Prognostic factors identified three risk groups in the LRF CLL4 trial, independent of treatment allocation
Bibliographic record
Abstract
BACKGROUND: Many prognostic markers have been identified in chronic lymphocytic leukemia, but there have been few opportunities to assess their relative importance in a large randomized trial. The aim of this study was to determine which of the available markers independently predicted outcome in patients requiring treatment and to use these to define new risk groups. DESIGN AND METHODS: A broad panel of clinical and laboratory markers, measured at randomization in patients entering the LRF CLL4 trial, was assessed with respect to treatment response, progression-free and overall survival, at a median follow-up of 68 months. RESULTS: Using the factors identified as independent predictors for progression-free survival, patients were subdivided into three risk groups: 6% had poor risk with known TP53 loss of greater than 10%; 72% had an intermediate risk without TP53 loss (≤ 10%) and with at least one of: unmutated IGHV genes and/or IGHV3-21 usage, 11q deletion, β-2 microglobulin greater than 4 mg/L; 22% had a good risk (with none of the above and mutated IGHV genes). The 5-year progression-free survival rates for these three groups were 0%, 12% and 34%, respectively, and the corresponding 5-year overall survival rates were 9%, 53% and 79% (both P<0.00005 independent of treatment allocation). In the intermediate risk group 250 patients, with data for all three risk factors, were further subdivided into intermediate-low (one risk factor) or intermediate-high (2 or 3 risk factors). The 5-year progression-free survival rates were 18% and 7% (P=0.0001) and the 5-year overall survival rates were 68% and 40% (P<0.00005), respectively. CONCLUSIONS: This study demonstrates the role of biomarkers in prognosis and shows that, in patients requiring treatment, disease stage may no longer be an independent predictor of outcome. If validated independently, the risk groups defined here may inform the design of future trials in chronic lymphocytic leukemia.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".