Next Article in Journal
Prediction of Congenital Portosystemic Shunt in Neonatal Hypergalactosemia Using Gal-1-P/Gal Ratio, Bile Acid, and Ammonia
Next Article in Special Issue
Exceptionally High Cystic Fibrosis-Related Morbidity and Mortality in Infants and Young Children in India: The Need for Newborn Screening and CF-Specific Capacity Building
Previous Article in Journal
Advancing Neonatal Screening for Pyridoxine-Dependent Epilepsy-ALDH7A1 Through Combined Analysis of 2-OPP, 6-Oxo-Pipecolate and Pipecolate in a Butylated FIA-MS/MS Workflow
Previous Article in Special Issue
Neonatology Providers Need Education About Cystic Fibrosis Newborn Screening Algorithms
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJNS
Volume 11
Issue 3
10.3390/ijns11030060
IJNS-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Refining CFTR-Related Metabolic Syndrome (CRMS)/Cystic Fibrosis Screen Positive, Inconclusive Diagnosis (CFSPID) Diagnosis: Impact of CFTR2 Variant Classifications

by
MacKenzie Wyatt
1,2,*,
Alexandra Quinn
1,2,
Lincoln Shade
3 and
Meghan McGarry
1,2
1
Department of Pediatrics, University of Washington School of Medicine, Seattle, WA 98105, USA
2
Center for Respiratory Biology and Therapeutics, Seattle Children’s Research Institute, Seattle, WA 98101, USA
3
Institute for Biomedical Informatics, Multidisciplinary Science, University of Kentucky, 725 Rose St Building, Suite 230, Lexington, KY 40536, USA
*
Author to whom correspondence should be addressed.
Int. J. Neonatal Screen. 2025, 11(3), 60; https://doi.org/10.3390/ijns11030060
Submission received: 16 June 2025 / Revised: 21 July 2025 / Accepted: 24 July 2025 / Published: 30 July 2025
(This article belongs to the Special Issue Advances in Cystic Fibrosis Newborn Screening: From Laboratory Testing to Diagnosis)
Browse Figures
Versions Notes

Abstract

An unintended consequence of cystic fibrosis (CF) newborn screening (NBS) is the identification of infants with a positive NBS who do not meet the diagnostic criteria for CF (two CF-causing variants and/or sweat chloride > 60 mmol/L). This indeterminate diagnosis is called cystic fibrosis transmembrane conductance regulator (CFTR)-related metabolic syndrome (CRMS) or CF screen positive, inconclusive diagnosis (CFSPID). CRMS/CFSPID occurs when it is not clearly known whether CFTR variants are disease-causing. In 2024, the CFTR2 classification of many CFTR variants was changed from unknown significance to either CF-causing variants or variants of varying clinical consequences (VVCCs). We conducted a meta-analysis of CRMS/CFSPID cases from manuscripts to describe how the diagnoses would change using two different variant panels: (1) only CF-causing CFTR variants (PanelCF-causing) and (2) CF-causing variants and VVCCs (PanelCF-causing+VVCCs). Using the PanelCF-causing, 8.7% had two CF-causing variants (reclassified as CF), while 91.3% had less than two CF-causing variants (reclassified as Undetected). Using the PanelCF-causing+VVCCs, 51.4% had either two VVCCs or one VVCC with one CF-causing variant detected (reclassified as CRMS/CFSPD), 39.9% had less than two CF-causing variants detected (reclassified as Undetected), and 8.7% had two CF-causing variants (reclassified as CF). In conclusion, using the updated CFTR2 classification of CFTR variants significantly decreases the number of children with CRMS/CFSPID and gives a definitive diagnosis of CF to some children while not detecting as many children who are unlikely to develop CF.

1. Introduction

Cystic Fibrosis (CF) is an autosomal recessive genetic condition caused by variants in the CFTR gene, marked by disease in the lungs, pancreas, sinuses, and gastrointestinal tract [1]. Newborn screening (NBS) has been implemented in every state in the United States since 2010 [2]. CF NBS algorithms vary greatly within and between programs but in the US typically begin with an initial biomarker test, immunoreactive trypsinogen (IRT) [3]. Then, if IRT is elevated, the dried blood spot is tested for CFTR variants either in a panel or by genetic sequencing [4]. The next step is a sweat chloride test, which evaluates the concentration of chloride on the skin [5]. Sweat chloride is the gold standard diagnostic test for CF. One unintended consequence of CF NBS is the identification of infants who do not meet the diagnostic criteria for a formal CF diagnosis with a sweat chloride test (>60 mmol/L) [6]. Infants who have a positive newborn screen but do not meet the formal diagnostic criteria for CF can receive an indeterminate diagnosis known as cystic fibrosis transmembrane conductance regulator (CFTR)-related metabolic syndrome (CRMS) or CF screen positive, inconclusive diagnosis (CFSPID) [7]. Some CFTR variants (1) have an unknow impact on CF, or (2) cause CF only some of the time [8]. Uncertainty of CFTR variants leads to diagnosis of CRMS/CFSPID. Approximately 5–11% of children with CRMS/CFSPID develop clinical features of CF and convert to a CF diagnosis [9].
Not all variants in the CFTR gene definitively cause CF; some variants are benign, some are variants of varying clinical consequences (VVCCs), and the clinical impact of some variants is unknown [10]. The CFTR2 project is an international research project designed to improve the classification of the clinical impact of CFTR variants [11,12]. The CFTR2 database recently expanded the classification from 400 CFTR variants to over 1000 variants, with many variants of unknown significance reclassified as disease-causing.
Our study, a retrospective meta-analysis of CRMS/CFSPID, sought to understand the impact of the CFTR2 expansion of the classification of CFTR genetic variants on prior CRMS/CFSPID diagnoses from the literature. We hypothesized that children with CRMS/CFSPID would have more definitive reclassified diagnoses based on the updated classifications of CFTR genetic variants in the CFTR2 database.

2. Materials and Methods

The study population consisted of people diagnosed with CRMS/CFSPID and individual CFTR variants as reported in the literature. The primary endpoint was to determine the genetic diagnosis using the updated CFTR2 database [12]. We approached the task of reclassifying genetic diagnosis by utilizing (1) only the 1085 CF-causing variants (PanelCF-causing) and (2) the 1085 CF-causing variants and 55 VVCCs (PanelCF-causing+VVCCs). We included all studies that published the CFTR variants of children with a reported diagnosis of CRMS/CFSPID. We included studies that published the CFTR genetic variants for each individual and excluded any studies that published CFTR genetic variants by population variant frequency only. The inclusion criteria were articles of any cross-sectional, case-control, cohort, randomized controlled trial, as well as case reports. We excluded articles that were not available in English. This study was approved by the Institutional Review Board at Seattle Children’s Hospital.

