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<p>The diagnostic performance of the Amyloid Probability Score 2 (APS2; the algorithmic result of the PrecivityAD2™ blood test) was originally trained and validated in two cohorts of cognitively impaired (CI) individuals and is in clinical use. Here, we further test the repeatability and reliability of the prespecified APS2 algorithm and cut point in an independent cohort. APS2 diagnostic performance was determined using amyloid positron emission tomography (PET) as the reference standard. Concordance with amyloid PET was high (AUC–ROC 0.95 (95% CI): 0.93–0.98); 54% of participants had a positive APS2. The previously validated APS2 cut point yielded an overall accuracy of 91% (95% CI: 86–94%), sensitivity 90% (95% CI: 83–94%) and specificity 92% (95% CI: 84–96%). Our findings demonstrate that the prespecified APS2 algorithm and cut point are repeatable, reliable, robust, accurate, and generalizable for identifying brain beta-amyloid pathology in patients with cognitive impairment and being evaluated in a clinical care setting.</p>

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Independent validation of the PrecivityAD2™ blood test to identify presence or absence of brain amyloid pathology in individuals with cognitive impairment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月4日

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  • Justine Coppinger,
  • Tim West,
  • Kris M. Kirmess,
  • Ilana Fogelman,
  • Sutapa Ray,
  • Philip B. Verghese,
  • Joel B. Braunstein,
  • Kevin E. Yarasheski

摘要

The diagnostic performance of the Amyloid Probability Score 2 (APS2; the algorithmic result of the PrecivityAD2™ blood test) was originally trained and validated in two cohorts of cognitively impaired (CI) individuals and is in clinical use. Here, we further test the repeatability and reliability of the prespecified APS2 algorithm and cut point in an independent cohort. APS2 diagnostic performance was determined using amyloid positron emission tomography (PET) as the reference standard. Concordance with amyloid PET was high (AUC–ROC 0.95 (95% CI): 0.93–0.98); 54% of participants had a positive APS2. The previously validated APS2 cut point yielded an overall accuracy of 91% (95% CI: 86–94%), sensitivity 90% (95% CI: 83–94%) and specificity 92% (95% CI: 84–96%). Our findings demonstrate that the prespecified APS2 algorithm and cut point are repeatable, reliable, robust, accurate, and generalizable for identifying brain beta-amyloid pathology in patients with cognitive impairment and being evaluated in a clinical care setting.