Distinct Age-Related Clinical Features and Risk Assessment in Chinese With Chronic Lymphocytic Leukemia
Bibliographic record
Abstract
The biological and clinical features of chronic lymphocytic leukemia (CLL) exhibited profound heterogeneity across Chinese and patients of predominately European descent. However, the age-related peculiarities and risk assessment of Chinese CLL patients remained ill-defined. The present study demonstrated that CLL patients were characterized by the earlier age at onset in China (median age at diagnosis: 63 years old) than in the United States (median age at diagnosis: 69 years old). Young patients from Shandong Provincial Hospital CLL database displayed prolonged overall survival than the Surveillance, Epidemiology, and End Results cohort. Furthermore, among Chinese CLL patients, young patients showed an increased relapse rate compared with elderly patients. To optimize the risk assessment of CLL patients, novel risk score models named PR-Score and HBG-Score were developed for predicting the outcomes of young and elderly CLL patients respectively. The neonatal survival prediction systems were superior to international prognostic index for CLL (CLL-IPI) and Binet stage in assessing the overall survival and progression free survival of CLL patients. The analyses highlighted refinement of risk evaluation for CLL patients in different age groups, providing insights into individualized diagnosis and treatment of CLL.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".