The US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are leading benchmarks for reliance approval pathways, while many regulatory authorities streamline their review processes by referencing these authorities’ evaluations and decisions. Major postmarketing (MPM) modifications, reflecting benefit–risk updates, are often added to approved labels. This study aimed to identify variables associated with significant MPM safety modifications by FDA and EMA to understand their potential impact on regulatory decision-making in the reliance process.

Retrospective cohort study of new drug applications and supplemental indications approved by the Israeli Ministry of Health (MOH) between 2014 and 2019. The primary outcome was time to first MPM safety modification by the FDA/EMA. Associated factors, including clinical and regulatory variables, were examined using both univariate and multivariable Cox regression analyses.

Applications with FDA and/or EMA approval at the time of assessment in Israel were included.

467 applications met the inclusion criteria. Oncology therapeutics (HR 2.19 (95% CI 1.71 to 2.80)), approval based on early phase clinical trials data—phase 1 (HR 3.14 (95% CI 1.29 to 7.63)) and phase 2 (HR 1.97 (95% CI 1.47 to 2.64)), facilitated approval pathways (HR 1.68 (95% CI 1.31 to 2.17)) and approval based on a surrogate endpoint (HR 1.92 (95% CI 1.31 to 2.46)), were associated with higher rates of MPM modifications. MPM modifications were documented in 53.1% of applications that underwent a single Advisory Committee on Drug Registration (ACDR) review cycle, compared with 68.67% of applications that required multiple review cycles (HR 1.6, (95% CI 1.19 to 2.16), p=0.001). In multivariable analysis, oncology indications (HR 1.71 (95% CI 1.31 to 2.25)), facilitated approval pathways (HR 1.46 (95% CI 1.13 to 1.92)) and applications approved following multiple review cycles (HR 1.42 (95% CI 1.14 to 2.58)) were found to be predictive factors correlated with MPM modifications.

By considering these associated factors, regulators can strengthen the reliance pathway assessment process, supporting a balance between streamlined evaluation procedures and maintaining rigorous safety and efficacy standards.

Dementia is a major global health problem with increasing prevalence. Hearing loss has been identified as the most modifiable risk factor for dementia. The Age-Related Cognition and Hearing (ARCH) study is a 3-year prospective, controlled, observational comparative cohort study comparing cochlear implants (Implants) and hearing aids (HAs) for reducing cognitive decline associated with age-related hearing loss (ARHL), based on patient-reported real-world outcomes of auditory function, cognitive performance, listening environment, social interaction and psychosocial well-being. Upon its completion in 2029, the ARCH study is expected to yield significant evidence regarding the comparative effects of two primary hearing interventions—Implants and HAs, to delay and ameliorate cognitive decline associated with ARHL.

210 older adults are divided into six study subgroups (N=35) with: (1) moderate to profound hearing loss or age-typical normal hearing, (2) use of Implants or HAs and (3) mild cognitive impairment (MCI) or normal cognition. Listeners in the HA groups have hearing loss that is consistent with Implant candidacy and qualification through Centers for Medicare & Medicaid Services in the USA. The primary study outcome is a 3-year change in real-time patient-reported outcomes collected while participants are in their natural listening environments using ecological momentary assessment (EMA) methodologies. Secondary outcomes include lab-based audiometric and neuropsychological testing, and patient-reported outcomes of social isolation, loneliness, depression, anxiety and quality of life.

Cross-sectional analyses will use factor analysis to reduce EMA items into domains, followed by regression and mixed-effects models to test group differences and identify specific EMA items driving those effects. Machine-learning approaches will complement these models by predicting outcomes, identifying key variables and uncovering data-driven patterns. Longitudinal mixed-effects models will assess how EMA factor scores and cognition change over time and whether real-world EMA experiences mediate cognitive trajectories. Additional analyses will compare real-time EMA responses with retrospective patient-reported outcome measures and laboratory-based cognitive and auditory assessments, with sample size adjusted for up to 10% attrition.

All study procedures follow institutional review board requirements and the Declaration of Helsinki at the University of Iowa (IRB# 202403385), with informed consent processes tailored to ensure understanding among participants with MCI. Study findings will be disseminated through a multi-tiered strategy aimed at maximising scientific, clinical and public health impact. Peer-reviewed manuscripts will be submitted to leading journals in audiology, geriatrics, cognitive ageing and public health, with interim and final results presented at national and international conferences and professional society meetings.