• Annals of Saudi medicine · Mar 2022

    Cut-off values in newborn screening for inborn errors of metabolism in Saudi Arabia.

    • Adbul Rafiq Khan, Ali Alothaim, Ahmed Alfares, Adil Jowed, Souad Marwan Al Enazi, Saad Mohammed Al Ghamdi, Ahmed Al Seneid, Areej Algahtani, ZahraniSaleh AlSAFrom the Department of Pathology and Laboratory Medicine, King Abdulaziz Medical City, Riyadh, Saudi Arabia., Majid AlFadhel, Omar Aldibasi, Lamya Abdulaziz AlOmair, Rafah Bajudah, and Abeer Nawaf Alanazie.
    • From the Department of Pathology and Laboratory Medicine, King Abdulaziz Medical City, Riyadh, Saudi Arabia.
    • Ann Saudi Med. 2022 Mar 1; 42 (2): 107-118.

    BackgroundNewborn screening identifies individuals affected by a specific disorder within an apparently healthy population prior to the appearance of symptoms so that appropriate interventions can be initiated in time to minimize the harmful effects. Data on population based cut-off values, disease ranges for true positive cases, false positive rates, true positive rates, cut-off verification and comparisons with international cut-off ranges have not been done for Saudi Arabia.ObjectiveEstablish population-based cut-off values and analyte ratios for newborn screening assays and clinically validate the values.DesignPopulation-based screening.SettingTertiary care hospitals and laboratories.MethodsAfter method verification, initial cut-off values were established by analyzing 400-500 dry blood spot (DBS) samples which were further evaluated after one year. About 74 000 patient results were reviewed to establish cut-off ranges from DBS samples received from five different hospitals during 2013-2020. Analysis was performed by tandem mass spectrometry (TMS) and a genetic screening processor. Confirmation of initial positive newborn screening results for different analytes were carried out using gas chromatography-mass spectrometry, high performance liquid chromatography and TMS.Main Outcome MeasuresCut-off values, ratios, positive predictive values, false positive rate, true positive rate and disease range.Sample Size74 000 samples.ResultsPopulation based cut-off values were calculated at different percentiles. These values were compared with 156 true positive samples and 80 proficiency samples. The false positive rate was less than 0.04 for all the analytes, except for valine, leucine, isovalerylcarnitine (C5), biotinidase (BTD), 17-hydroxyprogesterone and thyroid stimulating hormone. The highest false positive rate was 0.14 for BTD which was due to pre-analytical errors. The analytical positive predictive values were greater than 80% throughout the eight years.ConclusionWe have established clinical disease ranges for most of the analytes tested in our lab and several ratios which gives excellent screening specificity and sensitivity for early detection. The samples were representative of the local populations.LimitationsNeed for wider, population-based studies.Conflict Of InterestNone.

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