Top 10 research priorities for early-stage colorectal cancer: a Canadian patient-oriented priority-setting partnership
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer, one of the most commonly diagnosed cancers, is now being detected earlier and treatments are improving, which means that patients are living longer. Partnering with Canadian clinicians, patients and researchers, we aimed to determine research priorities for those living with early-stage colorectal cancer in Canada. METHODS: We followed the well-established priority-setting partnership outlined by the James Lind Alliance to identify and prioritize unanswered questions about early-stage (i.e., stages I-III) colorectal cancer. The study was conducted from September 2018 to September 2020. We surveyed patients, caregivers and clinicians from across Canada between June 2019 and December 2019. We categorized the responses using thematic analysis to generate a list of unique questions. We conducted an interim prioritization survey from April 2020 to July 2020, with patients, caregivers and clinicians, to determine a shorter list of questions, which was then reviewed at a final meeting (involving patients, caregivers and clinicians) in September 2020. At that meeting, we used a consensus-based process to determine the top 10 priorities. RESULTS: For the initial survey, 370 responses were submitted by 185 individuals; of the 98 individuals who provided demographic information, 44 (45%) were patients, 16 (16%) were caregivers, 7 (7%) were members of an advocacy group, 26 (27%) were health care professionals and 5 (5%) were categorized as "other." The responses were refined to create a list of 66 unique unanswered questions. Twenty-five respondents answered the interim prioritization survey: 13 patients (52%), 2 caregivers (8%), 3 advocacy group members (12%) and 7 health care professionals (28%). This led to a list of the top 30 questions. The final consensus meeting involved 20 individuals (10 patients [50%], 3 caregivers [15%] and 7 health care professionals [35%]), who agreed to the top 10 research priorities. The priorities covered a range of topics, including screening, treatment, recurrence, management of adverse effects and decision-making. INTERPRETATION: We determined the top research priorities for early-stage colorectal cancer using a collaborative partnership of stake-holders from across Canada. The priorities covered a broad range of topics that could be addressed by future research, including improved screening practices, the role of personalized medicine, the management of adverse effects of treatment, decision-making and prevention of recurrence.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| 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 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".