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<p>Acquired aplastic anemia (AA) can present similarly to inherited bone marrow failure syndromes (IBMFS) but treatment differs. AA diagnosis relies on excluding IBMFS; however, genetic testing is not always available, may delay care or be inconclusive. We developed the Predictive Aplastic Score System (PASS), a clinical tool using readily available data to distinguish AA from IBMFS in adults. The training cohort included 212 adults (162 AA, 50 IBMFS). Compared to IBMFS, AA patients were older and more likely to have acute-onset, severe cytopenias. Using logistic regression with LASSO, we selected seven clinical variables for model inclusion: severity, acuity, age, IBMFS red flags, AA-associated conditions, AA-associated somatic changes, and telomere lengths. The model achieved AUC of 0.990 (95% CI: 0.982–0.999), with 100% positive predictive value (PPV) for AA for scores ≥30. 86.8% of patients with scores &lt;0 had IBMFS. We validated PASS in 716 patients from four external cohorts with AUC of 0.977 (95% CI: 0.968–0.987). Threshold analysis confirmed 100% PPV for scores ≥30, rapidly diagnosing 80% of AA cases. PASS is a practical and accurate clinical tool that can rapidly distinguish AA from IBMFS for most adult patients. To promote clinical adoption, we developed an&#xa0;open-access web calculator (<a href="https://pennmedicine.shinyapps.io/passcalc/">https://pennmedicine.shinyapps.io/passcalc/</a>).</p>

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Development and validation of the predictive aplastic score system (PASS): a simplified tool to diagnose acquired aplastic anemia in adults

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月27日

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  • Gabriel Aleixo,
  • HeeJin Cheon,
  • Jiayin Zheng,
  • Stephanie Soewito,
  • Jimmy Lee,
  • Eléonore Kaphan,
  • Neha Kalakuntla,
  • Wei-Ying Jen,
  • Sumasri Kotha,
  • Alex Rupsee,
  • Mia Djulbegovic,
  • Jairo A. Matthews,
  • Tapan M. Kadia,
  • Timothy S. Olson,
  • Régis Peffault de Latour,
  • Flore Sicre De Fontbrune,
  • Taha Bat,
  • Courtney D. DiNardo,
  • Daria V. Babushok

摘要

Acquired aplastic anemia (AA) can present similarly to inherited bone marrow failure syndromes (IBMFS) but treatment differs. AA diagnosis relies on excluding IBMFS; however, genetic testing is not always available, may delay care or be inconclusive. We developed the Predictive Aplastic Score System (PASS), a clinical tool using readily available data to distinguish AA from IBMFS in adults. The training cohort included 212 adults (162 AA, 50 IBMFS). Compared to IBMFS, AA patients were older and more likely to have acute-onset, severe cytopenias. Using logistic regression with LASSO, we selected seven clinical variables for model inclusion: severity, acuity, age, IBMFS red flags, AA-associated conditions, AA-associated somatic changes, and telomere lengths. The model achieved AUC of 0.990 (95% CI: 0.982–0.999), with 100% positive predictive value (PPV) for AA for scores ≥30. 86.8% of patients with scores <0 had IBMFS. We validated PASS in 716 patients from four external cohorts with AUC of 0.977 (95% CI: 0.968–0.987). Threshold analysis confirmed 100% PPV for scores ≥30, rapidly diagnosing 80% of AA cases. PASS is a practical and accurate clinical tool that can rapidly distinguish AA from IBMFS for most adult patients. To promote clinical adoption, we developed an open-access web calculator (https://pennmedicine.shinyapps.io/passcalc/).