Wait Times Experienced by Lung Cancer Patients in the BC Southern Interior to Obtain Oncologic Care: Exploration of the Intervals from First Abnormal Imaging to Oncologic Treatment
Bibliographic record
Abstract
BACKGROUND: Lung cancer is associated with rapid disease progression, which can significantly progress over a duration of four to eight weeks. This study examines the time interval lung cancer patients from the interior of British Columbia (BC) experience while undergoing diagnostic evaluation, biopsy, staging, and preparation for treatment. METHODS: A chart review of lung cancer patients (n=231) referred to the BC Cancer Agency Centre for the Southern Interior between January 1, 2010 and December 31, 2011 was performed. Time zero was defined as the date of the first abnormal chest imaging. Time intervals, expressed as median averages, to specialist consult, biopsy, oncologic referral, initial oncology consultation, and commencement of oncologic treatment were obtained. RESULTS: The median time interval from first abnormal chest imaging to a specialist consultation was 18 days (interquartile range, IQR, 7-36). An additional nine days elapsed prior to biopsy in the form of bronchoscopy, CT-guided biopsy, or sputum cytology (median; IQR, 3-21); if lobectomy was required, 18 days elapsed (median; IQR, 9-28). Eight days were required for pathologic diagnosis and subsequent referral to the cancer centre (median; IQR, 3-16.5). Once referral was received, 10 days elapsed prior to consultation with either a medical or radiation oncologist (median, IQR 5-18). Finally, eight days was required for initiation of radiation and/or chemotherapy (median; IQR, 1-15). The median wait time from detection of lung cancer on imaging to oncologic treatment in the form of radiation and/or chemotherapy was 65.5 days (IQR, 41.5-104.3). INTERPRETATION: Patients in the BC Southern Interior experience considerable delays in accessing lung cancer care. During this time, the disease has the potential to significantly progress and it is possible that a subset of patients may lose their opportunity for curative intent treatment.
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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 | 0.000 | 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".