NIPT/Cell-Free DNA ScreeningPredictive Value Calculator
This calculator will allow you to estimate the Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of prenatal cell-free DNA screening, also commonly referred to as non-invasive prenatal testing (NIPT) or non-invasive prenatal screening (NIPS), based on estimates of population prevalence or by entering your own prevalence numbers. The results of this calculator only apply to patients who have a result from NIPT/cfDNA.
Estimates of NIPT/cfDNA sensitivity and specificity based on a meta-analysis of available studies (Gil et al 2015) are included as default data for some conditions for which NIPT/cfDNA screens. The user may also input the sensitivity and specificity information based on test performance of a specific laboratory. For some conditions, such as microdeletions, there is insufficient data available in the medical literature to determine test performance. The user may wish to contact the specific NIPT/cfDNA lab for sensitivity and specificity information for specific conditions included on NIPT/cfDNA panels.
The calculator utilizes the incidence of trisomy chromosome conditions screened for by the age of the pregnant patient at 16 weeks gestational age. For some conditions, such as 45,X and the microdeletion conditions, the incidence does not vary significantly with the pregnant patient’s age. In some cases, prevalence at gestational ages prior to 16 weeks may be higher, and prevalence at greater than 16 weeks may be lower, given the possibility of spontaneous loss in pregnancies with some chromosome conditions. The prevalence defaults may not be the best estimates of an individual patient’s prior risk for a chromosome condition. Users should be aware that other factors such as ultrasound findings or the results of biochemical aneuploidy screening may affect the estimated prior risk for a chromosome condition for an individual patient and this should be considered when using this calculator. See the FAQs page for more information.
The default performance metrics for {{ disorderSelection }} are set at a sensitivity of {{sensDefault}} and specificity of {{specDefault}} based on the weighted and pooled data from a meta-analysis by Gil et al (2015). The user may wish to change these inputs to reflect the performance statistics provided by the referral laboratory.
Refer to the laboratory report for information specific to sensitivity and specificity to this test.
PPV (not rounded): {{ notRoundedPPV*100 }}%
PPV = (sensitivity x prevalence) / ((sensitivity x prevalence) + (1 – specificity)(1 – prevalence))
PPV = ({{ varSens }} x {{varPrev}}) / (({{ varSens }} x {{ varPrev }}) + (1 – {{ varSpec }})(1 – {{varPrev}}))
Please note: the post-test probability for an individual patient may differ based on other factors that influence her unique prior risk to have an affected pregnancy, such as gestational age of the patient, ultrasound findings and biochemical screening.
Full NPV (not rounded): {{ notRoundedNPV*100 }}%
NPV = specificity x (1-prevalance) / ((1-sensitivity) x prevalence + specificity x (1-prevalence))
NPV = {{varSpec}} x (1-{{ varPrev }}) / ((1-{{ varSens }}) x {{ varPrev }} + {{ varSpec }} x (1-{{ varPrev }}))
Please note: the post-test probability for an individual patient may differ based on other factors that influence her unique prior risk to have an affected pregnancy, such as gestational age of the patient, ultrasound findings and biochemical screening.
Sensitivity
Sensitivity refers to the detection rate - the proportion of all individuals with a condition who are correctly identified as “positive” by a screening test. If 1,000 tested individuals have a given condition and 990 of them test “positive“ for that condition, the test’s sensitivity is 99%. Sensitivity = Detection Rate = 990/1,000 = 99%
Specificity
Specificity refers to the proportion of all individuals without a condition who are correctly identified as “negative” by a screening test. If 99,000 out of 100,000 unaffected individuals do not have a condition and 98,000 test “negative”, the test’s specificity is 99%. Specificity = 98,000/99,000 = 99%
Positive Predictive Value (PPV)
The Positive Predictive Value (PPV) represents the proportion of positive test results that are truly positive. It answers the question: “If my test is positive, what is the chance my baby is affected?” For example, a PPV of 50% indicates that half of the cases in a given population who have a positive test result are predicted to actually be affected with the condition. Although test sensitivity and specificity are expected to remain the same across a broad population, the PPV of a test varies based on the prevalence of the condition in a given population. The rarer the condition in a given population, the lower the PPV when sensitivity and specificity remain unchanged.
