Update on the safety and efficacy of retroviral gene therapy for immunodeficiency due to adenosine deaminase deficiency
Bibliographic record
Abstract
Adenosine deaminase (ADA) deficiency is a rare, autosomal-recessive systemic metabolic disease characterized by severe combined immunodeficiency (SCID). The treatment of choice for ADA-deficient SCID (ADA-SCID) is hematopoietic stem cell transplant from an HLA-matched sibling donor, although <25% of patients have such a donor available. Enzyme replacement therapy (ERT) partially and temporarily relieves immunodeficiency. We investigated the medium-term outcome of gene therapy (GT) in 18 patients with ADA-SCID for whom an HLA-identical family donor was not available; most were not responding well to ERT. Patients were treated with an autologous CD34(+)-enriched cell fraction that contained CD34(+) cells transduced with a retroviral vector encoding the human ADA complementary DNA sequence (GSK2696273) as part of single-arm, open-label studies or compassionate use programs. Overall survival was 100% over 2.3 to 13.4 years (median, 6.9 years). Gene-modified cells were stably present in multiple lineages throughout follow up. GT resulted in a sustained reduction in the severe infection rate from 1.17 events per person-year to 0.17 events per person-year (n = 17, patient 1 data not available). Immune reconstitution was demonstrated by normalization of T-cell subsets (CD3(+), CD4(+), and CD8(+)), evidence of thymopoiesis, and sustained T-cell proliferative capacity. B-cell function was evidenced by immunoglobulin production, decreased intravenous immunoglobulin use, and antibody response after vaccination. All 18 patients reported infections as adverse events; infections of respiratory and gastrointestinal tracts were reported most frequently. No events indicative of leukemic transformation were reported. Trial details were registered at www.clinicaltrials.gov as #NCT00598481.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".