Structured Clinical Trial Information Vital in Multiple Sclerosis Drug Development

Although randomized controlled trials (RCTs) are considered the standard for testing the safety and efficacy of investigational drugs for multiple sclerosis, their timelines, enrollment criteria, and atypical comparators limit the relevance to standard clinical practice.

In a new study published in BMC Medicine, researchers described how real-world data (RWD) complements the evidence base from RCTs in multiple sclerosis (MS), and explains the importance of structural data analysis in order to avoid biases. It is generally believed that RTCs and real-world evidence (RWE) are important for gaining a better understanding of treatment effects and disease outcomes, and are increasingly viewed as complementary by clinicians.

There has been a growing emphasis on gaining information on MS beyond phase 3 RCTs. In 2014, published RWE studies in MS exceeded that of published phase 2 and 3 studies by more than 2-fold. This growth is driven by the growing demand from health decision-makers and payers for post-approval evidence to inform reviews of reimbursement, pricing, formulation and indication changes, and licenses for new therapies, according to the study.

Post-approval RWE studies are important because they provide information on compliance with current treatment guidelines, define treatment responder subgroups, identify suboptimal therapies, optimize treatment sequencing, define treatment responder subgroups, and monitor for rare and serious adverse events. Furthermore, they can provide valuable insights before product development.

Pre-launch RWE studies can be useful in mapping out the natural and drug-modified disease history, current practice patterns, and service structures. This is useful in MS to gain information on the disease characteristics, treatment behaviors, and health care availability for real patients with MS.

When closer to product launch, RWE can provide additional insights into early clinical experience, patient tolerability, safety, identification of untreated patients, and resource use, the researchers wrote. Since MS is a lifelong disease and RCTs have a short duration, it limits researchers from studying long-term treatment effects and disease course.

However, common endpoints in phase 2 and 3 MS studies, such as inflammatory lesions and relapse rates, are considered important surrogate markers for predicting the anticipated long-term prevention of disability, and they can only be validated through RWE methodologies, according to the study. When collecting high-quality datasets in clinical practice, it requires agreement on a common minimum dataset, and the use of special documentation software to collect disease-specific and demographic information.

The standards are important to the practice to help offset the perception that the quality of RWD is inferior compared with data gathered in RCTs, the study noted. Typically, electronic medical record-based data collection is event-based, with visits and other data recorded as they occur.

RCTs use a schedule design, where the timing and data collection are explicitly specified at each visit. To reduce the bias introduced by non-randomized study designs in RWD, regression and stratification analytical techniques can be used.

By adjusting the association between treatment and outcome to account for other variables that may affect the outcome, regression can improve the accuracy of an estimated treatment effect on a certain outcome measure. In MS, the variables include baseline Expanded Disability Status Scale (EDSS) scores, disease duration, and prior relapse rate.

When patient cohorts are divided into subgroups with similar variables, stratification can enable a comparison of outcomes among patients with similar characteristics. There are also numerous circumstances where propensity scoring has been effective at reducing bias, and it is increasingly being used in longitudinal MS observational studies, the researchers wrote.

Propensity scores can aid stratification or regression through posterior result adjustment. So far, RWE has contributed to gaining a better understanding of MS disease course and risk factors.

These studies also report a decreased life expectancy in MS patients compared with the general population, and have shown how factors, such as increased age at disease onset and the primary progressive subtype of MS, are associated with faster disability progression. Furthermore, RWE studies have helped to guide patient management and treatment decisions in MS through answering questions related to treatment effects in clinical practices, something RCTS cannot address.

By supplementing RCT data and providing information on long-term efficacy and tolerability of treatments in a real-world setting across generalizable populations, RWE provides a valuable contribution to the evidence base for MS therapies, according to the study. Furthermore, RWE gives longitudinal outcome information that can be directly used for pharmacoeconomic evaluation of treatment patterns and sequencing outcomes.

Study designs that include analytical methods, appropriate data collection, and unified minimum dataset are imperative for creating evidence that can be reasonably used to influence treatment guidelines and decisions, as well as to satisfy the need of stakeholders to monitor disease-modifying therapy (DMT) performance post-approval, according to the study.

To further expand RWE generation in MS, information on additional outcome measures can be collected, such as MRI and cognition, to examine their importance in guiding treatment. Lastly, expanding the data pool through collaborations helps improve the utility and validity of RWE to physicians and regulatory bodies and will help improve physician and patient engagement, the study concluded.