Combined modality therapy <i>versus</i> chemotherapy alone as an induction regimen for primary central nervous system lymphoma: a decision analysis
Bibliographic record
Abstract
In immunocompetent patients with primary central nervous system (CNS) lymphoma, combined modality therapy (CMT) using high-dose methotrexate and whole brain radiotherapy has improved response rates compared to chemotherapy alone. The trade-off is delayed and potentially devastating treatment-related neurotoxicity. A Markov decision-analytic model compared CMT to chemotherapy alone in patients with primary CNS lymphoma. Baseline probabilities were derived from a systematic literature review. Outcomes were life expectancy and quality-adjusted life expectancy. Sensitivity analyses were performed. The life expectancy was 2·69 years for CMT and 2·77 years for chemotherapy alone. The quality-adjusted life expectancies for the two strategies were 1·70 and 1·67 quality-adjusted life years (QALYs) respectively. In younger patients <60 years of age, CMT yielded a quality-adjusted life expectancy of 2·71 QALYs, compared to 2·09 QALYs for chemotherapy alone, yielding an expected benefit with CMT of 0·62 QALYs or 7·4 quality-adjusted months. There was no difference between the strategies in the older group. The model was robust to key variables for the younger group. The preferred induction strategy for younger patients appears to be CMT, maximizing life expectancy, and QALYs. This analysis confirms that the preferred strategy for older patients is chemotherapy alone.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".