Study: Cutting false-positives in newborn screening
The aim of Newborn Screening Programs is to identify potentially fatal or disabling conditions in newborns as early as possible. Typically, the analysis is performed within a few days of an infant being born. This allows an early identification and treatment of those babies affected and helps to reduce mortality and morbidity rates. If left untreated, these conditions can also have a serious impact, such as lifelong nervous system damage.
LC-MS/MS is the method of choice as it is able to screen for a wide range of biomarkers for inborn errors of metabolism (IEM) in a single test using dry blood spot (DBS) samples, while also providing high accuracy of data. Over 50 disorders in a single analysis can be determined in a rapid and high throughput fashion that include aminoacidemias, fatty acid oxidation disorders, organic acidemias and other disorders.
The study from Saudi Arabia
As for many tests, there’s a threshold value (a ‘cut-off’ value) that indicates which levels are normal or abnormal, requiring precise and clinically validated data. While more and more disorders are being screened, the analysis should also remain accurate and free from false-positive or false-negative results. This is why a recent study from Khan et al. [ref x] in Saudi Arabia looked to re-assess population-based cut-off values and analyte ratios over a longer period of time.
The study took place from 2013 to 2020 with the newborn screening being performed by LC-MS/MS and genetic screening. For amino acids and acylcarnitine, the non-derivatised assay from Chromsystems was used. The study also included the biomarkers 17-hydroxyprogesterone (17-OHP), thyroid stimulating hormone (TSH), biotinidase activity (BTD), and galactose-1-phosphate uridyltransferase deficiency (GALT).
The initial cut-off values were established using 400-500 DBS samples collected by the heel prick method. Over the 8 years, this number increased to over 74,000 samples, leading to statistical parameters and disease ranges changing over time. Each year, the cut-off values for abnormal results were changed in line with these newly obtained data.
More data, better cut-offs
After eight years, the screening results of all normal patient samples were reviewed, and population-based cut-off values were calculated for all analytes. The initial and newly established cut-off values were compared, and necessary changes were made. By having enough data, the cut-off values for abnormal results were dramatically reduced, leading to a reduction in false-positive results, a more accurate analysis and more positive prediction values for multiple analytes.
The authors concluded that “establishing specific and population-based cut-off values and analyte ratios are imperative for quick and accurate diagnoses of IEM […] and support a reduction in false positive rates”. This in turn prevents unnecessary second tier testing and avoidable family anxiety that comes with this extra testing.
According to the authors, the study is one of the largest to date but is only representative of the local population in Saudi Arabia where the study was performed. The future aim is to expand the study to produce a model based on a wider population. “The results will be helpful for all laboratories and physicians across the country.”
Last Update: February 10, 2023
Adbul Rafiq Khan, Ali Alothaim, iDAhmed Alfares, Adil Jowed, Souad Marwan Al Enazi, Saad Mohammed Al Ghamdi, Ahmed Al Seneid, Areej Algahtani, Saleh Al Zahrani, Majid AlFadhel, Omar Aldibasi, Lamya Abdulaziz AlOmair, Rafah Bajudah, and Abeer Nawaf Alanazie: Cut-off values in newborn screening for inborn errors of metabolism in Saudi Arabia. Annals of Saudi Medicine, 7 Apr. (2022). https://www.annsaudimed.net/doi/10.5144/0256-4947.2022.107