2.1. Literature Search

The authors followed the Preferred Reporting Items for Systematic Review and Meta-Analysis of Diagnostic Test Accuracy (PRISMA-DTA) [13]. The literature search started on 10 October 2024, and concluded on 15 February 2025. We searched for literature via PubMed and Google Scholar (Figure 1). The citations of identified manuscripts were searched for the relevant literature. The search keywords used were ‘CFTR-Related Metabolic Syndrome,’ ‘Cystic Fibrosis transmembrane conductance regulator related metabolic syndrome,’ ‘CRMS/CFSPID,’ ‘Cystic Fibrosis Screen Positive, Inconclusive Diagnosis,’ and ‘CFSPID.’ The search was conducted in English. All records were reviewed for inclusion of CFTR genetic variants. Two authors (MW and MM) conducted the initial search. The diagnostic criteria of CF and CRMS/CFSPID are shown in Table 1.

2.2. Data Extraction and Labeling

The literature and the Supplemental Data were extracted for CFTR variants, IRT, sweat chloride values, and age at diagnosis (conducted by MW and verified by MM and AQ). We gathered the pertinent data, including study identity (author and publication year), study characteristics (location, dates, study design, follow-up), and NBS information (NBS algorithm).
The literature was searched for duplicate entries of children with CRMS/CFSPID based on region, year of newborn screen, CFTR variants, IRT, sweat chloride concentration, and age of diagnosis. Duplicate entries of children from various studies were counted only once. Children with an initial elevated sweat chloride (>60 mmol/L) were excluded, since they met the diagnosis of CF.
The clinical interpretation of CFTR variants was determined based on the CFTR2 database (conducted by MW and verified by MM). If the CFTR variant was in the CFTR2 database, it was classified as either ‘CF-causing,’ ‘variant of varying clinical consequences (VVCC),’ or ‘non-CF-causing.’ If a CFTR variant was not in the database, it was labeled ‘variant of unknown significance (VUS).’ If a child did not have a CFTR variant found, it was labeled as ‘not identified.’ Variant category definitions are given in Table 2.

2.3. Diagnostic Criteria for Reclassified Diagnosis Based on CFTR2 Database

We reclassified the reported diagnoses based on the updated CFTR genetic variant classifications in the CFTR2 database. Based on a child’s genetic variants’ clinical implications, we determined their genetic diagnosis (Table 3) by two mechanisms. First, using PanelCF-causing, reclassification diagnosis was determined as ‘CF’ if a child had 2 CF-causing variants. Otherwise, a child was reclassified as ‘Undetected’ for any other combination of variants. Second, using PanelCF-causing+VVCCs, reclassification diagnosis was determined as CRMS/CFSPID if there were two CFTR variants (CF-causing and 1 VVCC or 2 VVCCs), ‘CF’ if a child had two CF-causing variants, or ‘Undetected’ if there were fewer than two CF-causing or VVCC CFTR variants detected.

2.4. Sub-Analysis of Children with CRMS/CFSPID Who Converted

All the children included in our meta-analysis had been clinically diagnosed with CRMS/CFSPID, which we will refer to as the ‘reported diagnosis’. Some manuscripts reported data on children with CRMS/CFSPID who converted to CF (CRMS/CFSPID→CF) or CFTR-related disorder (CRMS/CFSPID→CFTR-RD). We performed a sub-analysis on these children.

2.5. Secondary Outcomes Analyses

We compared the initial sweat chloride concentration and IRT level between the reclassified diagnoses using PanelCF-causing+VVCCs.

2.6. Statistical Analyses

Descriptive statistics are presented as median (interquartile range [IQR]) for continuous variables and number (%) for categorical variables. For initial group comparisons, we used Mann–Whitney U, Cochran’s Q statistic, Stuart–Maxwell, Wilcoxon signed-rank, chi-squared, or McNemar tests, as appropriate. Statistical significance was defined as p-value < 0.05. Statistical analyses were performed using R version 4.0.1.1. Figures were created using the R ggplot2 package. ChatGPT 4.o was used only to revise the coding for statistical analysis.

3. Results

3.1. Literature Review

Upon searching PubMed, Google Scholar, and the citations of identified manuscripts, 17 papers met the inclusion criteria (Figure 1). Of these 17 manuscripts, nine were from Europe, five were from North America, one was from Australia, and two were from North America and Europe (Table 4). After reviewing the manuscripts, 537 children with CRMS/CFSPID were identified. We excluded two children for an initial sweat chloride >60 mmol/L. We excluded duplicative data from 19 children who had data in multiple manuscripts in our study and only counted them once. There were duplicates of twelve children in the papers from California, USA, and duplicates of seven children in the papers from Italy that were excluded. A total of 516 children with CRMS/CFSPID were included for analysis. Of the 516 children with CRMS/CFSPID, 136 children had a reported diagnosis of CRMS/CFSPID→CF and 15 children had a reported diagnosis of CRMS/CFSPID→CFTR-RD.

3.2. Primary Outcomes: Reclassification Diagnoses

When using PanelCF-causing, a child could be reclassified with the diagnosis of ‘CF’ or ‘undetected.’ There were no genetic diagnoses of ‘CRMS/CFSPID’ and thus the diagnosis was eliminated. In comparison, when using a CF-causing and VVCC variant panel, children were reclassified with ‘CF,’ ‘CRMS/CFSPID,’ or ‘undetected.’ (Table 5, Figure 2).
First, using PanelCF-causing, 45 (8.7%) children would have two CF-causing variants, and their reclassified diagnosis was CF. Otherwise, 471 (91.3%) children would have fewer than two CF-causing variants identified, and their reclassified diagnosis was undetected. No children would have a reclassified diagnosis of CRMS/CFSPID.
Next, using PanelCF-causing+VVCCs, 264 (51.1%) children would have two CFTR variants detected (1 CF-causing and 1 VVCC or 2 VVCCs), and their reclassified diagnosis was CRMS/CFSPID. Using PanelCF-causing+VVCCs, 45 (8.7%) children would have a reclassified diagnosis of CF, which is the same percentage as with the PanelCF-causing. Otherwise, using PanelCF-causing+VVCCs, 207 (40.0%) children would have less than two variants identified, and their reclassified diagnosis was undetected.
Four children had complex variant combinations (more than two variants identified): CF-causing variant/VVCC and VVCC; CF-causing variant/VVCC, VVCC, and VVCC; CF-causing variant and VVCC/non-CF-causing variant; VVCC, VVCC, and VVCC/VVCC and VVCC.
There was substantial heterogeneity for the presence of one CF-causing variant within the studies (I2 = 72.4%) (Figure S1). There was considerable heterogeneity for the presence of two CF-causing variants within the studies (I2 = 77.4%) (Figure S2).

3.3. Subanalysis of Children with CRMS/CFSPID Who Converted

The CFTR genetic variants of 136 children with CRMS/CFSPID→CF are shown in Table 6. First, using PanelCF-causing, 91 (66.9%) children with a reported diagnosis of CRMS/CFSPID→CF would be ‘undetected’ and thus missed for CF diagnosis. Second, using PanelCF-causing+VVCCs, 71 (52.2%) children with CRMS/CFSPID→CF have a reclassified diagnosis of CRMS/CFSPID, and only 19 (14.0%) children with CRMS/CSPID→CF would be ‘undetected’ and thus missed for CF diagnosis (Figure 2).
More children remain classified as CRMS/CFSPID, and fewer children with a reported diagnosis of CRMS/CFSPID→CF would be missed with the PanelCF-causing+VVCCs compared to using only using PanelCF-causing (Stuart-Maxwell p-value < 0.05).

