A Population Survival Kinetics Assessment of Extensive Small Cell Lung Cancer and Rationale for Maintenance Therapy
Bibliographic record
Abstract
Progression-free survival (PFS) and overall survival (OS) curves generally approximate first-order kinetics. On log-linear plots, convex curves with downward inflection (indicating late acceleration of progression/death) might arise from stopping effective therapies. We digitized published PFS/OS curves for etoposide/platinum-treated extensive small-cell lung cancer (SCLC) and other malignancies and replotted the curves log-linearly. Of 26 SCLC PFS curves, 21 (81%) were highly convex (with a marked late down-turn), and 26 (100%) were moderately or highly convex vs. 35/888 (4%) highly convex and 186 (21%) moderately/highly convex curves for other cancers (p < 0.0001). For SCLC, all 32 OS curves were moderately or highly convex vs. 87/363 (24%) that were moderately/highly convex for other cancers (p < 0.0001). The SCLC PFS curves had an initial downward inflection at a median of 3.1 months (around the completion of first-line chemotherapy), then a second inflection at 5.4 months, with further acceleration of progression. The median PFS half-life was 11.9 months while receiving treatment vs. 1.7 months after the second inflection point. Immunotherapy benefit appeared to be limited to 6–10% of the population. SCLC PFS/OS curves are more often convex than for other cancers, reflecting SCLC chemotherapy sensitivity but rapid progression following the completion of first-line chemotherapy. Effective maintenance strategies are needed.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".