Systematic review of frailty assessment in ovarian cancer studies.
Bibliographic record
Abstract
5564 Background: Frailty is a state of vulnerability to poor resolution of homeostasis following a stressor event, such as chemotherapy or surgery. Better knowledge of frailty assessments (FA) in ovarian cancer could help drive a global and individualized care strategy. Methods: A search was performed in 10 databases including Medline, Embase and Cochrane (up to March 2022). The search strategy utilized a combination of keywords and controlled vocabulary related to ovarian cancer, frailty/geriatric assessment. Studies performing FA in patients with ovarian cancer on systemic therapy, surgery and surveillance were included. The 2020 PRISMA checklists were followed, and the study was registered in PROSPERO (CRD42022323409). Primary objective was to identify frailty scales used in ovarian cancer studies. Secondary objectives were to describe impact of results on decision making and outcomes, adherence to ASCO Vulnerability Assessment (VA) guidelines. Results: 2,259 articles were screened, and 48 included in the final analysis. Studies were published between 2004-2022 and included 84,575 patients. 23 studies (48%) had an age limit for inclusion (≥65 to ≥80 years). Six studies were interventional (1 phase 3 clinical trial [CT], rest phase 2) and 42 were observational (45% retrospective). FA were highly variable. Median number of tests to assess frailty were 3 (range 1-13). Most studies used a combination of tests (several may apply): validated frailty scales (21 studies, 43.7%), nutritional/sarcopenia status (20 studies, 41.7%), functionality/physical performance (19 studies, 39.6%), geriatric assessment (7 studies, 14.6%). Global measures with all the comprehensive assessment items of the ASCO VA guideline were included in 14.6% of studies. FA was not used for decision making in any study. One FA designed for ovarian cancer was identified, the GINECO Geriatric Vulnerability score. Frailty was the primary objective in 26 studies (54%), out of which 12 were retrospective. Among them, study objectives were highly variable including survival, complications, or cost of surgery (13 studies) and systemic therapy (7 studies), prognosis (4 studies), treatment compliance and dependence (1 each). All but one (a prognostic study) met its primary outcome demonstrating worse outcomes in frail patients. Conclusions: Frailty assessments are heterogeneous in ovarian cancer studies. Most studies do not adhere to the ASCO vulnerability assessment guidelines. An association between frailty and poor outcomes was detected in surgical and systemic therapy studies. There is room for improvement, as none of the assessed studies used the frailty for decision making.[Table: see text]
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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 | 0.015 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".