Comparison of 2-Weekly Versus 4-Weekly Durvalumab Consolidation for Locally Advanced NSCLC Treated With Chemoradiotherapy: A Brief Report
Bibliographic record
Abstract
Introduction Durvalumab 10 mg/kg every 2 weeks for 1 year after chemoradiation has improved overall survival (OS) in unresectable stage III NSCLC. Subsequently, a 20 mg/kg 4-weekly regimen was approved. The study goal was to compare the efficacy and toxicity of the two regimens. Methods All patients with NSCLC treated with curative-intent chemoradiation followed by durvalumab from March 1, 2018 to December 31, 2020 at BC Cancer, British Columbia, Canada were included in this retrospective review. Durvalumab dosing schedule, toxicity, progression, and OS were collected. Comparisons between treatment groups were made using chi-square and independent t tests. Kaplan-Meier curves and log-rank test were used to analyze OS. Results A total of 152 patients were included in the 2-weekly group and 53 patients in the 4-weekly group. The median follow-up was 19.7 months and 12.0 months, respectively. The median OS was not reached, but 12-month survival rates were 88.4% versus 85.2% ( p = 0.55). Toxicity profiles were similar in terms of sites and severity. Conclusions There was no significant difference in efficacy or toxicity between the 2-weekly and 4-weekly durvalumab in this cohort of patients with advanced NSCLC previously treated with curative-intent chemoradiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".