3.4. Secondary Outcomes: IRT/Sweat Chloride Data

Initial sweat chloride concentration data were available for 227 children. The mean initial sweat chloride concentration level for all children with CRMS/CFSPID was 37.3 mmol/L (95%CI 25.5–49.1). The mean sweat chloride concentration level was statistically significantly higher in the 37 children reclassified from PanelCF-causing+VVCCs as CF (44.7, 95% CI 34.4–50.0) compared to the 91 children reclassified as CRMS/CFSPID (35.4, 95% CI: 22.1–48.7) and the 99 children reclassified as undetected (36.4, 95% CI: 26.7–46.1, Kruskal–Wallis p < 0.001) (Figure 3).
Initial IRT data were available for 75 children. The mean initial IRT level for all children with CRMS/CFSPID was 107.0 ng/mL (95%CI 43.18–170.8). Using PanelCF-causing+VVCCs, initial IRT levels did not differ significantly between children reclassified as CF, CRMS/CFSPID, or undetected (Kruskal–Wallis p = 0.15) (Supplemental Information).

4. Discussion

In this meta-analysis of published cases of CRMS/CFPSID, we found that using CFTR genetic classifications based on the 2024 CFTR2 database improves definitive diagnoses in children previously diagnosed with CRMS/CFSPID. Using a PanelCF-causing, one could eliminate CRMS/CFSPID diagnoses by genetic classification. However, using a PanelCF-causing would miss 91 (66.9%) of published CRMS/CFSPID→CF conversions. These cases would be a false negative newborn screen and would need to be diagnosed based on clinical symptoms, thus leading to delayed CF diagnoses. Using PanelCF-causing+VVCCs, CRMS/CFPSID diagnoses would be reduced but not eliminated. PanelCF-causing+VVCCs would detect a higher percentage of those with CRMS/CFSPID conversions but still miss 19 (14.0%) of the published CRMS/CFSPID→CF conversions.
There is still controversy over detecting CRMS/CFPSID by newborn screening [31]. Some people believe CRMS/CFSPID should not be detected by newborn screening for multiple reasons. Being diagnosed with CRMS/CFSPID can lead to anxiety for families due to the uncertainty and can lead to unnecessary overmedicalization and testing [32,33,34,35,36,37,38,39]. There was no standardized guidance on management for these children until 2024, so it has been confusing for providers on the follow-up of these children [40]. Some newborn screening programs detect more CRMS/CFSPID than CF [31]. Additionally, CRMS/CFSPID can lead to valuable resources and staffing needs for CF centers [41]. These resources can take away from children with CF. These children must be followed by CF centers, and thus appointment slots for sweat testing and physician follow-up are being utilized. There is a low conversion rate of CRMS/CFSPID→CF, so some programs do not feel as though they need to be detected via newborn screening and should be diagnosed later in life [21].
Other programs believe CRMS/CFSPID should be detected by newborn screening. Some centers’ goals are to identify every child who is at risk for converting to CF and CFTR-RD. Some centers have the resources to follow all these children. It is important to consider that children of minoritized races, ethnicities, or ancestries face increased barriers to being diagnosed after a false negative newborn screening, as there is still a false perception that CF occurs in a white, European population, despite CF occurring in all populations across the world [42,43].
Using both strategies with CFTR2 (only CF-causing variants or CF-causing variants and VVCCs) as part of a newborn screen leads to faster definitive diagnoses for children and less uncertainty, as more children are initially classified as CF or undetected, and fewer children are initially classified as CRMS/CFSPID. Using only CF-causing variants eliminates the diagnosis of CRMS/CFSPID, but more children with a reported diagnosis of CRMS/CFSPID→CF are undetected and thus missed. Using CF-causing variants and VVCCs still retains the diagnosis of CRMS/CFSPID, but it reduces the number of children who have this label and leads to more children with CRMS/CFSPID→CF who retain the diagnosis of CRMS/CFSPID to be followed for diagnostic conversion. Children with CRMS/CFSPID largely fall into two categories: those who will convert to CF and those who have a persistent CRMS/CFSPID diagnosis [44]. By applying the new knowledge we have with the CFTR2 database, we reduce the number of children with CRMS/CFSPID and improve the specificity of the diagnosis of CRMS/CFSPID. Our meta-analysis is one of the most extensive studies of children with CRMS/CFSPID and their individual CFTR variant combinations and helps illuminate the impact of the CFTR2 database on diagnoses. Our findings are similar to past studies that show that a child with a CF-causing variant and a VVCC is more likely to convert from CRMS/CFSPID to CF [45].
We found that initial sweat chloride levels were significantly higher in children who were reclassified as CF compared to CRMS/CFSPID or undetected. A sweat chloride test is the gold standard diagnostic test for CF, so these findings support diagnosis by genetic reclassification based on the CFTR2 database. Prior studies have examined the relationship between the increase in sweat chloride concentration over time and CRMS/CFSPID→CF diagnosis. Salinas et al. (2023) showed that a gradual increase in sweat chloride is associated with an increased risk of converting from CRMS/CFSPID to CF, but Terlizzi et al. (2023) showed more variability in the sweat chloride [22,46]. The IRT was not significantly different between groups, which differs from some of the literature that suggests a higher IRT predicts conversion from CRMS/CFSPID→CF [45]. Some studies have found that IRT concentration is higher in CRMS/CFSPID→CF compared to CRMS/CFSPID [24]. There has not been an explicit cutoff for IRT that is predictive of a child with CRMS/CFSPID→CF [16,47].
These findings are important in light of the 2025 CF Foundation CF newborn screening guidelines, which allow newborn screening programs to choose to perform sweat testing on children with only CF-causing variants or CF-causing variants and VVCCs, which will impact CRMS/CFSPID diagnoses [2]. Genetic sequencing labs can allow NBS programs to determine whether the results will reveal only the CF-causing variants or the CF-causing variants and VVCCs [48]. Using only CF-causing variants decreases the number of sweat tests that a center must perform. Some CF centers do not have the staffing to conduct all the sweat tests in a reasonable time, which can delay CF diagnoses. Additionally, using a panel of only CF-causing variants eliminates the diagnosis of CRMS/CFSPID. The only way a child would have CRMS/CFSPID would be if the algorithm had a very high IRT cutoff. Using only either panel and calling out only those with two variants eliminates the number of children a CF center must follow, as some centers do not have enough CF providers and appointment slots. The downside of using only CF-causing variants is that a significant number of children with CRMS/CFSPID→CF would be reclassified as undetected unless they had a very high IRT level and thus would not be followed. This can delay diagnosis and treatment for children with CRMS/CFSPID→CF, which has been shown to lead to worse clinical outcomes [43].
Using CF-causing variants and VVCCs in newborn screens and diagnostic testing is beneficial as it can reduce the amount of CRMS/CFSPID while also retaining a smaller group of children with CRMS/CFSPID to follow. This increases the likelihood that a child will convert from CRMS/CFSPID→CF within this group, making the diagnosis more specific and useful. Using this method increases the number of children requiring a sweat chloride concentration and to be followed by a CF center. Not only does this lead to increased staffing and resource needs at the CF center, but sweat chloride concentrations and clinic visits are expensive and time-consuming for families as well. Using VVCCs can be important for health equity. Although reported race and ethnicity is a social construct and a poor proxy of genetic ancestries, some variants are rarer overall but occur more frequently in racial and ethnic minority groups [42,49]. This is a problem within CF, and any genetic disease where variant panels were developed based on a predominantly non-Hispanic white or European populations [50]. This bias leads to misdiagnoses and delayed care [43].
When choosing which NBS algorithm and variant panel to use, the newborn screening program must determine its goals. Some programs want to detect every child with CF or at risk of CF, regardless of the number of children with an indeterminate diagnosis. Other programs have the goal of establishing a definitive diagnosis for families of CF and minimizing the number of those with CRMS/CFSPID. We have shown that using a variant panel with only CF-causing variants or CF-causing variants and VVCCs, the amount of CRMS/CFSPID is reduced as more children will be definitively diagnosed with CF sooner, and fewer healthy children will receive a CRMS/CFSPID diagnosis. We have shown that a variant panel with VVCCs detects more children who convert from CRMS/CFSPID→CF compared to a variant panel with only CF-causing variants and leads to fewer missed cases.
This study highlights the importance of investigating to ascertain increased knowledge of CFTR variants. It is important to understand which VVCCs are more likely to be CF-causing vs normal, and which VVCCs in combination with certain variants are more likely to be CF-causing. CF centers should be reviewing their cases from their center, paying attention to the variants and any false negative NBS cases to ensure their methods are capturing their population. Additionally, they should be reviewing their cases to ensure equity. As populations evolve to become more diverse, missed cases may become more prevalent in areas that previously were more homogenous [42]. Public health measures should be continually reassessed and modified to ensure equity. Our study demonstrates the importance of publishing newborn screening data to help further this knowledge of the clinical impact of CFTR variants. Most newborn screening programs did not have any representation in the literature, whereas some centers in Italy and Canada are very well represented. This study was made possible by prior publications and the Supplemental Data. Our study demonstrates the need to understand how other biomarkers and clinical factors predict CRMS/CFSPID conversion to CF [45]. Terlizzi et al. show that the literature on CRMS/CFSPID is varied and highlights the need for an international registry for CRMS/CFSPID [45].
Although our findings were specific to CF, the same principles can be applied to any newborn screen that has a genetic component. Newborn screens that include genetic testing can have these indeterminate results as well, including Severe Combined Immunodeficiency (SCID), metabolic disorders, and congenital hypothyroidism [51,52,53]. The American College of Medical Genetics and Genomics has categories of variant classification that include variants of varying clinical consequences with different nomenclature [54]. They categorize genes as likely benign or likely pathogenic when we know the certainty of its influence on disease (at least 90%) or a variant of unknown significance when the certainty is less than 90% [54]. These genes can also be reclassified as benign or pathogenic as more information becomes known. Variants in classic galactosemia, phenylketonuria, and medium-chain acyl-CoA dehydrogenase (MCAD) deficiency have all had variants reclassified as more information becomes available [55]. Some children have variants that must be followed to ensure no symptoms at a later date, which leads to a similar pattern. Our study highlights the need to pool resources and gather information to understand variants to obtain more definitive diagnoses.
One limitation of our study is reporting bias. Few NBS programs publish any data on their CRMS/CFSPID newborn screening. There is likely a preference to publish cases of children with CRMS/CFSPID who convert to CF over cases of just CRMS/CFSPID. Thus, we could be overrepresenting the children with CRMS/CFSPID who convert to CF. Another limitation of this study is that there are differing durations of follow-up for each study, and theoretically, children can convert from CRMS/CFSPID to CF or CFTR-RD at any given time. Some children likely converted to CF after publication, so the reported diagnosis could be underrepresenting CRMS/CFSPID→CF and can thus be underrepresenting the amount of missed diagnoses from the proposed strategies. Another limitation is the heterogeneity of algorithmic differences based on geography. Some children may be diagnosed with CRMS/CFSPID in one location and followed at another location where they converted to CF and thus would not be documented. A child with the same variants would be more likely to be diagnosed with CRMS/CFSPID in a location that screens for more CFTR variants. Despite these limitations, our findings are valid and important for modeling how CFTR2 could impact diagnosis. It provides an example for CF centers to use when analyzing their own prior data to decide how to proceed with variant panels or genetic sequencing as more states and regions begin to adopt the recommendations from the new newborn screening guidelines.
Our study has a diversity of children from a variety of areas around the world that have differing NBS algorithms. Additionally, we applied the same diagnostic reclassification schema based on CFTR2, which increases generalizability. This strengthens the generalizability of our study. Our generalizability is limited because each study followed children for differing amounts of time. Our study does have high heterogeneity (see Supplemental Data), as each region has differing NBS algorithms, but CFTR2 is sourced from all over the world and is very robust, strengthening our findings [12].

