Evidence map›Paper›PMID 38248793›Full record

ReviewJournal of personalized medicine2024

Laboratory Tools to Predict CFTR Modulator Therapy Effectiveness and to Monitor Disease Severity in Cystic Fibrosis.

Mafalda Bacalhau, Mariana Camargo, Miquéias Lopes-Pacheco

Open access · goldAbstract readReview
In one paragraph

Review in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

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

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

2 · The registry

The trial behind it

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

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

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

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

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Mafalda BacalhauBiosystems & Integrative Sciences Institute (BioISI), Faculty of Sciences, University of Lisbon, 1749-016 Lisbon, Portugal.
Mariana CamargoDepartment of Surgery, Division of Urology, Sao Paulo Federal University, Sao Paulo 04039-060, SP, Brazil.ORCID 0000-0003-2861-8550
Miquéias Lopes-PachecoBiosystems & Integrative Sciences Institute (BioISI), Faculty of Sciences, University of Lisbon, 1749-016 Lisbon, Portugal.ORCID 0000-0002-7444-9359
University of Lisbon · PTUniversidade Federal de São Paulo · BR

Funding

Cystic Fibrosis Foundation LOPES21I0Cystic Fibrosis Foundation LOPES23G0
6 · The paper itself

Abstract

The implementation of cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulator drugs into clinical practice has been attaining remarkable therapeutic outcomes for CF, a life-threatening autosomal recessive genetic disease. However, there is elevated CFTR allelic heterogeneity, and various individuals carrying (ultra)rare CF genotypes remain without any approved modulator therapy. Novel translational model systems based on individuals' own cells/tissue are now available and can be used to interrogate in vitro CFTR modulator responses and establish correlations of these assessments with clinical features, aiming to provide prediction of therapeutic effectiveness. Furthermore, because CF is a progressive disease, assessment of biomarkers in routine care is fundamental in monitoring treatment effectiveness and disease severity. In the first part of this review, we aimed to focus on the utility of individual-derived in vitro models (such as bronchial/nasal epithelial cells and airway/intestinal organoids) to identify potential responders and expand personalized CF care. Thereafter, we discussed the usage of CF inflammatory biomarkers derived from blood, bronchoalveolar lavage fluid, and sputum to routinely monitor treatment effectiveness and disease progression. Finally, we summarized the progress in investigating extracellular vesicles as a robust and reliable source of biomarkers and the identification of microRNAs related to CFTR regulation and CF inflammation as novel biomarkers, which may provide valuable information for disease prognosis.

Indexed as

airway cellsbioassaybiomarkersextracellular vesiclesinflammationmicroRNAorganoidsprecision medicinetheratyping

Identifiers

PMID38248793
PMCPMC10820563
OpenAlexW4390877684

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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