The Relationships between Frailty and Quality of Life in Elderly Women with Breast Cancer
Bibliographic record
Abstract
Background: It is well known that oncologic management of elderly patients is complicated, and physicians should well define the ultimate goals when choosing treatment modalities. Cancer treatment should not necessarily focus on survival but aim for a good quality of life for the patient in light of their frailty. Patients and Methods: This is a retrospective cross-sectional survey study. One hundred fifty-eight women with breast cancer participated in this study. The PRISMA-7 Frailty Index and WHOQOL-OLD Module assessed participants’ frailty and quality of life. SPSS 26.0 and Medcalc 14 [Acacialaan 22, B-8400 Ostend, Belgium] programs were used for statistical analyses. Statistically significant associations between the PRISMA-7 scale and the WHOQOL-OLD Module were assessed. Results: Of the158 participants, the median age [min-max] was 71 [65-96] years, and 61.2% had stage I and II breast cancer. Lumpectomy was 61.1%, and 75% received chemotherapy-radiotherapy and hormone therapy. For the WHOQOL-OLD domains; financial status [p=0.001] with the sensory ability domain, work status [p<0.001] and education status[p=0.004] with the autonomy domain, education status [p=0.002] with PPF activity domain, education status [p=0.001] and work status [p=0.007] with the social participation domain, treatment modality [p=0.003] with death &dying domain, number of comorbidities [p=0.004] with intimacy domain statistically significant. The total score was associated with education status [p=0.005] and the number of comorbidities [p=0.010]. Frailty correlated positively with age [cut-off age 68 years; p<0.001]. Education status was inversely associated with increased frailty [p=0.003]. The relationship between the PRISMA-7 scale and the WHOQOL-OLD Module correlated negatively in five out of six dimensions except for the Intimacy domain. Conclusions: It is necessary to design customized cancer management programs to improve specific components of elderly women with breast cancer with increased frailty by revealing the associations in domains of QoL.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".