A clinically actionable nomogram for predicting invasive pulmonary aspergillosis: A nested case-control study.

A nine-variable nomogram predicts invasive pulmonary aspergillosis with moderate accuracy (AUC 0.75) using routine clinical data, aiding early diagnosis.

• Why it matters: Early prediction of IPA is crucial because delayed diagnosis leads to high mortality, yet current models lack practicality and timely utility in clinical settings.
• What they did: A nested case-control study analyzed 1,002 IPA cases and 2,004 controls from a 10-year cohort, developing a nomogram based on nine independent risk factors through multivariable logistic regression.
• The result: The nomogram demonstrated stable discrimination and excellent calibration, offering a practical tool for clinicians to identify high-risk patients early and improve treatment outcomes.