Survival impact of aggressive treatment on patients with oligometastatic non-small cell lung cancer (NSCLC).
Bibliographic record
Abstract
e20669 Background: The new 2016lung cancer classification differentiates oligometastatic (M1b) better prognostic from plurimetastatic (M1c) disease. A prospective study presented at 2016 ASCO showed improved PFS in patients with oligometastatic brain disease treated aggressively compared to a more palliative treatment but OS data is pending. Methods: This study is a single-center retrospective study including 643 patients with metastatic lung cancer diagnosed in an University center (CHUM) from 2005-2015 and followed more than 6 months (median follow up 13.3mo) . Only 67 patients (10.4%) were found to have synchronous oligometastatic disease at diagnosis. Results: Amongst the 67 patients, the localization of metastatic disease was as follows: 74% brain (n = 50), 9% adrenal gland (n = 6), 7% contralateral pulmonary lobe (n = 5), 6% bone (n = 4) and 3% liver (n = 2). 29 patients received radical treatment to primary and metastatic site (group A) and 36 patients received non-aggressive treatments (group B). There was no statistically significant difference between the two groups in terms of demographic and histological characteristics. The radical treatment group A had a mOS of 26mo and a mPFS of 12.8m compared to mOS of 5mo (p = 0.0001) and mPFS of 4.8mo (p = 0.010) for group B. This difference was observed when stratifying according to stage of primary lung disease (stage I mOS 42mo vs 16mo, stage II mOS 34mo vs 6mo and stage III mOS 22mo vs 4mo) and according to to oligometastatic site. Interestingly, addressing aggressively the primary lung cancer improved median survival even when the oligometastasis was not resected (26mo v and 24mo respectively), but not when oligometastasis only was resected and primary was treated palliatively (5mo vs 3 mo). Adjuvant chemotherapy given after radical treatment did not improve mPFS or mOS (12.83 vs12.47 months, p = 0.860). Conclusions: Radical treatment of oligometastatic NSCLC in this unselected population improved mPFS and mOS compared to other treatment strategies. As overall survival data of the prospective trial presented at 2016 ASCO meeting is pending, the more radical approach should be emphasized when patients present with oligometastatic lung cancer disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".