Negative Predictive Value (NPV)
The Negative Predictive Value (NPV) represents the proportion of negative test results that are truly negative. It answers the question: “If my test is negative, what is the chance that my baby is unaffected?” For example, if the NPV is 99% in a given population, then approximately 99% of individuals who have a negative test result in that population would be expected to have an unaffected pregnancy. In this example, 1% of women receiving a negative result will have an affected pregnancy (false negative result).
False Positive Rate
The False Positive Rate (FPR) reflects the percentage of unaffected cases that test positive. If 1,000 of 99,000 unaffected individuals have a positive test result, the false positive rate is 1,000/99,000 = .01 or 1%.
False Negative Rate
The False Negative Rate (FNR) reflects the percentage of affected cases that test negative. If 100 of 1,000 affected individuals have a negative test result, the false negative rate in is 100/1,000 = .01 or 1%.
Accuracy
Accuracy describes the proportion of all tests that are correctly called. For rare conditions, as is often the case for conditions screened with cfDNA/NIPS, the majority of individuals screened will be correctly called as “negative” and therefore cfDNA/NIPS is described as “highly accurate”. However, the chance that any positive result is a true positive result depends on the Positive Predictive Value (PPV) of the test (see above). It is important to note that although the prior probability of many chromosome conditions is influenced by the pregnant patient’s (or egg donor’s) age, other factors such as biochemical screening results and ultrasound markers may also indicate the likelihood of a condition in an individual pregnancy. The table below illustrates components of accuracy:
| AFFECTED n = 1,000 | UNAFFECTED n = 99,000 | TOTAL TESTED n=100,000 | |
|---|---|---|---|
| Tested POSITIVE | True Positive = 990 | False positive = 1,000 | PPV - 990/1,990= 49.75% |
| Tested NEGATIVE | False negative = 10 | True negative = 98,000 | NPV - 98,000/98,010 = 98.99% |
| Sensitivity - 990/1000 = 99.00% | Specificity - 98,000/99,000 = 98.99% |
Frequently Asked Questions
What prevalence information should I use when calculating predictive values?
Use the best estimate for the individual patient. Some factors that influence the likelihood of a chromosome condition in a pregnancy include biochemical screening results, ultrasound findings, or a personal or family history of a chromosome condition. Not sure what estimate to use? Consider referral to a genetic counselor for assessment and counseling. A genetic counselor can be located on the National Society of Genetic Counselors website.
Where do the prevalence estimates come from?
A taskforce including members of the National Society of Genetic Counselors and the Perinatal Quality Foundation reviewed the medical literature and came to consensus regarding the best estimates for prevalence for the conditions included in this calculator. Sources can be found under the Reference tab.
For the trisomy and sex chromosome conditions, the estimates are from review of the data and reflect best estimates for prevalence at 16 weeks gestational age. For some conditions, the prevalence varies by the pregnant patient’s age. In some cases, prevalence at gestational ages prior to 16 weeks may be higher, and prevalence at greater than 16 weeks may be lower, given the possibility of spontaneous loss in pregnancies with some chromosome conditions. The prevalence defaults may not be the best estimates of an individual patient’s prior risk for a chromosome condition.
There is limited information regarding the prevalence of microdeletion conditions during pregnancy. Most of the estimates of prevalence come from the pediatric population and therefore, it is possible that this may not represent the prenatal prevalence for these microdeletions. Underestimates of prevalence would result in a lower PPV. Furthermore, there may be specific ultrasound findings or family history that would suggest a higher baseline risk and this should be taken into account when using this calculator.
