Physical Activity and Colorectal Cancer Prognosis According to Tumor-Infiltrating T Cells
Bibliographic record
Abstract
Abstract Background Evidence suggests that high-level physical activity may potentially reduce cancer mortality through its immune enhancement effect. We therefore hypothesized that survival benefits associated with physical activity might be stronger in colorectal carcinomas with lower immune reaction at diagnosis. Methods Using molecular pathological epidemiology databases of 470 colon and rectal carcinoma cases in the Nurses’ Health Study and the Health Professionals Follow-up Study, we assessed the prognostic association of postdiagnosis physical activity in strata of densities of CD3+ cells, CD8+ cells, CD45RO (PTPRC)+ cells, or FOXP3+ cells in tumor tissue. Cox proportional hazards regression model was used to adjust for potential confounders, including microsatellite instability, CpG island methylator phenotype, long interspersed nucleotide element-1 methylation, KRAS, BRAF, and PIK3CA mutations, and expression of CTNNB1 (beta-catenin), PTGS2 (cyclooxygenase-2), and IRS1. Results The association of postdiagnosis physical activity with colorectal cancer-specific mortality differed by CD3+ cell density (Pinteraction < .001). Multivariable-adjusted colorectal cancer-specific mortality hazard ratios for a quartile-unit increase in physical activity were 0.56 (95% confidence interval = 0.38 to 0.83) among cases with the lowest quartile of CD3+ cell density compared with 1.14 (95% confidence interval = 0.79 to 1.65) in cases with the highest quartile. We observed no differential survival association of physical activity by densities of CD8+ cells, CD45RO+ cells, or FOXP3+ cells. Conclusions The association between postdiagnosis physical activity and colorectal cancer survival appeared stronger for carcinomas with lower T cell infiltrates, suggesting an interactive effect of exercise and immunity on colorectal cancer progression.
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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 | 0.000 |
| 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) | 0.002 | 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".