• Web-Based Application for Statin Self-Qualification is ‘Step Forward’ for OTC Approval Chances – CREST Study Lead Author

    A novel web-based application found to be “nearly as accurate” as clinician assessment in identifying appropriate patients for non-prescription statins is an “encouraging step-forward” in the bid to win an over-the-counter (OTC) approval, according to the lead author on AstraZeneca's CREST study.

    The findings – from 500 participants, 83 of whom had limited literacy – come amid a flurry of regulatory rejections for non-prescription statins.

    They were reported Monday online ahead of the Sept. 14 issue of the Journal of the American College of Cardiology.

    Efforts to win OTC approval for statins have ramped-up in response to the problem of undertreatment. Despite the "pivotal role" of the drug class in public health efforts to improve cardiovascular outcomes by lowering low-density lipoprotein cholesterol (LDL-C), studies show that only around one half of eligible patients are actually treated, the authors – led by Steven E. Nissen, MD, from the Cleveland Clinic – noted.  

    “Barriers to effective treatment are complex but include reluctance of patients to seek regular medical care and lack of access to health care resources in some communities,” the authors wrote.

    Five prior attempts at regulatory approval for OTC statins have failed, the researchers pointed out, highlighting in particular the inability to ensure that only appropriate patients would have access to the drugs has been an issue in regulatory rejections.

    The current study, therefore, set out to test a technology-assisted self-selection approach via a web-based tool developed under Software as a Medical Device regulation, and whether it could qualify patients appropriate – or not – for treatment with AstraZeneca's rosuvastatin 5 mg daily.

    The application was programmed to replicate current guidance on treatment with a moderate-intensity statin, as well as with warnings and precautions for rosuvastatin specifically. CREST pitted participant-determined treatment eligibility based on the technology against clinician assessments.

    Participants of any sex, over the age of 20 years, were recruited via digital advertising routes such as paid searches, social media or display advertising, traditional media such as radio, television, print, community outreach and supplemental methods, including flyers.

    They had to be able to read, speak and understand English, although at least 80 of the planned 500 were required to have limited literacy as defined by the Rapid Estimate of Adult Literacy in Medicine (REALM) test. Those with strong links to the healthcare sector – where either the participant or a member of their household was a healthcare practitioner, employed by a healthcare practice, a manufacturer of medicines, a consumer health company or similar – were excluded from the trial.

    The participating 500 were 62.2% female, had a mean age of 59.5 ± 12.7 years – with the majority (39.8%) over 65 years – were mostly white (61%), and a plurality had graduated college or technical school (44.8%).

    Patients attended a research site to perform the web assessment, part of which included confirmation that they had received tests within the last 12 months for triglycerides, total cholesterol, LDL cholesterol, high-density lipoprotein (HDL) cholesterol and blood pressure.

    Subsequent survey questions included those about cholesterol levels, other medications and cardiovascular health history.

    The application then gave one of three outcomes: “OK to use,” “not right for you,” or “ask a doctor.”

    For the primary endpoint, participant selection using the web tool was concordant with clinician selection in 481 (96.2%) of 500 participants (95% confidence interval [CI]: 94.1% to 97.7%).

    Of these, 23 (4.6%) were deemed appropriate for treatment and 458 (91.6%) were deemed to be inappropriate.

    “Discordance was due to incorrect self-selection (‘OK to use’) in 3 cases, incorrect rejection (‘not right for you’) in 14 cases and an incorrect ‘ask a doctor’ outcome in 2 cases,” the researchers said.

    The study, therefore, found the technology was “successful in overcoming a significant barrier to the development of a non-prescription statin by ensuring that a high percentage of ineligible consumers were denied access and that only those with an appropriate level of risk were deemed eligible to access this medication,” the researchers concluded.

    “This study was successful in making certain that the wrong people would not get these drugs, and is an encouraging step forward in the pursuit of a non-prescription statin,” Nissen added in a press statement on the findings.

    Caution

    However, in an accompanying editorial, Neha J. Pagidipati, MD, MPH, from the Duke Clinical Research Institute, and Eric D. Peterson, MD, MPH, from the University of Texas Southwestern, urged caution.

    “Before we leap into this new world of technology aided self-directed care […] we need both optimized digital decision-aids and larger implementation studies,” they urged.

    “On the technology side, although Nissen et al found that patients were reasonable at reporting their health histories, the accuracy, completeness, and ease of collection of heath information could be improved if the tools had been digitally integrated with the participants’ electronic medical record.”

    They also called for larger real-world studies.

    “Although such studies will take resources, the potential upside gained from better cardiovascular prevention could be enormous. The time has come for us to learn how to safely empower patients to self-prescribe preventive therapies.”

    Sources:

    Nissen SE, Hutchinson HG, Wang TY, et al. Technology-Assisted Self-Selection of Candidates for Nonprescription Statin Therapy. J Am Coll Cardiol 2021;78:1114-1123.

    Pagidipati NJ, Peterson ED. Should Cardiovascular Preventive Therapy Be Over-the-Counter? J Am Coll Cardiol 2021;78:1124-1126.

    Image Credit: Vitalii Vodolazskyi – stock.adobe.com

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