A survey on diagnostic methods and treatment strategies used in patients with Waldenström's macroglobulinaemia in The Netherlands.
Bibliographic record
Abstract
BACKGROUND: Waldenström's macroglobulinaemia (WM) is defined as a lymphoplasmacytic lymphoma primarily located in the bone marrow, accompanied by an immunoglobulin M (IgM) monoclonal protein in the serum. The symptoms are highly variable, which can sometimes lead to a diagnostic delay. Currently, there is a wide range of therapeutic options used for the management of WM but no approved therapeutic agents are available specifically for this disease. METHODS: An online survey was prepared and sent out to haematologists and haemato-oncologists in The Netherlands, together with an invitational letter to participate. Information was gathered about the preferred methods of diagnosing and treating patients with WM in general, and about the last WM patient diagnosed in their department. RESULTS: 83 (31.8%) responses were obtained, out of which 68 (81.9%) contained responses to all three parts of the survey. The respondents most commonly used either rituximab-CVP or chlorambucil as first-line treatment, whereas rituximab in combination with purine analogues was the most frequently applied second-line treatment. The prevention of an IgM 'flare' was managed by the respondents in various ways, and rituximab maintenance treatment was not commonly used. CONCLUSION: This survey indicates that in general the diagnostic methods and treatment options for WM are well known to a representative number of Dutch haematologists. The areas of uncertainty are knowledge about asymptomatic vs symptomatic disease, risk of hyperviscosity in relation to IgM level, and the occurrence and prevention of an IgM 'flare'. These issues should be addressed in clinical research and guidelines to improve care for WM patients in The Netherlands.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".