Newborn Screening for Cystic Fibrosis
Martin Kharrazi, PhD, MPHa, Juan Yang, PhD, MSa, Tracey Bishop, BSa, Shellye Lessing, MSa, Suzanne Young, MPHb, Steven Graham, MPHa,b, Michelle Pearl, PhDb, Helen Chow, PhDa, Thomson Ho, PhDa, Robert Currier, PhDa, Leslie Gaffneya, Lisa Feuchtbaum, DrPHa, on behalf of the California Cystic Fibrosis Newborn Screening Consortium
abstractOBJECTIVES:This article describes the methods used and the program performance results for the
ﬁrst 5 years of newborn screening for cysticﬁbrosis (CF) in California.
METHODS:From July 16, 2007, to June 30, 2012, a total of 2 573 293 newborns were screened for CF by using a 3-step model: (1) measuring immunoreactive trypsinogen in all dried blood spot specimens; (2) testing 28 to 40 selected cysticﬁbrosis transmembrane conductance regulator (CFTR)mutations in specimens with immunoreactive trypsinogen values$62 ng/mL (top 1.6%); and (3) performing DNA sequencing on specimens found to have only 1 mutation in step 2. Infants with$2 mutations/variants were referred to CF care centers for diagnostic evaluation and follow-up. Infants with 1 mutation were considered carriers and their parents offered telephone genetic counseling.
RESULTS:Overall, 345 CF cases, 533 CFTR-related metabolic syndrome cases, and 1617 carriers were detected; 28 cases of CF were missed. Of the 345 CF cases, 20 (5.8%) infants were initially assessed as having CFTR-related metabolic syndrome, and their CF diagnosis occurred after age 6 months (median follow-up: 4.5 years). Program sensitivity was 92%, and the positive predictive value was 34%. CF prevalence was 1 in 6899 births. A total of 303CFTRmutations were identiﬁed, including 78 novel variants. The median age at referral to a CF care center was 34 days (18 and 37 days for step 2 and 3 screening test–positive infants, respectively).
CONCLUSIONS:The 3-step model had high detection and low false-positive levels in this diverse population.
WHAT’S KNOWN ON THIS SUBJECT:Several newborn screening models for cysticﬁbrosis (CF) exist, including DNA-based models that use mutation panels. There is limited experience with models (such as used in California) that include comprehensive DNA sequence testing methods as part of newborn screening.
WHAT THIS STUDY ADDS:California’s 3-step newborn screening model for CF showed high efﬁciency, sensitivity, and positive predictive value. More than 300 mutations were found, reﬂecting the state’s diverse population. Some CF transmembrane conductance regulator–related metabolic syndrome cases converted to CF over time.
California Department of Public Health, Richmond, California; andbSequoia Foundation, La Jolla, California
Dr Kharrazi conceptualized and designed the study and drafted the initial manuscript; Dr Yang assisted with data collection at the cysticﬁbrosis specialty care centers (CFCs), analyzed and interpreted the data, and reviewed and revised the manuscript; Ms Bishop helped design the data collection instruments, helped coordinate data collection at the CFCs, and critically reviewed the manuscript; Ms Lessing conceptualized and designed the cysticﬁbrosis carrier genetic counseling aspect of the study, coordinated data collection of genetic counseling information, and critically reviewed the manuscript; Ms Young helped design the data collection instruments, helped coordinate data collection at the CFCs, helped analyze and interpret the data, and critically reviewed the manuscript; Mr Graham helped design the 3-step algorithm and the data collection instruments, linked screen-positive cases to death record data, helped analyze and interpret the data, and critically reviewed the manuscript; Dr Pearl helped design the 3-step algorithm and the data collection instruments and critically reviewed and revised the manuscript; Dr Chow assisted in the development of cysticﬁbrosis laboratory testing, reviewed laboratory results, and critically reviewed the manuscript; Dr Ho supervised screening laboratory data collection and critically reviewed and revised the manuscript; Dr Currier assisted with analysis and interpretation of the data and critically reviewed the manuscript; Ms Gaffney oversaw the design of the data collection instruments and the study, and critically reviewed the manuscript; Dr Feuchtbaum assisted with analysis and interpretation of the data and critically reviewed and revised the manuscript; and all authors approved the
ﬁnal manuscript as submitted and agree to be accountable for all aspects of the work. www.pediatrics.org/cgi/doi/10.1542/peds.2015-0811
Cysticﬁbrosis (CF) is the most common life-limiting autosomal recessively inherited disease in white populations.1It is caused by
mutations in the cysticﬁbrosis transmembrane conductance regulator (CFTR) gene that encodes the CFTR protein, which participates inﬂuid homeostasis across mucosal surfaces.2In 2004, the Centers for Disease Control and Prevention concluded that newborn screening (NBS) for CF was justiﬁed to minimize the impact of nutritional deﬁciencies and poor growth (and possibly lung disease) caused by CF through early detection and proper care.3By 2010, NBS for CF had been instituted throughout the United States.4
During development of NBS for CF in California (2000–2005), the California Department of Public Health Genetic Disease Screening Program (GDSP) established 6 requirements and goals (Fig 1). One challenge that California faced was a poor understanding of commonCFTR mutations within its large and heterogeneous population. After establishing a CF registry and researching theCFTRmutations and immunoreactive trypsinogen (IRT) levels in CF case subjects and control subjects from 3 main race/ethnic groups in California, GDSP developed a 3-step model (IRT–mutation panel–DNA sequencing) for CF NBS.
