The Geographical Deprivation Index is Independently Associated With All-Cause Long-Term Mortality in Resectable Lung Cancer
Bibliographic record
Abstract
OBJECTIVES: We aimed at assessing the relationships between social deprivation and survival of resectable lung cancer. METHODS: We performed (a) a nationwide study based on the Epithor project on patients undergoing surgery for lung cancer to assess the impact of the French Deprivation Index (FDI) of the department where surgery was performed on overall survival (OS); (b) an institutional study on consecutive patients referred to a single surgical centre to assess the impact of the FDI of the patients' department of residence on OS. Survival analyses were performed by Kaplan-Meier estimator, log-rank tests, and univariable and multivariable Cox analyses. For the national study, survival analysis was also adjusted for predicted mortality using a prognostic score validated in a previous Epithor study. RESULTS: In the nationwide study, including 54 500 patients, higher FDI (more disadvantaged) of Department where surgery was performed was associated with shorter long-term OS with an unadjusted hazard ratio (HR) of 1.10 (95% CI, 1.08-1.11) per unit increase in the Index, and a HR adjusted on predicted mortality of 1.14 (1.13-1.15). In the institutional study including 864 patients, a higher FDI of the patient's department of residence was associated with shorter long-term OS, with an unadjusted HR of 1.17 (1.08-1.26) per unit increase in the index, and a HR adjusted on usual confounders of 1.12 (1.03-1.22). In both studies, there was no evidence of a non-linear association between the index and mortality. CONCLUSIONS: Strategies to reduce territorial inequalities seem necessary to improve the outcome of resectable lung cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| 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".