Cystic fibrosis-related mortality trends in Brazil for the 1999-2017 period: a multiple-cause-of-death study

Augusto Hasiak Santo1, Luiz Vicente Ribeiro Ferreira da Silva-Filho2,3

  • 1. Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo (SP) Brasil (aposentado).

Insights

Mortality rates for cystic fibrosis (CF) are increasing in Brazil, with a significant rise in the median age at death. This trend highlights the evolving impact of CF on public health outcomes.

Area of Science:

  • Public Health
  • Epidemiology
  • Medical Statistics

Background:

  • Cystic Fibrosis (CF) is a genetic disorder affecting multiple organs.
  • Understanding mortality trends is crucial for public health interventions.

Purpose of the Study:

  • To analyze causes of death and mortality data for cystic fibrosis in Brazil.
  • To utilize a multiple-cause-of-death methodology for comprehensive analysis.

Main Methods:

  • Extracted annual mortality data from 1999-2017 from the Brazilian National Ministry of Health.
  • Selected death certificates listing ICD-10 code E84 (CF) as an underlying or associated cause.
  • Calculated standardized mortality rates and performed joinpoint regression analysis.

Main Results:

  • Identified 2,854 CF-related deaths between 1999 and 2017.
  • Observed a continuous upward trend in CF death rates, with significant annual percent changes in males and females.
  • Noted a substantial increase in the median age at death, from 7.5 to 56.5 years.

Conclusions:

  • Significant increase in CF-related death rates in Brazil.
  • Concurrent rise in the median age at death indicates improved survival.
  • Respiratory diseases are the primary associated cause of death in CF patients.
Abstract

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,...
542
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...
310
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
522
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
376
Life Tables01:22

Life Tables

A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
330
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...
401