The goal of this article is to present the methods used and program performance results for theﬁrst 5 years of routine CF NBS in California after 2 to 7 years (average: 4.5 years)
of follow-up. We discuss how well the California model met its goals and the implications of theﬁndings on our current understanding of CF and cysticﬁbrosis transmembrane conductance regulator–related metabolic syndrome (CRMS)5and on other commonly used CF NBS models.
The study population included infants who underwent CF NBS in California from July 16, 2007, to June 30, 2012. The CF algorithm (Fig 2) uses the base program’s 1-time collection onﬁlter paper of blood spots through a heel stick at$12 hours of age (median: 30 hours). Theﬁlter paper card is transported to 1 of 7
laboratories for analysis of serum IRT by using the AutoDELFIA Neonatal IRT Kit (PerkinElmer, Waltham, MA). Quality control samples are
incorporated into each assay batch on every analytical instrument used in CF screening. Daily quality control results are charted and examined for short- and long-term drift. Specimens with an IRT level$62 ng/mL (top 1.6%) are sent for analysis at the Stanford Molecular Pathology Laboratory (Stanford University, Palo Alto, CA) using a 28- to 40-CFTR mutation panel (Table 1). The IRT cutoff was determined by maximizing the sum of sensitivity and speciﬁcity in a California study of archived blood spots from 715 prescreening CF case subjects and 5026 control subjects. Mutations on the California panel were selected accordingly: (1) highest allelic frequencies from a second study of 1648 comprehensively genotyped, prescreening, California CF cases to achieve a race/ethnicity-speciﬁc rate$95% of CF case detection through mutation panel testing in Hispanic, non-Hispanic white, and African-American subjects; (2) include 1 prevalent gross deletion not detectable by using DNA sequence testing, CFTRdele2,3(21kb)6; and (3) include only mutations with clear CF-causing potential. For example, the common yet variable R117H
mutation was not included on the panel.7After testing, IRT levels and mutation panel results (when IRT is positive) are reported at the same time as analyte results for other screened disorders. Newborns with 2 mutations identiﬁed after panel testing are referred to 1 of 17 California- and Cystic Fibrosis Foundation (CFF)-approved pediatric cysticﬁbrosis specialty care center (CFCs) for diagnostic evaluation and follow-up.
Specimens found to have only 1 mutation after panel testing are sent for eitherCFTRgene scanning and sequence analysis using the Ambry Test: CF (Ambry Genetics, Aliso Viejo, CA)8,9from July 16, 2007 to June 30, 2010 or directCFTRDNA Sanger sequencing at Stanford Molecular Pathology Laboratory from July 1, 2010 to June 30, 2012. These sequencing methods are highly comprehensive and capable ofﬁnding novel mutations. Sequencing results are reported via a supplemental report to hospitals and primary care providers. If only 1 mutation is identiﬁed, the newborn is considered a screening test–negative carrier, and parents and the primary care provider are sent letters describing the infant’s carrier status. Parents of carriers are offered free telephone genetic counseling in Spanish or English. If$2 mutations (as deﬁned in Fig 310–12) are identiﬁed after sequencing, primary care providers are contacted by telephone to arrange referral to a CFC for genetic counseling of parents, and sweat chloride tests (SCTs) and other diagnostic tests of the child. Parents are sent a letter and pamphlet with information about the positive screening results and the need for conﬁrmatory SCTs.
Pediatric CFCs in California routinely report all subjects diagnosed with CF with negative CF NBS test results to GDSP as part of their quality assurance procedures. The reasons why CF was missed are thoroughly investigated, and they may include
performing multiplex ligation-dependent probe ampliﬁcation13 (MRC-Holland, Amsterdam, The Netherlands) to determine gross deletions or duplications when 1 or no mutation was detected. These aforementioned methods meet or exceed implementation, design, and reporting guidelines for CF NBS programs.14
SCT results and diagnostic and clinical follow-up data are collected from CFCs via GDSP’s secure, online screening information system. SCTs are performed by CFF-accredited laboratories according to current standards15and guidelines.16Parents are encouraged to provide salt supplementation and hydration to the infant before testing. Follow-up is conducted with the use of guidelines developed by CFCs and GDSP.17 Diagnostic services and medical care
for uninsured families are covered by California Children’s Services.
