TY - JOUR
T1 - CT strain metrics allow for earlier diagnosis of bronchiolitis obliterans syndrome after hematopoietic cell transplant
AU - Sharifi, Husham
AU - Bertini, Christopher D.
AU - Alkhunaizi, Mansour
AU - Hernandez, Maria
AU - Musa, Zayan
AU - Borges, Carlos
AU - Turk, Ihsan
AU - Bashoura, Lara
AU - Dickey, Burton F.
AU - Cheng, Guang Shing
AU - Yanik, Gregory
AU - Galban, Craig J.
AU - Guo, Huawei Henry
AU - Godoy, Myrna C.B.
AU - Reinhardt, Joseph M.
AU - Hoffman, Eric A.
AU - Castro, Mario
AU - Rondon, Gabriela
AU - Alousi, Amin M.
AU - Champlin, Richard E.
AU - Shpall, Elizabeth J.
AU - Lu, Ying
AU - Peterson, Samuel
AU - Datta, Keshav
AU - Nicolls, Mark R.
AU - Hsu, Joe
AU - Sheshadri, Ajay
N1 - Publisher Copyright:
© 2024 by The American Society of Hematology.
PY - 2024/10/8
Y1 - 2024/10/8
N2 - Bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation (HCT) is associated with substantial morbidity and mortality. Quantitative computed tomography (qCT) can help diagnose advanced BOS meeting National Institutes of Health (NIH) criteria (NIH-BOS) but has not been used to diagnose early, often asymptomatic BOS (early BOS), limiting the potential for early intervention and improved outcomes. Using pulmonary function tests (PFTs) to define NIH-BOS, early BOS, and mixed BOS (NIH-BOS with restrictive lung disease) in patients from 2 large cancer centers, we applied qCT to identify early BOS and distinguish between types of BOS. Patients with transient impairment or healthy lungs were included for comparison. PFTs were done at month 0, 6, and 12. Analysis was performed with association statistics, principal component analysis, conditional inference trees (CITs), and machine learning (ML) classifier models. Our cohort included 84 allogeneic HCT recipients, 66 with BOS (NIH-defined, early, or mixed) and 18 without BOS. All qCT metrics had moderate correlation with forced expiratory volume in 1 second, and each qCT metric differentiated BOS from those without BOS (non-BOS; P < .0001). CITs distinguished 94% of participants with BOS vs non-BOS, 85% of early BOS vs non-BOS, 92% of early BOS vs NIH-BOS. ML models diagnosed BOS with area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.74-0.94) and early BOS with AUC of 0.84 (95% CI, 0.69-0.97). qCT metrics can identify individuals with early BOS, paving the way for closer monitoring and earlier treatment in this vulnerable population.
AB - Bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation (HCT) is associated with substantial morbidity and mortality. Quantitative computed tomography (qCT) can help diagnose advanced BOS meeting National Institutes of Health (NIH) criteria (NIH-BOS) but has not been used to diagnose early, often asymptomatic BOS (early BOS), limiting the potential for early intervention and improved outcomes. Using pulmonary function tests (PFTs) to define NIH-BOS, early BOS, and mixed BOS (NIH-BOS with restrictive lung disease) in patients from 2 large cancer centers, we applied qCT to identify early BOS and distinguish between types of BOS. Patients with transient impairment or healthy lungs were included for comparison. PFTs were done at month 0, 6, and 12. Analysis was performed with association statistics, principal component analysis, conditional inference trees (CITs), and machine learning (ML) classifier models. Our cohort included 84 allogeneic HCT recipients, 66 with BOS (NIH-defined, early, or mixed) and 18 without BOS. All qCT metrics had moderate correlation with forced expiratory volume in 1 second, and each qCT metric differentiated BOS from those without BOS (non-BOS; P < .0001). CITs distinguished 94% of participants with BOS vs non-BOS, 85% of early BOS vs non-BOS, 92% of early BOS vs NIH-BOS. ML models diagnosed BOS with area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.74-0.94) and early BOS with AUC of 0.84 (95% CI, 0.69-0.97). qCT metrics can identify individuals with early BOS, paving the way for closer monitoring and earlier treatment in this vulnerable population.
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U2 - 10.1182/bloodadvances.2024013748
DO - 10.1182/bloodadvances.2024013748
M3 - Article
C2 - 39163616
AN - SCOPUS:85206241731
SN - 2473-9529
VL - 8
SP - 5156
EP - 5165
JO - Blood Advances
JF - Blood Advances
IS - 19
ER -