Expert consensus opinion on the management of hairy cell leukemia in elderly patients
Bibliographic record
Abstract
The management of hairy cell leukemia (HCL) in elderly patients is becoming increasingly important as more patients are diagnosed at advanced ages (≥75 years) due to longer life expectancy. This expert consensus, based on a survey of international specialists from the Hairy Cell Leukemia Consortium, explores management strategies for this age group. Cladribine monotherapy remains the preferred first-line treatment, but its application varies, with dosage adjustments common to improve tolerability. Experts stress a holistic approach that considers advanced age, comorbidities, and individual patient circumstances. Although functional status and comorbidities are routinely assessed, structured frailty tools are rarely used. For relapsed cases, targeted therapies, including BRAF inhibitors with anti-CD20 antibodies, are favored. Challenges include managing comorbidities, infection risks, and a lack of geriatric-specific evidence. While current treatments are effective, the findings highlight the critical need for data exclusively derived from elderly HCL patients to develop tailored guidelines and improve outcomes in this vulnerable population.
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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 | 0.013 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".