Survival Outcomes of Salvage Therapy for Local and Regionally Recurrent NSCLC
Bibliographic record
Abstract
Introduction The treatment of locally recurrent NSCLC after initial curative therapy is variable. We sought to perform a real-world analysis of curative and palliative therapeutic strategies used in locally recurrent NSCLC and explore the impact of baseline factors and the previous and recurrent treatment on outcomes. Methods A retrospective cohort study was done including all patients with stage I to III NSCLC who were referred to BC Cancer and received curative-intent therapy between 2005 and 2012. Patients were followed up to determine whether they developed locoregional recurrence. Two cohorts were created: curative-intent treatment at recurrence (surgery, radiotherapy with ≥50Gy ± chemotherapy, stereotactic radiosurgery) and palliative treatment. The primary outcome was overall survival (OS). Results A total of 1571 patients received curative-intent therapy during the study period. Of these, 179 (11%) developed a local and regional recurrence. A total of 51 patients (28%) were treated with curative intent at recurrence (12 surgery, 39 radiotherapy ± chemotherapy), and 128 (72%) received palliative treatment only. Patients receiving curative-intent therapy were more likely to have an Eastern Cooperative Oncology Group performance status of 0 to 1 (90% versus 58%), earlier stage at diagnosis (51% stage I) and receive more aggressive staging investigations at recurrence, pathologic confirmation (75% versus 27%) and positron emission tomography (77% versus 27%). OS was longer in the cohort receiving curative-intent therapy, with an OS of 34.3 months versus 9.8 months ( p < 0.001) in palliative treatment. Conclusions In this real-world population, isolated locoregional recurrences occurred in 11% of patients. Curative-intent treatment at recurrence is associated with a reasonable chance of long-term survival, making aggressive therapy of locoregional recurrences an important treatment consideration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".