NIPT/cfDNA Resources
- ACOG and SMFM statements:
- Joint ACOG and SMFM Practice Bulletin #226: Screening for Fetal Chromosomal Abnormalities. Obstet Gynecol, 2020 Oct; 136 (4)
- Joint ACOG and SMFM Practice Bulletin #163: Screening for Fetal Aneuploidy. Obstet Gynecol, 2016 May; 127 (5)
- Committee Opinion No. 640: Cell-Free DNA Screening for Fetal Aneuploidy. Obstet Gynecol, 2015 Sept: 126(3)
- ACOG Non-Invasive Prenatal Testing: An Advocacy Tool Kit for Obstetric Health Care Professionals and Patients
- The Society for Maternal and Fetal Medicine (SMFM) Consult Series #36: Prenatal Aneuploidy Screening using Cell Free DNA
- SMFM Article: Cell free DNA is not a Simple Blood Test
- SMFM Statement: Maternal serum cell-free DNA screening in low risk women
- International society statements:
- International Society for Prenatal Diagnosis (ISPD) Position statement on the use of non-invasive prenatal testing for the detection of fetal chromosomal conditions in singleton pregnancies
- International Society for Prenatal Diagnosis (ISPD) Position Statement from the Chromosome Abnormality Screening Committee on Behalf of the Board of the International Society for Prenatal Diagnosis
- The European Society of Human Genetics (ESHG) and the American Society of Human Genetics (ASHG) joint policy statement on Non-invasive prenatal testing for aneuploidy and beyond: Challenges of responsible innovation in prenatal screening.
- Genetic society statements:
- Noninvasive Prenatal Testing/Noninvasive Prenatal Diagnosis: The Position of the National Society of Genetic Counselors
- American College of Medical Genetics and Genomics Statement on Noninvasive Prenatal Screening for Fetal Aneuploidy
- Provider support resources:
Professional Organizations
- National Society of Genetic Counselors ( www.nsgc.org )
- How to Find a Genetic Counselor ( https://www.nsgc.org/page/find-a-genetic-counselor )
- Perinatal Quality Foundation ( www.perinatalquality.org )
- American Congress of Obstetricians and Gynecologists ( www.acog.org )
- Society for Maternal Fetal Medicine ( www.smfm.org )
Patient Resources on Specific Conditions
- Trisomy 21 (Down) syndrome:
- National Institute of Health: The Down Syndrome Consortium ( downsyndrome.nih.gov/resources )
- National Center for Prenatal and Postnatal Resources ( lettercase.org/partners-down-syndrome-collaborative )
- National Down Syndrome Society ( ndss.org )
- National Down Syndrome Congress ( ndsccenter.org )
- Trisomy 18 and trisomy 13:
- Support Organization for Trisomy 18, 13, and Related Disorders ( trisomy.org )
- Trisomy 18 Foundation ( trisomy18.org )
- Trisomy 22:
- Support for Disorders of Chromosome 22 ( c22c.org )
- Trisomy 16:
- Disorders of Chromosome 16 ( trisomy16.org )
- Sex chromosome variations:
- Klinefelter’s syndrome, TripleX, and XXY: AXYS ( genetic.org )
- Turner syndrome: Turner Syndrome Society of the US ( turnersyndrome.org )
- 22q deletion (DiGeorge) syndrome:
- 22q Foundation ( 22q.org )
- 15q syndromes:
- Prader-Willi Association USA ( pwsausa.org )
- Angelman Syndrome Foundation ( angelman.org )
- 11q deletion (Jacobsen) syndrome:
- 11q Research and Resource Support group ( 11qusa.org )
- 8q deletion (Langer-Giedion) syndrome:
- Chromosome Disorder Outreach ( chromodisorder.org )
- 5p deletion (Cri-du-chat) syndrome:
- Five P Minus Society ( fivepminus.org )
- 4p deletion (Wolf-Hirschhorn) syndrome:
- 4p Support Group ( 4p-supportgroup.org )
- Wolf-Hirschhorn: The real story about Wolf-Hirschhorn syndrome ( wolfhirschhorn.org )
- 1p36 deletion syndrome:
- 1p36 Deletion Support & Awareness ( 1p36dsa.org )
- Spina bifida:
- Spina Bifida Association ( spinabifidaassociation.org )
References
- Battaglia A, Carey JC, Wright TJ. Wolf-Hirschhorn (4p-) syndrome. Adv Pediatr. 2001;48:75–113.
