Enhanced interpretation of newborn screening results without analyte cutoff values.

PURPOSE: To improve quality of newborn screening by tandem mass spectrometry with a novel approach made possible by the collaboration of 154 laboratories in 49 countries. METHODS: A database of 767,464 results from 12,721 cases affected with 60 conditions was used to build multivariate pattern recognition software that generates tools integrating multiple clinically significant results into a single score. This score is determined by the overlap between normal and disease ranges, penetration within the disease range, differences between conditions, and weighted correction factors. RESULTS: Ninety tools target either a single condition or the differential diagnosis between multiple conditions. Scores are expressed as the percentile rank among all cases with the same condition and are compared to interpretation guidelines. Retrospective evaluation of past cases suggests that these tools could have avoided at least half of 279 false-positive outcomes caused by carrier status for fatty-acid oxidation disorders and could have prevented 88% of known false-negative events. CONCLUSION: Application of this computational approach to raw data is independent from single analyte cutoff values. In Minnesota, the tools have been a major contributing factor to the sustained achievement of a false-positive rate below 0.1% and a positive predictive value above 60%

Enhanced interpretation of newborn screening results without analyte cutoff values

Purpose: To improve quality of newborn screening by tandem mass spectrometry with a novel approach made possible by the collaboration of 154 laboratories in 49 countries. Methods: A database of 767,464 results from 12,721 cases affected with 60 conditions was used to build multivariate pattern recognition software that generates tools integrating multiple clinically significant results into a single score. This score is determined by the overlap between normal and disease ranges, penetration within the disease range, differences between conditions, and weighted correction factors. Results: Ninety tools target either a single condition or the differential diagnosis between multiple conditions. Scores are expressed as the percentile rank among all cases with the same condition and are compared to interpretation guidelines. Retrospective evaluation of past cases suggests that these tools could have avoided at least half of 279 false-positive outcomes caused by carrier status for fatty-acid oxidation disorders and could have prevented 88% of known false-negative events. Conclusion: Application of this computational approach to raw data is independent from single analyte cutoff values. In Minnesota, the tools have been a major contributing factor to the sustained achievement of a false-positive rate below 0.1% and a positive predictive value above 60%. © 2012 American College of Medical Genetics and Genomics

Enhanced interpretation of newborn screening results without analyte cutoff values

Purpose: To improve quality of newborn screening by tandem mass spectrometry with a novel approach made possible by the collaboration of 154 laboratories in 49 countries. Methods: A database of 767,464 results from 12,721 cases affected with 60 conditions was used to build multivariate pattern recognition software that generates tools integrating multiple clinically significant results into a single score. This score is determined by the overlap between normal and disease ranges, penetration within the disease range, differences between conditions, and weighted correction factors. Results: Ninety tools target either a single condition or the differential diagnosis between multiple conditions. Scores are expressed as the percentile rank among all cases with the same condition and are compared to interpretation guidelines. Retrospective evaluation of past cases suggests that these tools could have avoided at least half of 279 false-positive outcomes caused by carrier status for fatty-acid oxidation disorders and could have prevented 88% of known false-negative events. Conclusion: Application of this computational approach to raw data is independent from single analyte cutoff values. In Minnesota, the tools have been a major contributing factor to the sustained achievement of a false-positive rate below 0.1% and a positive predictive value above 60%. © 2012 American College of Medical Genetics and Genomics

Clinical validation of cutoff target ranges in newborn screening of metabolic disorders by tandem mass spectrometry: A worldwide collaborative project.

Purpose: To achieve clinical validation of cutoff values for newborn screening by tandem mass 215 spectrometry through a worldwide collaboration. Methods: Cumulative percentiles of amino 216 acids and acylcarnitines in dried blood spots of approximately 30 million normal newborns and 217 10,615 true positive cases are compared to assign clinical significance, which is achieved when 218 the median of a disease range is either >99%ile or <1%ile of the normal population. The cutoff 219 target ranges of analytes and ratios are then defined as the interval between the limits of the two 220 populations. When overlaps occur, adjustments are made to maximize sensitivity and specificity 221 taking in consideration all available factors. Results: As of December 1, 2010, 129 sites in 45 222 countries have uploaded to the project website a total of 23,970 percentile data points, 558,168 223 analyte results of 10,615 true positive cases with 64 conditions, and 5,088 cutoff values. The 224 average rate of submission of true positive cases between December 1, 2008 and December 1, 225 2010 was 4.7 cases per day (3,418 cases). This cumulative evidence generated 91 and 23 high 226 and low target cutoff ranges, respectively. The overall proportion of cutoff values within the 227 respective target range was 43% (2,176/5,088). Conclusions: An unprecedented level of 228 cooperation and collaboration has allowed the objective definition of cutoff target ranges for 114 229 markers applied to newborn screening of rare metabolic disorders. This set of data could be used 230 as baseline for monitoring of future performance