Quality of Life in Long-Term Breast Cancer Survivors
Bibliographic record
Abstract
PURPOSE: There is considerable interest in the quality of life (QOL) of long-term breast cancer (BC) survivors. We studied changes in QOL from time of BC diagnosis to long-term survivorship and compared QOL in long-term survivors to that of age-matched women with no history of BC. PATIENTS AND METHODS: In all, 535 women with localized BC (T1-3N0-1M0) were recruited from 1989 to 1996 and followed prospectively, completing QOL questionnaires at diagnosis and 1 year postdiagnosis. Between 2005 and 2007, those alive without distant recurrence were recontacted to participate in a long-term follow-up (LTFU) study. A control group was recruited from women presenting for screening mammograms, and both groups completed LTFU QOL questionnaires. Longitudinal change in BC survivors and differences between BC survivors and controls were assessed in eight broad categories with clinically significant differences set at 5% and 10% of the breadth of each QOL scale. RESULTS: A total of 285 patients with BC were included in the study, on average 12.5 years postdiagnosis. Longitudinally, clinically significant improvements were observed in overall QOL by 1 year postdiagnosis with further improvements by LTFU. Some clinically significant improvements over time were seen in all categories. A total of 167 controls were recruited. Deficits were observed in self-reported cognitive functioning (5.3% difference) and financial impact (6.3% difference) in BC survivors at LTFU compared with controls. CONCLUSION: Long-term BC survivors show improvement in many domains of QOL over time, and they appear to have similar QOL in most respects to age-matched noncancer controls, although small deficits in cognition and finances were identified.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".