Table 2A

Variables predictive of mortality for T0 model

Beta-coefficient from lasso*
FEV1 (% predicted)−0.044
 Private insurance onlyReference group
 Medicare only0
 Combination of any insurance including Medicaid0.16
Ventilation machine (non-invasive)
 NoReference group
Oxygen therapy
 NoReference group
 Yes, continuously0.46
 Yes, nocturnal and/or with exertion0
 Yes, during exacerbation0
 Yes, prn0
Burkho complex (Burkholderia species)
 NoReference group
Liver disease, cirrhosis
 NoReference group
Renal failure requiring dialysis
 NoReference group
 NoReference group
 Regularly, <1 ppd0.429
 Regularly, 1 ppd or more0
Mutation class
 1–3Reference group
 Unknown missing0.302
# of pulmonary exacerbations in the year preceding advanced stage CF diagnosis0.093
Baseline lung transplant evaluation status
 Not pertinentReference group
 Accepted, on waiting list−0.102
 Evaluated, final decision pending0
 Evaluated, rejected0
  • Parameter estimates do not represent the true magnitude of effect. In other words, unlike in Cox regression models that use classical techniques of variable selection, exponentiation of the lasso beta-coefficient is not an estimate of the true HR. However, when taken in context of the model it can determine relative importance in prediction and positive or negative association with the predicted outcome.

  • *A negative value indicates predictive of lower mortality.

  • CF, cystic fibrosis; FEV1, forced expiratory volume in 1 s.