Development of a Medicare Health Outcomes Survey Deficit-Accumulation Frailty Index and Its Application to Older Patients With Newly Diagnosed Multiple Myeloma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose To develop a frailty index using the Rockwood Accumulation of Deficits approach for the Medicare Health Outcomes Survey (MHOS) and apply it in a subset of older patients with newly diagnosed multiple myeloma. Methods Data from 2,692,361 patients without cancer, > 66 years of age, in SEER-MHOS linked databases between 1998 and 2009 were analyzed. A frailty index was constructed, resulting in a 25-item scale; cutoff values were created for individuals classified as frail. This frailty index was then applied to 305 patients with newly diagnosed myeloma in the database to predict overall survival. Results In the derivation cohort of patients without cancer, the median age was 74 years and the mean frailty index was 0.23 (standard deviation, 0.17). Among patients without cancer, each 10% increase in frailty index (approximately three to four more deficits) was associated with a 40% increased risk for death (adjusted hazard ratio, 1.397; 95% CI, 1.396 to 1.399; P < .001). In the cohort of patients with newly diagnosed myeloma, the median age was 76 years and the mean frailty index was 0.28 (standard deviation, 0.17). Each 10% increase in frailty index was associated with a 16% increased risk for death (adjusted hazard ratio, 1.159; 95% CI, 1.080 to 1.244; P < .001). Fifty-three percent of patients with multiple myeloma were considered frail. The estimated median overall survival of patients considered frail was 26.8 months, compared with 43.7 months ( P = .015) for those who were not. Conclusion The MHOS-based frailty index was prognostic for patients with multiple myeloma in predicting overall survival.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it