The NCS‐LSD cohort study: a description of the methods and analyses used to assess the long‐term effectiveness of enzyme replacement therapy and substrate reduction therapy in patients with lysosomal storage disorders is a research paper published in Journal of Inherited Metabolic Disease (2014). On theSindex it has a DataRank of 0.540. It has been cited 10 times, with 5 citing works in its 1-hop citation network.
AbstractLysosomal storage disorders (LSDs) comprise more than 50 extremely rare, inherited metabolic diseases resulting from a deficiency of specific lysosomal enzymes required for normal macromolecular metabolism. The National Collaborative Study for Lysosomal Storage Disorders (NCS‐LSD), was a longitudinal cohort study which collected prospective and retrospective clinical data, and patient‐reported data from adults and children with a confirmed diagnosis of Gaucher disease, Fabry disease, mucopolysaccharidosis type I (MPS I), mucopolysaccharidosis type II (MPS II), Pompe disease and Niemann Pick disease type C (NPC) in the UK. The study aimed to determine the natural history of these conditions and estimate the effectiveness and cost of therapies. Clinical outcomes were chosen to reflect disease progression. Age‐ and gender‐adjusted treatment effects were estimated using generalised linear mixed models. Treated patients contributed data before and during treatment while untreated patients contributed natural history data. A total of 711 adults and children were recruited to this study from the seven LSD treatment centres in England. Data was collected from 2008 to 2011. This paper describes the methods used to collect and analyse clinical data for this study. The clinical findings are reported separately in a series of condition‐specific articles in this issue.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.360
From this paper's citation signal
Citation Network Contribution
0.181
From 5 citing papers with measurable signal
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 67% comes from its base citations and 33% from the citation network (5 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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