A systematic review comparing allogeneic hematopoietic stem cell transplant to gene therapy in sickle cell disease
Bibliographic record
Abstract
INTRODUCTION: Allogeneic hematopoietic stem cell transplant (HSCT) and gene therapy (GT) are two potentially curative approaches for sickle cell disease (SCD), but they have never been compared in clinical trials. OBJECTIVE: To compare the safety and efficacy of HSCT and GT to assist clinicians and patients in making informed treatment decisions. METHODS: Phase I-III clinical trials and case reports/series were included. Regimens included HSCT from all stem cell sources, lentiviral gene therapy, and gene editing, with any conditioning regimen. We searched Medline and EMBASE databases as of 1st June 2020 for studies reporting HSCT and GT outcomes in SCD. The Newcastle-Ottawa scale was used to assess the risk of bias. Descriptive statistics and post-hoc imputation for standard deviations of mean change in FEV1 and FVC were performed. RESULTS: = 40). Length of follow-up was 3,881.5 and 58.7 patient-years for HSCT and GT, respectively. Overall quality of evidence was low, with no randomized controlled trials identified. Two-year overall survival for HSCT was 91%; mortality was 2.5% for GT. Acute chest syndrome and vaso-occlusive episodes were reduced post-HSCT and GT. Meta-analysis was not possible due to lack of comparator and heterogeneity in outcome measures reporting. Very few studies reported post-transplant end-organ function. Six secondary malignancies (5 post-HSCT, 1 post-GT) were reported. DISCUSSION: Reporting of SCD-related complications and patient-important outcomes is lacking for both strategies. We advocate for standardized reporting to better compare outcomes within and between treatment groups.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".