A Real-World Evaluation of Atezolizumab Plus Platinum-Etoposide Chemotherapy in Patients With Extensive-Stage SCLC in Canada
Bibliographic record
Abstract
Introduction The real-world data evaluating treatment outcomes of atezolizumab plus carboplatin-etoposide chemotherapy (atezolizumab) for extensive-stage SCLC (ESCLC) are lacking. Our objective was to evaluate real-world outcomes of ESCLC treated with atezolizumab. Methods A retrospective analysis of provincial patients with ESCLC who started first-line (1L) systemic treatment was conducted. We primarily evaluated the progression-free survival (PFS) and overall survival (OS) outcomes in association with atezolizumab compared with platinum-etoposide chemotherapy (chemotherapy) while adjusting for relevant demographic and clinical factors. Adverse events (AEs) during 1L were evaluated. Results A total of 67 patients were identified. Of the 34 patients who received atezolizumab, 24% had Eastern Cooperative Oncology Group performance status greater than or equal to 2, approximately 50% were more than or equal to 65 years, 21% received cisplatin-etoposide chemotherapy before atezolizumab, and 12% had thoracic radiation (tRT). Within the atezolizumab versus chemotherapy group, the median PFS equals to 6.0 versus 4.3 months ( p = 0.03) whereas OS = 12.8 versus 7.1 months ( p = 0.01). Relative to chemotherapy, the hazard ratio (95% confidence interval) for PFS was 0.53 (0.28–1.02) and OS was 0.42 (0.20–0.88) with atezolizumab. tRT compared with no tRT receipt correlated with reduced death risk (hazard ratio [95% confidence interval] = 0.33 [0.13–0.88]). AE-related treatment withdrawal with atezolizumab was 32% and 15% with chemotherapy ( p = 0.02). Within the tRT subgroup, 25% versus 20% in atezolizumab versus chemotherapy group, respectively, discontinued 1L owing to AE. Conclusions This is the first real-world study revealing comparable survival with that in the IMpower133 trial. Treatment discontinuation from AEs was higher with atezolizumab among Canadian patients with ESCLC. Our data suggest safe use of tRT and chemoimmunotherapy, but its efficacy for ESCLC warrants further study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".