Evidence map›Paper›PMID 26293390›Full record

ArticleEuropean journal of pediatrics2016

Screening for cystic fibrosis in New York State: considerations for algorithm improvements.

Denise M Kay, Breanne Maloney, Rhonda Hamel, Melissa Pearce, Lenore DeMartino, Rebecca McMahon, Emily McGrath, Lea Krein, Beth Vogel, Carlos A Saavedra-Matiz and 2 more

Abstract read
PubMed Publisher
In one paragraph

Article in European journal of pediatrics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Neonatal Screening for Cystic Fibrosis in Hungary-First-Year Experiences.International journal of neonatal screening · 2023
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Denise M KayDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. denise.kay@health.ny.gov.
Breanne MaloneyDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. breanne.maloney@health.ny.gov.
Rhonda HamelDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. rhonda.hamel@health.ny.gov.
Melissa PearceDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. melissa.pearce@health.ny.gov.
Lenore DeMartinoDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. lenore.demartino@health.ny.gov.
Rebecca McMahonDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. rebecca.mcmahon@health.ny.gov.
Emily McGrathDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. emily.mcgrath@health.ny.gov.
Lea KreinDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. lea.krein@health.ny.gov.
Beth VogelDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. beth.vogel@health.ny.gov.
Carlos A Saavedra-MatizDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. carlos.saavedra@health.ny.gov.
Michele CagganaDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. michele.caggana@health.ny.gov.
Norma P TavakoliDivision of Genetics, Wadsworth Center, New York State Department of Health, David Axelrod Institute, 120, New Scotland Ave., Albany, NY, 12208, USA. norma.tavakoli@health.ny.gov.
New York State Department of Health · USWadsworth Center · USUniversity at Albany, State University of New York · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Newborn screening for cystic fibrosis (CF), a chronic progressive disease affecting mucus viscosity, has been beneficial in both improving life expectancy and the quality of life for individuals with CF. In New York State from 2007 to 2012 screening for CF involved measuring immunoreactive trypsinogen (IRT) levels in dried blood spots from newborns using the IMMUCHEM(™) Blood Spot Trypsin-MW ELISA kit. Any specimen in the top 5% IRT level underwent DNA analysis using the InPlex(®) CF Molecular Test. Of the 1.48 million newborns screened during the 6-year time period, 7631 babies were referred for follow-up. CF was confirmed in 251 cases, and 94 cases were diagnosed with CF transmembrane conductance regulated-related metabolic syndrome or possible CF. Nine reports of false negatives were made to the program. Variation in daily average IRT was observed depending on the season (4-6 ng/ml) and kit lot (<3 ng/ml), supporting the use of a floating cutoff. The screening method had a sensitivity of 96.5%, specificity of 99.6%, positive predictive value of 4.5%, and negative predictive value of 99.5%.

conclusionConsiderations for CF screening algorithms should include IRT variations resulting from age at specimen collection, sex, race/ethnicity, season, and manufacturer kit lots. WHAT IS KNOWN: Measuring IRT level in dried blood spots is the first-tier screen for CF. Current algorithms for CF screening lead to substantial false-positive referral rates. WHAT IS NEW: IRT values were affected by age of infant when specimen is collected, race/ethnicity and sex of infant, and changes in seasons and manufacturer kit lots The prevalence of CF in NYS is 1 in 4200 with the highest prevalence in White infants (1 in 2600) and the lowest in Black infants (1 in 15,400).

Indexed as

AlgorithmsCystic FibrosisCystic Fibrosis Transmembrane Conductance RegulatorFemaleGenetic TestingHumansInfantInfant, NewbornMaleMutationNeonatal ScreeningNew YorkPrevalenceSensitivity and SpecificityTrypsinogenCystic Fibrosis Transmembrane Conductance RegulatorTrypsinogenCFTRCystic fibrosisImmunoreactive trypsinogenMutation analysisNewborn screening

Identifiers

PMID26293390
OpenAlexW1664470896

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.