Lack of clinical experience with a newly cleared or approved device or medication is a hurdle to product adoption in any branch of health care. It is no surprise that clinicians who are less familiar with any new product or device will approach it cautiously before adopting it in-office.
Clinicians often wait to see what their peers’ reactions are before adopting a new drug or contact lens. Yet, it is undeniable that the advent of a new technology has the potential to bring an improved treatment option for managing a disease entity, treating an otherwise neglected population, or expanding a patient population.
For clinicians eager to adopt a new medication or device, information from clinical trials can provide a window into how to use the product and how best to select patients to ensure improved outcomes. Clinical trial data provides a guide to the use, effectiveness, and safety of a product.
Clinical Trials 101
The Data In the United States, new ophthalmic drugs must undergo scrutiny by the U.S. Food and Drug Administration (FDA). A fundamental part of that is the clinical trial process. Data from clinical trials determines a product’s labeling and demonstrates both its safety and efficacy.
The approval/clearance process generates an extensive amount of information, and clinical trial data are often shared through publication in peer-reviewed journals before the product reaches the market. A careful review of clinical trial data and a basic understanding of the FDA approval/clearance process provides a guide for eager clinicians in the adoption and use of an innovative product.
Closely evaluating data from the clinical trials of a medication requires familiarity with interpreting the published data. Information from these studies—from patient selection criteria to study results—serves as a guide to clinical adoption and proper use of the new device or medication.
Clinical trial data can help predict patient acceptance and can help with developing in-office patient selection and disease management and care protocols. The data can aid in deciding whether a new pharmacologic agent would be of clinical use to practitioners and would benefit their patient base.
Selection Criteria A good interpretation of clinical trial data is important. One of the first things that should be considered is the overall number of study subjects. The higher the number of enrolled subjects (the “n”), the more reliable the predictive outcomes.
The clinical trial should have a large enough sample size to provide realistic conclusions on the effectiveness and safety of the medication or device being studied, as should the percentage of subjects completing the trial. A high discontinuation rate often signals problems relating to one or more factors; most commonly, these are compliance, study design, adverse events, or safety.
When assessing performance or efficacy in a trial, note the probability value, or P value. The calculated probability value helps to demonstrate that the results of a trial were not reached by chance but rather are statistically significant. It is worthwhile to note differences in P values among studies and groups, as this can help to validate whether there are sufficient data to statistically back up trial outcomes.
Confidence in study design is imperative for FDA approval/clearance. Because of this, an examination of study design is critical. Clinical trials for new medications are randomized to offer greater confidence in the efficacy and safety data generated. When making comparisons with other clinical trials and to better understand and compare a study’s design, it is important to understand selection criteria for study participants, because this defines the population for which the drug would theoretically provide the most benefit.
By matching initial patient selection to the study selection criteria, clinicians will be more likely to have a positive result in line with those of the clinical trial. Patient exclusion and inclusion criteria for enrollment can be a helpful predictive factor for clinical results when first using a device or medication.
It is useful to note whether patients included in a trial were symptomatic or asymptomatic, as this will give practitioners a better guide for initial patient selection criteria and what results they can expect in their patient population.
Outcomes When reading clinical trials, practitioners should also make sure to analyze closely the differences in the main outcome measures for the study. For example, a glaucoma drug will likely produce a reduction in intraocular pressure, but it is also important to understand the outcomes over specific time points.
Critically assessing new technology allows clinicians to pick and choose medications that showcase their innovative spirit and achieve enhanced patient outcomes. Often, new therapies and devices can improve treatment outcomes without negatively affecting costs. It is important to be knowledgeable about the products that practitioners use in their clinical practice. When they decide to adopt a new device or prescribe a new medication, a good understanding of the published literature and studies, including clinical trials, is invaluable.
When reviewed from a clinical perspective, clinical trial data should be a compass guiding practitioners’ adoption of new technologies. Promotional presentations and product mentions during conferences are also helpful for indirectly gathering experience with new products. These opportunities offer ways to interact with clinicians who have had extensive experience with the new medication or device.
Published after product approval/clearance, postmarket (a.k.a. phase 4) studies can also provide a better understanding of the use of the product after its initial FDA approval/clearance. Being able to understand clinical trial data is a crucial first step in judging a new product’s performance, safety, and efficacy.
Clinical trials provide a clinical compass and become useful in understanding new products and how these products will perform in well-defined populations. Astute clinicians still realize that reading clinical trial data is no substitute for clinical experience; day-to-day experience is essential for a comprehensive assessment of how and when new products will be appropriate for their practices and how to use them to best help their patients. CLS