Discussion:
In this study in children with sickle-cell disease, we show that PFT
estimates representing obstructive airway disease (FEV25%-75%,
FEV1/FVC, R5%), restrictive lung disease (FVC%, TLC%), and biomarkers
of inflammation (neutrophil%) were associated with DLCO; and that
models built based on those variables can calculate “estimated DLCO
(e-DLCO)” with precision. Moreover, we demonstrate that DLCO and e-DLCO
are significantly associated with worse clinical outcomes, including
more frequent ACS/VOC events and evidence of pulmonary hypertension.
These results advance our understanding of factors associated with
impaired gas exchange in SCD.
Most pediatric SCD centers in the US do not offer a multi-disciplinary
clinic, and PFTs –including DLCO– are not routinely obtained in
children with SCD. Clinical status can change rapidly in these children,
and PFTs along with other biomarkers need to be obtained at close
intervals to estimate the correlation among clinical parameters and
build a prediction model. Thus, despite the prognostic significance of
impaired gas-exchange, DLCO are not always incorporated into a standard
of care in C-SCD, and in-depth clinical research on DLCO is rarely
conducted.
Children with SCD in our cohort had significantly lower PFTs than their
peers without SCD, consistent with previous studies that have reported
impaired lung function in SCD18,33. On the other hand,
we did not find associations between biomarkers of systemic involvement
and DLCO, as has been described in adult SCD
literature13. This could be partially explained by
differences in disease severity or progression in adults with SCD
compared to younger populations.
Obstructive airway disease is a relatively early phenomenon in SCD lung
involvement, and it can be measured both by spirometry and with IOS. We
found that FEV25%-75% and FEV1/FVC were positively correlated with
DLCO, while R5(%) showed a negative correlation; obstructive airway
disease could thus have an association with impaired gas diffusion in
children with SCD. One of the novel aspects of this study was our
ability to examine the association between IOS estimates and DLCO.
Although an association between IOS estimates and DLCO has never been
studied in SCD, a negative correlation between airway resistance
(measured by IOS) and DLCO has been reported in adult patients with
idiopathic pulmonary fibrosis34. With age, airway
resistance increases16 and DLCO(%) decreases in
C-SCD18; thus, the significant inverse correlation
between R5(%) and DLCO(%) may represent a parallel decline in gas
diffusion and airway obstruction.
Restrictive airway disease is a relatively late phenomenon in youth with
SCD33. As the disease progresses, lung volumes and
DLCO simultaneously decline due to recurrent inflammation, pulmonary
hypertension, and eventually pulmonary
fibrosis13,35,36. The positive correlation we report
between DLCO and lung volume indices such as FVC(%) and TLC(%) may
indicate that diminished lung volumes further contribute to impaired gas
diffusion. Advanced lung disease, either obstructive or restrictive, can
affect alveolar ventilation in adults, leading to alterations in
DLCO35; our results indicate these alterations start
early on in children and even in the absence of severe PFT
abnormalities.
Recurrent SCD crises lead to parenchymal disease and impaired gas
diffusion18,37. Neutrophils generate extracellular
traps and stimulate endothelial activation in SCD38.
Neutrophil activation and other pro-inflammatory pathways in SCD may
lead to thromboembolism in the pulmonary microvasculature, triggering
VOC39. Thus, neutrophilia may indicate disease
severity in C-SCD and it is recognized as a major predictor of mortality
in SCD5. We found that neutrophilia (either absolute
neutrophil counts or percent of total white blood cells) were inversely
correlated to DLCO, and neutrophil(%) was among the top three
predictors of DLCO. Absolute neutrophil counts have been reported to
have inverse correlation with DLCO in the general
population40, but to our knowledge, this is the first
report correlating neutrophilia with impaired gas exchange in pediatric
SCD.
While diffusing capacity is an important biomarker of SCD lung pathology
and is associated with clinical outcomes, diffusion limitation and its
probable predictors have not been well studied in C-SCD. Using two
different statistical approaches, we evaluated PFT and laboratory
predictors of DLCO and identified models that were able to accurately
calculate eDLCO. eDLCO closely approximated measured values and was also
significantly associated with SCD clinical outcomes. While both
mixed-effects regression and XGBoost identified the same predictors, the
machine learning model achieved higher precision as evident by lower
MAPE (1.81% for XGBoost vs. 9.1% for the linear mixed model). While
XGBoost had better precision powered by its ability to adjust for
non-linear variable interactions, the reproducibility of the rank list
by the linear mixed model adds value, reliability, and a more intuitive
interpretation of the models. For instance, both models found that FVC
had superior predictive ability compared to FVC25-75;
these findings are similar to what has been previously reported in
adults without SCD40. More importantly, we tested the
XGBoost algorithm with LOOP and the precision of DLCO prediction was
within the accepted range (between 10-20%), which further validates the
prediction model31. To the best of our knowledge, no
previous study has utilized machine-learning tools to estimate DLCO in
C-SCD.
The study has several limitations that should be acknowledged. It was a
retrospective, single-center study, and thus we cannot evaluate the
effect of center-level practices on our results. Since an external
cohort was not available to validate the prediction model, further
studies will be needed to validate our findings. We lacked racial and
genotypical diversity in the study population, although this is probably
fairly representative of the SCD population as a whole. Most of the
subjects were in their early teens and had stable lung function, and
therefore we cannot extrapolate to younger or older ages; the predictor
rank list may have been different if young children or in adults with
advanced SCD lung disease. At the same time, our study has several
strengths. We had repeated longitudinal data for the cohort, including
spirometry, lung volumes, and IOS measurements. We used two different
statistical approaches; while one was more accurate than the other in
estimating DLCO, both selected the same predictors, which included easy
to obtain spirometric and laboratory values. Finally, both measured and
estimated DLCO were associated with SCD clinical outcomes.
In conclusion, in a cohort of children with SCD, we report several
markers associated with impaired gas exchange, including PFT estimates
representing restrictive lung disease (FVC%), obstructive airway
disease (FEV25%-75%), and inflammation (blood neutrophil%). DLCO was
associated with disease severity indicators of SCD, and we were able to
use simple predictors to calculate eDLCO, which was significantly
associated with disease outcomes. This underscores the clinical
relevance of our prediction models and could help to identify children
at risk.