5. Conclusions

The expansion of CFTR2 improves definitive diagnosis of CF and reduces the number of children with uncertain diagnoses with CRMS/CFSPID. We show that using only CF-causing variants removes CRMS/CFSPID cases but misses more children who convert from CRMS/CFSPID→CF compared to using CF-causing variants and VVCCs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijns11030060/s1, Figure S1: Forest plot of 1 CF-causing variant; Figure S2: Forest plot of 2 CF-causing variants.

Author Contributions

Conceptualization, M.W. and M.M.; methodology, M.W. and M.M.; software, M.W., L.S. and M.M.; validation, M.W., A.Q. and M.M.; formal analysis, M.W. and L.S.; investigation, M.W. and M.M.; resources, A.Q.; data curation, M.W. and M.M.; writing—original draft preparation, M.W.; writing—review and editing, A.Q. and M.M.; visualization, M.W., A.Q. and M.M.; supervision, M.M.; project administration, M.W. and M.M.; funding acquisition, M.W. and M.M. All authors have read and agreed to the published version of the manuscript.

Funding

The research of Dr. Wyatt is funded by the Cystic Fibrosis Foundation (CFF) Clinical Fellowship Award, grant number WYATT24B0 and WYATT25D0, the Rosenfeld Funds, and the Corkery Endowment. The work of Dr. McGarry is funded by the National Institutes of Health (NIH), grant number 5K23HL133437-05, and the Cystic Fibrosis Foundation (CFF), grant number MCGARR16A0. The work of Dr. Shade is funded by the National Institutes of Health (NIH) Ruth L. Kirschstein National Research Service Award F30 Fellowship and by the National Institute of Neurological Disorders and Stroke (NINDS) F30-NS124136.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Seattle Children’s Hospital (protocol code STUDY00005212 and 12/17/2024).

Informed Consent Statement

Not applicable.