CFCs make a determination for aﬁnal diagnosis of CF or CRMS by using published guidelines.5,18DNA testing on biological parents of screening test–positive infants with nonelevated SCT values was recommended and then offered by GDSP starting July 1, 2010, to determine thecis/trans mutation phase (ie, on same/different chromosomes, respectively). In 2014, all CF screening test–positive and false-negative CF cases were reviewed for accuracy and consistency to conﬁrm the diagnoses of CF, CRMS, and CF carrier. Newborns with positive CF screening test results were considered to have CRMS unless there was evidence of$1 of the following CF diagnostic criteria: 2 identiﬁed CF-causing mutations (per the Clinical and Functional Translation of
CFTRProject [CFTR2]),19a SCT value$60 mmol/L, last fecal elastase value#200µg/g, neonatal meconium ileus, a sibling with the same genotype and positive SCT results diagnosed with CF, or physician’s discretion. A carrier diagnosis was given when known mutations/ variants were documented to be in thecisphase according to parent studies or the literature.
The CF prevalence, detection rate, and positive predictive value were estimated overall and according to 5 race/ethnicity categories. Age at blood collection, IRT result, panel mutation result, sequencing result, referral,ﬁrst evaluation,ﬁrst SCT, diagnosis, and treatment initiation were reported overall and according to panel- and sequence-positive groups by using the 25th, 50th, and 75th percentiles. The study protocol
was approved by the California Health and Human Services Agency Committee for the Protection of Human Subjects (project no. 12-0600354).
Figure 2 presents the number of infants in each step of the program. During theﬁrst 5 years, 2 573 293 newborns had an IRT test completed, representing 98.8% of births. Of these, 40 646 (1.6%) had an IRT
value$62 ng/mL and were tested for 28 to 40CFTRmutations. The allelic frequency of these mutations is found in Supplemental Table 8. No panel mutations were identiﬁed in 38 149 (93.9%) hypertrypsinogenemic newborns. Two panel mutations were identiﬁed in 194 (0.5%), and these newborns were referred to a CFC for SCT and follow-up. Of the 174 (89.7%) infants with 2 panel mutations who underwent SCT, 162 (93.1%) had initial valid positive test results ($60 mmol/L).
Of the hypertrypsinogenemic newborns, 2303 (5.7%) had 1 panel mutation, and their blood spots subsequently underwent DNA sequencing. After sequencing, 1485 (64.5%) newborns still had only 1 mutation identiﬁed, and telephone genetic counseling was offered to these parents. One or more parents of 180 (12.1%) infants received such counseling.
Two or more mutations were identiﬁed in 818 (35.5%) newborns (64 had$3 mutations) after sequencing and were referred to a CFC for SCT and follow-up. Of these, 77 (9.4%) had an initial valid positive SCT result, and 76 were diagnosed with CF at,6 months of age (median age: 51 days; 25th–75th percentile: 42–64 days). Of the 818 newborns, 741 (90.6%) had a nonpositive initial valid SCT result (,60 mmol/L) and were followed up by a CFC. To date, 132 (17.8%) of these newborns were determined to be CF carriers (Fig 2). Of the 741 newborns, 74 (10.0%) have been diagnosed with CF (median age: 129.5 days; 25th–75th percentile: 61–272 days) with the remaining noncarriers given an initial CRMS diagnosis. Twenty initial CRMS case subjects had their diagnosis changed to CF at.6 months of age (Table 2). CRMS remained the diagnosis for 533 (71.9%) children; 47 (8.8%) of these children had a maximum SCT value in the
intermediate range (40–59 mmol/L). A typical child with CRMS had a high IRT value, 1 panel mutation, and
$1 mutation/variant from DNA sequencing in thetransphase and a maximum SCT result,60 mmol/L.
