Autologous haematopoietic cell transplantation for non‐<scp>H</scp>odgkin lymphoma with secondary <scp>CNS</scp> involvement
Bibliographic record
Abstract
Pre-existing central nervous system (CNS) involvement may influence referral for autologous haematopoietic cell transplantation (AHCT) for patients with non-Hodgkin lymphoma (NHL). The outcomes of 151 adult patients with NHL with prior secondary CNS involvement (CNS(+) ) receiving an AHCT were compared to 4688 patients without prior CNS lymphoma (CNS(-) ). There were significant baseline differences between the cohorts. CNS(+) patients were more likely to be younger, have lower performance scores, higher age-adjusted international prognostic index scores, more advanced disease stage at diagnosis, more aggressive histology, more sites of extranodal disease, and a shorter interval between diagnosis and AHCT. However, no statistically significant differences were identified between the two groups by analysis of progression-free survival (PFS) and overall survival (OS) at 5 years. A matched pair comparison of the CNS(+) group with a subset of CNS(-) patients matched on propensity score also showed no differences in outcomes. Patients with active CNS lymphoma at the time of AHCT (n = 55) had a higher relapse rate and diminished PFS and OS compared with patients whose CNS lymphoma was in remission (n = 96) at the time of AHCT. CNS(+) patients can achieve excellent long-term outcomes with AHCT. Active CNS lymphoma at transplant confers a worse prognosis.
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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) | 0.001 | 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 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".