Examination of current Algoma District cancer program practices and local referral processes for patients with prostate cancer.
Bibliographic record
Abstract
352 Background: The Algoma District Cancer Program (ADCP) is located in Sault Ste. Marie, ON, Canada and services the needs of the 125,000 individuals residing in the Algoma District, which has an area of approximately 49,000 square kilometres. Due to its geographic isolation in Northern Ontario, maintaining standards of care can be challenging to deliver. The objective of this project is to document any improvements in the referral process and treatment of patients with prostate cancer at the ADCP since the arrival of new medical oncologists in July 2013. Methods: Patients who had been seen by a medical oncologist at ADCP from July 2013 to July 2015 were included in this study. Patient charts were analyzed in order to gather information including date of diagnosis, stage at time of referral, date of consult with medical oncologist, previous treatments trialed, and dates of treatment. Patients were divided into two groups, diagnosed prior to 2014 and after 2014, to examine progress at ADCP. Results: From July 2013 to July 2015, there were 73 patients seen by a medical oncologist at ADCP with a diagnosis of prostate cancer. Of these patients, 54 were diagnosed prior to 2014 and 19 were diagnosed after 2014. For all patients diagnosed prior to 2014, the average number of years from diagnosis to a medical oncology consult was 5.24 years, with the longest being 19 years for two patients. In comparison, for all patients diagnosed after 2014, a medical oncologist saw them only 0.26 years on average after they were diagnosed. Since 2014, lines of therapy administered after referral to medical oncology have become greater than before 2014. Specifically for stage IV prostate cancer patients, the average number of lines of therapy ordered by a medical oncologist has increased for patients diagnosed after 2014. Conclusions: Since the arrival of new medical oncologists at ADCP in July 2013, the average number of years after diagnosis that a patient is referred to the clinic has decreased, while the average lines of therapies utilized after their consult with a medical oncologist has increased, showing an improvement in both referral processes and adherence to standard guidelines in the treatment of prostate cancer patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".