Abstract 6299: Population kinetics (PopKin) of non-small cell lung cancer (NSCLC) adjuvant therapy
Bibliographic record
Abstract
Abstract Background: Disease-free survival (DFS) and overall survival (OS) follow 1st order kinetics. Curve Popkin assessment yields biological insights. Chemotherapy (chemo) improves outcome in resected NSCLC. We performed adjuvant DFS and OS PopKin assessments. Methods: We digitized published DFS and OS curves. We used GraphPad Prism for curve exponential decay nonlinear regression analysis (EDNLRA). Results: We assessed 1 trial with adjuvant osimertinib and 5 with platinum-based postoperative chemo and control arms. With osimertinib, DFS and OS curves were convex on log-linear plots, suggesting rapid tumor regrowth once therapy is discontinued. In chemo trials, 10 of 10 DFS curves and 9 of 10 OS curves fit 2-phase decay EDNLRA models (Table 1). Popkin calculations indicate that of control patients destined to recur, 12% would recur by 2 months after surgery, 22% by 4 months and 31% by 6 months. Conclusion: PopKin suggests osimertinib delays recurrence rather than preventing it. Combined chemo analyses suggest chemo converts 15% of patients from rapidly to slowly recurring, but many “shifted” patients eventually recur. Hence, chemo may induce reversible tumor senescence rather than eradicating micrometastases. Anti-senescent cell strategies might prove beneficial. Frequent scans are warranted in the 1st postoperative year for early detection of recurrences. Table 1. EDNLRA of adjuvant chemo and control DFS and OS curves Arm Overall t1/2 a % Fastb Fast group t1/2 c % Slowd Slow group t1/2 e Control DFS 40.1 57 11.0 43 212.7 Chemo DFS 47.2 42 11.7 58 120.8 Control OS 51.9 69 25.8 31 1.3 x 1012 Chemo OSf 61.4 75 45.9 25 1.3 x 1012 aMedian t1/2 (half-life, months) on 1-phase decay EDNLRA. bMedian % of all patients in rapidly recurring/dying subgroup on 2-phase decay EDNLRA. cMedian t1/2 in rapidly recurring/dying subgroup on 2-phase decay EDNLRA. dMedian % in slowly recurring/dying subgroup. eMedian t1/2 in slowly recurring/dying subgroup. fIn 1 study, OS curve did not fit a 2-phase decay model Citation Format: David J. Stewart. Population kinetics (PopKin) of non-small cell lung cancer (NSCLC) adjuvant therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6299.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".