Table 3 displays the median age at blood collection, IRT test results, panel mutation test results, and sequencing results for all CF NBS screening test–positive children; the data are stratiﬁed according to screening step. Typically, newborns had an IRT result by 5 days of age, and if the IRT level was$62 ng/mL, the mutation panel was completed by
TABLE 1 Chronology of theCFTRMutation Panels Used by the California NBS Program: July 16,
2007, to June 30, 2012
Date Added Mutations Added or Removed–cDNA Name (Legacy Name)
July 16, 2007 c.164+2T.A (296+2T.A) 28 c.254G.A (G85E)
c.274-1G.A (406-1G.A) c.489+1G.T (621+1G.T) c.579+1G.T (711+1G.T) c.595C.T (H199Y) c.933_935delCTT (F311del) c.1000C.T (R334W) c.1519_1521delATC (I507del) c.1521_1523delCTT (F508del) c.1585-1G.A (1717-1G.A) c.1624G.T (G5423) c.1646G.A (S549N) c.1652G.A (G551D) c.1657C.T (R5533) c.1675G.A (A559T) c.1680-1G.A (1812-1G.A)
c.1973-1985del13insAGAAA (2105-2117del13insAGAAA) c.2175_2176insA (2307insA)
c.2988+1G.A (3120+1G.A) c.3196C.T (R1066C) c.3266G.A (W10893) c.3485G.T (R11623)
c.3611G.A (W12043[3743G.A]) c.3717+12191C.T (3849+10kbC.T) c.3744delA (3876delA)
c.3846G.A (W12823) c.3909C.G (N1303K)
October 4, 2007 c.1153_1154insAT (1288insTA) 29 December 12, 2007 c.54-5940_273+10250del21kb (CFTRdele2,3(21kb)) 38
c.531delT (663delT) c.613C.T (P205S) c.803delA (935delA) c.1475C.T (S492F)
c.1923_1931del9insA (2055del9.A) c.223C.T (R753)
August 12, 2008 c.988G.T (G3303) 40
c.3612G.A (W12043[3744G.A]) c.3659delC (3791delC)
c.164+2T.A (296+2T.A), removed
16 days. For those with only 1 panel mutation, sequencing results were available at a median age of 36 days. The ages at referral,ﬁrst evaluation at a CFC,ﬁrst SCT result, diagnosis, and treatment initiation data are also given in Table 3. Newborns were referred within 2 days of being reported as screening test–positive. Most (75%) panel-positive cases were evaluated at a CFC when the child was#30 days old, with a median age at diagnosis and treatment initiation of 25 and
24 days, respectively. Seventy-ﬁve percent of infants identiﬁed according to sequencing results were evaluated at a CFC by 60 days of age, with a median age at diagnosis of 148 days.
Thirteen deaths occurred among the 1012 children who were CF screening test–positive. Five died (of prematurity and/or malformations) before follow-up could be completed, and 8 died after referral. Four of these deaths were likely CF related (ages 1, 8, 12, and 36 months) (Supplemental Table 9).
In 5 years, GDSP has thus far identiﬁed 1617 CF carriers (1485 screening test–negative and 132 screening test–positive children); 533 CRMS cases; and 373 CF cases (194 [∼39 per year] with 2 mutations from the panel in step 2, 151 [∼30 per year] infants by sequencing in step 3 (allelic mutation frequency in Supplemental Table 10), and 28 [∼6 per year] screening test–negative).
Of these missed cases, 14 (50%) had an IRT value below the cutoff, 9 (32.1%) had no panel mutations identiﬁed, and 5 (17.9%) did not have a second mutation detected after sequencing (Table 4).
Table 5 illustrates the 373 CF cases distributed according to the 6 diagnostic review criteria used. A total of 70.8% of the CF cases met$2 criteria. Small percentages had at least 1 SCT result$60 mmol/L (11.5%) or 2 CF-causing mutations (8.9%) as the sole criterion. The remainder of the CF cases (8.8%) were diagnosed based solely on other clinical evidence or physician’s discretion. Overall, 53 (14.2%) of CF case subjects had meconium ileus (43 detected and 10 missed by the screening program).
Table 6 provides selected population and screening statistics. CF birth prevalence was 1 in 6899 overall, 1 in 4162 in non-Hispanic white subjects, 1 in 9259 in Hispanic subjects, and 1 in 9071 in African-American subjects. The overall case detection rate and positive predictive value for the program were 92% and 34%, respectively. Detection rates were 91% to 100% for California’s 3 main race/ethnicity groups.
Over the study period, 303 different
CFTRmutations were identiﬁed, including 78 novel variants. Of 85 children carrying a novel variant, 21 (24.7%) have been diagnosed with CF to date.
This 5-year analysis from the California CF program has many strengths. Theﬁndings were derived from a diverse and large number of screened newborns (.2.5 million), and genotyping as part of screening was comprehensive in terms of mutations and Intron 8 Poly (T) Tract (IVS 8) status before referral to CFCs. This screening provided timely, high-quality genotype information to CFC staff so that important decisions could be made regarding clinical
Deﬁnition of a CFTR mutation from DNA se-quence testing used by the California NBS program: July 16, 2007, to June 30, 2012. NCBI, National Center for Biotechnology Information.
TABLE 2 Genotype of 20 Children According to Age Diagnosis Was Changed From CRMS to CF in
the California NBS Program: July 16, 2007, to June 30, 2012
GenotypeacDNA Name (Legacy Name)
No. of Patients
Age in Years at Diagnostic Changeb c.1521_1523delCTT (F508del) / c.[1210–12];[1210-34TG]
5 1 (n= 2) 3 (n= 1) 4 (n= 2) c.1521_1523delCTT (F508del) / c.3454G.C (D1152H)c 2 0.5d(n= 1) 2 (n= 1) c.1521_1523delCTT (F508del) / c.350G.A (R117H)c 2 1 (n= 1) 2d(n= 1) c.223C.T (R753) / c.[1210–12];[1210-34TG]
c.2988+1G.A (3120+1G.A) / c.164+28A.G (296+28A.G)e 1 1d c.1521_1523delCTT (F508del) / c.226C.A (L32M)e 1 2 c.1521_1523delCTT (F508del) / c.3475T.C (S1159P)e 1 2 c.933_935delCTT (delF311)e/ c.[1210–12];[1210-34TG]
c.531delT (663delT) / c.314T.A (I105N)e 1 3
c.1521_1523delCTT (F508del) / c.1841A.G (D614G)e 1 3
c.1521_1523delCTT (F508del) / c.290T.C (V97A)e 1 3
c.1519_1521delATC (I507del) / c.[1210–12];[1210-34TG] (IVS8 (TG)12-5T)c
c.1624G.T (G5423) / c.3454G.C (D1152H)c 1 5 c.2988+1G.A (3120+1G.A) / c.[1210–12];[1210-34TG]
(IVS 8 (TG)12-5T)c
aCF-causing mutation according to CFTR2,19unless noted.
