Improving outcomes for Colorado's IRT-IRT-DNA cystic fibrosis newborn screening algorithm by implementing floating cutoffs
The Colorado Newborn Screening Program (CO-NBS) screens for cystic fibrosis (CF) by measuring immunoreactive trypsinogen (IRT) from two screens coupled with DNA analysis (IRT/IRT/DNA). The Colorado CF Care Center identified 8 missed CF cases among 358,187 infants screened by the CO-NSP since 2016. R...
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| Veröffentlicht in: | Molecular genetics and metabolism 2021-09, Vol.134 (1-2), p.65-67 |
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| container_title | Molecular genetics and metabolism |
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| creator | Martiniano, Stacey L. Croak, Kendra Bonn, Gregory Sontag, Marci K. Sagel, Scott D. |
| description | The Colorado Newborn Screening Program (CO-NBS) screens for cystic fibrosis (CF) by measuring immunoreactive trypsinogen (IRT) from two screens coupled with DNA analysis (IRT/IRT/DNA). The Colorado CF Care Center identified 8 missed CF cases among 358,187 infants screened by the CO-NSP since 2016. Retrospective analysis of CO-NSP IRT data shows that a 96th percentile floating IRT cutoff with a 50 ng/mL fixed cutoff on the first screen, and second screen 50 ng/mL fixed cutoff would have identified 7 of the 8 missed cases. These efforts demonstrate the importance of continuous quality improvement in order to increase sensitivity and reduce missed cases. |
| doi_str_mv | 10.1016/j.ymgme.2021.08.005 |
| format | Article |
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The Colorado CF Care Center identified 8 missed CF cases among 358,187 infants screened by the CO-NSP since 2016. Retrospective analysis of CO-NSP IRT data shows that a 96th percentile floating IRT cutoff with a 50 ng/mL fixed cutoff on the first screen, and second screen 50 ng/mL fixed cutoff would have identified 7 of the 8 missed cases. 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The Colorado CF Care Center identified 8 missed CF cases among 358,187 infants screened by the CO-NSP since 2016. Retrospective analysis of CO-NSP IRT data shows that a 96th percentile floating IRT cutoff with a 50 ng/mL fixed cutoff on the first screen, and second screen 50 ng/mL fixed cutoff would have identified 7 of the 8 missed cases. These efforts demonstrate the importance of continuous quality improvement in order to increase sensitivity and reduce missed cases.</description><subject>Algorithms</subject><subject>Cystic fibrosis</subject><subject>Cystic Fibrosis - diagnosis</subject><subject>Cystic Fibrosis - genetics</subject><subject>Data Interpretation, Statistical</subject><subject>False negative</subject><subject>Floating cutoff</subject><subject>Genetic Testing - methods</subject><subject>Genetic Testing - standards</subject><subject>Genetic Testing - statistics & numerical data</subject><subject>Humans</subject><subject>Infant, Newborn</subject><subject>Mutation</subject><subject>Neonatal Screening - methods</subject><subject>Neonatal Screening - standards</subject><subject>Newborn screen</subject><subject>Quality improvement</subject><subject>Retrospective Studies</subject><subject>Sensitivity</subject><subject>Sensitivity and Specificity</subject><subject>Trypsinogen - analysis</subject><issn>1096-7192</issn><issn>1096-7206</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1v1DAQhi0Eoh_wC5CQb3BJGDtxPg4cqi0fK1UgoXK2HHu8eBXHi520Wn49TrflyGE0I8078-p9CHnDoGTAmg_78uh3HksOnJXQlQDiGTln0DdFy6F5_jSznp-Ri5T2AIyJvn5Jzqq67nrWwjn5s_WHGO7ctKNhmXXwmKgNkW7CGKIy4V2i2x-3xVrX366oPqbZaWrdEENyiU54P4Q40aQj4rR-UeMuRDf_8nQ4UucPI3qc5nVjx6AeBr3Mwdr0irywakz4-rFfkp-fP91uvhY3379sN1c3ha5EPxcGqpYJUXOlGoGct70Gq7GrcoBmaCvTcQTRM1AKmbFt09emwk53ZmihFrq6JO9Pf3PQ3wumWXqXNI6jmjAsSXLRZjAgWJOl1Umqc7wU0cpDdF7Fo2QgV-hyLx-gyxW6hE5m6Pnq7aPBMng0_26eKGfBx5MAc8w7h1Em7XDSaFxEPUsT3H8N_gID4JVq</recordid><startdate>202109</startdate><enddate>202109</enddate><creator>Martiniano, Stacey L.