The Risk Of BK Virus Haemorrhagic Cystitis After Allogeneic Hematopoietic Stem Cell Transplantation Is Increased With Myeloablative Conditioning, CMV Viremia and Acute Gvhd
Bibliographic record
Abstract
Introduction BK virus associated hemorrhagic cystitis (HC) is a common complication post allogeneic hematopoietic cell transplantation (HSCT). A number of retrospective studies have suggested a variety of risk factors for HC following HSCT including busulfan-containing myeloablative conditioning regimens, unrelated donors, and the occurrence of graft versus host disease (GVHD). However, these risk factors were not observed consistently and have led us to review the incidence and risk factors for BK-HC confirmed by microbiologic test at our institution. Methods and patients We retrospectively reviewed 339 patients who received HSCT between 2009 and 2012 at the Princess Margaret Cancer Centre, Toronto Canada. The diagnosis of BK-HC was based on clinical features, urinalysis and detection of BK virus by urine PCR. The cumulative incidence of BK-HC was calculated considering competing risks and Gray’s method was used for univariable analysis. To confirm the results of the univariable analysis, we conducted a multivariable analysis using the Fine-Gray method and EZR software. Results Out of 339 patients, 79 patients (23.3%) developed BK-HC. The median onset was 47 days (range 16-749) after HSCT. The median time to resolution of symptoms was 21 days (range 4-260). The clinical grades were as follows: grade 1 (n=14, 17.9%), 2 (n=34, 43.0%), 3 (n=22, 27.8%) and 4 (n=8, 10.1%). Sixty-two patients (83.7%) out of 74 had urine BK virus PCR testing which showed a high titer of BK virus PCR (mean 2.56x1010 (SD 7.41x1010) and median 6.19x109). The cumulative incidence of BK-HC at 2 years was 24.0% (95% CI, 19.4-28.9). There was no difference in transplant characteristics between the HC and non-HC groups, in terms of age, gender, gender match, diagnosis, HLA match and donor type, stem cell source, T-cell depletion, GVHD prophylaxis and CMV serostatus. However there was a higher incidence of BK-HC in the group of patients receiving myeloablative conditioning (62/208, 29.8%) vs (17/132, 12.9%, p<0.001) in the reduced intensity conditioning group. In the univariable model three risk factors for BK-HC were identified: myeloablative conditioning (31.2% in myeloablative vs 12.4% in reduced intensity; p<0.001), HLA mismatch (34.9% in mismatched vs 22.0% in matched, p=0.027), CMV viremia (28.6% in CMV+ vs 19.1% in CMV-; p=0.023) and acute GVHD (30.2% in aGVHD vs 12.0% in without aGVHD; p<0.001). Unrelated donor or T-cell depletion did not increase the risk of HC in univariable analysis. Multivariable analysis confirmed that these 3 factors were independent risk factors for BK-HC: myeloablative conditioning (p<0.001; HR 2.38, 95% CI, 1.35-4.17), CMV viremia (p=0.012; HR 1.77, 95% CI, 1.10-2.83) and aGVHD (p<0.001; HR 2.26, 95% CI, 1.23-4.13). HLA mismatch was not an independent risk factor. The 2-year overall survival (OS) of the study cohort was 51.6%. The development of BK-HC did not affect transplant outcomes with respect to OS (p=0.446). We observed a higher incidence of 1-year non-relapse mortality (NRM) in the BK-HC group 39.7% vs 24.2% in the non HC group, but this was not confirmed in the multivariable analysis. Conclusion Symptomatic BK-HC is a frequent complications following HSCT with a 2-year cumulative incidence of 24.0%. Three risk factors for BK-HC were identified including myeloablative conditioning, CMV viremia and aGVHD. While this infection did not adversely impact survival, it is associated with significant morbidity and constitutes an unmet need given the lack of effective therapy. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".