Evidence map›Paper›PMID 36245384›Full record

ArticleJournal of neuromuscular diseases2022

Characterizing the Occurrence of Key Clinical Milestones in Duchenne Muscular Dystrophy in the United States Using Real-World Data.

Shelagh M Szabo, Alexa C Klimchak, Christina Qian, Susan Iannaccone, Evan Popoff, Katherine L Gooch

Abstract read
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Article in Journal of neuromuscular diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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

6 authors.

Shelagh M SzaboBroadstreet Health Economics & Outcomes Research, Vancouver BC, Canada.
Alexa C KlimchakSarepta Therapeutics, Inc, Cambridge MA, USA.
Christina QianBroadstreet Health Economics & Outcomes Research, Vancouver BC, Canada.
Susan IannacconeUniversity of Texas Southwestern, Harry Hines Blvd, Dallas TX, USA.
Evan PopoffBroadstreet Health Economics & Outcomes Research, Vancouver BC, Canada.
Katherine L GoochSarepta Therapeutics, Inc, Cambridge MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundData on the clinical course of Duchenne muscular dystrophy (DMD) exist from well-characterized clinical cohorts but estimates from real-world populations are fewer.

objectiveThe objective was to estimate the prevalence of key clinical milestones by age, among real-world commercially-insured DMD patients in the United States.

methodsMarketScan claims (2013-2018) were used to identify males with DMD. The percentages with wheelchair use or experiencing scoliosis, neurologic/neuropsychiatric involvement, cardiomyopathy, and respiratory involvement were tabulated; as were the median (interquartile range [IQR]) ages at first observed occurrence within the claims data.

resultsAmong DMD patients (n = 1,964), the median (IQR) baseline age was 15 (9-21) years, and median follow-up was 1.7 years. Wheelchair use was observed in 55% of those aged 8 to 13 years at cohort entry; scoliosis, among 38% of those 8 to 10 and 52% of those 11 to 13 years; neurologic/neuropsychiatric involvement, among 41-43% of those 8 to 13 years; respiratory involvement, among 45% of those 14 to 19 years; and cardiomyopathy, among 68% of those 14 to 16 and 58% of those 17 to 19 years.

conclusionsThe prevalence of key clinical milestones across ages was broadly consistent with published findings. Variability in estimates reflect clinical heterogeneity; these contemporary estimates from real-world data help characterize clinical outcomes in DMD.

Indexed as

CardiomyopathiesMuscular Dystrophy, DuchenneScoliosisWheelchairsCohort StudiesHumansMaleUnited Statesclaimsclinical outcomesDMDreal-world

Identifiers

PMID36245384
PMCPMC9697036

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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.