HCT Frailty Scale for Younger and Older Adults Undergoing Allogeneic Hematopoietic Cell Transplantation
Bibliographic record
Abstract
Abstract The HCT Frailty Scale is an easy prognostic tool composed of (a) Clinical Frailty Scale; (b) Instrumental Activities of Daily Living; (c) Timed-up-and-Go test; (d) Grip Strength; (e) Self-Health Rated Questionnaire; (f) Falls tests; (g) Albumin and C-reactive protein levels. This scale was designed to classify allogeneic hematopoietic cell transplant (alloHCT) candidates into fit, pre-frail and frail groups, irrespective of age. This study evaluates the ability of this frailty classification to predict overall survival (OS) and non-relapse mortality (NRM) in adult patients of all ages, in a prospective sample of 298 patients transplanted between 2018 and 2020. At first consultation, 103 (34.6%) patients were fit, 148 (49.7%) pre-frail, and 47 (15.8%) were frail. The 2-year OS and NRM of the three groups were 82.9%, 67.4%, and 48.3% (P<0.001), and 5.4%, 19.2%, and 37.7% (P<0.001). For patients younger than 60 years (n=174), the 2-year OS and NRM of fit, pre-frail, and frail groups were 88.4%, 69,3% and 53.1% (P=0.002), and 5.8%, 22,8%, and 34.8% (P=0.005), respectively; and in patients older than 60 (n=124), OS and NRM were 75.5%, 63.8% and 41.4% (P=0.006), and 4.9%, 16.4%, and 42.1% (P=0.001). In conclusion, frailty predicted worse transplant outcomes in both younger and older adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".