Clinical outcomes of EGFR+ NSCLC pts treated with immune checkpoint inhibitors (ICI).
Bibliographic record
Abstract
9069 Background: ICIs have limited efficacy in EGFR+ NSCLC with ORR ~10% if PDL1 > 25% in ATLANTIC, yet ICIs are often used in later lines of therapy as pts and providers feel there may be little risk. The impacts of ICI in this setting are poorly understood. We describe our institutional experience of ICI use in EGFR+ NSCLC. Methods: MGH pts with advanced EGFR+ NSCLC treated with ICI (any line) were retrospectively reviewed for demographics, PDL1, treatment duration and patient outcomes. Disease flare was defined as hospital/hospice admission due to progression or death (Chaft CCR 2011) within 30d of ICI. Results: 40 pts with EGFR+ NSCLC (22 del19, 11 L858R, 5 ins20, 2 other) received ICI between 7/2012-12/2018. 13 were on a clinical trial. 4 had SCLC transformation. Median # of prior therapies = 3 (range, 0-8). Of 16 with PDL1 quantified, 8 had PDL1 > 25%. ICI regimens were: nivolumab (nivo; n = 16), pembrolizumab (pembro; 9), atezolizumab (atezo; 3), ipilimumab/nivo (7), carboplatin/pemetrexed (pem)/pembro (3), pem/pembro (1), paclitaxel/atezo (1). 18 pts stopped TKI ≤21d prior to ICI start. Median duration of treatment (DOT) was 25 days (range, 1-1482). DOT was > 1 yr for 2 pts (5%), treated with 1st-line nivo/erlotinib (erlo) and 3rd-line nivo. All 8 pts with PDL1 > 25% had DOT < 2 mos. Disease flare within 30d of ICI occurred in 16/40 (40%) overall, 8/18 (44%) who stopped TKI ≤21d of ICI start, and 14/26 (54%) who received ICI in 4thline or later. 8 pts had concurrent TKIs (4 erlo/nivo, 2 erlo/pembro, 1 erlo/atezo, 1 osimertinib (osi)/nivo); 3/8 discontinued ICI for toxicity (all 3 treated first-line). 5 pts received osi immediately post-ICI. There was no pneumonitis on osi post-ICI; 1 pt developed gr3 LFTs and gr4 hypoNa. Conclusions: In this real world cohort of EGFR+ NSCLC, clinical benefit from ICI (assessed by DOT) was rare, including pts with high PDL1. 5% had durable benefit (both pts received ICI in earlier lines of therapy). A previously underappreciated negative outcome of ICI is that admission to hospital, hospice or death within 30d of ICI occur in up to 54% pts. This may be related to disease flare or hyperprogression and suggests that use of ICI in heavily pretreated EGFR+ NSCLC may negatively impact outcomes at end-of-life and should be used with caution.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".