Abstract 441: Potential implications of population kinetic characteristics of PD-1/PDL-1 monoclonals combined with chemotherapy in lung cancer
Bibliographic record
Abstract
Abstract Background: PD-1/PDL-1 inhibitors are active in non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) and improve progression-free survival (PFS) and overall survival (OS) when added to chemotherapy, even in tumors with low PDL-1 expression. We recently reported that for most agents assessed in most solid tumors, PFS and OS curves follow first order kinetics (Stewart Crit Rev Oncol Hematol 2020 Apr;148:102896; Stewart Crit Rev Oncol Hematol 2020 Sep;153103039). On log-linear plots, some curves approximate straight lines. Some have late convexity, potentially due to therapy interruption or dose reduction. Some have an inflection point to the right and fit 2 phase models on exponential decay nonlinear regression analysis (EDNLRA), potentially due to presence of 2 distinct subpopulations with differing rates of progression or death. Most PD-1/PDL-1 curves have 2 phase decay (suggesting distinct sensitive and resistant populations defined by a dichotomous present-vs-absent factor), while the majority of log-linear plots for chemotherapy are convex or approximate straight lines. Here we assessed characteristics of PFS and OS curves for PD-1/PDL-1 inhibitors when combined with chemotherapy. Methods: Published NSCLC and SCLC PFS and OS curves were digitized using the application https://apps.automeris.io/wpd/. GraphPad Prism 7 was used for 1 phase and 2 phase decay EDNLRA. Terminal curve portions with fewer than 10 remaining patients were excluded. Results: For chemotherapy, 22 of 152 PFS curves (14%) and 8 of 102 OS curves (8%) fit 2-phase decay models per our published definition, compared to 43 of 47 PFS curves (91%) and 24 of 24 OS curves (100%) for PD-1/PDL-1 inhibitors, and 1 of 18 PFS curves (6%) and 5 of 18 OS curves (28%) for PD-1/PDL1 inhibitors combined with chemotherapy (p less than 0.0001). Results were similar for SCLC (20 PFS and 27 OS curves) and NSCLC (197 PFS curves and 117 OS curves assessed). Conclusions: PFS and OS population kinetic characteristics for combinations of PD-1/PDL-1 inhibitors with chemotherapy are much more similar to those seen with chemotherapy than for those with single agent PD-1/PDL-1 inhibitors. The underlying biological reasons are uncertain, but this observation suggests that PD-1/PDL-1 inhibitors may potentiate chemotherapy in some tumors that are not intrinsically sensitive to these inhibitors as single agents. Alternatively, concurrent chemotherapy might antagonize the unknown mechanism of resistance to immunotherapy that drives 2 phase PFS and OS curve decay. This raises the question whether PD-1/PDL-1 inhibitors and chemotherapy might also potentiate each other in other tumor types not generally regarded as being sensitive to PD-1/PDL-1 inhibitors (eg, resistant breast and colon cancer variants, EGFR mutant NSCLC, etc). Citation Format: David J. Stewart, Abdulaziz Alshareef Aljassim. Potential implications of population kinetic characteristics of PD-1/PDL-1 monoclonals combined with chemotherapy in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 441.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".