Clinical Trials - why the patient's voice matters

The sheer importance of detail in clinical trials cannot be underestimated.

However, all too often, conversations surrounding them fixate on numbers.

From total enrolment to discontinuations, withdrawals, sample size, demographic representation and on-to margins and the all-important p-value, statistics are a vital element of every clinical trial.

But the story should never end there.

At the core of every clinical trial, there is a very real need to ensure the impact of the treatment on patients’ signs/symptoms, functioning and overall health-related quality of life is thoroughly assessed.

By focusing on statistical information with little or no attention given to clinical significance, there is an enormous risk of leaving your clinical development program vulnerable.

This is especially relevant when dealing with therapeutic areas such as oncology and rare disease, where patient-reported outcomes are of huge importance to regulators and panel experts.

Understanding the difference

To fully understand the importance of clinical and statistical significance, it is perhaps best to note the difference between the two.

Statistical significance refers to the probability that a study's results are due to chance, while clinical significance/meaningfulness refers to the magnitude of the actual treatment effect, i.e., whether it has a genuine, palpable effect on patients' lives and functions.

Clinical meaningfulness is impacted by a range of factors. This can include the type of treatment, the severity of the condition, and the individual circumstances of each patient.

Meanwhile, statistical significance is subject to the individual understanding of the data, identification of patterns and trends, and the drawing of conclusions.

One very common scenario is where a pivotal trial’s primary outcome measures may achieve the beloved set p-value.

However, the effect of the treatment is so small that it is not clinically meaningful.

In this situation, an advisory committee (AdComm) or oral explanation (OE) utilizing the experiences and insights of those active in clinical trials may prevail as part of the debate on its route to approval.

Indeed, you would be hard-pressed to examine the transcripts of any AdComm and not encounter contentious dialogue between the sponsor and the panel concerning the clinical benefit (meaningfulness) of the drug on statistics alone.

On the other hand, there are also instances where a trial may not prove to be statistically significant, but the treatment effect may be large enough to be clinically meaningful.

However, the best-case scenario is where the trial is both statistically and clinically significant. Here, the patient-reported outcome health-related questionnaire is weighed higher up in the hierarchy and viewed as either a key secondary endpoint or coprimary.

Challenges faced

Evaluating clinical meaningfulness and interpreting data are not without their challenges.

The most common examples include:

• Defining clinical meaningfulness is subjective and varies from person to person.
• As it involves understanding the statistical significance of the results, as well as the clinical relevance of the findings, data interpretation is complex.
• Clinical trial results are affected by a variety of factors that include the study design, the patient population, and the length of follow-up. For example, a clinical trial that is conducted for a short period may not be able to detect the long-term benefits of a treatment.
• There can often be a disconnect between the results of clinical trials and the real-world experience of patients. Different measures may be appropriate for different diseases or conditions. For example, a measure of pain relief may be more appropriate for a patient with arthritis, while a measure of overall survival may be more appropriate for a patient with cancer.

Incorporating the patients’ voice

The realization of the importance of the patient’s voice is a growing trend and many sophisticated regulatory bodies are now developing patient-focused drug development guidelines.

These are designed to inform the inclusion of patient experience when developing new medical therapies and products.

In America, the Food and Drug Administration (FDA) is leading the way, dedicating significant resources and progressing current thinking in guidance documents by the 21st Century Cures Act and The Food and Drug Administration Reauthorization Act of 2017 Title I.

The objective here is to get the sponsor actively thinking about what it all means to the patient by incorporating patient experience into the benefit-risk assessment to inform regulatory decision-making.

Whether it is through clinical outcome assessments (COA), which either measure and describe or reflect how a patient feels, functions, or survives, or the use of biomarkers and surrogate endpoints (both requiring robust validation measures), the goal is to include patient-centric measurement to tell the data narrative which corresponds to the pure mathematics of statistical analysis.

COAs are composed of multiple elements and include patient-reported outcome (PRO) measures, clinician-reported outcome (ClinRO) measures, observer-reported outcome (ObsRO) measures, and performance outcome (PerfO) measures.

By including fit-for-purpose measures in clinical trials, sponsors can generate critical evidence for regulators to evaluate the efficacy and safety of their product. And after approval, this data can also inform cost-effectiveness analyses for payer decision-making.

The latter point is crucial when it comes to Health Technology Assessment (HTA), given that the healthcare system in Europe, unlike in the United States, influences regulatory decision-making.

Not without its challenges, often sponsors will endeavor the approach of clinical benefit in terms of meaningfulness through biomarkers and surrogate endpoints where the major hurdle is the issue of specificity.

Health authorities require all biomarkers and surrogate markers used in clinical trials to be specific to the disease or condition that they are being used to measure.

This can be time intensive and includes the need to present a convincing argument to the regulators for acceptance. Sometimes a public hearing will be convened on this topic alone for a given therapeutic target.

However, despite the challenges, biomarkers and surrogate markers are valuable tools for the development and approval of new drugs and biologics.

Conclusion

Harnessing the patient experience and channeling the voice of the patient is worth the effort.

When interpreting research results, it is important to consider both statistical and clinical significance.

While achieving statistical significance will always remain at the core of clinical trial outcomes, it is essential to develop clear and consistent definitions of clinical meaningfulness by including patient-centric clinical information using COAs, biomarkers, and surrogate endpoints in the study design.

It is also paramount to consider the patient's perspective when interpreting the results of clinical trials and conducting clinical trials that are relevant to the real-world experience of patients.

As discussed above, with its unique challenges, COAs are an important tool for assessing the impact of treatment on a patient's quality of life.

However, when used in conjunction with other measures of efficacy (biomarkers and surrogates) as clinical endpoints, this information can provide a more comprehensive picture of the benefits and risks of each treatment.

This will help to ensure that the results are interpreted in a way that is accurate and meaningful.

Kavya Sunkavalli is Senior Manager of Regulatory Affairs at G&L Healthcare Advisors.