bDiagnosis change from CRMS to CF due to positive SCT results ($60 mmol/L), unless noted. cMutation of varying clinical consequence according to CFTR2.
dDiagnosis change due to abnormal fecal elastase results (#200µg/g). eMutation not evaluated by CFTR2.
care, testing, and treatment,
especially now that mutation-speciﬁc therapy technology is advancing.20 The clinical diagnosis of CF was reviewed and veriﬁed by using a set of standard criteria. The length of the
follow-up period for screening test–positive individuals extended into early childhood, with CF diagnosed in children as old as 7 years. GDSP made repeated efforts to ensure thorough reporting of all CF
case reports. Despite these efforts, follow-up of CRMS cases was less complete than for CF cases after 1 year of age. Because children who become symptomatic presumably return to a CFC, thereby triggering reporting to
TABLE 3 Time From Birth to Critical Screening Steps and Critical Follow-up Steps According to CF Screening Test–Positive Step in the California NBS
Program: July 16, 2007, to June 30, 2012
Screening and Follow-up Step Total (N= 1012) Panel Positive (n= 194) Sequencing Positive (n= 818)
Median 25th%–75th% Median 25th%–75th% Median 25th%–75th% Time from birth to critical screening steps
Age at blood spot collection, h 26 23–35 29 24–41 26 23–34
Age at IRT test result (step 1) 5 4–6 5 4–7 5 4–6
Age at panel result (step 2) 16 14–18 16 14–19 16 14–19
Age at sequencing result (step 3) — — — — 36 29–43
Time from birth to critical follow-up steps
Age at referral 34 26–43 18 16–20 37 31–45
Age atﬁrst evaluation 47 35–61 24 18–32 51 41–64
Age atﬁrst SCT 56 42–78 46.5 28–85 57 44–77
Age at diagnosis 88 46–248 25 18–41 148 60–296
Age at treatment initiation 53 34–94 24 19–35 67 48–152.5
All values are in days unless otherwise noted.—, not applicable.
TABLE 4 Numbers and Selected Characteristics of 28 False-Negative CF Cases According to Screening Step in the California NBS Program: July 16, 2007,
to June 30, 2012
Screening Step N IRT Level (ng/mL)a/Genotype, cDNA Name (Legacy Name) Race/Ethnicity Reason for CF Diagnosis
1. IRT below cutoff 14 9 / (mutations not identiﬁed) White (n= 5) Meconium ileus (n= 2) 9 / c.1727G.C (G576A)/ c.2002C.T (R668C) Hispanic (n= 3) Family history (n= 2) 16 / c.1521_1523delCTT (F508del)/ c.1624G.T (G5423) Other/multiple (n= 6) Symptoms (n= 12) 28 / c.1521_1523delCTT (F508del)/ c.1521_1523delCTT (F508del)
28 / c.14C.T (P5L)/ c.870-7_870-5delTTT (1002-7delTTT) 29 / (mutations not identiﬁed)
31 / c.1521_1523delCTT (F508del)/ c.2175_2176insA (2307insA) 31 / (mutation not identiﬁed)/ c.[1210–12];[1210-34TG]
(IVS 8 (TG)13-5T)
34 / c.1521_1523delCTT (F508del)/ c.933_935delCTT (F311del) 48 / c.1521_1523delCTT (F508del)/ c.1521_1523delCTT (F508del) 51 / c.1521_1523delCTT (F508del)/ c.1521_1523delCTT (F508del) 52 / (mutations not identiﬁed)
54 / c.1521_1523delCTT (F508del)/ c.1792_1798delAAAACTA (1924del7)
58 / c.303_304insA (435insA)/ c.617T.G (L206W)
2. No mutations on panel 9 c.2822delT/ c.2822delT (n= 3) Hispanic (n= 7) Meconium ileus (n= 4) c.1153_1154insAT (1288insTA)/ c.1153_1154insAT (1288insTA)b Other/multiple (n= 2) Family history (n= 4) c.165-3C.T (297-3C.T)/ c.4147_4148insA (4279insA)/
Symptoms (n= 8)
c.220C.T (R74W)/ c.601G.A (V201M)/ c.2562T.G (T854T or 2694T/G)/ c.[1210–12];[1210-34TG] (IVS 8 (TG)13-5T) c.579+5G.T (711+5G-.T)/ c.948delT (1078delT)
c.3368-2A.G (3500-2A-.G)/ c.1679+1643G.T (1811+1643G.T) c.1792_1798delAAAACTA (1924del7)/ c.2668C.T (Q8903) 3. Second mutation not detected by
using DNA sequencing
5 c.1521_1523delCTT (F508del)/ (Ex6b_10dup) White (n= 3) Meconium ileus (n= 4) c.1652G.A (G551D)/ c.3964-78_4242+577del (CFTRdel22,23) Hispanic (n= 1) Family history (n= 2) c.1519_1521delATC (I507del)/ c.1680-877G.Tc Unknown (n= 1) Symptoms (n= 3) c.1521_1523delCTT (F508del)/ c.328G.C (D110H)d
c.1521_1523delCTT (F508del)/ (mutation not identiﬁed)
cDNA, complementary DNA.
