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A new framework for evaluating the health impacts of treatment for Gaucher disease type 1

Overview of attention for article published in Orphanet Journal of Rare Diseases, February 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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1 news outlet
policy
1 policy source
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13 X users

Citations

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6 Dimensions

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27 Mendeley
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Title
A new framework for evaluating the health impacts of treatment for Gaucher disease type 1
Published in
Orphanet Journal of Rare Diseases, February 2017
DOI 10.1186/s13023-017-0592-6
Pubmed ID
Authors

Michael L. Ganz, Sean Stern, Alex Ward, Luba Nalysnyk, Martin Selzer, Alaa Hamed, Neal Weinreb

Abstract

The Disease Severity Scoring System (DS3) is a validated measure for evaluating Gaucher disease type 1 (GD1) severity. We developed a new framework, consisting of health states, transition probabilities between those states, and preferences for those states (utilities) based on the DS3 to predict long-term outcomes of patients starting treatment. We defined nine mutually exclusive (alive) health states based on three DS3 categories: mild (0 ≤ DS3 ≤ 3.5) without symptoms of bone disease; mild with bone pain, mild with severe skeletal complications (SSC) defined as lytic lesions, avascular necrosis, or fracture; moderate (3.5 < DS3 ≤ 6.5) without SSC; moderate with SSC; marked (6.5 < DS3 ≤ 9.5) without SSC; marked with SSC; severe (9.5 < DS3 ≤ 19) without SSC; and severe with SSC. Health-state transition probabilities and utilities were estimated from a longitudinal sample of patients with GD1 who started enzyme replacement therapy (the DS3 Score Study). Age dependent GD1-specific mortality was derived from published data. We used a Markov state-transition model to illustrate how to estimate time spent in each health state. The average predicted utilities for each health state ranged from 0.76 for mild disease with no clinical symptoms of bone disease to 0.52 with severe disease with SSC. Transition probabilities depended on disease severity (DS3 score) at treatment initiation and whether patients had undergone a total splenectomy or had an intact spleen/partial splenectomy prior to starting treatment. Patients who started treatment with intact or residual spleens spent more time in better health states than those who started treatment with total splenectomy. This new framework, which is based on the DS3, can be used to project the long-term outcomes of GD1 patients starting treatment. The framework could also be used to compare the long-term outcomes of different GD1 treatment options. NCT01136304 . Registered: May 31, 2010 (retrospectively registered).

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Master 4 15%
Student > Bachelor 3 11%
Student > Ph. D. Student 3 11%
Student > Doctoral Student 2 7%
Other 4 15%
Unknown 6 22%
Readers by discipline Count As %
Medicine and Dentistry 9 33%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Business, Management and Accounting 2 7%
Nursing and Health Professions 2 7%
Economics, Econometrics and Finance 2 7%
Other 3 11%
Unknown 7 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 April 2021.
All research outputs
#1,721,340
of 23,642,687 outputs
Outputs from Orphanet Journal of Rare Diseases
#179
of 2,728 outputs
Outputs of similar age
#34,917
of 311,381 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#9
of 59 outputs
Altmetric has tracked 23,642,687 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,728 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 311,381 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.