Early cytomegalovirus reactivation remains associated with increased transplant-related mortality in the current era: a CIBMTR analysis
Bibliographic record
Abstract
Single-center studies have reported an association between early (before day 100) cytomegalovirus (CMV) reactivation and decreased incidence of relapse for acute myeloid leukemia (AML) following allogeneic hematopoietic cell transplantation. To substantiate these preliminary findings, the Center for International Blood and Marrow Transplant Research (CIBMTR) Database was interrogated to analyze the impact of CMV reactivation on hematologic disease relapse in the current era. Data from 9469 patients transplanted with bone marrow or peripheral blood between 2003 and 2010 were analyzed according to 4 disease categories: AML (n = 5310); acute lymphoblastic leukemia (ALL, n = 1883); chronic myeloid leukemia (CML, n = 1079); and myelodysplastic syndrome (MDS, n = 1197). Median time to initial CMV reactivation was 41 days (range, 1-362 days). CMV reactivation had no preventive effect on hematologic disease relapse irrespective of diagnosis. Moreover, CMV reactivation was associated with higher nonrelapse mortality [relative risk [RR] among disease categories ranged from 1.61 to 1.95 and P values from .0002 to <.0001; 95% confidence interval [CI], 1.14-2.61). As a result, CMV reactivation was associated with lower overall survival for AML (RR = 1.27; 95% CI, 1.17-1.38; P <.0001), ALL (RR = 1.46; 95% CI, 1.25-1.71; P <.0001), CML (RR = 1.49; 95% CI, 1.19-1.88; P = .0005), and MDS (RR = 1.31; 95% CI, 1.09-1.57; P = .003). In conclusion, CMV reactivation continues to remain a risk factor for poor posttransplant outcomes and does not seem to confer protection against hematologic disease relapse.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".