Delay in Diagnosis of Patients with Head-and-Neck Cancer in Canada: Impact of Patient and Provider Delay
Bibliographic record
Abstract
Background: Head-and-neck cancers (hncs) often present at an advanced stage, leading to poor outcomes. Late presentation might be attributable to patient delays (reluctance to seek treatment, for instance) or provider delays (misdiagnosis, prolonged wait time for consultation, for example). The objective of the present study was to examine the length and cause of such delays in a Canadian universal health care setting. Methods: Patients presenting for the first time to the hnc multidisciplinary team (mdt) with a biopsy-proven hnc were recruited to this study. Patients completed a survey querying initial symptom presentation, their previous medical appointments, and length of time between appointments. Clinical and demographic data were collected for all patients. Results: The average time for patients to have their first appointment at the mdt clinic was 15.1 months, consisting of 3.9 months for patients to see a health care provider (hcp) for the first time since symptom onset and 10.7 months from first hcp appointment to the mdt clinic. Patients saw an average of 3 hcps before the mdt clinic visit (range: 1-7). No significant differences in time to presentation were found based on stage at presentation or anatomic site. Conclusions: At our tertiary care cancer centre, a patient's clinical pathway to being seen at the mdt clinic shows significant delays, particularly in the time from the first hcp visit to mdt referral. Possible methods to mitigate delay include education about hnc for patients and providers alike, and a more streamlined referral system.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".