Debate on the conservative and aggressive treatment options for the optimal management of indolent non-Hodgkinʼs lymphoma
Bibliographic record
Abstract
Indolent non-Hodgkin's lymphoma (NHL) is currently considered to be an incurable disease, with a median survival of 6-8 years. In the absence of a cure, the variety of therapeutic options available for patients with indolent NHL range from 'watchful waiting' to high-dose therapy (HDT) with autologous stem-cell transplantation (ASCT). There is no current consensus on standard treatment. Conventional chemotherapy is clearly not curative, and many clinicians prefer to delay chemotherapy until the patient develops overt symptoms that require treatment. On the one hand, long-term studies indicate that 'watchful waiting' has no effect on overall survival. On the other hand, aggressive treatment strategies, such as HDT with ASCT, may increase disease-free survival in some patients, particularly when used early in the treatment algorithm, but are also associated with potential toxicity. Thus the selection of therapy for each patient involves balancing the benefit of the treatment with any side effects and detriment to quality of life. The development of innovative therapies for indolent NHL, such as monoclonal antibodies with or without chemotherapy, requires a reassessment of the treatment choices. Good clinical responses and time to progression have so far been achieved in clinical trials of rituximab and other agents including radiolabelled antibodies, but in view of the long median survival of patients with indolent NHL, it will be some years before it can be conclusively demonstrated whether such treatments have an effect on the natural history of the disease or produce a cure. This issue raises an important question: outside the setting of a clinical trial, should patients be treated aggressively with therapies that do not yet have proven curative ability? This article considers the evidence and relative merits for the conservative approach to indolent NHL, where patients are treated according to symptoms in order to maintain a normal quality of life wherever possible, and for the aggressive approach, where the lymphoma is targeted soon after the diagnosis.
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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 | 0.024 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.024 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".