ArticleTransplantation2026
Further Personalizing Medicine in Immune Disorders: Genomic Findings and Hematopoietic Cell Transplantation Survival.
Article in Transplantation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Genome Sequencing Enhances Precision and Clinical Utility of Pharmacogenetic Data Compared to Arrays.Journal of clinical pharmacology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
46 authors.
Funding
Abstract
backgroundHematopoietic cell transplantation (HCT) provides effective long-term management for some inborn errors of immunity. Genetic findings can inform donor selection, considerations in conditioning intensity and agents, and graft-versus-host disease prophylaxis. Exome/genome sequencing is increasingly accessible but of uncertain clinical utility. We aimed to evaluate the clinical utility of comprehensive genomic evaluations through review of HCT at our center.
methodsWe performed exome/genome sequencing on pre-HCT samples from participants between 2017 and 2023. We reported primary findings (PF) and secondary findings (SF). Post hoc, we analyzed medication and pharmacogenetic (PGx) data.
resultsWe analyzed pre-HCT exome/genome sequencing (n = 84 exome, n = 63 genome, n = 32 with both) for 179 probands. Most (143/179; 79.9%) had a PF underlying the HCT indication, with GATA2 being most common (n = 59). Three percent of participants had an SF predisposing to cancer or cardiovascular disease. Most (n = 108/179; 60.3%) received ≥1 medication(s) that may have been further optimized with PGx. Using Kaplan-Meier survival analysis, we compared the survival rates of participants with 0, 1, and ≥2 genomic risk factors (GRF: absence of PF; presence of SF or PGx). Survival at 3 y was 94.8%, 84.8%, and 58.5% for those with 0, 1, and ≥2 GRF, respectively (log-rank: 16.10, df = 2, P = 0.0003), indicating statistically significant survival differences by GRF.
conclusionsComprehensive genomic evaluation is an emerging avenue for tailoring HCT approaches, and identification of HCT-relevant findings may be common. On multivariate analysis, GRF was associated with survival in this retrospective cohort. Prospective research is warranted to further integrate genomic data into precision treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.