Referral pathways and diagnosis: UK government actions fail to recognize complexity of lymphoma
Bibliographic record
Abstract
To gain survival advantages potentially associated with prompt diagnosis, the UK government introduced identical waiting-time targets for all cancers, and guidelines to ensure that general practitioners make appropriate hospital referrals. For lymphoma, the evidence guiding these actions is limited. This study examined referral pathways in patients with lymphoma and variations in time to diagnosis by discipline of first referral. A case series study was conducted including all patients aged over 25 years, newly diagnosed with lymphoma in the UK county of West Yorkshire, during 2000. Data were extracted from primary care and hospital records of 189 patients. Referral pathways were described, and the number of days between first referral and diagnosis calculated. A distinct referral pathway did not exist; patients were initially referred to many disciplines. Surgical referrals predominated, and only 12% of patients were sent directly to haematology. Time to diagnosis varied by discipline and was shorter for patients sent to haematology than for most other common disciplines. UK government actions to ensure the prompt diagnosis of patients with lymphoma are not evidence-based. The complexity of the referral pathway in patients with lymphoma, which affects time to diagnosis, has been underestimated. Further government actions should be evidence-based, ensuring prompt diagnosis of lymphoma from whatever discipline patients originate.
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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 | 0.000 |
| 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".