Age ≥60 Is an Added Risk Factor for Mortality in High-Risk HCT-CI Patients Undergoing Allogeneic Stem Cell Transplant
Bibliographic record
Abstract
Introduction: Allogeneic hematopoietic stem cell transplant (HCT) is the only curative option for many hematologic malignancies, yet non-relapse mortality (NRM) remains a challenge. Since its development in 2003, the HCT Comorbidity Index (HCT-CI) has been widely adopted to estimate NRM and overall survival (OS), helping assess HCT eligibility. A 2024 retrospective study of HCT recipients over 65 at our centre showed increasing age did not impact prognosis in this older population, but that an HCT-CI of ≥3 predicted for worse outcomes. This study aims to determine transplant-related outcomes in all adult HCT patients with high-risk HCT-CI, and to evaluate the impact of age and HCT characteristics on OS and relapse-free survival (RFS). Methods: Retrospective study of patients with HCT-CI score ≥3 who underwent HCT from January 2014 to January 2024 at the Royal Victoria Hospital. OS and RFS were estimated using Kaplan-Meier analysis and compared with logrank tests. NRM, relapse rate (RR), and acute graft-versus-host disease (aGVHD) were compared by chi-squared tests. Results: We identified 74 patients aged 20 to 72, of whom 49% were 20-59 years old and 51% were ≥60. Median HCT-CI was 3 (range 3-7), with 77% having a score of 3-4 and 23% of ≥5. Donor types were 44% matched unrelated, 26% matched related, 15% mismatched unrelated, 12% haploidentical, and 3% mismatched related. Conditioning was reduced-intensity (RIC) in 61% and myeloablative (MAC) in 39%. T-cell depletion (TCD) was used in 64% of cases, and included alemtuzumab (58%), antithymocyte globulin (19%), and post-transplant cyclophosphamide (23%). Most common HCT indications were acute myeloid leukemia (45%), myelodysplastic syndrome (16%), myeloproliferative neoplasm (14%), and acute lymphoblastic leukemia (12%). Median OS was 7.5 months and RFS 7 months, with 44% OS at 1 year and 33% at 2 years. NRM was 45.2% at 1 year and 53.6% at 2 years. Leading causes of NRM were sepsis (38%) and pneumonia (26%). There was no significant difference in OS, RFS or NRM when comparing donor type, transplant year, conditioning intensity, or HCT-CI of 3-4 vs ≥5. OS was significantly different between patients aged 20-59 and ≥60 years (47.1% vs 14.3%, p=0.027). This was driven by significantly increased 2-year NRM (p=0.011), with no difference in RR. The compared age groups had no difference in HCT-CI score, performance status, transplant year, or TCD. Grade II-IV aGVHD was 16.2% at 100 days and 26% at 1 year, without difference by age or HCT-CI group. MAC group had significantly higher 100-day aGVHD than RIC (31% vs 6.7%, p=0.009). Patients receiving TCD had higher 100-day NRM compared to the non-TCD group (p=0.011), without significant difference in 2-year OS or RR. Within the TCD group, 2-year OS was 45% in patients aged 20-59 (n=20) and 13% in those ≥60 (n=23). This was not statistically significant (0.249), perhaps due to lack of power. NRM cause in the TCD group was primarily sepsis (54%) and pneumonia (25%), whereas in the non-TCD group it was sepsis (38%) and GVHD (31%). Only GVHD was statistically significant as a cause of NRM between groups (p=0.023). Conclusion: At our institution, high-risk HCT-CI patients older than 60 had significantly worse 2-year OS than those 20-59, driven by significantly higher NRM. This may be due to older patients with comorbidities having less reserve to overcome the physiologic challenge of HCT and suggests that patient age and HCT-CI both need to be considered in assessing HCT eligibility. Patients ≥60 fared poorly with any high-risk HCT-CI score ≥ 3. In our high-risk cohort, TCD was associated with less GVHD-related mortality but higher 100-day NRM, though this finding is confounded by the fact unrelated donor transplants were more likely to receive TCD. As TCD becomes more common, strategies to mitigate the risk of infection-driven mortality are needed in this population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".