Data Availability Statement

All participant data that underlie the results reported in this manuscript are publicly available and deidentified. Individual participant data that underlie the results reported in this manuscript and a corresponding data dictionary will be shared electronically with other researchers for the purpose of conducting systematic reviews with meta-analyses and upon approval by the corresponding author. For this, researchers requesting the data will need to have their study approved by an independent review committee (such as an institutional review board) and directly contact the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
CFcystic fibrosis
NBSnewborn screening
CFTRcystic fibrosis transmembrane conductance regulator
CRMScystic fibrosis transmembrane conductance regulator (CFTR)-related metabolic syndrome
CFSPIDcystic fibrosis screen positive, inconclusive diagnosis
CFTR2The Clinical and Functional TRanslation of CFTR
IRTimmunoreactive trypsinogen
VVCCsvariant of varying clinical consequences
PRISMA-DTAPreferred Reporting Items for Systematic Review and Meta-Analysis of Diagnostic Test Accuracy
VUSvariant of unknown significance
CFTR-RDCFTR-related disorder
PanelCF-causingpanel using only CF-causing variants
PanelCF-causing+VVCCspanel using CF-causing variants and VVCCs
IQRinterquartile range
PKUphenylketonuria
MCADmedium-chain acyl-CoA dehydrogenase

References

  1. Ong, T.; Ramsey, B.W. Cystic Fibrosis: A Review. JAMA 2023, 329, 1859–1871. [Google Scholar] [CrossRef]
  2. McGarry, M.E.; Raraigh, K.S.; Farrell, P.; Shropshire, F.; Padding, K.; White, C.; Dorley, M.C.; Hicks, S.; Ren, C.L.; Tullis, K.; et al. Cystic Fibrosis Newborn Screening: A Systematic Review-Driven Consensus Guideline from the United States Cystic Fibrosis Foundation. Int. J. Neonatal Screen. 2025, 11, 24. [Google Scholar] [CrossRef]
  3. Rosenfeld, M.; Sontag, M.K.; Ren, C.L. Cystic Fibrosis Diagnosis and Newborn Screening. Pediatr. Clin. N. Am. 2016, 63, 599–615. [Google Scholar] [CrossRef]
  4. Bienvenu, T.; Lopez, M.; Girodon, E. Molecular Diagnosis and Genetic Counseling of Cystic Fibrosis and Related Disorders: New Challenges. Genes 2020, 11, 619. [Google Scholar] [CrossRef]
  5. Gonska, T. The Sweat Chloride Test Has Lived up to the Changes in CF Care. J. Cyst. Fibros. 2022, 21, 381–382. [Google Scholar] [CrossRef]
  6. Farrell, P.M.; White, T.B.; Ren, C.L.; Hempstead, S.E.; Accurso, F.; Derichs, N.; Howenstine, M.; McColley, S.A.; Rock, M.; Rosenfeld, M.; et al. Diagnosis of Cystic Fibrosis: Consensus Guidelines from the Cystic Fibrosis Foundation. J. Pediatr. 2017, 181, S4–S15.e1. [Google Scholar] [CrossRef]
  7. Ren, C.L.; Borowitz, D.S.; Gonska, T.; Howenstine, M.S.; Levy, H.; Massie, J.; Milla, C.; Munck, A.; Southern, K.W. Cystic Fibrosis Transmembrane Conductance Regulator-Related Metabolic Syndrome and Cystic Fibrosis Screen Positive, Inconclusive Diagnosis. J. Pediatr. 2017, 181, S45–S51.e1. [Google Scholar] [CrossRef]
  8. Sinha, A.; Southern, K.W. Cystic Fibrosis Transmembrane Conductance Regulator-Related Metabolic Syndrome/Cystic Fibrosis Screen Positive, Inconclusive Diagnosis (CRMS/CFSPID). Breathe 2021, 17, 210088. [Google Scholar] [CrossRef]
  9. Sciortino, S.; Graham, S.; Bishop, T. Diagnostic Transitions of Cystic Fibrosis and CRMS Compared After 12 Years of Newborn Screening in California. J. Pediatr. 2025, 276, 114287. [Google Scholar] [CrossRef]
  10. Ideozu, J.E.; Liu, M.; Riley-Gillis, B.M.; Paladugu, S.R.; Rahimov, F.; Krishnan, P.; Tripathi, R.; Dorr, P.; Levy, H.; Singh, A.; et al. Diversity of CFTR Variants across Ancestries Characterized Using 454,727 UK Biobank Whole Exome Sequences. Genome Med. 2024, 16, 43. [Google Scholar] [CrossRef]
  11. Castellani, C.; CFTR2 Team. CFTR2: How Will It Help Care? Paediatr. Respir. Rev. 2013, 14 (Suppl. S1), 2–5. [Google Scholar] [CrossRef]
  12. CFTR2: The Clinical and Functional Translation of CFTR. Available online: https://cftr2.org/mutations_history (accessed on 15 October 2024).
  13. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
  14. Castaldo, A.; Cimbalo, C.; Castaldo, R.J.; D’Antonio, M.; Scorza, M.; Salvadori, L.; Sepe, A.; Raia, V.; Tosco, A. Cystic Fibrosis-Screening Positive Inconclusive Diagnosis: Newborn Screening and Long-Term Follow-Up Permits to Early Identify Patients with CFTR-Related Disorders. Diagnostics 2020, 10, 570. [Google Scholar] [CrossRef]
  15. Ooi, C.Y.; Castellani, C.; Keenan, K.; Avolio, J.; Volpi, S.; Boland, M.; Kovesi, T.; Bjornson, C.; Chilvers, M.A.; Morgan, L.; et al. Inconclusive Diagnosis of Cystic Fibrosis After Newborn Screening. Pediatrics 2015, 135, e1377–e1385. [Google Scholar] [CrossRef]
  16. Munck, A.; Bourmaud, A.; Bellon, G.; Picq, P.; Farrell, P.M.; DPAM Study Group. Phenotype of Children with Inconclusive Cystic Fibrosis Diagnosis after Newborn Screening. Pediatr. Pulmonol. 2020, 55, 918–928. [Google Scholar] [CrossRef]
  17. Gunnett, M.A.; Baker, E.; Mims, C.; Self, S.T.; Gutierrez, H.H.; Guimbellot, J.S. Outcomes of Children with Cystic Fibrosis Screen Positive, Inconclusive Diagnosis/CFTR Related Metabolic Syndrome. Front. Pediatr. 2023, 11, 1127659. [Google Scholar] [CrossRef]
  18. Terlizzi, V.; Mergni, G.; Buzzetti, R.; Centrone, C.; Zavataro, L.; Braggion, C. Cystic Fibrosis Screen Positive Inconclusive Diagnosis (CFSPID): Experience in Tuscany, Italy. J. Cyst. Fibros. 2019, 18, 484–490. [Google Scholar] [CrossRef] [PubMed]
  19. Hatton, A.; Bergougnoux, A.; Zybert, K.; Chevalier, B.; Mesbahi, M.; Altéri, J.P.; Walicka-Serzysko, K.; Postek, M.; Taulan-Cadars, M.; Edelman, A.; et al. Reclassifying Inconclusive Diagnosis after Newborn Screening for Cystic Fibrosis. Moving Forward. J. Cyst. Fibros. 2022, 21, 448–455. [Google Scholar] [CrossRef]
  20. Rock, M.J.; Baker, M.; Antos, N.; Farrell, P.M. Refinement of Newborn Screening for Cystic Fibrosis with next Generation Sequencing. Pediatr. Pulmonol. 2023, 58, 778–787. [Google Scholar] [CrossRef]
  21. Terlizzi, V.; Claut, L.; Tosco, A.; Colombo, C.; Raia, V.; Fabrizzi, B.; Lucarelli, M.; Angeloni, A.; Cimino, G.; Castaldo, A.; et al. A Survey of the Prevalence, Management and Outcome of Infants with an Inconclusive Diagnosis Following Newborn Bloodspot Screening for Cystic Fibrosis (CRMS/CFSPID) in Six Italian Centres. J. Cyst. Fibros. 2021, 20, 828–834. [Google Scholar] [CrossRef]
  22. Salinas, D.B.; Ginsburg, D.K.; Wee, C.P.; Saeed, M.M.; Brewington, J.J. Gradual Increase in Sweat Chloride Concentration Is Associated with a Higher Risk of CRMS/CFSPID to CF Reclassification. Pediatr. Pulmonol. 2023, 58, 1074–1084. [Google Scholar] [CrossRef] [PubMed]
  23. Kharrazi, M.; Yang, J.; Bishop, T.; Lessing, S.; Young, S.; Graham, S.; Pearl, M.; Chow, H.; Ho, T.; Currier, R.; et al. Newborn Screening for Cystic Fibrosis in California. Pediatrics 2015, 136, 1062–1072. [Google Scholar] [CrossRef]
  24. Ooi, C.Y.; Sutherland, R.; Castellani, C.; Keenan, K.; Boland, M.; Reisman, J.; Bjornson, C.; Chilvers, M.A.; van Wylick, R.; Kent, S.; et al. Immunoreactive Trypsinogen Levels in Newborn Screened Infants with an Inconclusive Diagnosis of Cystic Fibrosis. BMC Pediatr. 2019, 19, 369. [Google Scholar] [CrossRef]