</creator><creator>Croak, Kendra</creator><creator>Bonn, Gregory</creator><creator>Sontag, Marci K.</creator><creator>Sagel, Scott D.</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202109</creationdate><title>Improving outcomes for Colorado's IRT-IRT-DNA cystic fibrosis newborn screening algorithm by implementing floating cutoffs</title><author>Martiniano, Stacey L. ; Croak, Kendra ; Bonn, Gregory ; Sontag, Marci K. ; Sagel, Scott D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-d03715542aa65e2279c0fce839176b73d82e05910aae1df7694d3e8c8db7045c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Cystic fibrosis</topic><topic>Cystic Fibrosis - diagnosis</topic><topic>Cystic Fibrosis - genetics</topic><topic>Data Interpretation, Statistical</topic><topic>False negative</topic><topic>Floating cutoff</topic><topic>Genetic Testing - methods</topic><topic>Genetic Testing - standards</topic><topic>Genetic Testing - statistics & numerical data</topic><topic>Humans</topic><topic>Infant, Newborn</topic><topic>Mutation</topic><topic>Neonatal Screening - methods</topic><topic>Neonatal Screening - standards</topic><topic>Newborn screen</topic><topic>Quality improvement</topic><topic>Retrospective Studies</topic><topic>Sensitivity</topic><topic>Sensitivity and Specificity</topic><topic>Trypsinogen - analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Martiniano, Stacey L.</creatorcontrib><creatorcontrib>Croak, Kendra</creatorcontrib><creatorcontrib>Bonn, Gregory</creatorcontrib><creatorcontrib>Sontag, Marci K.</creatorcontrib><creatorcontrib>Sagel, Scott D.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Molecular genetics and metabolism</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Martiniano, Stacey L.</au><au>Croak, Kendra</au><au>Bonn, Gregory</au><au>Sontag, Marci K.</au><au>Sagel, Scott D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improving outcomes for Colorado's IRT-IRT-DNA cystic fibrosis newborn screening algorithm by implementing floating cutoffs</atitle><jtitle>Molecular genetics and metabolism</jtitle><addtitle>Mol Genet Metab</addtitle><date>2021-09</date><risdate>2021</risdate><volume>134</volume><issue>1-2</issue><spage>65</spage><epage>67</epage><pages>65-67</pages><issn>1096-7192</issn><eissn>1096-7206</eissn><abstract>The Colorado Newborn Screening Program (CO-NBS) screens for cystic fibrosis (CF) by measuring immunoreactive trypsinogen (IRT) from two screens coupled with DNA analysis (IRT/IRT/DNA). 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| ispartof | Molecular genetics and metabolism, 2021-09, Vol.134 (1-2), p.65-67 |
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| source | MEDLINE; ScienceDirect Journals (5 years ago - present) |
| subjects | Algorithms Cystic fibrosis Cystic Fibrosis - diagnosis Cystic Fibrosis - genetics Data Interpretation, Statistical False negative Floating cutoff Genetic Testing - methods Genetic Testing - standards Genetic Testing - statistics & numerical data Humans Infant, Newborn Mutation Neonatal Screening - methods Neonatal Screening - standards Newborn screen Quality improvement Retrospective Studies Sensitivity Sensitivity and Specificity Trypsinogen - analysis |
| title | Improving outcomes for Colorado's IRT-IRT-DNA cystic fibrosis newborn screening algorithm by implementing floating cutoffs |
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