Physiologic colonic uptake of <sup>18</sup>F-FDG on PET/CT predicts immunotherapy response and gut microbiome diversity in patients with advanced non-small cell lung cancer (NSCLC).
Bibliographic record
Abstract
9600 Background: Immune checkpoint inhibitors (ICI) represent the backbone treatment of advanced non-small cell lung cancer (aNSCLC) patients. Emerging evidence suggests increased gut microbiome (GM) diversity is associated with favorable response. Conversely, antibiotic-induced dysbiosis may be associated with deleterious outcomes in patients receiving ICI in multiple retrospective studies and one prospective study. 18F-FDG physiologic colonic uptake on PET/CT increases following treatment with antibiotics and could be a surrogate marker for GM diversity and therefore clinical response. The aim of this study was to determine if 18F-FDG physiologic colonic uptake prior to ICI initiation correlates with outcomes and GM metagenomics in patients with advanced NSCLC. Methods: 71 patients with aNSCLC who underwent PET/CT prior to ICI were identified. For each patient, the colon was manually contoured, SUVmax was measured in each segment of the colon by a nuclear medicine specialist and average SUVmax was calculated for the whole colon. Patients were stratified in two groups according to median colon SUVmax (low vs high uptake). 18F-FDG physiologic colonic uptake was then compared to overall survival (OS), objective response (ORR), and progression-free survival (PFS). For patients with available stool samples (n = 10), GM composition was defined using metagenomics sequencing. Results: 71 patients (54% men, median age: 68 years) with aNSCLC were included in the study and ICI was the first line of therapy in 38% of those patients. The mean colon SUV for the low and high uptake groups were 1.41 (CI 95% 1.35-1.47) and 2.18 (CI 95% 1.90-2.46) respectively. The high uptake group had a higher proportion of non-responders (p = 0.033) and significant shorter PFS (4.1 months vs 11.3 months, p = 0.005). In the caecum, high uptake also correlated with numerically shorter OS (10.82 vs 27.56 months, p = 0.058) compared to low uptake group. Despite the low number of samples, metagenomics sequencing revealed that PLS-DA (Partial Least Squares Discriminant Analysis) for diversity was lower in the high SUV group (p = 0.008). Conclusions: Higher colon SUVmax on pre-ICI FDG PET/CT is associated with worse clinical outcomes and lower baseline GM diversity in patients with advanced NSCLC. Here, we propose that 18F-FDG physiologic colonic uptake on PET/CT could serve as a surrogate marker of GM diversity and predicts clinical 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 | 0.000 |
| 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) | 0.001 | 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".