  25. Groves, T.; Robinson, P.; Wiley, V.; Fitzgerald, D.A. Long-Term Outcomes of Children with Intermediate Sweat Chloride Values in Infancy. J. Pediatr. 2015, 166, 1469–1474.e1. [Google Scholar] [CrossRef]
  26. Çoksüer, F.; Kartal Öztürk, G.; Duman Şenol, H.; Barlık, M.; Özaslan, M.M.; Girgin Dindar, B.; Ocak, E.; Halis, E.; Atacan Öğütcü, Ş.; Gülen, F.; et al. Newborn Screening Program for Cystic Fibrosis in Türkiye: Experiences from False-Negative Tests and Requirement for Optimization. Balk. Med. J. 2025, 42, 45–53. [Google Scholar] [CrossRef] [PubMed]
  27. Terlizzi, V.; Claut, L.; Colombo, C.; Tosco, A.; Castaldo, A.; Fabrizzi, B.; Lucarelli, M.; Cimino, G.; Carducci, C.; Dolce, D.; et al. Outcomes of Early Repeat Sweat Testing in Infants with Cystic Fibrosis Transmembrane Conductance Regulator-related Metabolic Syndrome/CF Screen-positive, Inconclusive Diagnosis. Pediatr. Pulmonol. 2021, 56, 3785–3791. [Google Scholar] [CrossRef] [PubMed]
  28. Dolce, D.; Claut, L.; Colombo, C.; Tosco, A.; Castaldo, A.; Padoan, R.; Timpano, S.; Fabrizzi, B.; Bonomi, P.; Taccetti, G.; et al. Different Management Approaches and Outcome for Infants with an Inconclusive Diagnosis Following Newborn Screening for Cystic Fibrosis (CRMS/CFSPID) and Pseudomonas Aeruginosa Isolation. J. Cyst. Fibros. 2023, 22, 73–78. [Google Scholar] [CrossRef]
  29. Ginsburg, D.; Wee, C.P.; Reyes, M.C.; Brewington, J.J.; Salinas, D.B. When CFSPID Becomes CF. J. Cyst. Fibros. 2022, 21, e23–e27. [Google Scholar] [CrossRef]
  30. Skov, M.; Bækvad-Hansen, M.; Hougaard, D.M.; Skogstrand, K.; Lund, A.M.; Pressler, T.; Olesen, H.V.; Duno, M. Cystic Fibrosis Newborn Screening in Denmark: Experience from the First 2 Years. Pediatr. Pulmonol. 2020, 55, 549–555. [Google Scholar] [CrossRef]
  31. Terlizzi, V.; Fevola, C.; Presti, S.; Claut, L.; Ambroni, M.; Calderazzo, M.A.; Esposito, I.; Fabrizzi, B.; Leonetti, G.; Lombardo, M.; et al. Critical Issues in the Management of CRMS/CFSPID Children: A National Real-World Survey. Pediatr. Pulmonol. 2025, 60, e27483. [Google Scholar] [CrossRef]
  32. Loukou, I.; Moustaki, M.; Douros, K. The Psychological Impact on Parents of Children Who Receive an Inconclusive Diagnosis for Cystic Fibrosis Following Newborn Screening: A Systematic Mini-Review. Children 2024, 11, 93. [Google Scholar] [CrossRef] [PubMed]
  33. Perobelli, S.; Zanolla, L.; Tamanini, A.; Rizzotti, P.; Maurice Assael, B.; Castellani, C. Inconclusive Cystic Fibrosis Neonatal Screening Results: Long-Term Psychosocial Effects on Parents. Acta Paediatr. 2009, 98, 1927–1934. [Google Scholar] [CrossRef]
  34. Hayeems, R.Z.; Miller, F.A.; Barg, C.J.; Bombard, Y.; Carroll, J.C.; Tam, K.; Kerr, E.; Chakraborty, P.; Potter, B.K.; Patton, S.; et al. Psychosocial Response to Uncertain Newborn Screening Results for Cystic Fibrosis. J. Pediatr. 2017, 184, 165–171.e1. [Google Scholar] [CrossRef]
  35. Tluczek, A.; Levy, H.; Rock, M.J.; Ondoma, C.; Brown, R.L. Impact of Intermediate Cystic Fibrosis Classification on Parents’ Perceptions of Child Vulnerability and Protectiveness. J. Fam. Nurs. 2019, 25, 287–313. [Google Scholar] [CrossRef]
  36. Ginsburg, D.K.; Salinas, D.B.; Cosanella, T.M.; Wee, C.P.; Saeed, M.M.; Keens, T.G.; Gold, J.I. High Rates of Anxiety Detected in Mothers of Children with Inconclusive Cystic Fibrosis Screening Results. J. Cyst. Fibros. 2023, 22, 420–426. [Google Scholar] [CrossRef]
  37. Tosco, A.; Marino, D.; Polizzi, S.; Tradati, V.; Padoan, R.; Giust, C.; Fabrizzi, B.; Taccetti, G.; Merli, L.; Terlizzi, V. A Multicentre Italian Study on the Psychological Impact of an Inconclusive Cystic Fibrosis Diagnosis after Positive Neonatal Screening. Children 2023, 10, 177. [Google Scholar] [CrossRef]
  38. Tluczek, A.; Chevalier McKechnie, A.; Lynam, P.A. When the Cystic Fibrosis Label Does Not Fit: A Modified Uncertainty Theory. Qual. Health Res. 2010, 20, 209–223. [Google Scholar] [CrossRef] [PubMed]
  39. Johnson, F.; Southern, K.W.; Ulph, F. Psychological Impact on Parents of an Inconclusive Diagnosis Following Newborn Bloodspot Screening for Cystic Fibrosis: A Qualitative Study. Int. J. Neonatal Screen. 2019, 5, 23. [Google Scholar] [CrossRef] [PubMed]
  40. Green, D.M.; Lahiri, T.; Raraigh, K.S.; Ruiz, F.; Spano, J.; Antos, N.; Bonitz, L.; Christon, L.; Gregoire-Bottex, M.; Hale, J.E.; et al. Cystic Fibrosis Foundation Evidence-Based Guideline for the Management of CRMS/CFSPID. Pediatrics 2024, 153, e2023064657. [Google Scholar] [CrossRef]
  41. Krishnananthan, T.; Pao, C. The Implications and Management of Cystic Fibrosis Screen Positive, Inconclusive Diagnosis Patients. Paediatr. Respir. Rev. 2019, 31, 21–24. [Google Scholar] [CrossRef] [PubMed]
  42. McGarry, M.E.; Ren, C.L.; Wu, R.; Farrell, P.M.; McColley, S.A. Detection of Disease-causing CFTR Variants in State Newborn Screening Programs. Pediatr. Pulmonol. 2023, 58, 465–474. [Google Scholar] [CrossRef]
  43. Martiniano, S.L.; Wu, R.; Farrell, P.M.; Ren, C.L.; Sontag, M.K.; Elbert, A.; McColley, S.A. Late Diagnosis in the Era of Universal Newborn Screening Negatively Affects Short- and Long-Term Growth and Health Outcomes in Infants with Cystic Fibrosis. J. Pediatr. 2023, 262, 113595. [Google Scholar] [CrossRef] [PubMed]
  44. Barben, J.; Castellani, C.; Munck, A.; Davies, J.C.; de Winter-de Groot, K.M.; Gartner, S.; Kashirskaya, N.; Linnane, B.; Mayell, S.J.; McColley, S.; et al. Updated Guidance on the Management of Children with Cystic Fibrosis Transmembrane Conductance Regulator-Related Metabolic Syndrome/Cystic Fibrosis Screen Positive, Inconclusive Diagnosis (CRMS/CFSPID). J. Cyst. Fibros. 2021, 20, 810–819. [Google Scholar] [CrossRef]
  45. Terlizzi, V.; Manti, S.; D’Amico, F.; Parisi, G.F.; Chiappini, E.; Padoan, R. Biochemical and Genetic Tools to Predict the Progression to Cystic Fibrosis in CRMS/CFSPID Subjects: A Systematic Review. Paediatr. Respir. Rev. 2024, 51, 46–55. [Google Scholar] [CrossRef] [PubMed]
  46. Terlizzi, V.; Dolce, D. Variability of the Sweat Test in Children with Cystic Fibrosis Previously CRMS/CFSPID: A Retrospective Monocenter Experience. J. Cyst. Fibros. 2023, 22, 496–498. [Google Scholar] [CrossRef] [PubMed]
  47. Gonska, T.; Keenan, K.; Au, J.; Dupuis, A.; Chilvers, M.A.; Burgess, C.; Bjornson, C.; Fairservice, L.; Brusky, J.; Kherani, T.; et al. Outcomes of Cystic Fibrosis Screening-Positive Infants with Inconclusive Diagnosis at School Age. Pediatrics 2021, 148, e2021051740. [Google Scholar] [CrossRef]
  48. Deignan, J.L.; Gregg, A.R.; Grody, W.W.; Guo, M.H.; Kearney, H.; Monaghan, K.G.; Raraigh, K.S.; Taylor, J.; Zepeda-Mendoza, C.J.; Ziats, C. Updated Recommendations for CFTR Carrier Screening: A Position Statement of the American College of Medical Genetics and Genomics (ACMG). Genet. Med. 2023, 25, 100867. [Google Scholar] [CrossRef]
