Impact of cytomegalovirus (<scp>CMV</scp>) seroconversion pre‐allogeneic hematopoietic cell transplantation on posttransplant outcomes
Bibliographic record
Abstract
Cytomegalovirus (CMV) reactivation post-allogeneic hematopoietic cell transplantation (post-alloHCT) increases morbidity and mortality. We sought to determine the frequency of CMV seroconversion in patients pre-alloHCT and to investigate the impact on posttransplant outcomes. We retrospectively investigated 752 adult patients who underwent alloHCT at our center from January 2015 to February 2020 before the adoption of letermovir prophylaxis. CMV serology was assessed at consult and pretransplant. The cohort was divided into four groups based on pretransplant CMV seroconversion: negative to positive (Group 1), positive to negative (Group 2), consistently negative (Group 3), and consistently positive (Group 4). Eighty-nine patients (12%) had seroconverted from negative to positive, 17 (2%) from positive to negative, 151 (20%) were consistently seronegative, and 495 (66%) were consistently seropositive pretransplant. For the four CMV serostatus groups, cumulative incidence of CMV reactivation at 6 months posttransplant was 4.5%, 47.1%, 6.6%, and 76.6% for Groups 1, 2, 3, and 4, respectively (p < .0001). No differences between groups were seen regarding Grade III-IV acute graft-versus-host disease (GVHD) (p = .91), moderate/severe chronic GVHD (p = .41), or graft failure (p = .28). On multivariable analysis, there was no impact of CMV serostatus group on overall survival (p = .67), cumulative incidence of relapse (p = .83) or non-relapse mortality. alloHCT patients who demonstrate CMV seroconversion pretransplant from negative to positive have a very low risk of CMV reactivation posttransplant. The observed seroconversion may be due to passive CMV immunity acquired through blood products. Quantitative CMV immunoglobulin G/immunoglobulin M pretransplant may help differentiate between true seroconversion and passively transmitted CMV immunoglobulin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".