Abstract 2250: Systemic inflammation and sarcopenia predict colorectal cancer survival
Bibliographic record
Abstract
Abstract Importance: A higher neutrophil-to-lymphocyte ratio (NLR, indicating systemic inflammation), and sarcopenia (reduced skeletal muscle mass) predict morbidity/mortality in a variety of cancers, but no prior research examines associations of pre-diagnostic NLR with at-diagnosis sarcopenia, nor whether NLR and sarcopenia combined identify early-stage patients with poor prognosis in colorectal cancer (CRC).Objective: To evaluate the association between pre-diagnosis NLR and at-diagnosis sarcopenia and of their combination with CRC survival, controlling for age, ethnicity, sex, body mass index, stage, and cancer site. Design, Setting, and Participants: This observational cohort with prospectively-collected data included 2470 patients diagnosed with stage I-III CRC at Kaiser Permanente from 2006-2011 with computed tomography (CT) scans from clinical care (mean days pre-diagnosis=6). Exposures: Systemic inflammation measured via average NLR in the 24 months pre-diagnosis (mean count=3 measures, mean months pre-diagnosis=7). The reference value was NLR below 3, indicating low/no inflammation. Main Outcomes and Measures: Sarcopenia, defined by published cutoffs for skeletal muscle index (CT muscle area in cm2 at the third lumbar vertebra divided by squared height in m2; below 52-cm2/m2 and 38-cm2/m2 for normal/overweight men and women, respectively, and below 54-cm2/m2 and 47-cm2/m2 for obese men and women, respectively), and incident death (overall or CRC-related). Results: Average age was 63 years; half of patients were female. NLR above 3 and sarcopenia were common (46% and 44%, respectively). Over a median of 6 years, we observed 656 deaths, 357 from CRC. Elevated NLR was associated with sarcopenia in a dose-response manner (compared to NLR below 3, Odds Ratio [OR]=1.35; 95%CI:1.10-1.67 for NLR 3-5; OR=1.47; 95%CI:1.16-1.85 for NLR above 5). NLR above 3 and sarcopenia were also independently associated with survival (Hazard Ratio [HR]=1.65; 95%CI:1.45-1.98 for overall death and HR=1.29; 95%CI:1.09-1.53 for CRC death); patients with both sarcopenia and NLR above 3 (versus neither), had double the risk of death overall (HR=2.53; 95%CI:1.87-3.41) and from CRC (HR=2.19; 95%CI:1.74-2.75). Conclusions and Relevance: Host inflammatory/immune response shortly prior to diagnosis predicts muscularity at diagnosis. Low muscle combined with systemic inflammation predicts worse CRC prognosis regardless of stage. A better understanding of the crosstalk between inflammatory/immune responses and the onset of changes in skeletal muscle may open new therapeutic avenues to improve cancer outcomes. Citation Format: Elizabeth M. Cespedes Feliciano, Candyce H. Kroenke, Jeffrey Meyerhardt, Carla M. Prado, Patrick T. Bradshaw, Marilyn Kwan, Jingjie Xiao, Stacey Alexeef, Erin K. Weltzien, Adriemme L. Castillo, Bette J. Caan. Systemic inflammation and sarcopenia predict colorectal cancer survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2250. doi:10.1158/1538-7445.AM2017-2250
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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 | 0.002 |
| 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) | 0.003 | 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".