aIRT level listed only when below the cutoff value (62 ng/mL).
bCase missed before mutation was added to the California mutation panel.
GDSP, underreporting of CF was probably small.
Unlike traditional 2-step IRT-DNA programs, which consider any hypertrypsinogenemic newborn with
$1CFTRmutation as screening test–positive, the California program required$2 mutations to be considered positive.CFTRsequencing, as a third step conducted in,1 in 1000 infants screened, reduced the number of CF carriers referred for SCT by two-thirds (1485 fewer newborns) compared with the 2-step model.
Using a broad deﬁnition for a secondCFTRmutation, 35% of hypertrypsinogenemic infants with 1 mutation from the California panel had a second mutation/variant (or more) identiﬁed from sequencing. Theﬁndings of 303 differentCFTR mutations, including 78 novel variants, indicate great population heterogeneity and novelty. Previously, an in-depth analysis of a 3-year subset of the current data showed that a signiﬁcant portion (10 of 55 [18%]) of the novel mutations were likely CF-causing,21aﬁnding that is consistent with this 5-year study.
The presence of$2 mutations in all screening test–positive infants by deﬁnition prompted CFCs to implement a diagnostic follow-up period of at least 1 year in
asymptomatic infants with initial SCT values,60 mmol/L. This method resulted in detection of 74 (27.3%) more CF cases, the diagnosis in 20 occurring after 6 months of age; it also revealed that in a portion of screening test–positive infants, SCT and/or fecal elastase values changed into the CF diagnostic range as the child aged. Many of the mutations associated with this change were of varying clinical consequence (Table 2).19A recent study of newborns with an initial CRMS diagnosis followed up for 3 years by 8 CFCs outside California found that 2 (3%) of 75 obtained a subsequent diagnosis of CF due to elevated SCT values,22a
ﬁgure consistent with that reported here in California. Longer term follow-up studies (probably into adulthood) are needed to better understand the factors that contribute to evolution of the CF phenotype.
In an attempt to focus screening on severe CF cases, we split mutation testing into 2 steps (panel and sequencing) and restricted panel mutations to those that we found to be clearly CF-causing in the California population. Theoretically, this approach has maximized severe CF case identiﬁcation in the panel step, compared with most other programs. According to CFTR2, 37 panel mutations are CF-causing, and 3 have not yet been evaluated; this outcome highlights the importance at a regional level of including mutations found in conﬁrmed clinical cases in the screened population and not solely basing the choice of mutations on those evaluated by CFTR2. In the sequencing step, a broad deﬁnition of mutation was used (Fig 3); although this deﬁnition enhanced sensitivity, its use led to a diagnosis of CRMS 1.5 times more common than CF in our screening test–positive population
(533 vs 345, respectively). With traditional IRT-DNA algorithms, these same CRMS cases and others are considered screening test–positive and are referred for SCT; however, after receiving SCT results
,30 mmol/L, most are misdiagnosed as carriers because of a lack of comprehensive genotyping. It is potentially very stressful for parents to learn that their child is screening test–positive and then be told by the CFC that their child does not
currently exhibit signs and symptoms of CF but may do so in the future.23 California uses follow-up guidelines that encourage CFC visits quarterly for at least 1 year for children with CRMS; thus, SCTs can be repeated, symptoms evaluated, and other testing and monitoring performed. The short- and long-term
psychosocial effects on parents and costs to families of caring for a child with CRMS must be evaluated, along with efforts to reduce psychosocial distress. By continuing to limit the deﬁnition of screening test–positive results to only those genotypes that cause CF using knowledge gained over time from the screening program, CFTR2, and elsewhere, the
California algorithm will be able to clarify the value of identifying infants with CRMS as well as continue to adjust the referral algorithm by removing benign variants.24
No CF NBS algorithm will detect all cases of CF. The detection rate of CF in California (total 345 [69 per year]) was 92%, exceeding program expectations of 90%. This rate includes infants with meconium ileus. Because cases of meconium ileus are identiﬁed in the absence of screening, removing these infants from the calculation produces a detection rate of 95%. Reports from other programs typically range from 92% to 98% (Table 7)25–29; however, these rates are likely overestimated due to shorter follow-up periods and/or less rigorous identiﬁcation of missed cases than the present study.
