Population-Based Longitudinal Study of Follow-Up Care for Breast Cancer Survivors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To describe the patterns of follow-up care provided to a population-based cohort of breast cancer survivors, and to assess factors associated with adherence to guidelines on follow-up care. PATIENTS AND METHODS: We conducted a retrospective longitudinal study of all women with surgically treated breast cancer who were without evidence of recurrence, advanced breast cancer, or new primary cancer and were diagnosed in Ontario, Canada, within a 2-year period (n = 11,219). They were followed for 5 years. The cohort was identified through the Ontario Cancer Registry, and individuals were linked across population-based administrative health databases. Frequency of and adherence to guideline recommendations for oncologist and primary care physician (PCP) visits; surveillance imaging for metastatic disease; and surveillance mammograms by year from diagnosis, age group, and income quintile were analyzed. Factors associated with adherence to guideline recommendations were analyzed. RESULTS: Most women saw both oncologists and PCPs in each follow-up year. Approximately two thirds had surveillance mammograms in each follow-up year. Overall, two thirds had either fewer or greater than recommended oncology visits, one quarter had fewer than recommended surveillance mammograms, and half had greater than recommended surveillance imaging for metastatic disease. CONCLUSION: This population-based study shows substantial variation in adherence to guideline recommendations, with both overuse and underuse of surveillance visits and tests. Most importantly, a substantial proportion are receiving more than recommended imaging for metastatic disease but fewer than recommended mammograms for detection of local recurrence or new primary cancer, for which effective intervention is possible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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 it