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Record W4417015040 · doi:10.1182/blood-2025-6473

Evaluating efficacy and safety of hydroxyurea and thalidomide for beta-thalassemia: A systematic review andmeta-analysis.

2025· article· en· W4417015040 on OpenAlexaboutno aff
Mehak Gul, Syed Maaz, I. Saif, FNU Kalpina, Hafsa Shahid, Muhammad Yasir, Hafiz Muhammad Asif Javed

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsThalidomideRegimenAdverse effectObservational studyConfidence intervalAnemia

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION Therapeutic interventions such as hydroxyurea and thalidomide have individually demonstrated a reduction in transfusion requirements in beta-thalassemia; however, the combined effects of these agents remain inadequately studied. This meta-analysis aims to determine the efficacy and safety of the combined use of hydroxyurea and thalidomide in transfusion-dependent beta-thalassemia patients. METHODS Using PRISMA guidelines a comprehensive search was conducted across PubMed, Scopus, Cochrane Library, and ClinicalTrials.gov from inception till May 30, 2025. Four studies evaluating the safety and efficacy of thalidomide plus hydroxyurea in beta-thalassemia patients were included. Data was analyzed using OpenMetaAnalyst software. Pooled estimates were reported as mean ± standard deviation (SD) and 95 % confidence intervals (CI), using a random-effects model. Heterogeneity was assessed using I2 statistics. Subgroup analyses were conducted based on follow-up duration (≤ 6 months vs. > 6 months). Quality assessment was performed using the Newcastle-Ottawa Scale. Some characteristics were described systematically. RESULTS A total of 372 patients (60% male; age range: 2-50 years) from 4 observational studies were included in this analysis. The median baseline hemoglobin was 7.3 g/dL (range, 6.4-9), ferritin was 2436 ng/ml (range, 1482-2974), and the median serum bilirubin was 1.865 mg/dl (range, 1.8-1.9). The treatment regimen consisted of hydroxyurea, thalidomide and aspirin. The pooled rates for overall response (OR) and complete response (CR) were 72% (95% CI 0.679-0.776, I2= 16.39%, p = 0.310) and 61.6% (95% CI 0.521-0.707, I2 = 71.57%, p = 0.014), respectively. The pooled rates for increase in hemoglobin and reduction in serum ferritin were -87% (95% CI -1.526 to -0.219, I2 = 94.12%, p < 0.0.001) and 58% (95% CI 0.229-0.931, I2 = 80.65%, p = 0.001). Subgroup analysis reported an ORR of 72.1% (95% CI: 58.4 to 85.9%, I2 = 66.36 %, p = 0.085) for ≤ 6 months and 71.0% (95% CI: 65.9 to77.0%, I2 = 0%, p = 0.074) for > 6months, respectively. CR was 57.3% (95%CI: 38.2 - 76.3%, I2 = 79.85%, p= 0.026) and 64.6% (95% CI: 49.7 - 79.6%, I2 = 82.26%, p= 0.018) in the respective subgroups. Ferritin levels showed non-significant change at < 6 months (0.560 ng/dl; 95% CI: -0.197 to 1.316 ng/dl, I2 = 88.4%, p= 0.003), but a significant reduction at > 6 months (0.639 ng/dl; 95% CI: 0.294 to 0.984, I2 = 61.29%, p= 0.108). Hemoglobin increased by 1.385 g/dl (95% CI: 0.947 to 1.823, I2 = 63.24%, p= 0.099) and 0.37 g/dl (95% CI: 0.170 to 0.570, I2 = 0%, p= 0.346), respectively. Billirubin levels demonstrated no significant change (-0.03 mg/dl 95% CI: -0.200 to 0.140, I2 = 90.62%, p= 0.001). Adverse effects were reported in 29.9% (95% CI: 5.7 to 54%, I2 = 0%, p= 0.001) of patients. CONCLUSION The combination therapy of hydroxyurea and thalidomide has shown safety and efficacy in the treatment of beta-thalassemia. The results have shown improved haemoglobin levels and reduced ferritin levels, while bilirubin levels showed no significant change. However, given lack of high quality data, further randomised controlled trials are required to validate these results and assess long-term outcomes.

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)0.014
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.024
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.339
Teacher spread0.314 · 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 designMeta-analysis
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".

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Citations0
Published2025
Admission routes1
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