Long-term safety of gantenerumab in participants with Alzheimer's disease: A phase III, open-label extension study (SCarlet RoAD).

Background: Gantenerumab is a fully human anti-amyloid-β (Aβ) immunoglobulin G1 monoclonal antibody for subcutaneous (SC) administration. The efficacy and safety of low-dose (105 mg or 225 mg) gantenerumab were investigated in SCarlet RoAD (SR; NCT01224106), a Phase III, double-blind (DB), placebo-controlled study in participants with prodromal Alzheimer's disease. Following a pre-planned futility analysis, SR was converted into an open-label extension (OLE) study.

Long-Term Safety of Gantenerumab in Participants with Alzheimer's Disease: A Phase III, Double-Blind, and Open-Label Extension Study (Marguerite RoAD).

Background: Gantenerumab is an anti-amyloid-β immunoglobulin G1 monoclonal antibody for subcutaneous (SC) administration. The efficacy and safety of low-dose (105 mg or 225 mg) gantenerumab were investigated in Marguerite RoAD (MR; NCT02051608), a Phase III, double-blind (DB), placebo-controlled study in participants with mild Alzheimer's disease (AD) dementia. Following a preplanned futility analysis of the SCarlet RoAD study (NCT01224106), MR was converted into an open-label extension (OLE).

Care partner-informed meaningful change thresholds for the Clinical Dementia Rating-Sum of Boxes for trials of early Alzheimer's disease.

Introduction: Consensus definitions of meaningful within-patient change (MWPC) on the Clinical Dementia Rating-Sum of Boxes (CDR-SB) are needed. Existing estimates use clinician-rated anchors in clinically diagnosed Alzheimer's disease (AD) populations. Incorporating the care partner perspective offers important insights, and evaluating biomarker-confirmed cohorts aligns estimates with ongoing trials.

Rejoinder to the letter: "Standard and reference-based conditional mean imputation: Regulators and trial statisticians be aware!".

We appreciate Cro et al.'s efforts to bring wider attention to the debate surrounding variance estimation for reference-based imputation methods. However, we believe that the way this debate is presented as "multiple imputation" versus "conditional mean imputation" can be misleading.