Pooled safety analysis and management of sotorasib-related adverse events in <i>KRAS</i> G12C-mutated advanced non-small cell lung cancer
Bibliographic record
Abstract
INTRODUCTION: We describe the safety of sotorasib monotherapy in patients with KRAS G12C-mutated advanced non-small cell lung cancer (NSCLC) and discuss practical recommendations for managing key risks. METHODS: Incidence rates of treatment-related adverse events (TRAEs) were pooled from 4 clinical trials: CodeBreaK 100 (NCT03600883), CodeBreaK 101 (NCT04185883), CodeBreaK 105 (NCT04380753), and CodeBreaK 200 (NCT04303780) and graded according to CTCAE v5.0. Adverse events were deemed sotorasib-related per investigator causality assessment. RESULTS: In the pooled population (n = 549), TRAEs were reported in 388 (70.7%) patients (grade 1: 124 [22.6%]; grade 2: 117 [21.3%]; grade ≥ 3: 147 [26.8%]). Gastrointestinal and hepatic TRAEs, including diarrhea (171 [31.1%]), nausea (80 [14.6%]), elevated alanine aminotransferase (ALT; 68 [12.4%]), and elevated aspartate aminotransferase (AST; 67 [12.2%]) were the most common (≥10%). Dose interruption and dose reduction of sotorasib resulted in the resolution of >90% of diarrhea events; median time to resolution were 18.0 days and 22.0 days, respectively. Similar trends were observed for elevated ALT and AST events. Patients who stopped immunotherapy <3 months before initiating sotorasib had a higher incidence of treatment-related hepatotoxicity (80/240 [33.3%]) than those who stopped immunotherapy ≥3 months before initiating sotorasib (26/188 [13.8%]). Treatment-related pneumonitis/interstitial lung disease (ILD) and corrected QT (QTc) prolongation were observed in 9 (1.6%) and 4 (0.7%) patients, respectively. Two (0.4%) patients died with TRAEs, 1 with ILD whose ultimate cause of death was disease progression, and the other with an unknown cause. CONCLUSIONS: Sotorasib has a well-characterized safety profile in patients with KRAS G12C-mutated advanced NSCLC, and key risks are manageable with dose modification.
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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 | 0.001 |
| 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".