Long‐term outcomes among 2‐year survivors of autologous hematopoietic cell transplantation for Hodgkin and diffuse large b‐cell lymphoma
Bibliographic record
Abstract
BACKGROUND: Autologous hematopoietic cell transplantation (auto-HCT) is a standard therapy for relapsed classic Hodgkin lymphoma (cHL) and diffuse large B-cell lymphoma (DLBCL); however, long-term outcomes are not well described. METHODS: This study analyzed survival, nonrelapse mortality, late effects, and subsequent malignant neoplasms (SMNs) in 1617 patients who survived progression-free for ≥2 years after auto-HCT for cHL or DLBCL between 1990 and 2008. The median age at auto-HCT was 40 years; the median follow-up was 10.6 years. RESULTS: The 5-year overall survival rate was 90% (95% confidence interval [CI], 87%-92%) for patients with cHL and 89% (95% CI, 87%-91%) for patients with DLBCL. The risk of late mortality in comparison with the general population was 9.6-fold higher for patients with cHL (standardized mortality ratio [SMR], 9.6) and 3.4-fold higher for patients with DLBCL (SMR, 3.4). Relapse accounted for 44% of late deaths. At least 1 late effect was reported for 9% of the patients. A total of 105 SMNs were confirmed: 44 in the cHL group and 61 in the DLBCL group. According to a multivariate analysis, older age, male sex, a Karnofsky score < 90, total body irradiation (TBI) exposure, and a higher number of lines of chemotherapy before auto-HCT were risk factors for overall mortality in cHL. Risk factors in DLBCL were older age and TBI exposure. A subanalysis of 798 adolescent and young adult patients mirrored the outcomes of the overall study population. CONCLUSIONS: Despite generally favorable outcomes, 2-year survivors of auto-HCT for cHL or DLBCL have an excess late-mortality risk in comparison with the general population and experience an assortment of late complications. Cancer 2018;124:816-25. © 2017 American Cancer Society.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".