Systematic review of the clinical prediction rules for the calculation of the risk of Down syndrome based on ultrasound findings in the second trimester of pregnancy

Abstract

Clinical prediction rules allow for the integration of second-trimester ultrasound findings to calculate the risk of DS. However, results from the different clinical prediction rules are not concordant and may generate situations of overestimation or underestimation of the risk of DS. It is thus necessary to validate these clinical prediction rules externally to decide which is most suitable for clinical use.

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“…This risk scores are available either as interactive calculator or a spreadsheet [28]. Another example is showed by Moreno-Cid et al, who performed a systematic review of the clinical prediction rules for risk of Down syndrome based on ultrasound findings in pregnancy [29]. These authors showed that only three of the rules were validated (two internally and one externally) and four of them were incorporated into a software application [30][31][32][33].…”

Prevalência das malformações congênitas identificadas em fetos com trissomia dos cromossomos 13, 18 e 21

“…Em 2014, publicou-se um estudo de revisão sistemática sobre as regras de predição clínica para o cálculo do risco de síndrome de Down, baseadas em achados ultrassonográficos no segundo trimestre de gestação. Este artigo, após revisar 10 preditores clínicos, sendo dois com validação interna e um com externa, concluiu que os resultados não são concordantes e podem gerar situações de superestimação ou subestimação do risco de trissomia do cromossomo 21, apesar das inúmeras evidências sobre o fenótipo dos fetos esta trissomia 24 . Dentre as malformações presentes nos casos de trissomia do cromossomo 21 identificados neste trabalho, destacam-se as cardiopatias, principalmente CIV (24,0%), comunicação interatrial (20,0%) e defeito de septo atrioventricular -DSAV (20,0%).…”

Role of the second‐trimester ‘genetic sonogram’ for Down syndrome screen in the era of first‐trimester screening and noninvasive prenatal testing

“…Significant heterogeneity among the studies is a problem that cannot be resolved by subanalysis of data based on the type of population studied (high risk vs screening) . Not surprisingly, a recent study evaluating published algorithms for calculation of DS risk on the same population found wild discrepancies in terms of both detection rates of cases at risk and FPRs …”

“…Finally, the models dichotomized continuous predictors (such as nuchal fold thickness and humerus length), thus potentially making inefficient use of the predictive ability of those markers . A recent systematic review of the proposed algorithms found that at a cutoff risk for DS of 1/270, the proposed algorithms have detection rates ranging from 77.4% to 93.5% and FPRs ranging from 17.9% to 34.6% …”

“…5 Not surprisingly, a recent study evaluating published algorithms for calculation of DS risk on the same population found wild discrepancies in terms of both detection rates of cases at risk and FPRs. 26 Similar to the scoring systems, use of individual positive LR does not take into account the reassurance provided by the absence of other sonographic markers of DS, nor does it take into account the effects of gestational age and maternal age on risk of DS and FPRs, respectively. Moreover, calculation of the combined LR by multiplying the LR of each individual marker can be cumbersome, and because the independence of the markers from each other has not been demonstrated, combined calculations can only assume such independence.…”