Adding Clinical Variables Aids in Lung Allocation for Transplants
New variables ID the sickest waitlist candidates with cystic fibrosis, chronic obstructive pulmonary disease
WEDNESDAY, July 3, 2019 (HealthDay News) -- Adding clinical variables improves the accuracy of lung allocation score (LAS) for transplant candidates, according to a study published online June 14 in the American Journal of Respiratory and Critical Care Medicine.
Carli J. Lehr, M.D., from the Cleveland Clinic, and colleagues used data from the Scientific Registry of Transplant Recipients and the Cystic Fibrosis Foundation Patient Registry to identify variables associated with waitlist and posttransplant mortality for cystic fibrosis (CF) lung transplant candidates. Additionally, the authors assessed the impact of including new CF-specific variables in the LAS. Analysis included all lung transplant waitlist candidates (aged ≥12 years) from 2011 through 2014 (9,043 patients on the lung transplant waiting list and 6,110 lung transplant recipients; 1,020 and 677 with CF, respectively).
The researchers found that for CF candidates, any Burkholderia sp. (hazard ratio [HR], 2.8; 95 percent confidence interval [CI], 1.2 to 6.6), 29 to 42 days hospitalized (HR, 2.8; 95 percent CI, 1.3 to 5.9), massive hemoptysis (HR, 2.1; 95 percent CI, 1.1 to 3.9), and relative drop in forced expiratory volume (FEV1) ≥30 percent over 12 months (HR, 1.7; 95 percent CI, 1.0 to 2.8) increased waitlist mortality risk. There was an increased posttransplant mortality risk with pulmonary exacerbation time of 15 to 28 days (HR, 1.8; 95 percent CI, 1.1 to 2.9). In chronic obstructive pulmonary disease (COPD) candidates, a relative drop in FEV1 of ≥10 percent was associated with increased waitlist mortality risk (HR, 2.6; 95 percent CI, 1.2 to 5.4). For CF patients, variability in LAS score and rank increased. For COPD candidates, priority for transplant increased. For other diagnosis groups, access did not change.
"Adding CF-specific variables improved discrimination among waitlisted CF candidates, and benefited COPD candidates," the authors write.