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Record W4409993594 · doi:10.7759/cureus.83304

The Use of Bone Marrow Transplantation (BMT) or Hematopoietic Stem Cell Transplantation (HSCT) in Pediatric Patients Diagnosed With Ataxia-Telangiectasia: A Systematic Review

2025· review· en· W4409993594 on OpenAlexaboutno aff
Saad Alqarni, Lujaine M Al Murayeh, Bayan Y Mushari, Noura H Alotaibi

Bibliographic record

VenueCureus · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHematopoietic stem cell transplantationTransplantationAtaxia-telangiectasiaStem cellBone marrow transplantationHematopoietic stem cellHaematopoiesisSurgery

Abstract

fetched live from OpenAlex

Ataxia-telangiectasia (A-T) is a rare neurological disorder that leads to early death due to immunodeficiency, leukemia, and lymphoma. Given the underlying immune dysfunction and predisposition to hematologic cancers, bone marrow transplantation (BMT) or hematopoietic stem cell transplantation (HSCT) has emerged as a potential therapeutic strategy in pediatric patients with A-T. Therefore, longer follow-ups are needed to assess associated risks, side effects, procedures, and eligibility criteria. This systematic review aims to fill this gap by consolidating evidence from different parts of the world on the use of HSCT in pediatric patients diagnosed with A-T. The study used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to search five databases (PubMed, Web of Science, ScienceDirect, Google Scholar, and MEDLINE) for relevant published papers. The review covered studies on both classical and variant forms of A-T. The studies included are those with primary outcomes related to engraftment success, immunological reconstitution, survival rates, transplant-associated toxicity, infection prevalence, cancer management, and neurological progression. Only papers published in English between 2010 and 2024 were eligible for inclusion. Two experienced researchers independently assessed the retrieved papers for inclusion. A structured data collection sheet was used to retrieve relevant information from the selected articles. The risk of bias of the items included prospective and retrospective, cross-sectional, and cohort studies was assessed using the Newcastle Ottawa Quality Assessment Scale. Eight studies were included, comprising various designs including prospective, retrospective, and population-based cohorts. Among these, three studies reported actual use of HSCT or BMT in pediatric patients with A-T, showing immune reconstitution and reduced infections, but limited impact on neurological decline. Reduced-intensity conditioning (RIC) was associated with better survival and fewer complications compared to myeloablative regimens. The remaining studies discussed HSCT theoretically or focused on supportive care, immunological profiles, cancer risk, or nutritional challenges. Overall, outcomes varied, with limited evidence supporting routine use of HSCT in A-T due to associated risks and uncertain long-term benefits. In conclusion, HSCT shows potential in improving immune function and reducing infections in A-T patients. However, it has minimal effect on halting neurological progression. Given the risks and limited long-term data, HSCT is not currently recommended as a standard treatment for A-T.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.010
Bibliometrics0.0070.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.019
GPT teacher head0.257
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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