Evidence map›Paper›PMID 27917919›Full record

ArticleScientific reports2016

NIPTRIC: an online tool for clinical interpretation of non-invasive prenatal testing (NIPT) results.

Birgit Sikkema-Raddatz, Lennart F Johansson, Eddy N de Boer, Elles M J Boon, Ron F Suijkerbuijk, Katelijne Bouman, Catia M Bilardo, Morris A Swertz, Martijn Dijkstra, Irene M van Langen and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Birgit Sikkema-RaddatzUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.
Lennart F JohanssonUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.
Eddy N de BoerUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.
Elles M J BoonDepartment of Clinical Genetics, Laboratory for Diagnostic Genome Analysis, Leiden University Medical Centre, Leiden, the Netherlands.
Ron F SuijkerbuijkUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.
Katelijne BoumanUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.
Catia M BilardoUniversity of Groningen, University Medical Centre Groningen, Department of Obstetrics and Gynaecology, Groningen, the Netherlands.
Morris A SwertzUniversity of Groningen, University Medical Centre Groningen, Genomics Coordination Centre, Department of Genetics, Groningen, the Netherlands.
Martijn DijkstraUniversity of Groningen, University Medical Centre Groningen, Genomics Coordination Centre, Department of Genetics, Groningen, the Netherlands.
Irene M van LangenUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.
Richard J SinkeUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.
Gerard J Te MeermanUniversity of Groningen, University Medical Centre Groningen, Department of Genetics, Groningen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To properly interpret the result of a pregnant woman's non-invasive prenatal test (NIPT), her a priori risk must be taken into account in order to obtain her personalised a posteriori risk (PPR), which more accurately expresses her true likelihood of carrying a foetus with trisomy. Our aim was to develop a tool for laboratories and clinicians to calculate easily the PPR for genome-wide NIPT results, using diploid samples as a control group. The tool takes the a priori risk and Z-score into account. Foetal DNA percentage and coefficient of variation can be given default settings, but actual values should be used if known. We tested the tool on 209 samples from pregnant women undergoing NIPT. For Z-scores < 5, the PPR is considerably higher at a high a priori risk than at a low a priori risk, for NIPT results with the same Z-score, foetal DNA percentage and coefficient of variation. However, the PPR is effectively independent under all conditions for Z-scores above 6. A high PPR for low a priori risks can only be reached at Z-scores > 5. Our online tool can assist clinicians in understanding NIPT results and conveying their true clinical implication to pregnant women, because the PPR is crucial for individual counselling and decision-making.

Indexed as

AdultAge FactorsAmniocentesisCell-Free Nucleic AcidsDecision MakingDown SyndromeFemaleFetusGenetic TestingGestational AgeHumansPredictive Value of TestsPregnancyPrenatal DiagnosisResearch DesignRisk AssessmentCell-Free Nucleic Acids

Identifiers

PMID27917919
PMCPMC5137038

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.