Management of Hodgkin Lymphoma in Relapse after Autologous Stem Cell Transplant
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recurrence of Hodgkin lymphoma (HL) occurs in about 50% of patients after autologous stem cell transplantation (ASCT), usually within the first year, and represents a significant therapeutic challenge. The natural history of recurrent HL in this setting may range from a rapidly progressive to a more indolent course. Patients in this setting are often young, without comorbidities and able to tolerate additional therapies: expectations are often still high. The approach to treatment depends on clinical variables (time to relapse, perceived sensitivity to additional cytotoxic therapy, disease stage), prior history of radiation therapy, the availability of an HLA-identical donor, and the availability of new agents via clinical trials. Although very few of these patients can be cured, results from reported series, albeit often small and sometimes with relatively short follow-up, document that excellent disease control can be achieved with radiation, single or multiagent chemotherapy, and reduced-intensity allogeneic transplantation. The results of these approaches will be reviewed, and a treatment algorithm incorporating the use of standard or investigational agents or approaches will be discussed.
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.
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) | 0.001 | 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 it