TY - JOUR
T1 - A 2-stage model of heterogenous treatment effects for brain atrophy in multiple sclerosis utilizing the MS PATHS research network
AU - Hersh, Carrie M.
AU - Sun, Zhaonan
AU - Conway, Devon S.
AU - Sotirchos, Elias S.
AU - Fitzgerald, Kathryn C.
AU - Hua, Le H.
AU - Ziemssen, Tjalf
AU - Naismith, Robert T.
AU - Pellegrini, Fabio
AU - Grossman, Cynthia
AU - Campbell, Nolan
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/11
Y1 - 2024/11
N2 - Background: Two-stage models of heterogenous treatment effects (HTE) may advance personalized medicine in multiple sclerosis (MS). Brain atrophy is a relatively objective outcome measure that has strong relationships to MS prognosis and treatment effects and is enabled by standardized MRI. Objectives: To predict brain atrophy outcomes for patients initiating disease-modifying therapies (DMT) with different efficacies, considering the patients’ baseline brain atrophy risk measured via brain parenchymal fraction (BPF). Methods: Analyses included patients enrolled in the Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) network who started DMT and had complete baseline data and ≥ 6-month brain MRI follow-up. All brain MRIs were acquired using standardized acquisition sequences on Siemens 3T scanners. BPF change risk was derived by linear mixed effects models using baseline covariates. Model performance was assessed by predicted versus actual BPF change R2. Propensity score (PS) weighting was used to balance covariates between groups defined by DMT efficacy (high: natalizumab, alemtuzumab, ocrelizumab, and rituximab; moderate: dimethyl fumarate, fingolimod, and cladribine; low: teriflunomide, interferons, and glatiramer acetate). HTE models predicting 1 year change in BPF were built using a weighted linear mixed effects model with low-efficacy DMT as the reference. Results: Analyses included 581 high-, 183 moderate-, and 106 low-efficacy DMT-treated patients. The mean and median number of brain MRI observations per treatment period were 2.9 and 3.0, respectively. Risk model performance R2=0.55. After PS weighting, covariate standardized mean differences were <10 %, indicating excellent balance across measured variables. Changes in BPF between baseline and follow-up were found to be statistically significant (p < 0.001), suggesting a pathological change. Patients with low brain atrophy risk had a similar outcome regardless of DMT selection. In patients with high brain atrophy risk, high- and moderate-efficacy DMTs performed similarly, while a 2-fold worse BPF change was predicted for patients selecting low-efficacy DMTs (p < 0.001). Similar results were observed in a sensitivity analysis adjusting for pseudoatrophy effects in a sub-population of patients treated with natalizumab. Conclusions: The relative benefit of selecting higher efficacy treatments may vary depending on patients’ baseline brain atrophy risk. Poor outcomes are predicted in individuals with high baseline risk who are treated with low-efficacy DMTs.
AB - Background: Two-stage models of heterogenous treatment effects (HTE) may advance personalized medicine in multiple sclerosis (MS). Brain atrophy is a relatively objective outcome measure that has strong relationships to MS prognosis and treatment effects and is enabled by standardized MRI. Objectives: To predict brain atrophy outcomes for patients initiating disease-modifying therapies (DMT) with different efficacies, considering the patients’ baseline brain atrophy risk measured via brain parenchymal fraction (BPF). Methods: Analyses included patients enrolled in the Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) network who started DMT and had complete baseline data and ≥ 6-month brain MRI follow-up. All brain MRIs were acquired using standardized acquisition sequences on Siemens 3T scanners. BPF change risk was derived by linear mixed effects models using baseline covariates. Model performance was assessed by predicted versus actual BPF change R2. Propensity score (PS) weighting was used to balance covariates between groups defined by DMT efficacy (high: natalizumab, alemtuzumab, ocrelizumab, and rituximab; moderate: dimethyl fumarate, fingolimod, and cladribine; low: teriflunomide, interferons, and glatiramer acetate). HTE models predicting 1 year change in BPF were built using a weighted linear mixed effects model with low-efficacy DMT as the reference. Results: Analyses included 581 high-, 183 moderate-, and 106 low-efficacy DMT-treated patients. The mean and median number of brain MRI observations per treatment period were 2.9 and 3.0, respectively. Risk model performance R2=0.55. After PS weighting, covariate standardized mean differences were <10 %, indicating excellent balance across measured variables. Changes in BPF between baseline and follow-up were found to be statistically significant (p < 0.001), suggesting a pathological change. Patients with low brain atrophy risk had a similar outcome regardless of DMT selection. In patients with high brain atrophy risk, high- and moderate-efficacy DMTs performed similarly, while a 2-fold worse BPF change was predicted for patients selecting low-efficacy DMTs (p < 0.001). Similar results were observed in a sensitivity analysis adjusting for pseudoatrophy effects in a sub-population of patients treated with natalizumab. Conclusions: The relative benefit of selecting higher efficacy treatments may vary depending on patients’ baseline brain atrophy risk. Poor outcomes are predicted in individuals with high baseline risk who are treated with low-efficacy DMTs.
KW - Brain atrophy
KW - Brain parenchymal fraction
KW - Disease-modifying therapy
KW - Heterogenous treatment effects
KW - Multiple sclerosis
KW - Personalized treatment
KW - Precision-medicine
KW - Real-world data
UR - http://www.scopus.com/inward/record.url?scp=85203408273&partnerID=8YFLogxK
U2 - 10.1016/j.msard.2024.105847
DO - 10.1016/j.msard.2024.105847
M3 - Article
C2 - 39260226
AN - SCOPUS:85203408273
SN - 2211-0348
VL - 91
JO - Multiple Sclerosis and Related Disorders
JF - Multiple Sclerosis and Related Disorders
M1 - 105847
ER -