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Abstract Details

Use of MLPA for the diagnosis of Duchenne Muscular Dystrophy: Systematic Review and Meta-Analysis
Child Neurology and Developmental Neurology
Child Neurology and Developmental Neurology Posters (7:00 AM-5:00 PM)
079
To estimate the detection rate of MLPA in the diagnosis of patients with clinical suspicion of DMD. 

Duchenne Muscular Dystrophy (DMD) requires a molecular test or immunohistochemistry to confirm the diagnosis. However, the latter is considered too invasive to be performed routinely. Recently, Multiplex Ligand-Dependent Amplification (MLPA) has become the method of choice for initial testing. Thus, to develop a concrete approach for the diagnosis of DMD, it is necessary to know how many cases can be detected using MLPA, and how many are missed. 

A systematic search was performed in the PubMed/Medline and Scopus databases until October 2020. The quality of the studies was evaluated with Quadas-2 in duplicate and independently using the GRADE approach. We included studies performed in patients with diagnosis of DMD in whom MLPA was used. Data was extracted to perform a meta-analysis of proportions and estimate the detection rate and un-detection rate. These were defined as the proportion of true positives and false negatives from total confirmed patients, respectively. The univariate model of random effects was used, and heterogeneity was evaluated with I2. Publication bias was assessed with a Funnel plot and Egger’s test. 

We screened 105 studies for full text review from1324 in the initial search. We selected 10 studies with a total of 3786 patients suspicious for DMD/BMD. We found a detection rate of 78.33% (CI95%: 74.58 - 82.09) and un-detection rate of 21.67% (CI95%: 17.91 - 25.42). I2 was 83.73% for both. For publication bias, Egger's test was not significant (p=0.118). Finally, the GRADE approach gave a low certainty to the body of evidence, due to risk of bias and inconsistency.

We determined the detection rate of MLPA for the diagnosis of DMD/BMD suspected patients at 78%. Although with low certainty, this suggests MLPA may be adequate for initial testing.

Authors/Disclosures
Marco M. Malaga, MD (University of California in San Francisco)
PRESENTER
Mr. Malaga has nothing to disclose.
Niels V. Pacheco, MD Mr. Pacheco has nothing to disclose.
No disclosure on file
No disclosure on file
Peggy C. Martinez Esteban, MD Dr. Martinez Esteban has nothing to disclose.
Carlos Alva-Diaz Carlos Alva-Diaz has nothing to disclose.