dat.crisafulli2020: Duchenne Muscular Dystrophy (DMD) Prevalence Data

In metadat: Meta-Analysis Datasets

Duchenne Muscular Dystrophy (DMD) Prevalence Data

Description

26 studies reporting estimates of the birth prevalence of Duchenne muscular dystrophy.

Usage

dat.crisafulli2020

Format

The data frame contains the following columns:

study	character	study label (first author, year)
pubyear	integer	publication year
country	factor	origin of investigated population
from, to	integer	time span of investigation (years)
cases	integer	number of DMD cases
total	integer	corresponding total population

Details

Duchenne muscular dystrophy (DMD) is a rare disease that is caused by a genetic mutation and is characterized by impairment through muscle weakness and a reduced life expectancy.

Crisafulli et al. (2020) reported on a systematic review of data on the epidemiology of DMD, including estimates of the birth prevalence (which is of the order of a few per ten thousand). One of the originally reported studies (Koenig, 2019) is omitted here, as it constitutes an obvious outlier, and the reliability of the reported data is doubtful; Crisafulli et al. (2020) pointed out that “Concerning birth prevalence, Koenig et al. were found to be outliers. This study had problems with data collection in the last study year, as due to privacy issues, DMD cases were under-reported.”

Concepts

medicine, epidemiology, proportions, dose-response models

Author(s)

Christian Roever, [e-mail]

Source

Crisafulli, S., Sultana, J., Fontana, A., Salvo, F., Messina, S., & Trifiro, G. (2020). Global epidemiology of Duchenne muscular dystrophy: an updated systematic review and meta-analysis. Orphanet Journal of Rare Diseases, 15, 141. ⁠https://doi.org/10.1186/s13023-020-01430-8⁠

Examples

# show (some) data
head(dat.crisafulli2020)

## Not run: 
# compute logarithmic proportions and associated standard errors
library(metafor)
logp <- escalc(measure="PLN",
               xi=cases, ni=total, slab=study,
               data=dat.crisafulli2020)

# perform meta-analysis
rma01 <- rma.uni(logp)

# show results
rma01

# illustrate in a forest plot
forest(rma01, xlim=c(-12,-5))

## End(Not run)

metadat documentation built on April 4, 2025, 4:36 a.m.