A Survey Detailing Early Onset Colorectal Cancer Patient and Caregiver Experiences in Canada
Bibliographic record
Abstract
The incidence of early onset colorectal cancer (EOCRC) in Canada has increased. To address the growing incidence of EOCRC, Colorectal Cancer Canada (CCC) developed the Never Too Young (N2Y) program to identify gaps in care and evaluate patient and caregiver experiences with CRC. The survey was available online using SurveyMonkey across Canada between 12 December 2022 and 1 May 2023. The patient and caregiver survey consisted of 113 and 94 questions, respectively. A total of 108 EOCRC patients and 20 caregivers completed the survey. Many respondents were unaware of EOCRC (41.6%) and the disease symptoms (45.2%) before diagnosis. Patient age at diagnosis was between 45 and 50 years in 31.7%, and 72.8% of them were diagnosed at stage III or IV. A perception of an initial misdiagnosis was common (67.4%) for EOCRC patients, and 51.2% felt dismissed due to their age. Patients and caregivers reported impacts of EOCRC on their mental health, with 70.9% of patients expressing a need for support with depression and 93.3% of caregivers experiencing a constant fear of recurrence of their loved one's cancer. Improving the Canadian population's awareness of EOCRC (e.g., CRC symptoms) is important for ensuring timely diagnoses. Similarly, it is critical to ensure that healthcare providers are aware of the increase in EOCRC cases and the unique needs of these patients. Re-evaluation of the CRC screening age should be undertaken in Canada to determine whether lowering the start age to 45 years will improve outcomes in this demographic.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".