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.