Esophagitis and Pneumonitis Related to Concurrent Chemoradiation ± Durvalumab Consolidation in Unresectable Stage III Non-Small-Cell Lung Cancer: Risk Assessment and Management Recommendations Based on a Modified Delphi Process
Bibliographic record
Abstract
The addition of durvalumab consolidation to concurrent chemoradiation therapy (cCRT) has fundamentally changed the standard of care for patients with unresectable stage III non-small-cell lung cancer (NSCLC). Nevertheless, concerns related to esophagitis and pneumonitis potentially impact the broad application of all regimen components. A Canadian expert working group (EWG) was convened to provide guidance to healthcare professionals (HCPs) managing these adverse events (AEs) and to help optimize the patient experience. Integrating literature review findings and real-world clinical experience, the EWG used a modified Delphi process to develop 12 clinical questions, 30 recommendations, and a risk-stratification guide. The recommendations address risk factors associated with developing esophagitis and pneumonitis, approaches to risk mitigation and optimal management, and considerations related to initiation and re-initiation of durvalumab consolidation therapy. For both AEs, the EWG emphasized the importance of upfront risk assessment to inform the treatment approach, integration of preventative measures, and prompt initiation of suitable therapy in alignment with AE grade. The EWG also underscored the need for timely, effective communication between multidisciplinary team members and clarity on responsibilities. These recommendations will help support HCP decision-making related to esophagitis and pneumonitis arising from cCRT ± durvalumab and improve outcomes for patients with unresectable stage III NSCLC.
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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 | 0.194 | 0.137 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".