Improvements in bone pain and patient quality of life in adults with Gaucher disease during substrate reduction therapy: a case series
Bibliographic record
Abstract
Background: Gaucher disease type 1 (GD1) is an inherited lysosomal storage disorder caused by a deficiency of glucocerebrosidase, and is characterised by haematological, visceral and bone manifestations that vary widely in terms of severity and age at onset. In particular, the bone manifestations of GD1 can restrict physical activity and impact heavily on patient quality of life (QoL). Here, we describe three GD1 patients who showed remarkable improvements in bone-related outcomes during treatment with oral miglustat, two of whom had previously failed to respond to relatively high doses of enzyme replacement therapy (ERT). In the third, needle phobia led to oral miglustat being used as the initial treatment. Case presentation: Case 1 is a 39 year-old female diagnosed aged 4 years (genotype N370S/L444P) and underwent ERT (alglucerase then imiglucerase) since 1994. In 2013 she discontinued ERT (treatment duration 19 years) due to ongoing and debilitating bone pain and fatigue, and switched to miglustat therapy. She has since experienced substantial reductions in bone pain and improved physical function. Case 2 is a 59 year-old female diagnosed aged 17 years (genotype N370S/H162P). She commenced ERT treatment in 2002, with a brief interruption in 2007, and continued on ERT (imiglucerase followed by velaglucerase) up to 2014: total ERT monotherapy duration 12 years. She subsequently received combination therapy (velaglucerase plus miglustat) for 2 years but finally switched to miglustat monotherapy in 2016 due to ongoing bone manifestations. Her bone pain has since improved a great deal, alongside improvements in QoL parameters. Case 3 is a 48 year-old male diagnosed aged 11 years (genotype R463C/L105R). Having not received any previous treatment he avoided ERT due to life-long needle phobia. He therefore started miglustat therapy in late-2017, and has received it for approximately 1 year. During this time he experienced vast improvements in QoL due to decreased bone pain. Interestingly in all three cases, there were little or no observed changes in objective bone parameters (bone marrow burden, bone mineral density). Conclusions: These three GD1 cases illustrate the potential to achieve substantial reductions in bone pain and improvements in QoL, even in patients who have failed to respond to long-term ERT with regard to bone status.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".