  49. Gouveia, M.H.; Meeks, K.A.C.; Borda, V.; Leal, T.P.; Kehdy, F.S.G.; Mogire, R.; Doumatey, A.P.; Tarazona-Santos, E.; Kittles, R.A.; Mata, I.F.; et al. Subcontinental Genetic Variation in the All of Us Research Program: Implications for Biomedical Research. Am. J. Human Genet. 2025, 112, 1286–1301. [Google Scholar] [CrossRef]
  50. Madden, K.; Mueller, R.; Brown, C.; Valverde, K.D.; Langfelder-Schwind, E. Facilitators and Barriers to Increasing Equity in Cystic Fibrosis Newborn Screening Algorithms. Pediatr. Pulmonol. 2025, 60, e27449. [Google Scholar] [CrossRef]
  51. Tasher, D.; Dalal, I. The Genetic Basis of Severe Combined Immunodeficiency and Its Variants. Appl. Clin. Genet. 2012, 5, 67–80. [Google Scholar] [CrossRef]
  52. Fonseca, T.; Macedo, M.F. Inherited Metabolic Disorders: From Bench to Bedside. Biomedicines 2024, 12, 174. [Google Scholar] [CrossRef] [PubMed]
  53. Ford, G.A.; Denniston, S.; Sesser, D.; Skeels, M.R.; LaFranchi, S.H. Transient versus Permanent Congenital Hypothyroidism after Age 3 Years in Infants Detected by the First vs. Second Newborn Screening Test in Oregon. Horm. Res. Paediatr. 2016, 86, 169–177. [Google Scholar] [CrossRef] [PubMed]
  54. Richards, S.; Aziz, N.; Bale, S.; Bick, D.; Das, S.; Gastier-Foster, J.; Grody, W.W.; Hegde, M.; Lyon, E.; Spector, E.; et al. Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 2015, 17, 405–424. [Google Scholar] [CrossRef] [PubMed]
  55. Narravula, A.; Garber, K.B.; Askree, S.H.; Hegde, M.; Hall, P.L. Variants of Uncertain Significance in Newborn Screening Disorders: Implications for Large-Scale Genomic Sequencing. Genet. Med. 2017, 19, 77–82. [Google Scholar] [CrossRef]
Ijns 11 00060 g001
Figure 1. PRISMA flow diagram of literature review.
Figure 1. PRISMA flow diagram of literature review.
Ijns 11 00060 g001
Ijns 11 00060 g002
Figure 2. Reclassification Diagnoses of CRMS/CFSPID cases reported in the literature using 2 Variant Panels: (a) reclassification diagnosis using PanelCF-causing eliminates CRMS/CFSPID diagnoses; (b) reclassification diagnosis using PanelCF-causing+VVCCs retains more children with CRMS/CFSPID and misses less children who convert to CF.
Figure 2. Reclassification Diagnoses of CRMS/CFSPID cases reported in the literature using 2 Variant Panels: (a) reclassification diagnosis using PanelCF-causing eliminates CRMS/CFSPID diagnoses; (b) reclassification diagnosis using PanelCF-causing+VVCCs retains more children with CRMS/CFSPID and misses less children who convert to CF.
Ijns 11 00060 g002
Ijns 11 00060 g003
Figure 3. Initial sweat chloride by reclassification diagnosis from PanelCF-causing+VVCCs. *** Statistical significance p-value < 0.05.
Figure 3. Initial sweat chloride by reclassification diagnosis from PanelCF-causing+VVCCs. *** Statistical significance p-value < 0.05.
Ijns 11 00060 g003
Table 1. Diagnostic criteria for CF and CRMS/CFSPID [6].
Table 1. Diagnostic criteria for CF and CRMS/CFSPID [6].
Diagnostic Criteria for CF and CRMS
Genetic CFTR variantsSweat chloride
Variant 1Variant 2Normal
(<30 mmol/L)		Intermediate
(30–60 mmol/L)		Elevated
(>60 mmol/L)
CF-causingCF-causingCFCFCF
CF-causing, VVCC, or VUSVVCC or VUSCRMSCRMSCF
CF-causing, VVCC, or VUSNon CF-causingNormal (Carrier)CRMSCF
Non CF-causingNon CF-causingNormalCRMSCF
Table 2. Definitions of variant categories used in this paper.
Table 2. Definitions of variant categories used in this paper.
Variant Interpretation TermsDefinition
CF-causing variant A CFTR variant that causes CF when in trans with another CF-causing variant
Variant of varying clinical consequences (VVCC) A CFTR variant that causes CF in some children but not others when in trans with another CF-causing variant.
Non CF-causing A CFTR variant that does not cause CF.
Variant of unknown significance (VUS) A CFTR variant that is not described in the CFTR2 database.
Not identified No CFTR variant identified.
Table 3. CFTR variant reclassification diagnostic schema.
Table 3. CFTR variant reclassification diagnostic schema.
CFTR Variant Reclassification Diagnostic Schema
Variant 1
CF-causing VVCCNon CF-causingVUSNot identified
Variant 2CF-causing CFCRMS/CFSPID or Undetected ***UndetectedUndetectedUndetected
VVCCCRMS/CFSPID or Undetected ***UndetectedUndetectedUndetected
Non CF-causingUndetectedUndetectedUndetected
VUSUndetectedUndetected
Not identifiedUndetected
*** Undetected using PanelCF-causing; CRMS/CFSPID using PanelCF-causing+VVCCs.
Table 4. Manuscripts included in meta-analysis.
Table 4. Manuscripts included in meta-analysis.
1st Author, YearLocationStudy TypeYears of StudyTotal CRMSCRMS→CFCRMS→CFTR-RDIRTInitial Sweat Chloride
Castaldo A, 2020 [14]ItalyRetrospective cohort2008–20199928✔✔
Ooi CY, 2015 [15]Canada, ItalyProspective cohort2007–2013829✔
Munck A, 2020 [16]FranceProspective cohort2002–20097021✔
Gunnett MA, 2023 [17]USARetrospective cross-sectional2008–20206311✔
Terlizzi, Vito, 2019 [18]ItalyRetrospective cross-sectional2011–2016505✔
Hatton A, 2022 [19]PolandCase series2006–2016234✔
Rock MJ, 2023 [20]USARetrospective cross-sectional2016–202122✔
Terlizzi V, 2021 [21]ItalyProspective cohort2011–201822184✔
Salinas DB, 2023 [22]USARetrospective cross-sectionalBefore 20232012
Kharrazi M, 2015 [23]USACross-sectional2007–20122020
Ooi CY, 2019 [24]Canada, ItalyProspective cohort2007–20161414✔✔
Groves T, 2015 [25]AustraliaRetrospective cohort1996–20101414✔✔
Çoksüer F, 2025 [26]TurkeyRetrospective cohort2015–202311✔✔
Terlizzi V, 2021 [27]ItalyProspective cohort2018–2020112✔✔
Dolce D, 2023 [28]ItalyRetrospective cohort2011–20181073✔
Ginsburg D, 2022 [29]USACase seriesBefore 20221010✔✔
Skov M, 2020 [30]DenmarkRetrospective cross-sectional2016–20183✔✔
Table 5. Reclassification diagnostic schema of all children with CRMS/CFSPID.
Table 5. Reclassification diagnostic schema of all children with CRMS/CFSPID.
CFTR Variant Types of Children with CRMS/CFSPID
Variant 1
(n = 516 *)CF-causing VVCCNon CF-causingVUSNot identified
Variant 2CF-causing 45 (8.7%)243 (47.1%)50 (9.7%)47 (9.1%)45 (8.7%)
VVCC21 (4.1%)15 (2.9%)10 (1.9%)8 (1.6%)
Non CF-causing2 (0.4%)2 (0.4%)2 (0.4%)
VUS1 (0.2%)1 (0.2%)
Not identified23 (4.5%)
* One child had a complex variant combination and was not included in a single category: CF-causing variant + VVCC in cis with 1 non CF-causing variant.
Table 6. Reclassification diagnostic schema of children with CRMS/CFSPID→CF.
Table 6. Reclassification diagnostic schema of children with CRMS/CFSPID→CF.
CFTR Variant Types of Children with CRMS/CFSPID→CF
Variant 1
(n = 136 *)CF-causing VVCCNon CF-causingVUSNot identified
Variant 2CF-causing 45 (33.1%)68 (50%)2 (1.5%)8 (5.9%)8 (5.9%)
VVCC3 (2.2%)---1 (0.7%)---
Non CF-causing---------
VUS------
Not identified---
* One child had a complex variant combination and was not included in a single category: CF-causing variant + VVCC in cis with 1 non CF-causing variant.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Wyatt, M.; Quinn, A.; Shade, L.; McGarry, M. Refining CFTR-Related Metabolic Syndrome (CRMS)/Cystic Fibrosis Screen Positive, Inconclusive Diagnosis (CFSPID) Diagnosis: Impact of CFTR2 Variant Classifications. Int. J. Neonatal Screen. 2025, 11, 60. https://doi.org/10.3390/ijns11030060

