Updated overall survival and safety profile of durvalumab monotherapy in advanced NSCLC.
Bibliographic record
Abstract
169 Background: Single-agent durvalumab is being evaluated in patients with advanced squamous and non-squamous NSCLC in an ongoing Phase 1/2 study (NCT01693562). Here we present updated survival and safety data in NSCLC patients. Methods: Treatment-naïve (1L) and previously treated (2L or 3L+) stage IIIB/IV NSCLC patients received durvalumab 10 mg/kg Q2W for up to 12 months. Patients were stratified by tumor PD-L1 expression (Ventana PD-L1 [SP263] Assay [PD-L1 high: ≥25% of tumor cells with membrane staining]), treatment line, and histology. Results: As of 05 September 2017, 304 NSCLC patients received durvalumab monotherapy. Median duration of follow-up was 35.6 (0.3–50.9) months. Investigator-assessed ORR ranged between 23.2% and 30.0% among PD-L1 high patients, and between 3.6% and 8.3% among PD-L1 low/negative patients. Median PFS and median OS were longer in PD-L1 high vs PD-L1 low/negative patients (Table). Any-grade treatment-related AEs (TRAEs) were reported in 57.2% of pts (including fatigue, 17.4%, decreased appetite, 9.2%, diarrhea, 8.9%); in 10.2% of pts these were Grade 3 or 4. TRAEs resulting in treatment discontinuation were reported in 17 patients (5.6%); 1 patient had a Grade 5 TRAE (pneumonia). Conclusions: In this ongoing phase 1 study, OS and safety profile appear encouraging in treatment-naïve and previously treated NSCLC patients, particularly among PD-L1 high patients. Further investigation regarding PD-L1 expression for selection of patients who most likely benefit from durvalumab is needed. Clinical trial information: NCT01693562. [Table: see text]
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".