Screening for sickle cell disease in newborns: a systematic review.

BACKGROUND: Sickle cell disease (SCD) is an inherited autosomal recessive disorder caused by the replacement of normal haemoglobin (HbA) by mutant Hb (sickle Hb, HbS). The sickle-shaped red blood cells lead to haemolysis and vaso-occlusion. Especially in the first years of life, patients with SCD are at high risk of life-threatening complications. SCD prevalence shows large regional variations; the disease predominantly occurs in sub-Saharan Africa. We aimed to systematically assess the evidence on the benefit of newborn screening for SCD followed by an earlier treatment start. METHODS: We systematically searched bibliographic databases (MEDLINE, EMBASE, Cochrane Databases, and the Health Technology Assessment Database), trial registries, and other sources to identify systematic reviews and randomised controlled trials (RCTs) or non-randomised trials on newborn screening for SCD. The last search was in 07/2020. Two reviewers independently reviewed abstracts and full-text articles and assessed the risk of bias of the studies included. Data were extracted by one person and checked by another. As meta-analyses were not possible, a qualitative summary of results was performed. RESULTS: We identified 1 eligible study with direct evidence: a Jamaican retrospective study evaluating newborn screening for SCD followed by preventive measures (prevention of infections and education of parents). The study included 500 patients with SCD (intervention group, 395; historical control group, 105). Although the results showed a high risk of bias, the difference between the intervention and the control group was very large: mortality in children decreased by a factor of about 10 in the first 5 years of life (0.02% in the intervention group vs. 0.19% in the control group, odds ratio 0.09; 95% confidence interval [0.04; 0.22], p < 0.001). CONCLUSION: The results are based on a single retrospective study including historical controls. However, the decrease of mortality by a factor of 10 is unlikely to be explained by bias alone. Therefore, in terms of mortality, data from this single retrospective study included in our systematic review suggest a benefit of newborn screening for SCD (followed by preventive measures) versus no newborn screening for SCD (weak certainty of conclusions).

The Reliable, Automatic Classification of Neonates in First-Tier MALDI-MS Screening for Sickle Cell Disease.

Previous research has shown that a MALDI-MS technique can be used to screen for sickle cell disease (SCD), and that a system combining automated sample preparation, MALDI-MS analysis and classification software is a relevant approach for first-line, high-throughput SCD screening. In order to achieve a high-throughput "plug and play" approach while detecting "non-standard" profiles that might prompt the misclassification of a sample, we have incorporated various sets of alerts into the decision support software. These included "biological alert" indicators of a newborn's clinical status (e. g., detecting samples with no or low HbA), and "technical alerts" indicators for the most common non-standard profiles, i.e., those which might otherwise lead to sample misclassification. We evaluated these alerts by applying them to two datasets (produced by different laboratories). Despite the random generation of abnormal spectra by one-off technical faults or due to the nature and quality of the samples, the use of alerts fully secured the process of automatic sample classification. Firstly, cases of ß-thalassemia were detected. Secondly, after a visual check on the tagged profiles and reanalysis of the corresponding biological samples, all the samples were correctly reclassified without prompting further alerts. All of the samples for which the results were not tagged were well classified (i.e., sensitivity and specificity = 1). The alerts were mainly designed for detecting false-negative classifications; all the FAS samples misclassified by the software as FA (a false negative) were marked with an alert. The implementation of alerts in the NeoScreening® Laboratory Information Management System's decision support software opens up perspectives for the safe, reliable, automated classification of samples, with a visual check solely on abnormal results or samples. It should now be possible to evaluate the combination of the NeoSickle® analytical solution and the NeoScreening® Laboratory Information Management System in a real-life, prospective study of first-line SCD screening.