One-half of the missed cases (14 of 28) had an IRT value below the cutoff of 62 ng/mL, corresponding to the top 1.6th percentile. Lowering the cutoff to 49.4 ng/mL, which corresponds to the top fourth percentile used by many states,4would have resulted in 4 fewer cases being missed by the IRT step (or,1 per year). The costs
TABLE 6 Selected CF Population and Screening Statistics According to Race/Ethnicity in the California NBS Program: July 16, 2007, to June 30, 2012
Race/Ethnicity Live Births Screened
CF Screening Test–Positive Subjects
CF Cases Detected From Screening
False-Negative CF Cases
Prevalence at Birth of CF
CF Case Detection Rate, %
Positive Predictive Value, %
Non-Hispanic white 657 597 413 150 8 1/4162 95 36
Hispanic 1 092 619 333 107 11 1/9259 91 32
African American 136 058 70 15 0 1/9071 100 21
Other/multiple 434 174 174 71 8 1/5496 90 41
Unknown 25 629 4 2 1 1/8543 67 50
Total 2 573 293 1012 345 28 1/6899 92 34
TABLE 7 CF Case Detection Rate and Positive Predictive Value for Other Selected NBS Programs
Location Algorithm CF Case Detection Rate, % Positive Predictive Value, % Reference
New South Wales, Australia IRT-IRT 92 5 25
New South Wales, Australia IRT-DNAa 94 28 V. Wiley, PhD, personal communication, 2015; B. Wilcken, MD, personal communication, 2015
Massachusetts IRT-DNA 98 9 26
Wisconsin IRT-DNA 95 9 27
Coloradob IRT-IRT 93 5 28
New York IRT-DNA 98 3 29
and inefﬁciencies to the program that would come with lowering the IRT cutoff value to the top fourth percentile (estimated by GDSP to be approximately twice the costs for mutation testing and genetic counseling for carriers and likely higher costs for additional referrals) are considered excessive compared with the small gain in sensitivity (1%–2%); they would also conﬂict with the program’s goal of equally maximizing both sensitivity and speciﬁcity. In theﬁrst 5 years, there was 1 mutation missed by the panel that appeared in.1 unrelated subjects (c.2822delT/c.2822delT found in 3 Hispanic subjects from 2 unrelated families) (Table 4), suggesting that the program could improve sensitivity∼1% by adding this mutation to California’s
40-mutation panel. The DNA sequencing step missed only a small number of subjects with unique gross insertions or deletions as the second mutation.
The positive predictive value of California’s 3-step program is 34% (31% excluding infants with meconium ileus). Reports from other programs typically range from 5% to 9% (Table 7). Reducing false-positive
ﬁndings produces large savings in program, medical, family, and societal costs, despite costs of US $500 to $1000 incurred by the program per DNA sequencing test. The California
ﬁndings are consistent with those modeled in a cost-effectiveness study of 4 different CF NBS algorithms.30 However, 2 recent studies31,32suggest that IRT/pancreatitis–associated protein algorithms may be even more cost-effective than California’s 3-step algorithm.
Age at reporting CF NBS results and at making a CF diagnosis are 2 challenging areas for the California program. CFF guidelines instruct that SCT should be performed by 2 to 4 weeks of age and diagnosis should occur by 1 to 2 months of age.18The literature suggests that subjects with CF diagnosed within 2 months of life
are most likely to beneﬁt from early interventions.33In California, 74.5% of CF NBS-positive newborns were seen by CFCs before age 2 months; this time frame was largely inﬂuenced by the 2 to 3 weeks needed to complete DNA sequencing. Improvements have been made to reduce this time by conducting both mutation panel and DNA sequence testing in the same physical location and in reducing assay testing time. New technologies, such as next-generation sequencing, may be valuable in further shortening this time.
The uptake of genetic counseling by parents of nearly 1500 nonreferred CF carriers identiﬁed by the program was 12.1%. It is unknown why so many parents are not using the telephone genetic counseling service, designed according to California’s NBS follow-up of hemoglobinopathy traits.34Given the large scale of prenatal CF carrier testing being conducted,35many parents may have already received CF genetic counseling. The program has not evaluated the effectiveness of the telephone genetic counseling program, although such a review is being considered.
