High-Dose Therapy and Autologous Hematopoietic Stem-Cell Transplantation Does Not Increase the Risk of Second Neoplasms for Patients With Hodgkin's Lymphoma: A Comparison of Conventional Therapy Alone Versus Conventional Therapy Followed by Autologous Hematopoietic Stem-Cell Transplantation
Bibliographic record
Abstract
PURPOSE: To determine the incidence of second malignancies among patients with Hodgkin's lymphoma (HL) treated with autologous hematopoietic stem cell transplantation (AHSCT) compared with patients receiving conventional therapy alone and to identify potential risk factors for their occurrence. PATIENTS AND METHODS: We analyzed data on 1,732 consecutive patients with HL treated at the British Columbia Cancer Agency from 1976 to 2001, including 202 patients undergoing AHSCT. The median follow-up duration was 9.8 years for the whole cohort, 9.7 years for those patients treated with conventional therapy, and 7.8 years from AHSCT. RESULTS: The cumulative incidence of developing any second malignancy 15 years after therapy for HL was 9% (risk ratio = 3.5; P < .001); however, the incidence did not differ between those patients receiving conventional therapy alone compared with those undergoing AHSCT (10% and 8%, respectively; P = .48). In multivariate analysis, the only factor significantly associated with an increased risk of developing any second neoplasm or solid tumor was age > or = 35 years (P < .0001). An increased risk of therapy-induced acute myeloid leukemia and therapy-induced myelodysplastic syndrome was seen for patients aged > or = 35 years (P = .03) and stage III/IV (P = .04). CONCLUSION: Patients with HL are at increased risk of developing a second neoplasm. However, those patients undergoing AHSCT do not seem to be at greater risk compared with those patients receiving conventional therapy alone, at least during the first decade after therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".