1. Variation Among Immunoreactive Trypsinogen Concentrations, Michigan Newborn Screening, 10/2007-4/2008 Steven J. Korzeniewski, MA, MSc, Maternal & Child Health Epidemiology Section Manager Grigorescu, V., Young, W., Hawkins, H., Cavanaugh, K., Nasr, S.Z., Langbo, C.

2. Outline Background Research question Methods Results Discussion Public Health Implications

3. Background CF Screening in MI commenced Oct. 2007 IRT is used to identify infants at increased risk of CF for DNA testing. Mutation analysis, using a panel of 40 CF mutations among > 96th percentile. In the absence of a mutation sweat testing is recommended only among infants having IRT concentrations > 99.8th percentile.

4. Research Question Anecdotal evidence suggested a high rate of false positives among NICU infants This study explores variations in IRT concentrations in hopes of developing a strategy to reduce false positives. R1: Do IRT concentrations vary among the general population by sex, race, birth weight, gestational age, and fetal growth ratio?

5. Methods Data: Newborn screening IRT concentrations and infant demographic data collected from Oct 2007-April 2008 were used for this study. Analysis: Crude and adjusted generalized linear models (GLM) of the association between demographic variables and IRT concentrations ▫Least squares means and p-values are reported ▫LS-means are within-group adjusted means, they estimate the marginal means for a balanced population (as opposed to the unbalanced design). Also called estimated population marginal means by Searle, Speed, and Milliken (1980). ▫We also calculated means and percentiles (96th, 99.8th) by race and gestational age strata

6. Results Generalized Linear Models of the Crude & Adjusted Associations between Initial Screening IRT Values & Subject Demographics, Michigan Newborn Screening, Oct. 2007- April 2008 Demographics CrudeAdjusted* IRT (LS Mean)P-value IRT (LS Mean)P-value Race (n=59150) American Indian26.4 <.0001 27.7 <.0001 Arab Descent26.427.7 Asian/Pacific Islander22.924.1 Black33.234.3 Multi-Racial27.128.4 White25.927.1 Gestational Age (n=67643) LT 28 wks27.1 <.0001 28.3 <.0001 28-37 wks29.028.5 >=37 wks27.127.9 Birth Weight (n=67643) <1800 grams29.3 <.0001 29.6 <.0001 1800g-2500g28.727.9 >=2500g27.027.1 Sex (n=64803) Female26.9 <.0001 27.9 <.0001 Male27.728.5 FGR (n=48039) < 25th %29.1 <.0001 30.9 <.0001 >= 25th% & < 75th%27.529.6 >=75th%26.628.9 Race*GA0.0005 *Adjusted for other demographic covariates included in the table (Race, GA, BW, Sex) and age at specimen collection. (N=58,789)

7. Results IRT Means & Percentiles (96th & 99.8th) by Race & Gestational Age, Michigan Newborn Screening, Oct/2007-April/2008, N=59,150 Race GA < 28 WeeksGA 28-37 WeeksGA > 37 Weeks NMean Percentile NMean Percentile NMean Percentile 9699.89699.89699.8 White 315126.1258167362326.82531613434625.8053106 Black 134432.1478163140235.3678224932333.0572133 American Indian 2620.2735501325.54434924827.1054150 Asian/Pacific Islander 11221.52426210224.834479124522.904892 Arab Descent 12726.696013910428.425981127326.245499 Multi-Racial 23125.23669823327.9160116205927.2455104 Total* 820027.1362163592528.99621665356327.1257115 *Total N exceeds the sum of racial categories because it includes those records missing race information.

8. Updated Results At one year (Oct 2007-Oct 2008) ▫Effect modification of race by gestational age absolved ▫Racial variation remained significant in both crude & adjusted models

9. Conclusion Failure to account for racial variation results in: ▫Over sampling of black infants  those at lower risk of CF ▫Under sampling of white infants  those at the greater risk of CF False positive and false negative rates could be inflated ▫However, no false negatives have been detected thus far

10. Public Health Implications Calculation of IRT % cutoffs stratified by race would: ▫Reduce the FPR & Improve PPV ▫Require further research to discern appropriate cutoffs, particularly for racial minorities or those with missing data ▫Require significant change in laboratory operating procedures  Sorting of cards  Verification of Race information  Development of strategy to calculate cutoffs over time

11. Acknowledgements Co-Investigators: Grigorescu, V., Young, W., Hawkins, H., Cavanaugh, K., Nasr, S.Z., Langbo, C. NBS Follow-up Staff CF Advisory Committee

12. Contact KorzeniewskiS@Michigan.gov Thank You