Dietary compounds and patterns associated with immune checkpoint inhibitor (ICI) outcomes in advanced non-small cell lung cancer (NSCLC).
Bibliographic record
Abstract
2567 Background: The gut microbiome is a modulator of ICI activity. Diet is among the most important factors influencing the gut microbiome. We previously showed that high fiber was not associated with outcome in NSCLC, in contrast to melanoma. However, the impact of dietary patterns and specific nutrients on ICI outcomes in NSCLC is unknown. Methods: At the CHUM Microbiome Centre, a nutritionist prospectively collected dietary history using a validated DHQ-II survey from 147 patients (pts) with advanced NSCLC treated with ICI alone or in combination with chemotherapy. Global dietary patterns and a systematic screen of 72 macro- and micronutrients (cut-offs defined by median) were examined for their association with progression-free survival (PFS) in univariable and multivariable cox-regression analyses. Associations between diet and immune-related adverse events (irAE) were examined. In 69 pts, shotgun metagenomic sequencing (WMS) was performed on fecal samples to determine differential abundance of bacteria using linear discriminant analyses, heatmaps, and MaAsLin2. Results: Median age was 68, 46% were male. Median follow-up was 13 months. Total caloric intake adjusted for basal metabolic rate (Mifflin-St Jeor equation using BMI and activity level) was not associated with PFS (p = 0.3). In univariable analyses, the following nutrients were associated with improved PFS: vitamin K (HR 0.62, p = 0.03), fat (HR 0.65, p = 0.04); while the following were associated with inferior PFS: starch (HR 1.61, p = 0.03), carbohydrates (HR 1.56, p = 0.04), sucrose (HR 1.62, p = 0.03), and iron (HR 1.7, p = 0.016). In a multivariable analysis examining all macro- and micronutrients and adjusting for BMI, vitamin K intake was significantly associated with improved PFS (HR 0.60, 95% CI 0.37, 0.97, p = 0.04). Fat-based diets such as keto-like diet (high fat, low starch) was associated with improved PFS in univariable (HR, 0.47, p = 0.008) and multivariable analyses (HR 0.37, 95%CI 0.2, 0.68, p = 0.001). Compared to high starch diet, western diet (high fat, high starch) was associated with increased risk of any grade irAE (24% vs 54%, respectively, p = 0.01). WMS analyses revealed biologically relevant signals; fat-based diets were associated with enrichment of favorable commensal bacteria such as Ruminococcus lactaris , Butyricimonas faecihominis , Lachnospiraceae spp, with low fat associated with deleterious Veillonella atypica . Starch-based diets were associated with high Prevotella spp. Sucrose-enriched diets were enriched with Candidatus saccharibacteria , a known sucrose-fermenting bacteria. Conclusions: Our results demonstrate the importance of diet on ICI outcomes in NSCLC and WMS results suggest this is mediated by the gut microbiome. Diet is a modifiable lifestyle factor which may be targeted to improve ICI activity, meriting study in a randomized trial.
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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".