HEalth and QUality of life in Oncological patients (Hequobip study): call to definitive guidelines for the improvement of long-term patients’ quality of life
Bibliographic record
Abstract
Abstract Purpose. There is no current consensus in the counseling about diagnostic and therapeutic guidelines for bone disease in breast cancer (BC) patients. Hence, we aimed to study the current state of clinical and therapeutic approach to bone disease in an Italian BC population treated with adjuvant and/or hormone therapy, alongside overall Quality of Life (QoL).Methods. This observational multicenter longitudinal ambispective study involved four Italian clinical units recruiting patients receiving either Aromatase Inhibitors (AI) or Tamoxifen. Data on BC, bone health, osteoporosis screening, anti-resorptive therapy types and timing were collected. We focused on bone health status and therapeutic approach adopted and adhesion rate to the different indications identified by the scientific board: ESCEO-2017 (I); ASCO-2019 (II); Note-79-AIFA-Determination (III).Results. 555 women (mean age 54.2 ± 9.5 years) were finally enrolled, most in iatrogenic menopause (62.2%). Half of patients (50.3%) had osteopenia, whilst only 18.4% osteoporosis. DXA exam was performed in 52.6% of cases within the first 24 months after BCtherapy. At enrollment, only 7% of patients received anti-resorptive therapy, whilst after they reached 48.3% of women, mainly Denosumab. Followed indications were mainly “type-III” (46.7%) vs. 16.6% “type-I” and “4.1% “type-II”. Patients showed a moderate impairment of global QoL referred to anxiety and depression, alongside an impairment in mobility and pain.Conclusion. Although clinicians indicate bone screening, they more often prescribe antiresorptive therapy without considering precise guidelines. This study focused on the need for a potential standardized approach to long-term management, which may lead to an improved Qol in BC patients.Trial registration number. Clinicaltrial.gov: NCT04055805.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.001 |
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".