Abstract PO1-16-12: The McPeak-Sirois Group Breast Metastases Registry
Bibliographic record
Abstract
Abstract Background: In 2020, the McPeak-Sirois Group (MPSG), a Quebec-based breast cancer trials consortium, launched a feasibility pilot project to register prospectively cases of metastatic breast cancer (MBC). This Breast Metastases Registry (BMR) had the following objectives: a) to measure real-world progression-free and overall survival; b) to capture real-world evidence in efficacy of novel therapeutic approaches and c) to facilitate the development of clinical research projects in MBC. Methods: The pilot phase was initiated in three major academic hospitals with the intention of testing the feasibility of building a BMR and to assess barriers before extension to other hospitals in the province of Quebec. Funding was obtained through non-profit organizations and the pharmaceutical industry. The project was approved by a research ethics board and informed consent was obtained from each patient. The main inclusion criteria was a MBC diagnosis at the time of enrolment. Metastatic diseases were considered de novo if the metastatic condition was detected at the same time of the primary disease diagnosis or within the following 4 months. The information in the BMR relates to participants’ health status, including but not limited to hospitalizations, diagnoses, medications, medical procedures and imaging, pathology, genetic and laboratory results. In addition to the prospective data, the registry also captures information retrospective to the date of enrollment. Results: Between July 30, 2021 and April 22, 2023, a total of 427 patients were approached by a research nurse and 423 patients enrolled and 4 refused (99.2% participation rate). Approximately one third of the cohort was diagnosed between 2021-2023 (30.3%) while 69.7% were in 2002-2020 timeframe. The majority was either HR+/HER2- (55.3%) or HER2+ (26.9%). The median age at the time of MBC diagnosis was 57 years (Q1-Q3 range: 47-67 years). We observed that 57.9% of patients had a relapsed MBC while de novo MBC comprised 42.1% of the cohort with the highest percentage in the HER2+ group (59.6%). The median time between primary cancer and metastatic disease in those with relapsed MBC is shorter in triple negative breast cancer (28.9 months) compared to 71.4 months in HR+ disease. Among all lines of treatment for metastatic disease, independently of age at time of MBC diagnosis, 21% of patients participated in a clinical trial. Discussion: The pilot project demonstrated the acceptability and feasibility of building a MBC provincial registry as illustrated by the high participation rate (more than 99%). The next step is to expand the registry to other hospital sites in Quebec, however, the main difficulty is having the necessary manpower (oncology registrars) to ensure data entry. Over one third of the MBC patients presented as de novo disease (and more than half of these with HER2+ disease). This proportion of de novo MBC is unusually high and is likely due to a recruitment bias during the pilot phase as data entry was prioritised for de novo diagnoses over MBC at time of recurrence and patients were recruited at any time in their MBC trajectory and not only at the time of their MBC diagnosis. Clinical trial participation was higher in our cohort compared to the usually reported 5% participation rate. This may be due to recruitment bias but needs to be evaluated further. Conclusion: We have found that recruiting patients in a metastatic cancer registry and collecting their real-world data is not only feasible but well received by patients. The limiting factor for expansion to other hospitals is lack of oncology registrars. At maturity, the BMR will be a unique and powerful resource for breast cancer research and will allow researchers and their collaborators to unite their efforts to better understand how stage IV breast cancer is treated and how management of the disease can be improved. The BMR could also have the potential to improve participation in clinical trials and to stimulate clinical research. Citation Format: Julie Lemieux, Danielle Charpentier, Dominique Johnson, Nathalie Bolduc, Caty Blanchette, Claude Nadon, Sarkis Meterissian. The McPeak-Sirois Group Breast Metastases Registry [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-16-12.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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".