Risk of Acute Leukemia Post-Autologous Stem Cell Tranplant (ASCT) for Hodgkin’s Lymphoma (HL) Depends on Choice of Salvage Chemotherapy and Use of Radiation.
Bibliographic record
Abstract
Abstract Background: Late treatment-related mortality (TRM) and second cancers (SC) have an important impact on the long-term outcome of patients (pts) with HL. The optimum salvage regimen (based on efficacy and acute and late toxicity) as part of second-line therapy with ASCT is not known. Pts undergoing ASCT are at high risk of both solid tumors and leukemia (Proc ASCO 2007 abstr #8016). We analyzed our single-institution data to determine the contribution of the components of salvage therapy to leukemia risk post-transplant. Methods: From Dec 1986 to Nov 2005, 321 pts with relapsed/refractory HL after doxorubicin-based primary chemotherapy (+ involved/extended field radiation [RT]: 46%) received salvage chemotherapy to best response, followed by etoposide 60 mg/kg day-4 and melphalan 160–180 mg/m2 [day-3] supported by autologous bone marrow (46%), mobilized PBSCs (49%) or both (5%) [day 0]. 27% received involved field RT post-ASCT. Risk of treatment failure and second cancers was estimated using competing risks methods. Leukemia risk with time was determined by cumulative incidence function. Results: Patient characteristics: male: 61%; median age 33 yrs (range16–67). No. of salvage regimens pre-ASCT: 1: 76%; 2: 19%; ≥3: 5%. Salvage chemotherapy: BCNU, etoposide, cytarabine, melphalan (miniBEAM, [MB]) 162 (50%); cisplatinum-based regimens (dexamethasone, cytarabine, cisplatin [DHAP] or gemcitabine, dexamethasone, cisplatin [GDP]) 128 (40%); other 10%. Disease status post-salvage chemotherapy: CR 28%, PR 66%. With a median follow-up of 4.7 yrs post-ASCT (range 1–17), estimates of OS, PFS and disease relapse are 53%, 53% and 46% at 5 years, and 39%, 51% and 48% at 10 yrs. The cumulative incidence of treatment-related death (from toxicity or SC) continues to increase from 9% (6–13) at 3 years to 15% (11–20) 10 yrs post-ASCT. The probability of SC is 5% (2.8–7.8) at 3 years and 12% (7.9–16.7) at 10 years (leukemia risk: 7%, solid tumour risk: 5%). There have been a total of 154 deaths, 104 from progressive HL alone and 37 from treatment-related events - 14 (9%) of these were from SC with no evidence of relapsed HL. There were an additional 11 deaths from a combination of causes (relapsed HL and other), 9 (6%) of these were related to SC. 30 SC were identified, 12 solid tumors and 18 AML/MDS. The risk of secondary acute leukemia differs according to salvage chemotherapy received - 0.9% (0.1–6.2) and 3.4% (0.7–15.1) at 3 and 10 yrs respectively in DHAP/GDP pts, compared to 4.6% (2.2–9.4) and 9.1% (5.4–15.3) in pts treated with MB [p=0.051]. Pts who received radiation (pre- or post-ASCT) have a leukemia risk of 4% (1.8–8) at 3yrs increasing to 8.5% (4.9–14.4) at 10yrs, while pts who never received radiation had a stable leukemia risk of 1.8% (0.3–12%) [p=0.19]. Conclusions: In this single institution experience with HL pts undergoing ASCT with a consistent salvage therapy strategy, long-term survivors have an on-going increasing risk of SC and leukemia which contributes to late mortality. Specific components of therapy appear to influence this risk. Our observation of an unexpected increased risk of AML in HL patients receiving miniBEAM salvage prior to transplant suggests that the contribution of other salvage regimens to late adverse effects warrants further investigation.
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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 | 0.001 | 0.003 |
| 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) | 0.003 | 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".