Association of Systemic Inflammation and Sarcopenia With Survival in Nonmetastatic Colorectal Cancer
Bibliographic record
Abstract
Importance: Systemic inflammation and sarcopenia are easily evaluated, predict mortality in many cancers, and are potentially modifiable. The combination of inflammation and sarcopenia may be able to identify patients with early-stage colorectal cancer (CRC) with poor prognosis. Objective: To examine associations of prediagnostic systemic inflammation with at-diagnosis sarcopenia, and determine whether these factors interact to predict CRC survival, adjusting for age, ethnicity, sex, body mass index, stage, and cancer site. Design, Setting, and Participants: A prospective cohort of 2470 Kaiser Permanente patients with stage I to III CRC diagnosed from 2006 through 2011. Exposures: Our primary measure of inflammation was the neutrophil to lymphocyte ratio (NLR). We averaged NLR in the 24 months before diagnosis (mean count = 3 measures; mean time before diagnosis = 7 mo). The reference group was NLR of less than 3, indicating low or no inflammation. Main Outcomes and Measures: Using computed tomography scans, we calculated skeletal muscle index (muscle area at the third lumbar vertebra divided by squared height). Sarcopenia was defined as less than 52 cm2/m2 and less than 38 cm2/m2 for normal or overweight men and women, respectively, and less than 54 cm2/m2 and less than 47 cm2/m2 for obese men and women, respectively. The main outcome was death (overall or CRC related). Results: Among 2470 patients, 1219 (49%) were female; mean (SD) age was 63 (12) years. An NLR of 3 or greater and sarcopenia were common (1133 [46%] and 1078 [44%], respectively). Over a median of 6 years of follow-up, we observed 656 deaths, 357 from CRC. Increasing NLR was associated with sarcopenia in a dose-response manner (compared with NLR < 3, odds ratio, 1.35; 95% CI, 1.10-1.67 for NLR 3 to <5; 1.47; 95% CI, 1.16-1.85 for NLR ≥ 5; P for trend < .001). An NLR of 3 or greater and sarcopenia independently predicted overall (hazard ratio [HR], 1.64; 95% CI, 1.40-1.91 and HR, 1.28; 95% CI, 1.10-1.53, respectively) and CRC-related death (HR, 1.71; 95% CI, 1.39-2.12 and HR, 1.42; 95% CI, 1.13-1.78, respectively). Patients with both sarcopenia and NLR of 3 or greater (vs neither) had double the risk of death, overall (HR, 2.12; 95% CI, 1.70-2.65) and CRC related (HR, 2.43; 95% CI, 1.79-3.29). Conclusions and Relevance: Prediagnosis inflammation was associated with at-diagnosis sarcopenia. Sarcopenia combined with inflammation nearly doubled risk of death, suggesting that these commonly collected biomarkers could enhance prognostication. A better understanding of how the host inflammatory/immune response influences changes in skeletal muscle may open new therapeutic avenues to improve cancer outcomes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".