Primary lung signet-ring cell carcinoma: a national analysis
Bibliographic record
Abstract
Background: Primary lung signet-ring cell carcinoma (LSRCC) is a rare form of aggressive lung cancer whose clinical features remain inadequately discerned. The objective of this study was to evaluate the clinicopathological characteristics and independent prognostic factors of primary LSRCC. Methods: Overall survival (OS) of patients with LSRCC, lung adenocarcinoma (LAC), and lung mucinous adenocarcinoma (LMAC) in the National Cancer Database from 2004 to 2018 was evaluated using Kaplan-Meier and multivariable Cox proportional hazards modeling. Independent prognostic indicators for patients with LSRCC were determined using multivariable Cox proportional hazards analysis. Results: A total of 1,705 LSRCC, 504,006 LAC, and 15,883 LMAC patients were included in our analysis. LSRCC histology was significantly associated with younger age, male sex, larger and more poorly differentiated tumors, later American Joint Committee on Cancer (AJCC) stage disease, higher clinical T, N, and M status, more use of chemotherapy, and less use of surgery when compared to LAC and LMAC patients. In unadjusted analysis, patients with LSRCC had significantly worse OS when compared to patients with LAC and LMAC. In multivariable analysis, patients with LSRCC experienced significantly worse OS when compared to only patients with LAC. Independent predictors of survival for patients with LSRCC were younger age, later year of diagnosis, lower Charlson/Deyo comorbidity condition scores, lower AJCC stage, higher income, smaller tumors, treatment with surgery, and receipt of chemotherapy. Conclusions: In this national analysis, LSRCC was found to be associated with distinct clinicopathological characteristics from those of LAC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".