- Battaglia A, Hoyme HE, Dallapiccola B, Zackai E, Hudgins L, McDonald-McGinn D, Bahi-Buisson N, Romano C, Williams CA, Braley LL, Zuberi SM, Carey JC. Further delineation of deletion 1p36 syndrome in 60 patients: a recognizable phenotype and common cause of developmental delay and mental retardation. Pediatrics. 2008;121:404–10.
- California Department of Health Services. Midtrimester Risk for Chromosome Abnormalities by Maternal Age at Term Chart. Accessed 09/26/2014
- Gil MM, Quezada MS, Revello R, Akolekar R, Nicolaides KH. Analysis of cell-free DNA in maternal blood in screening for fetal aneuploidies: updated meta-analysis. Ultrasound Obstet Gynecol. 2015 Mar;45(3):249-66. doi: 10.1002/uog.14791. Epub 2015 Feb 1.
- Gravholt CH, et al. Prenatal and postnatal prevalence of Turner syndrome: a registry study. BMJ 1996; 312:16-21
- Hook EB. Chromosomal abnormalities: prevalence, risks and recurrence. In Prenatal Diagnosis and Screening. Edinburgh: Churchill Livingstone 1992; 351-392.
- Hook EB, et al. Rates of chromosome abnormalities at different maternal ages. Obstet Gynecol:1981, 58(3); 282-5
- Lionti T, Reid SM, White SM, Rowell MM. A population-based profile of 160 Australians with Prader-Willi syndrome: Trends in diagnosis, birth prevalence and birth characteristics. Am J Med Genet A. 2015 Feb;167(2):371-8. doi: 10.1002/ajmg.a.36845. Epub 2014 Nov 25.
- Maas, N. M. C., Van Buggenhout, G., Hannes, F., Thienpont, B., Sanlaville, D., Kok, K., Midro, A., Andrieux, J., Anderlid, B.-M., Schoumans, J., Hordijk, R., Devriendt, K., Fryns, J.-P., Vermeesch, J. R. Genotype-phenotype correlation in 21 patients with Wolf-Hirschhorn syndrome using high resolution array comparative genome hybridisation (CGH). J. Med. Genet. 45: 71-80, 2008
- Mattina T1, Perrotta CS, Grossfeld P. Jacobsen syndrome. Orphanet J Rare Dis. 2009 Mar 7;4:9. doi: 10.1186/1750-1172-4-9.
- Mertz LG, Christensen R, Vogel I, Hertz JM, Nielsen KB, Grønskov K, Østergaard JR. Angelman syndrome in Denmark. birth incidence, genetic findings, and age at diagnosis. Am J Med Genet A. 2013 Sep;161A(9):2197-203. doi: 10.1002/ajmg.a.36058. Epub 2013 Aug 2.
- Niebuhr E. The Cri du Chat syndrome: epidemiology, cytogenetics, and clinical features. Hum Genet. 1978;44:227-75
- Norton ME, Jacobsson B, Swamy GK, et al. Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med. 2015 Apr 23;372(17):1589-97
- Oskarsdottir S, Vujic M, Fasth A. Incidence and prevalence of the 22q11 deletion syndrome: a population-based study in Western Sweden. Arch Dis Child. 2004;89:148–51.
- Snijders RJ, et al. Maternal age- and gestation-specific risk for trisomy 21. Ultrasound Obstet Gynecol. 1999 Mar;13(3): 167-70
- Snijders et al. Maternal age and gestational age specific risk for chromosomal defects. Fetal Diagn Ther. 1995 Nov-Dec; 10(6): 356-67
- Wellesley D, et al. Rare Chromosome Abnormalities, Prevalence and Prenatal Diagnosis Rates from Population-based Congenital Anomaly Registers in Europe. European Journal of Human Genetics (2012): n. pag. Web. 29 Nov. 2014
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