When the strength of a clinical endpoint lies in its design, challenges arise when measures are chosen simply because they are the best available options. As much of a trial’s success depends on the ability of outcome measures to assess features most significant to the disease, experts say clinical studies for the rare disorder Rett syndrome need better measures to objectively confirm symptom improvement.

Rett syndrome is a rare X-linked dominant disorder caused by a mutation in the MECP2 gene on the X chromosome. The condition, which is almost exclusively found in females, goes unnoticed for the first 6–18 months of life, and then slowly affects brain development, resulting in severe physical and mental impairments.

In recent times, there have been clinical advances in the Rett syndrome therapeutics space. In March 2023, Acadia Pharmaceuticals’Daybue (trofinetide) became the first and only US FDA-approved treatment for Rett syndrome. However, in January 2024, another late-stage drug, Anavex Life Sciences’ ANAVEX2-73 (blarcamesine), failed in a pivotal Phase III study, tanking the company’s stock by more than 36%. 

With an endgame to develop better therapeutic options and hopefully, a curative therapeutic option, the field needs a more holistic approach, consisting of behavioural and biomarker assessments, to evaluate Rett syndrome patients, says Dr. Drew Jones, vice president of clinical development at the International Rett Syndrome Foundation (IRSF). With several promising new therapies in development, it is crucial to develop outcome measures that adequately address this rare disease.

Fit-for-purpose endpoints

The limitation with existing outcome measures is that they lack specificity when it comes to gross motor and fine motor (hand function) impairments as well as autonomic functions, which are core diagnostic criteria of Rett syndrome, says Dr. Helen Leonard, associate professor at The University of Western Australia.

While Daybue improved motor function, communication, behaviour, and other symptoms characteristic of Rett syndrome, the effect size and improvements seen across the coprimary RSBQ and Clinical Global Impression-Improvement scale (CGI-I) endpoints as well as key secondary endpoint Communication and Symbolic Behaviour Scales (CSBS) were “rather modest,” says Dr. Walter Kaufmann, adjunct professor in the Department of Human Genetics at Emory University School of Medicine in Atlanta, Georgia.

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RSBQ is a 45-item, caregiver-focused checklist designed to delineate the behavioural phenotype and manifestations of Rett syndrome. CGI-I is a seven-point scoring scale that requires a clinician to assess severity across multiple clinical manifestations.

CGI-I and RSBQ were the coprimary endpoints in both Acadia’s Phase III LAVENDER study (NCT04181723) of Daybue and Anavex’s Phase III EXCELLENCE study (NCT04304482) of ANAVEX2-73. It is generally acknowledged that RSBQ was developed to measure behaviour in Rett syndrome, and not necessarily clinical severity, which is often what clinical trials measure, says Leonard. The scores also do not necessarily reflect the severity of the behaviour, she adds.

Motor function and communication problems are visibly apparent when a patient with Rett syndrome comes into the clinic, explains Kaufmann. However, the RSBQ scale does not have a specific item for communication, and items for motor function are “very limited” in the sense that they are geared towards assessing the behavioural impact on a motor function, he elaborates. This is completely different from what is seen as an impairment in gait or hand use, Kaufmann adds.

The field could move towards employing video motor assessments such as the Rett Syndrome Hand Function Scale (RSHFS) and the Rett Syndrome Gross Motor Scale (RSGMS), explains Leonard. These assessments, conducted in-house or at home, would allow a uniform rater to evaluate videos of patients and put forth a more objective evaluation, she elaborates. RSHFS and RSGMS have been developed by researchers at the Telethon Kids Institute at the University of Western Australia in Perth, Australia.

Neither RSBQ nor CGI-I alone is a sufficient measure, but synergistically, because all three measures trended towards improvement, there was enough theoretical power to indicate a significant result with Daybue, Kaufmann explains. In the Phase III Acadia study that backed Daybue’s approval, change from baseline to Week 12 in RSBQ total score was a decline of 5.1 with the drug versus a decline of 1.7 for placebo, as per a December 2021 press release. At Week 12, the CGI-I score was 3.5 in the treatment group compared to 3.8 in the placebo group. “The reality is that if you want to capture many symptoms in a global impression, you must ensure that one of them [symptoms] does not take over because then it is not a global impression but the result of one major improvement,” says Kaufmann.

Balancing data collection

The industry needs to expand its evaluation from behaviour and evaluate other endpoints such as biomarkers and/or mobility, says Jones. Additionally, there needs to be consideration for validated wearable devices that can track improvements in movement, breathing, and sleep, Jones explains.

The questionnaires are not effective at directly and objectively measuring symptoms in Rett syndrome patients, says Jana von Hehn, CSO and head of clinical development at the Rett Syndrome Research Trust (RSRT). The purpose of the biosensors is to shift the paradigm of how symptom data is measured, von Hehn adds.

RSRT is currently evaluating its biosensors in the VIBRANT (Validating Innovative Biosensors in Rett for AutoNomic Symptom Tracking) study (NCT06338267). The study is testing devices that assess symptoms such as sleep, breathing, heart rate, movement, and oxygen saturation. The wearable FDA-cleared biosensors being evaluated include RespiraSense, Vivalink (VV330) ECG patch, and the Kids O2 pulse oximeter ring, along with the non-FDA-cleared Emerald sensor. Existing validity data for the FDA-cleared devices will likely increase sponsor use of these devices in clinical studies, says von Hehn.

The field needs tools that focus on motor and autonomic (breathing) changes relevant to the disease, and this could be in the form of structural magnetic resonance imaging (MRI) scans that enable researchers to explore brain atrophy, or functional MRIs that evaluate changes in brain activity patterns, says Jones. Additionally, biochemical markers like brain-derived neurotrophic factor (BDNF) could assess key protein levels, and other electrophysical biomarkers such as electroencephalogram (EEG) patterns could be evaluated in these patients, Jones elaborates.

In the case of biosensor-collected biomarker data, the challenge is the volume of data collected, says Kaufmann. There are many logistical challenges to implementing these biosensors, specifically, in how the continuously collected data will be processed, stored, and shared, Kaufmann explains. Additionally, biosensors are also difficult to manage, especially when the patients being evaluated have many stereotypies or movement disorders that cause them to constantly wring or pat their hands, says Dr. Alan Percy, director of the Rett Syndrome Clinic at Children’s of Alabama in Birmingham, Alabama. It is challenging to differentiate between a stereotypy and functional motor use, and how that challenge will be addressed in a sensor is unknown, explains Percy.

Some biomarkers also lack the emphasis on function and quality of life (QOL) data, which is important and meaningful to collect to characterize treatment impact, says Kaufmann. The use of biomarkers and devices in Rett syndrome is fairly new, and as a result, there will be a significant learning curve to implementing EEG devices, reading devices, sleep devices, and neuroimaging, says Jones. Additionally, when establishing an effective benchmark to demonstrate improvement from treatment, the patient must wear the device for an extended period of time prior to treatment. Compliance with this will be a challenge, especially among patients with Rett syndrome, Jones explains.

The field must conduct more observational and non-clinical studies to validate how these biosensor or biomarker measures perform. Since biomarkers cannot capture function and QOL, the field will need to incorporate a QOL measure into the clinical and sensor data points.