AMA Style

Wyatt M, Quinn A, Shade L, McGarry M. Refining CFTR-Related Metabolic Syndrome (CRMS)/Cystic Fibrosis Screen Positive, Inconclusive Diagnosis (CFSPID) Diagnosis: Impact of CFTR2 Variant Classifications. International Journal of Neonatal Screening. 2025; 11(3):60. https://doi.org/10.3390/ijns11030060

Chicago/Turabian Style

Wyatt, MacKenzie, Alexandra Quinn, Lincoln Shade, and Meghan McGarry. 2025. "Refining CFTR-Related Metabolic Syndrome (CRMS)/Cystic Fibrosis Screen Positive, Inconclusive Diagnosis (CFSPID) Diagnosis: Impact of CFTR2 Variant Classifications" International Journal of Neonatal Screening 11, no. 3: 60. https://doi.org/10.3390/ijns11030060

APA Style

Wyatt, M., Quinn, A., Shade, L., & McGarry, M. (2025). Refining CFTR-Related Metabolic Syndrome (CRMS)/Cystic Fibrosis Screen Positive, Inconclusive Diagnosis (CFSPID) Diagnosis: Impact of CFTR2 Variant Classifications. International Journal of Neonatal Screening, 11(3), 60. https://doi.org/10.3390/ijns11030060

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop