Role of the total mutation burden (TMB) and tumor-infiltrating lymphocytes (TILs) on the development of second primary cancer after complete resection of non-small cell lung cancer (NSCLC).
Bibliographic record
Abstract
e21092 Background: Risk of developing SPC after complete surgical resection of NSCLC has been reported to be 3-6% per person-year. We hypothesized that genomic instability, as assessed by high TMB, and the absence of TILs in the primary tumor might be associated with SPC. Methods: The LACE [Lung Adjuvant Cisplatin Evaluation])-BIO database was used, which includes 3 randomized trials. TMB and TILs were analyzed on FFPE specimens. TMB was categorized into tertiles (high > 7.8 mutations/MB, moderate i.e. > 4 and < = 7.8, low < 4) and TILs as marked vs. other. Associations on competing time-to-event endpoints (SPC, and death without developing SPC) were evaluated using the Fine and Gray model stratified by trail and adjusted on treatment, age, gender, tumor stage, nodal stage, histology, performance status and surgery type. Results: TMB and TILs assessments were available for 879 patients without missing clinical covariates; 85 patients had marked TILs. During follow-up, 47 SPCs had been observed and 392 deaths without developing SPC. Regarding TMB, a significant association was found between low TMB and death without SPC (sub-distribution hazard ratio SHR = 1.36(1.06-1.74), see Table), suggesting a higher risk of death without SPC among patient with low TMB compared to those with moderate TMB; no strong effect was observed for SPC. Regarding TILs, a trend was observed between marked TILS and a lower risk of death (SHR = 0.70 [0.47-1.04]) but to a lesser extent for SPC (SHR = 0.80 [0.28-2.28]). Conclusions: This is the first study of the effect of genomic instability (measured by TMB) and host immune response (measured by TILs) in completely resected NSCLC on competing events of SPC and death, suggesting associations between TMB, TILs and death-without-SPC . There was no statistically significant association with SPC. However, the number of SPCs was small; these findings requires validation in other early stage lung cancer cohorts. [Table: see text]
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".