Related Experiment Video

Updated: Feb 11, 2026

Antibiotic Efficacy Testing in an Ex vivo Model of Pseudomonas aeruginosa and Staphylococcus aureus Biofilms in the Cystic Fibrosis Lung
09:26

Antibiotic Efficacy Testing in an Ex vivo Model of Pseudomonas aeruginosa and Staphylococcus aureus Biofilms in the Cystic Fibrosis Lung

Published on: January 22, 2021

7.7K

Early diagnosis from newborn screening maximises survival in severe cystic fibrosis

Gloria Tridello1, Carlo Castellani1,2, Ilaria Meneghelli1

  • 1Centre for Cystic Fibrosis, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.

ERJ Open Research
|April 26, 2018
PubMed

Insights

Newborn screening for cystic fibrosis (CF) significantly improves long-term survival. Early detection through CF newborn screening leads to better outcomes, especially for infants with severe symptoms.

Area of Science:

  • Medical Genetics
  • Pediatrics
  • Public Health

Background:

  • Newborn screening (NBS) for cystic fibrosis (CF) is increasingly implemented globally.
  • Limited data exist on the long-term survival impact of CF NBS.
  • Early diagnosis is crucial for managing CF progression.

Purpose of the Study:

  • To evaluate the long-term effects of cystic fibrosis newborn screening on patient survival.
  • To compare survival rates between patients diagnosed via NBS and those diagnosed symptomatically.
  • To assess the impact of NBS on different severity groups.

Main Methods:

  • Retrospective analysis of 586 patients diagnosed and followed between 1971 and 2014.
  • Categorization of patients into NBS, meconium ileus, and symptomatic diagnosis groups.
  • Grouping based on initial hospitalizations (mild, moderate, severe) to assess long-term outcomes.

Main Results:

  • The 30-year survival probability for the NBS group was 80.1%, compared to 71.0% for the symptomatic group.
  • Significantly higher 20-year survival rates were observed in the NBS group versus the symptomatic group for severe (85% vs. 64%) and moderate (94% vs. 86%) cases.
  • Cox-model analysis confirmed the survival benefits associated with NBS.

Conclusions:

  • Newborn screening for cystic fibrosis demonstrates a positive long-term impact on overall survival.
  • NBS effectively mitigates the poorer outcomes associated with early, severe CF presentations.
  • Implementing CF NBS is crucial for improving long-term prognosis in affected children.

More Related Videos

Growing a Cystic Fibrosis-Relevant Polymicrobial Biofilm to Probe Community Phenotypes03:53

Growing a Cystic Fibrosis-Relevant Polymicrobial Biofilm to Probe Community Phenotypes

Published on: April 19, 2024

1.2K
Expression and Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein in Saccharomyces cerevisiae14:56

Expression and Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein in Saccharomyces cerevisiae

Published on: March 10, 2012

19.1K

Related Concept Videos

Cystic Fibrosis: Pathogenesis01:23

Cystic Fibrosis: Pathogenesis

Cystic fibrosis (CF), an autosomal recessive disorder, significantly affects the function of exocrine glands. This genetically inherited disease is characterized by the production of thick and sticky mucus, which can severely affect various organs and systems in the body.
CF is primarily caused by a genetic mutation in a chromosome 7 gene coding for the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The most common gene mutation leading to CF is the ΔF508 mutation,...
895
Cystic Fibrosis: Management01:24

Cystic Fibrosis: Management

Cystic fibrosis (CF) is an autosomal recessive disorder that predominantly affects individuals of Northern European descent, occurring at a rate of 1 in 3500. It is caused by a genetic mutation in a gene on chromosome 7, most commonly the ΔF508 mutation, that codes for the cystic fibrosis transmembrane conductance regulator (CFTR) protein. This results in thicker mucus secretions and obstruction pathologies in multiple organs, including the lungs and sinuses.
Sinus disease and chronic...
549
Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
732
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
436
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
830
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
617