Minimally acceptable criteria and required sample size for an accuracy study of non-invasive prenatal testing of sickle cell disease in screen positive women in England: results of a decision tree model
Vittoria Vardanega, Ania Bobrowska, Benjamin Ruban-Fell, James A. Doorbar, Silvia Lombardo, Farah Seedat, Yvonne Daniel, Amanda Hogan, Mariska M. G. Leeflang, Kathy Mann, Anna Schuh, John Marshall · 2026
Read Minimally acceptable criteria and required sample size for an accuracy study of non-invasive prenatal testing of sickle cell disease in screen positive women in England: results of a decision tree model by Vittoria Vardanega, Ania Bobrowska, Benjamin Ruban-Fell, James A. Doorbar, Silvia Lombardo, Farah Seedat, Yvonne Daniel, Amanda Hogan, Mariska M. G. Leeflang, Kathy Mann, Anna Schuh, John Marshall (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13267277.txt.
Description
Vittoria Vardanega and colleagues model prenatal testing for sickle cell disease in England in a 2026 paper. Current screening tests the mother, then the father, then offers invasive testing when both carry the gene. When the father cannot be tested, women may wait or miss out. A blood test of the mother alone, called non-invasive prenatal testing, could fill the gap.
Using a decision tree, the team set the lowest test accuracy a future study should demand. One scenario allowed under 10 missed cases a year nationally; a stricter one allowed at most 2. The stricter bar needed about 99 percent sensitivity. Both scenarios implied study sizes too large for a single forward-looking study. The authors suggest design workarounds for rare conditions.
Catalog record
| CREATOR | Vittoria Vardanega, Ania Bobrowska, Benjamin Ruban-Fell, James A. Doorbar, Silvia Lombardo, Farah Seedat, Yvonne Daniel, Amanda Hogan, Mariska M. G. Leeflang, Kathy Mann, Anna Schuh, John Marshall |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 62466 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |