln(λ1) | −1.12 | −1.65 | −0.648 |
NSP3M (7–50) ~ λ1 | Effect of NSP3M 7–50 on ln(λ1) | 1.94 | 1.43 | 2.43 |
NSP3M (>50) ~ λ1 | Effect of NSP3M >50 on ln(λ1) | 3.3 | 2.08 | 5.07 |
NSP3M (<2) ~ λ2 | Effect of NSP3M <2 on ln(λ2) | −1.37 | −2.06 | −0.659 |
NSP3M (7–50) ~ λ2 | Effect of NSP3M 7–50 on ln(λ2) | 1.36 | 0.898 | 1.82 |
NSP3M (>50) ~ λ2 | Effect of NSP3M >50 on ln(λ2) | 2.53 | 1.98 | 3.1 |
AUC_LCM ~ λ1c
| Slope of AUC-ln(λ1) for LCM 1st event | −0.00917 | −0.0164 | −0.000334 |
AUC_CBZ ~ λ1c
| Slope of AUC-ln(λ1) for CBZ 1st event | −0.00658 | −0.015 | 0.00325 |
AUC_LCM ~ λ2c
| Slope of AUC-ln(λ1) for LCM 2nd + event | −0.00751 | −0.00985 | −0.006 |
AUC_CBZ ~ λ2c
| Slope of AUC-ln(λ1) for CBZ 2nd + event | −0.0153 | −0.0183 | −0.0122 |
AGE ~ λ1d
| Slope of AGE-ln(λ1) for LCM only | −0.0256 | −0.0449 | −0.0112 |
IIV ln(λ2) (SD) | Inter-individual variability ln(λ2) | 2.03 | 1.85 | 2.2 |
Covariate | Hazard ratioa
| 90% CIb
| |
---|---|---|---|
1st seizure | |||
NSP3M ≤1 vs. 2–6 | 0.58 | 0.44 | 0.73 |
NSP3M 7–50 vs. 2–6 | 2.60 | 2.02 | 3.31 |
NSP3M >50 vs. 2–6 | 5.09 | 2.79 | 12.20 |
AGE 65 vs. 41 | 0.74 | 0.59 | 0.88 |
AUCc LCM 300 vs. 100 | 0.40 | 0.20 | 0.97 |
AUC CBZ 130 vs. 210 | 0.77 | 0.55 | 1.14 |
2nd + seizures | |||
NSP3M ≤1 vs. 2–6 | 0.38 | 0.23 | 0.62 |
NSP3M 7–50 vs. 2–6 | 2.63 | 1.90 | 3.67 |
NSP3M >50 vs. 2–6 | 6.09 | 4.12 | 9.10 |
AUC LCM 300 vs. 100 | 0.34 | 0.25 | 0.42 |
AUC CBZ 130 vs. 210 | 0.42 | 0.35 | 0.50 |
3.5 Simulations
Subset | Dosing scenarioa
| Percentage seizure free (90% CI)b
| ||
---|---|---|---|---|
Dose step 1 | Dose step 2 | Dose step 3 | ||
All patients | (A) As in SP0993 | 54.4 (49.4–59.1) | 63.7 (59.4–68.4) | 68.4 (64.1–73.4) |
(B) NSP3M-based | 56.7 (51.7–61.4) | 66.1 (61.6–70.9) | 70.2 (65.7–74.7) | |
Subset with NSP3M ≥7 | (A) As in SP0993 | 30.5 (21.9–39.0) | 41 (31.4–49.5) | 49.5 (40.0–59.0) |
(B) NSP3M-based | 40 (28.6–52.4) | 52.4 (41.0–61.9) | 57.1 (46.7–65.7) |