Evidence map›Paper›PMID 42510783›Full record

ReviewGenes2026

Cystic Fibrosis: Modern Diagnostic and Therapeutic Advances from Molecular Pathogenesis to Multidisciplinary Management.

Liqin Ke, Lijun Guan, Yiyao Bao, Chao Tang

Abstract readReview
In one paragraph

Review in Genes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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

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

2 · The registry

The trial behind it

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

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

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

5 · Who and what money

Authors and funding

4 authors.

Liqin KeChildren's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou 310052, China.
Lijun GuanChildren's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou 310052, China.
Yiyao BaoChildren's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou 310052, China.ORCID 0009-0003-2185-2122
Chao TangChildren's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou 310052, China.ORCID 0000-0002-5072-5849

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cystic fibrosis (CF) is an autosomal recessive disorder caused by pathogenic variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. It is increasingly understood through a genomics-informed framework linking variant architecture to phenotype, diagnosis, and therapeutic eligibility. This review summarizes current evidence on CFTR structure, variant interpretation, genotype-phenotype heterogeneity, diagnostic workflows, and modern management. We highlight how full-gene sequencing, curated disease-liability databases, functional testing, and organoid-informed theratyping refine diagnosis and treatment selection; how disrupted chloride and bicarbonate transport drives muco-obstructive airway disease and multisystem complications; and why modulator therapy must still be integrated with respiratory, nutritional, endocrine, hepatobiliary, reproductive, and psychosocial care. We also outline unresolved challenges in rare variants, residual organ damage, ancestry-related diagnostic gaps, and mutation-agnostic therapeutic development.

Indexed as

Cystic FibrosisCystic Fibrosis Transmembrane Conductance RegulatorHumansMutationPhenotypeCFTR protein, humanCystic Fibrosis Transmembrane Conductance RegulatorCFTRCFTR modulatorscystic fibrosisgenomic diagnosticsgenotype–phenotype correlationprecision medicinevariant interpretation

Identifiers

PMID42510783
PMCPMC13408614

What OpenQuestion holds

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Registered trials

None linked

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