Prediction of adverse outcomes in children with sickle cell anemia: a study of the Dallas Newborn Cohort

Charles T Quinn, Nancy J Lee, Elizabeth P Shull, Naveed Ahmad, Zora R Rogers, George R Buchanan, Charles T Quinn, Nancy J Lee, Elizabeth P Shull, Naveed Ahmad, Zora R Rogers, George R Buchanan

Abstract

The Cooperative Study of Sickle Cell Disease reported that dactylitis, severe anemia, and leukocytosis in very young children with sickle cell disease (SCD) increased the risk of later adverse outcomes, including death, stroke, frequent pain, and recurrent acute chest syndrome. This model has not been validated in other cohorts. We evaluated its performance in the Dallas Newborn Cohort, a newborn inception cohort of children with SCD. We studied 168 children (55% male, 97% sickle cell anemia) with a mean follow-up of 7.1 years who provided 1188 patient-years of observation. Of the 23 (13.7%) subjects who experienced adverse events, 2 (1.2%) died, 14 (8.3%) had a stroke, 4 (2.4%) had frequent pain, and 3 (1.8%) had recurrent acute chest syndrome. No relationship existed between early clinical predictors and later adverse outcomes, with the possible exception of leukocyte count. Most subjects who experienced adverse events were predicted to be at low risk for those events. No subject who was predicted to be at high risk actually experienced an adverse outcome. The sensitivity of the model did not rise above 20% until specificity fell below 60%. We suggest that this model not be used as a criterion to initiate early interventions for SCD.

Figures

Figure 1
Figure 1
Performance of the CSSCD model and total leukocyte count as predictors in the DNC. (A) Receiver operating characteristic (ROC) curve for the prediction of adverse events in the DNC by the multivariable CSSCD model. The x-axis indicates the false positive rate (1 − specificity). The y-axis indicates sensitivity (the proportion of patients who were correctly classified). The area under the ROC curve is 0.409 (95% CI, 0.308-0.510; P = .161). Therefore, the CSSCD model was not better than prediction by chance. (B) ROC curve for prediction of adverse events in the DNC by leukocyte count as a single predictor. The area under the ROC curve is 0.634 (95% CI, 0.517-0.752; P = .039). Diagonal segments indicate ties.

Source: PubMed

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