Predictive and prognostic factors in patients with anaplastic lymphoma kinase rearranged early-stage lung adenocarcinoma
Bibliographic record
Abstract
OBJECTIVES: This study aimed to evaluate the predictive and prognostic factors in clinical stage I, anaplastic lymphoma kinase (ALK)-rearranged lung adenocarcinoma following radical surgery. Additionally, it sought to compare these factors with an external cohort of ALK wild-type patients. METHODS: A multicentric, retrospective, case-control analysis was conducted on patients with clinical T1-2 N0 ALK-rearranged lung adenocarcinoma who underwent anatomical resection and radical lymphadenectomy. Data were collected from 5 high-volume oncological centres. An external cohort of ALK wild-type patients was also analysed for comparison. Survival analyses were performed using the Kaplan-Meier method, and multivariable Cox regression analysis was used to identify prognostic factors. RESULTS: From January 2016 to December 2022, 63 patients with ALK-rearranged lung adenocarcinoma were included. High-grade tumours (G3) significantly associated with upstaging (odds ratio = 3.904, P = 0.04). Disease-free survival (DFS) and overall survival were significantly improved in upstaged patients receiving adjuvant treatment [hazard ratio (HR) = 0.18, P = 0.0042; HR = 0.24, P = 0.0004, respectively]. The solid or micropapillary histological subtypes were independently associated with worse DFS (HR = 3.41, P = 0.022). Comparison with 435 ALK wild-type patients showed worse DFS in the ALK-rearranged group (HR = 2.09, P = 0.0003). ALK-rearranged patients had higher rates of nodal upstaging, systemic and brain recurrences. CONCLUSIONS: Clinical T1-2 N0 ALK-rearranged lung adenocarcinoma is an aggressive disease with a specific tropism for lymph nodes and the brain. High-grade tumours are predictive of nodal upstaging. Adjuvant treatment significantly improves DFS and overall survival in upstaged patients, highlighting the need for personalized preoperative staging and post-surgical management in this cohort.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".