Stages I-II non-small cell lung cancer treated using either lobectomy by video-assisted thoracoscopic surgery (VATS) or stereotactic ablative radiotherapy (SABR): Outcomes of a propensity score-matched analysis.
Bibliographic record
Abstract
7009 Background: VATS procedures are increasingly used in early-stage NSCLC. As high local control rates are also seen with stereotactic ablative radiotherapy (SABR), we performed a propensity score-matched analysistocompare loco-regional control (LRC) after both treatments. Methods: Patients with stage I-II NSCLC treated at 6 hospitals (1 university and 5 regional hospitals) with VATS lobectomy were eligible. Details of SABR patients were obtained from a single-institutional database. All VATS-lobectomies were performed in accordance with ESTS guidelines. Patients were matched using propensity scores based on cTNM, age, gender, Charlson comorbidity score, lung function and performance score. Matching was performed blinded to all outcomes. Excluded were: synchronous lung tumors, COPD GOLD class 4 or history of prior lung cancer. A total of 86 VATS- and 527 SABR patients were eligible for matching (1:1 ratio, caliper distance of 0.025 without replacement). Loco-regional failure was defined as recurrence in/adjacent to the radiation planning target volume or surgical margins, the ipsilateral hilum or mediastinum. Recurrences were either biopsy-confirmed or PET-positive and reviewed by a tumor board. Patients upstaged during VATS and those developing recurrence were treated in accordance with national guidelines. Results: The matched cohort consisted of 128 patients with cT1-3N0 NSCLC following SABR (n=64) or VATS-lobectomy (n=64). Median follow-up was 30 and 16 months, respectively. The groups were well matched on baseline variables. SABR patients had better LRC rates at 1- and 3-years (96.8% and 93.3% vs. 86.9% and 82.6%, respectively, p= .03). Three-year progression-free survival (PFS) did not significantly differ after SABR (79.3% versus 63.2%, p = .09). Distant recurrence rates and overall survival (OS) did not significantly differ. Conclusions: Although loco-regional control was superior after SABR compared to VATS-lobectomy, PFS and OS did not differ at this time-point. Our findings support the current randomized controlled trial evaluating both treatments (ACOSOG Z4099).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".