Effect of Elagolix Exposure on Clinical Efficacy End Points in Phase III Trials in Women With Endometriosis-Associated Pain: An Application of Markov Model

Insa Winzenborg, Akshanth R Polepally, Ahmed Nader, Nael M Mostafa, Peter Noertersheuser, Juki Ng, Insa Winzenborg, Akshanth R Polepally, Ahmed Nader, Nael M Mostafa, Peter Noertersheuser, Juki Ng

Abstract

Elagolix is an oral gonadotropin-releasing hormone antagonist approved by the US Food and Drug Administration (FDA) for the management of moderate-to-severe pain associated with endometriosis and in combination with estradiol/norethindrone acetate approved for the management of heavy menstrual bleeding associated with uterine leiomyomas (fibroids) in premenopausal women. The objective of this work was to characterize the relationships between elagolix exposures and clinical efficacy response rates for dysmenorrhea (DYS) and nonmenstrual pelvic pain (NMPP) in premenopausal women enrolled in the pivotal phase III studies with moderate-to-severe pain associated with endometriosis. Relationships between elagolix average concentrations (Cavg ) and efficacy responses (DYS and NMPP) were characterized using a nonlinear mixed-effects discrete-time first order Markov modeling approach. Only age was statistically significant for NMPP but not considered clinically relevant. This work indicates that the selection of elagolix dose is not determined based on tested patient demographics, baseline, or endometriosis disease severity measures in covariate analysis. In other words, the work suggests no preference of one regimen over the other to treat endometriosis-associated pain (DYS or NMPP) for any patient subpopulation based on tested covariate groups.

Trial registration: ClinicalTrials.gov NCT01620528 NCT01931670 NCT01760954 NCT02143713.

Conflict of interest statement

I.W., A.R.P., A.N., N.M.M., P.N., and J.N. are employees and shareholders of AbbVie.

© 2020 AbbVie. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.

Figures

Figure 1
Figure 1
Schematic of the Markov Chain model. DYS, dysmenorrhea; IIV, interindividual variability; NMPP, non‐menstrual pelvic pain; NR, nonresponder state; Pij, i to j transition probability where i can take 0 or 1 and j can take 0, 1, 2, or 3 (P01, P10, P02, P12, P03, and P13) for DYS and NMPP as designated by letters “D” and “N”; R, responder state.
Figure 2
Figure 2
Effect of age (in years) on NMPP response rate at month 3. NMPP, nonmenstrual pelvic pain.
Figure 3
Figure 3
Exposure‐efficacy analyses visual predictive checks for DYS and NMPP. DYS, dysmenorrhea; NMPP, non‐menstrual pelvic pain. Visual predictive checks were created with 250 replicates each. Symbols with 90% confidence intervals represent observed data. Solid lines and shaded regions represent the median of the simulated data and 90% confidence intervals.
Figure 4
Figure 4
Observed vs. model‐predicted response rates at month 3 and month 6 for elagolix concentration quintiles and placebo. Response rates of DYS at monthe 3 and 6 (top panel) and NMPP at month 3 and 6 (bottom panel). Cavg, monthly averages of daily average plasma concentration; DYS, dysmenorrhea; NMPP, non‐menstrual pelvic pain.
Figure 5
Figure 5
Observed and model‐predicted percentages of patients remaining in the pivotal phase III studies over time. CI, confidence interval.

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Source: PubMed

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