Given that an additional 6.2% of CF cases identiﬁed to date were diagnosed after 6 months of age, CF NBS programs that do not conduct comprehensive genotyping (and which rely mainly on elevated SCT values and symptoms at initial follow-up to make a diagnosis of CF) may be mislabeling some infants who actually have CF as CF carriers. It is important that the genetic counseling that follows diagnostic testing emphasize that CF is still possible in these infants and that the appearance of any suggestive CF signs and symptoms as the child ages should result in prompt referral to a CFC for evaluation and
After 5 years, the 3-step (IRT– 40-mutation panel–DNA sequencing) CF NBS model used in a racially and ethnically diverse California
population is meeting its goals of high detection and low false-positive results. The follow-up of newborns with$2 mutations showed that CF cases are not always apparent in the
ﬁrst few months of life. Reliance on an initial SCT result$60 mmol/L (or even$30 mmol/L) to distinguish true CF cases from carriers in the absence of comprehensive genotyping is likely to miss a small portion of CF cases.
Dr Lisa Prach (GDSP) assisted with analyses and an early version of the article. Ruth Koepke (GDSP) helped collect data from CFCs in theﬁrst few years of the California CF NBS program. Dr Iris Schrijver (Stanford Molecular Pathology Laboratory) and Steven Keiles (Ambry Genetics) oversawCFTRmutation testing and results reporting, and they consulted on mutation panel derivation. Drs George Helmer and John Eastman (GDSP Genetic Disease Laboratory) helped in the development, validation, and implementation of laboratory testing methods. Dr Richard Parad (Harvard Medical School) provided useful information on implementation of the California CF NBS Program.
The following CFCs, center directors, and staff clinically followed-up CF NBS-positive newborns; provided the clinical data presented in the article; commented and provided input on multiple versions of the manuscript; and, together with the staff of the GDSP, comprise the California Cystic Fibrosis Newborn Screening
California: Dr Karen Ann Hardy and Deborah Kaley; Center for Excellence in Pulmonary Biology, Stanford University, Palo Alto, California: Dr Carlos E. Milla, Dr Richard Moss, and Dr Jacquelyn M. Zirbes; Sutter Cystic Fibrosis Center, Sutter Memorial Hospital, Sacramento, California: Dr Bradley Chipps, Dr Myrza Perez, Susan O’Bra, and Kasey Pearson; Kaiser Permanente Los Angeles Medical Center, Los Angeles, California: Dr Muhammad M. Saeed; Children’s Hospital Central California, Madera, California: Dr Reddivalam Sudhakar and Susan Lehto; University of California, San Francisco Medical Center, San Francisco, California: Dr Dennis Nielson, Diana Dawson, and Martha Richards; Kaiser Permanente Northern California, Oakland, California: Dr Gregory F. Shay and Mary Seastrand; University of
California Davis Medical Center, Sacramento, California: Dr Ruth McDonald, Dr Sanjay Jhawar, and Kim Franz; Division of Pediatric
Pulmonology, Children’s Hospital of Orange County, Orange, California: Dr Bruce Nickerson and Dawn McRitchie; Ventura County Medical Center, Ventura, California:
Dr Christopher Landon and Ann Thompson; Pediatric Pulmonary Division, Miller Children’s Hospital, Long Beach, California: Dr Eliezer Nussbaum, Dr Terry Chin, and Jill M. Edwards; Naval Medical Center, San Diego, California: Dr Henry Wojtczak; Department of Pediatrics, Division of Pediatric Pulmonology, Mattel Children’s Hospital, University of California, Los Angeles, California: Dr Marlyn S. Woo and Elaine Harrington; and Kaiser Permanente, San Diego, California: Susan D. Noetzel.
CFC: cysticﬁbrosis specialty care center
CFF: Cystic Fibrosis Foundation CFTR: cysticﬁbrosis
transmembrane conductance regulator CFTR2: The Clinical and Functional
Translation of CFTR Project
CRMS: cysticﬁbrosis transmembrane conductance regulator–related metabolic syndrome GDSP: California Department of
Public Health Genetic Disease Screening Program IRT: immunoreactive trypsinogen NBS: newborn screening
SCT: sweat chloride test
Address correspondence to Martin Kharrazi, PhD, MPH, Environmental Health Investigations Branch, California Department of Public Health, 850 Marina Bay Pkwy, Building P, Floor 3, Richmond, CA 94804. E-mail: firstname.lastname@example.org
PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275). Copyright © 2015 by the American Academy of Pediatrics
FINANCIAL DISCLOSURE:The authors have indicated they have noﬁnancial relationships relevant to this article to disclose.
FUNDING:No external funding.
POTENTIAL CONFLICT OF INTEREST:The authors have indicated they have no potential conﬂicts of interest to disclose.
COMPANION PAPER:A companion to this article can be found on page 1181, and online at www.pediatrics.org/cgi/doi/10.1542/peds.2015-3490.
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DOI: 10.1542/peds.2015-0811 originally published online November 16, 2015;
Lisa Feuchtbaum and on behalf of the California Cystic Fibrosis Newborn Screening
Graham, Michelle Pearl, Helen Chow, Thomson Ho, Robert Currier, Leslie Gaffney,
Martin Kharrazi, Juan Yang, Tracey Bishop, Shellye Lessing, Suzanne Young, Steven
Newborn Screening for Cystic Fibrosis in California
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