High-throughput non-invasive prenatal testing for fetal rhesus D status in RhD-negative women not known to be sensitised to the RhD antigen: a systematic review and economic evaluation

TY - JOUR

T1 - High-throughput non-invasive prenatal testing for fetal rhesus D status in RhD-negative women not known to be sensitised to the RhD antigen

T2 - a systematic review and economic evaluation

AU - Saramago, Pedro

AU - Yang, Huiqin

AU - Llewellyn, Alexis

AU - Walker, Ruth

AU - Harden, Melissa

AU - Palmer, Stephen

AU - Griffin, Susan

AU - Simmonds, Mark

N1 - © Queen’s Printer and Controller of HMSO 2018. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2018/3/21

Y1 - 2018/3/21

N2 - Background: High-throughput non-invasive prenatal testing (NIPT) for fetal rhesus (D antigen) (RhD) status could avoid unnecessary treatment with routine anti-D immunoglobulin for RhD-negative women carrying a RhD-negative fetus, although this may lead to an increased risk of RhD sensitisations. Objectives: To systematically review the evidence on the diagnostic accuracy, clinical effectiveness and implementation of high-throughput NIPT and to develop a cost-effectiveness model. Methods: We searched MEDLINE and other databases, from inception to February 2016, for studies of high-throughput NIPT free-cell fetal deoxyribonucleic acid (DNA) tests of maternal plasma to determine fetal RhD status in RhD-negative pregnant women who were not known to be sensitised to the RhD antigen. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) and A Cochrane Risk of Bias Assessment Tool: for Non-Randomised Studies of Interventions (ACROBAT-NRSI). Summary estimates of false-positive rates (FPRs) and false-negative rates (FNRs) were calculated using bivariate models. Clinical effectiveness evidence was used to conduct a simulation study. We developed a de novo probabilistic decision tree-based cohort model that considered four alternative ways in which the results of NIPT could guide the use of anti-D immunoglobulin antenatally and post partum. Sensitivity analyses (SAs) were conducted to address key uncertainties and model assumptions. Results: Eight studies were included in the diagnostic accuracy review, seven studies were included in the clinical effectiveness review and 12 studies were included in the review of implementation. Meta-analyses included women mostly at or post 11 weeks’ gestation. The pooled FNR (women at risk of sensitisation) was 0.34% [95% confidence interval (CI) 0.15% to 0.76%] and the pooled FPR (women needlessly receiving anti-D) was 3.86% (95% CI 2.54% to 5.82%). SAs did not materially alter the overall results. Data on clinical outcomes, including sensitisation rates, were limited. Our simulation suggests that NIPT could substantially reduce unnecessary use of antenatal anti-D with only a small increase in the risk of sensitisation. All large implementation studies suggested that large-scale implementation of high-throughput NIPT was feasible. Seven cost-effectiveness studies were included in the review, which found that the potential for the use of NIPT to produce cost savings was dependent on the cost of the test. Our de novo model suggested that high-throughput NIPT is likely to be cost saving compared with the current practice of providing routine antenatal anti-D prophylaxis to all women who are RhD negative. The extent of the cost saving appeared to be sufficient to outweigh the small increase in sensitisations. However, the magnitude of the cost saving is highly sensitive to the cost of NIPT itself. Limitations: There was very limited evidence relating to the clinical effectiveness of high-throughput NIPT, with no evidence on potential adverse effects. The generalisability of the findings to non-white women and multiple pregnancies is unclear. Conclusions: High-throughput NIPT is sufficiently accurate to detect fetal RhD status in RhD-negative women from 11 weeks’ gestation and would considerably reduce unnecessary treatment with routine anti-D immunoglobulin, potentially resulting in cost savings of between £485,000 and £671,000 per 100,000 pregnancies if the cost of implementing NIPT is in line with that reflected in this evaluation.

AB - Background: High-throughput non-invasive prenatal testing (NIPT) for fetal rhesus (D antigen) (RhD) status could avoid unnecessary treatment with routine anti-D immunoglobulin for RhD-negative women carrying a RhD-negative fetus, although this may lead to an increased risk of RhD sensitisations. Objectives: To systematically review the evidence on the diagnostic accuracy, clinical effectiveness and implementation of high-throughput NIPT and to develop a cost-effectiveness model. Methods: We searched MEDLINE and other databases, from inception to February 2016, for studies of high-throughput NIPT free-cell fetal deoxyribonucleic acid (DNA) tests of maternal plasma to determine fetal RhD status in RhD-negative pregnant women who were not known to be sensitised to the RhD antigen. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) and A Cochrane Risk of Bias Assessment Tool: for Non-Randomised Studies of Interventions (ACROBAT-NRSI). Summary estimates of false-positive rates (FPRs) and false-negative rates (FNRs) were calculated using bivariate models. Clinical effectiveness evidence was used to conduct a simulation study. We developed a de novo probabilistic decision tree-based cohort model that considered four alternative ways in which the results of NIPT could guide the use of anti-D immunoglobulin antenatally and post partum. Sensitivity analyses (SAs) were conducted to address key uncertainties and model assumptions. Results: Eight studies were included in the diagnostic accuracy review, seven studies were included in the clinical effectiveness review and 12 studies were included in the review of implementation. Meta-analyses included women mostly at or post 11 weeks’ gestation. The pooled FNR (women at risk of sensitisation) was 0.34% [95% confidence interval (CI) 0.15% to 0.76%] and the pooled FPR (women needlessly receiving anti-D) was 3.86% (95% CI 2.54% to 5.82%). SAs did not materially alter the overall results. Data on clinical outcomes, including sensitisation rates, were limited. Our simulation suggests that NIPT could substantially reduce unnecessary use of antenatal anti-D with only a small increase in the risk of sensitisation. All large implementation studies suggested that large-scale implementation of high-throughput NIPT was feasible. Seven cost-effectiveness studies were included in the review, which found that the potential for the use of NIPT to produce cost savings was dependent on the cost of the test. Our de novo model suggested that high-throughput NIPT is likely to be cost saving compared with the current practice of providing routine antenatal anti-D prophylaxis to all women who are RhD negative. The extent of the cost saving appeared to be sufficient to outweigh the small increase in sensitisations. However, the magnitude of the cost saving is highly sensitive to the cost of NIPT itself. Limitations: There was very limited evidence relating to the clinical effectiveness of high-throughput NIPT, with no evidence on potential adverse effects. The generalisability of the findings to non-white women and multiple pregnancies is unclear. Conclusions: High-throughput NIPT is sufficiently accurate to detect fetal RhD status in RhD-negative women from 11 weeks’ gestation and would considerably reduce unnecessary treatment with routine anti-D immunoglobulin, potentially resulting in cost savings of between £485,000 and £671,000 per 100,000 pregnancies if the cost of implementing NIPT is in line with that reflected in this evaluation.

KW - Meta-Analysis

UR - http://www.scopus.com/inward/record.url?scp=85044721737&partnerID=8YFLogxK

U2 - 10.3310/hta22130

DO - 10.3310/hta22130

M3 - Article

C2 - 29580376

SN - 1366-5278

VL - 22

SP - 1

EP - 172

JO - Health technology assessment

JF - Health technology assessment

IS - 13

ER -