Cancer, precision medicine, and Atlantic Canada: A priority setting exercise by the Atlantic Cancer Consortium Patient Advisory Committee
Bibliographic record
Abstract
Precision Medicine in oncology is a rapidly evolving field aiming to prevent and treat cancers based on detailed patient and tumor characteristics. To better develop research studies, healthcare services and policies, and access to Precision Medicine, integration of insight and experiences of cancer patients and family members is required. In this paper, we describe the patient and family priorities regarding Precision Medicine as identified by the Atlantic Cancer Consortium Patient Advisory Committee (ACC PAC). The ACC PAC was formed in January 2024 and met virtually five times between January and May of 2024. It included a diverse set of 12 patients and family members of patients from across the Atlantic Canadian provinces, a coordinator, an oncologist/clinician-scientist, and a cancer scientist. During meetings, the committee focused on identifying patient and family priorities in Atlantic Canada. Three guests with lived experiences were invited to further diversify the committee’s discussions. Discussions were summarized by the coordinator and cancer scientist. Summaries were then reviewed by the ACC PAC members in September 2024. The ACC PAC identified priorities on two general themes: (1) preventing and addressing cancer’s effects on the whole person/family (for example, by accessible information and support programs), and (2) understanding and accessing Precision Medicine (for example, by research, education, and wider implementation). While the ACC PAC members were optimistic about the utility of Precision Oncology, they also made it clear that it was unlikely to be sufficient without a team-based, holistic and equitable approach to cancer care. Better quality healthcare, education, resources, and effort by all stakeholders were established as essential for effective cancer control and Precision Medicine. A key responsibility falls on the shoulders of funders, organizations, policy-makers and governments in addressing cancer’s effects, improving public knowledge of cancer and Precision Medicine, and improving access to high-quality healthcare and precision medicines. Patient partners and committees such as the ACC PAC can inform and help every step of these efforts with their patient-centered insights and perspectives. In early 2024, we formed the Atlantic Cancer Consortium Patient Advisory Committee (ACC PAC). Our group includes patients and family members affected by cancer from all four provinces of Atlantic Canada, in addition to a coordinator, an oncologist/clinician-scientist, and a cancer scientist. Together, we have identified patient and family priorities as they relate to cancer and Precision Medicine. Here we describe these priorities and our recommendations. Precision Medicine is an emerging cancer care strategy. In this strategy, a person’s circumstances and detailed disease features are considered so that the person can get the best possible care. In cancer, Precision Medicine strategy can help improve treatment success and patient outcomes. Our work indicates that while Precision Medicine strategy is promising, it requires more understanding, research, education, and accessibility. In addition, there is a need for holistic and equitable care that is accessible to all and that involves various care providers that support the patient and family. We recommend that all stakeholders work together efficiently to address the issues faced by the individuals and families affected by cancer in the region. The heaviest responsibility to address these issues lies on healthcare organizations and governments.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".