CT‐Based Body Composition and Frailty as Predictors of Survival Among Older Adults With Gastrointestinal Malignancies
Bibliographic record
Abstract
BACKGROUND: Older adults with cancer are at an increased risk of treatment related toxicities and early death. Routinely collected clinico-demographic characteristics inadequately explain this increased risk limiting accurate prognostication. Prior studies have suggested that altered body composition and frailty are independently associated with worse survival among older adults with cancer; however, their combined influence remains unclear. METHODS: We used data from a single-institution prospective cohort study of older adults (≥ 60 years) who underwent geriatric assessment (GA) at the time of initial consultation with a medical oncologist from September 2017 to December 2020 and available baseline abdominal computed tomography within 60 days of GA. Using multi-slice CT images from T12 to L5 level, we assessed volumetric measures of skeletal muscle (SMV), visceral adipose tissue (VATV), subcutaneous adipose tissue (SATV) and averaged skeletal muscle density (SMD), computing sex-specific z for each measure. Frailty was measured using a 44-item frailty index using the deficit accumulation approach. Primary outcome of interest was overall survival (OS) defined as time from GA to death or last follow up. We used multivariable Cox regression model to study the independent association between the above four body composition measurements and OS adjusted for baseline confounders and frailty. RESULTS: We included 459 patients with a mean age of 69.7 ± 7.5 years, 60% males and 77% non-Hispanic Whites. Most had colorectal (27%) or pancreatic cancer (20%) and 48% had stage IV disease. Over a median follow up of 39.4 months, 209 patients (46%) died. In multivariable Cox regression models adjusted for age, sex, race, cancer type, cancer stage and frailty, skeletal muscle volume (HR 0.74; 95% CI 0.58-0.96; p = 0.02, per 1 SD increment) was independently associated with OS. The addition of body composition variables to baseline clinico-demographic variables and frailty led to a slightly improved model discrimination. CONCLUSIONS: SMV is independently associated with OS among older adults with newly diagnosed gastrointestinal cancers. Capturing body composition measurements in oncology practice may provide additional prognostic information for older adults with cancer above and beyond what is captured in routine clinical assessment including frailty.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".