Hematology-oncology provider perspectives regarding lymphoma treatment and cardioprotective strategies in patients with lymphoma at high risk for heart failure
Bibliographic record
Abstract
The optimal treatment of patients with diffuse large B-cell lymphoma (DLBCL) or Hodgkin lymphoma (HL) with preexisting cardiomyopathy is uncertain. An anonymous, electronic survey was distributed by e-mail to three US lymphoma cooperative groups, two community hospitals, and twelve academic medical systems, and distributed at one international lymphoma meeting. Fifty hematology-oncology providers caring for patients with lymphoma were included. In response to a vignette of a 67-yo with Stage III DLBCL with LVEF of 40–45%, 15 (30%) would use non-anthracycline regimens, 13 (26%) R-CHOP with liposomal doxorubicin instead of doxorubicin, 11 (22%) R-CHOP without modification and 6 (12%) R-CHOP with a continuous doxorubicin infusion. In a second vignette of a patient with HL in remission after frontline treatment with doxorubicin cumulative dose 300 mg/m2, 16 (32%) would order an echocardiogram after treatment. There was substantial variability in preferred treatment regimens with preexisting cardiomyopathy and in cardiac monitoring after anthracycline.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".