Low muscle mass, malnutrition, sarcopenia, and associations with survival in adults with cancer in the UK Biobank cohort
Bibliographic record
Abstract
Abstract Background Low muscle mass (MM) is a common component of cancer‐related malnutrition and sarcopenia, conditions that are all independently associated with an increased risk of mortality. This study aimed to (1) compare the prevalence of low MM, malnutrition, and sarcopenia and their association with survival in adults with cancer from the UK Biobank and (2) explore the influence of different allometric scaling (height [m 2 ] or body mass index [BMI]) on low MM estimates. Methods Participants in the UK Biobank with a cancer diagnosis within 2 years of the baseline assessment were identified. Low MM was estimated by appendicular lean soft tissue (ALST) from bioelectrical impedance analysis derived fat‐free mass. Malnutrition was determined using the Global Leadership in Malnutrition criteria. Sarcopenia was defined using the European Working Group on Sarcopenia in Older People criteria (version 2). All‐cause mortality was determined from linked national mortality records. Cox‐proportional hazards models were fitted to estimate the effect of low MM, malnutrition, and sarcopenia on all‐cause mortality. Results In total, 4122 adults with cancer (59.8 ± 7.1 years; 49.2% male) were included. Prevalence of low MM (8.0% vs. 1.7%), malnutrition (11.2% vs. 6.2%), and sarcopenia (1.4% vs. 0.2%) was higher when MM was adjusted using ALST/BMI compared with ALST/height 2 , respectively. Low MM using ALST/BMI identified more cases in participants with obesity (low MM 56.3% vs. 0%; malnutrition 50% vs. 18.5%; sarcopenia 50% vs. 0%). During a median 11.2 (interquartile range: 10.2, 12.0) years of follow up, 901 (21.7%) of the 4122 participants died, and of these, 744 (82.6%) deaths were cancer‐specific All conditions were associated with a higher hazard of mortality using either method of MM adjustment: low MM (ALST/height 2 : HR 1.9 [95% CI 1.3, 2.8], P = 0.001; ALST/BMI: HR 1.3 [95% CI 1.1, 1.7], P = 0.005; malnutrition (ALST/height 2 : HR 2.5 [95% CI 1.1, 1.7], P = 0.005; ALST/BMI: HR 1.3 [95% CI 1.1, 1.7], P = 0.005; sarcopenia (ALST/height 2 : HR 2.9 [95% CI 1.3, 6.5], P = 0.013; ALST/BMI: HR 1.6 [95% CI 1.0, 2.4], P = 0.037). Conclusions In adults with cancer, malnutrition was more common than low MM or sarcopenia, although all conditions were associated with a higher mortality risk, regardless of the method of adjusting for MM. In contrast, adjustment of low MM for BMI identified more cases of low MM, malnutrition, and sarcopenia overall and in participants with obesity compared with height adjustment, suggesting it is the preferred adjustment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".