Gaucher Disease: A Systematic Review and Meta-Analysis of Bone Complications and Their Response to Treatment.
Bibliographic record
Abstract
Abstract Gaucher disease (GD) is an inherited lysosomal storage disease, which is often managed by enzyme replacement therapy (ERT). While the response to ERT is gratifying in terms of hepatosplenomegaly, cytopenias, and general well-being, the response of bony disease is very slow, and in some cases non-existent. Skeletal manifestations are the most painful and debilitating components of GD type 1, and have a negative impact on the patient’s quality of life. Whether an increase in the dose of ERT has a beneficial effect, and whether substrate reduction therapy (SRT) stabilizes and/or ameliorates bony disease, is controversial. The aim of our study was to determine whether or not there is enough evidence to make a definitive statement about the effects of ERT and SRT on bony complications of Gaucher disease. We conducted a systematic review of all studies examining the effects of ERT and SRT on bony complications of Gaucher disease published before July 2008. The studies were identified by a computerized search using Medline, Embase, The Cochrane Database of Systematic Reviews, The Cochrane Central Register of Control Trials (CCTR), and bibliographies of papers subsequently retrieved from the search. Three hundred studies were grouped according to whether they deal with the natural history of GD or therapeutic issues and 17 studies were included in the review. Meta analyses were done using a random effects model and the studies compared baseline versus after-treatment values. Quantitative Chemical Shift Imaging (QCSI) of vertebral bone marrow (BM) fat fraction, Magnetic Resonance Imaging (MRI) T1-weighted signal, semi-quantitative MRI bone marrow burden (BMB) score, and bone mineral density (BMD) Z scores of spine and femur were used to assess the effects of ERT and SRT on bony complications. Of the 4 studies that measured BM fat fraction, 3 showed that fat fraction significantly increased after ERT (Weighted Mean Difference [WMD] of 0.17, 95 % CI of 0.13 to 0.2, n= 36, p < 0.00001) and one study showed a non-significant increase in fat fraction after SRT (n = 2, p = 1.23). MRI T1-weighted signal was measured in 6 studies (5 studies on ERT and one on SRT), and 44/78 (56%) of GD1 patients were responders to ERT versus 20/78 (25.6%) who did not respond to ERT. One study showed that BM infiltration generally decreased after SRT. Of the 3 studies that measured BMB score, 2 showed that BMB score significantly decreased after ERT (WMD of −4.98, 95 % CI of −8.38 to −1.57, n= 27, p = 0.004) and one study showed a stable BMB score after SRT (n = 6, p = 0.82).The 4 studies in which BMD Z score of lumbar spine (LS) was measured showed an increase in Z score after ERT (WMD of 0.37, 95 % CI of −0.05 to 0.79, n= 54, p = 0.09) and one study showed a significant increase in LS Z score after 6 months of SRT. Of the 3 studies that measured BMD Z score of femurs, 2 showed a non-significant increase in Z score after ERT (WMD of 0.16, 95 % CI of −0.29 to 0.61, n= 43, p = 0.48) and one study showed a significant increase in femur Z score after 6 months of SRT. These studies suggest that ERT may be more effective in ameliorating BM involvement than in increasing BMD Z scores. SRT may stabilize the BM involvement and generally increase the BMD Z scores. However, further investigations are needed on the effects of SRT on bony complications of GD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.041 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".