In each issue of the Journal of Dermatology for Nurse Practitioners & Physician Assistants (JDNPPA), Founders and Co-Editors-In Chief Douglas DiRuggiero, DMSc, MHS, PA-C, and Margaret Bobonich, DNP, FNP-C, DCNP, FAANP, will answer some of the pressing questions they have received from colleagues.
Comparing Apples to Oranges
Dear Margaret,
My dermatology office is hiring an advanced practice provider and asked which profession is “better.” What’s the difference between nurse practitioners (NPs) and physician assistants (PAs)?
A: This is such an important question—one that goes beyond simply comparing NPs and PAs. Many colleagues and patients struggle to understand the differences in their educational preparation and clinical practice. In short, the NP and PA professions are grounded in distinct philosophical models—nursing and medicine, respectively. There are differences in education, certification, licensure, and regulatory oversight, including whether and to what extent physician supervision is required.
Although dermatology NPs and PAs differ in education background and licensure, their clinical roles and responsibilities are often quite similar. The exam blueprints of the Dermatology Certified Nurse Practitioner (DCNP) exam for NPs and the Certificate of Added Qualifications in Dermatology (CAQ-Derm) for PAs are nearly identical. While certification is not mandatory for either profession, these blueprints provide an objective measure of the advanced knowledge and competencies required for each profession.
Trying to determine which profession is “better” is comparing apples to oranges.
The more important consideration is evaluating the individual’s professional qualifications, licensure, and fit for the specific roles and responsibilities within your practice. Regardless of whether you hire an NP, PA, MD, or DO, the key expectation is that all providers should be capable of delivering high-quality dermatologic care.
The ideal clinical environment fosters interprofessional collaboration, where professionals from dierent backgrounds work together to provide the highest-quality care. Interprofessional collaboration improves patient outcomes, enhances chronic disease management, reduces medical errors, and increases both patient and provider satisfaction. True “collaboration” is built not only on mutual respect but also on valuing the distinct strengths each profession brings to the table.
Working closely with both physicians and PAs has made me a better dermatology NP. Collaborating with my PA colleagues has enriched my clinical practice and fostered meaningful professional growth, broadening my perspective, enhancing my skills, and deepening my understanding of team-based care.
We are truly better together.
Sincerely,
Margaret Bobonich, DNP, FNP-C, DCNP, FAANP
How is Non-Responder Imputation Utilized in Clinical Trials?
Dear Douglas,
Can you explain non-responder imputation (NRI) vs. modified (MNRI)?
A: Mark Twain once famously said, “There are three kinds of lies: lies, damned lies, and statistics.” The implication is, of course, that statistics, or the analysis of numbers or data, can be manipulated to say whatever one wants them to say. With clinical trial data, accurate and truthful interruption of outcomes determines if a drug or procedure is safe and beneficial. Drug approval agencies, such as the U.S. Food and Drug Administration (FDA) or the European Medicines Agency (EMA), expect and ensure that clinical trial data undergoes validated, rigorous, and established statistical methodologies.
Both the NRI and the mNRI refer to missing ecacy data. In a perfect drug-trial world, if 100 patients are enrolled in a trial, every patient makes every trial-center appointment and ultimately completes the trial with no missed follow-up visits and no dropouts, but this simply does not happen! Trial participants can and do miss appointments for a wide variety of reasons: car troubles, illness or hospitalization, childcare issues, work or home commitments, and the list goes on. Sometimes, participants decide to opt out of the trial
Trial discontinuation can be for legitimate concerns such as disease worsening or adverse drug events, but issues not related to efficacy or safety (job transfers, loss of reliable transportation, or life status changes) can also contribute to a trial’s dropout rate.
NRI data will treat every missed visit and every participant dropout as a failure. Therefore, these two scenarios are both considered treatment failures: (1) a trial participant exits three months into the study because, despite drug and protocol compliance, their skin disease has significantly worsened and they disenroll; (2) a trial participant’s (in the same trial) skin clears 100%, but they quit the trial because a job transfer necessitates a long-distance move. NRI is unforgiving…every dropout is considered a drug failure, even if the drug was working. This creates a statistical benchmark that can underestimate the success of a trial outcome.
An mNRI attempts to level-set the ecacy results in a number of different ways—which is why it’s important to ask, “How did you modify the NRI data?” In general, an mNRI will view treatment failures as only those whose disease worsened and necessitated withdrawal or those who discontinue due to a drug-related adverse event. A solitary missed appointment in a long line of successful appointments doesn’t have to be treated as “no disease response,” but rather, the prior and subsequent follow-up appointments can be used as predictors of treatment response, and a value can be assumed or substituted. Therefore, missed appointments and trial discontinuations for non-drug-related circumstances are not reflected in many statistical analyses. This should provide a more accurate mathematical analysis but may also overestimate the number of positive responders.
I don’t think clinical drug trials were being conducted in Mark Twain’s day, but if they were, I hope he would see that data can be trusted, but only after the numbers have been held under a microscope.
I hope that clears things up for you!
Douglas DiRuggiero, DMSc, MHS, PA-C
FOR FURTHER READING
Langley RGB, Reich K, Papavassilis C, Fox T, Gong Y, Gu Ttner A. Methods for imputing missing efficacy data in clinical trials of biologic psoriasis therapies: Implications for interpretations of trial results. J Drugs Dermatol. 2017;16(8):734–741. https://pubmed.ncbi.nlm.nih.gov/28809988/
