Follow-Up Care for Breast and Colorectal Cancer Across the Globe: Survey Findings From 27 Countries
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The purpose of this study was to describe follow-up care for breast and colorectal cancer survivors in countries with varying levels of resources and highlight challenges regarding posttreatment survivorship care. METHODS: We surveyed one key stakeholder from each of 27 countries with expertise in survivorship care on questions including the components/structure of follow-up care, delivery of treatment summaries and survivorship care plans, and involvement of primary care in survivorship. Descriptive analyses were performed to characterize results across countries and variations between the WHO income categories (low, middle, high). We also performed a qualitative content analysis of narratives related to survivorship care challenges to identify major themes. RESULTS: Seven low- or /lower-middle-income countries (LIC/LMIC), seven upper-middle-income countries (UMIC), and 13 high-income countries (HICs) were included in this study. Results indicate that 44.4% of countries with a National Cancer Control Plan currently address survivorship care. Additional findings indicate that HICs use guidelines more often than those in LICs/LMICs and UMICs. There was great variation among countries regardless of income level. Common challenges include issues with workforce, communication and care coordination, distance/transportation issues, psychosocial support, and lack of focus on follow-up care. CONCLUSION: This information can guide researchers, providers, and policy makers in efforts to improve the quality of survivorship care on a national and global basis. As the number of cancer survivors increases globally, countries will need to prioritize their long-term needs. Future efforts should focus on efforts to bridge oncology and primary care, building international partnerships, and implementation of guidelines.
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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 | 0.000 | 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 it