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Record W3042419526 · doi:10.3747/co.27.5899

Postoperative Radiotherapy Option Based on Mediastinal Lymph Node Reclassification for Patients with pN2 Non-small-Cell Lung Cancer

2020· article· en· W3042419526 on OpenAlexvenueno aff
J. Jin, Yaping Xu, Xiao Hu, M. Chen, Min Fang, Qin Hang

Bibliographic record

VenueCurrent Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineLung cancerMediastinal lymph nodeLymph nodePort (circuit theory)Radiation therapyMultivariate analysisUnivariate analysisLymphCancerMetastasisOncologyInternal medicineSurgeryPathology

Abstract

fetched live from OpenAlex

Background: In this research, we used the mediastinal lymph node reclassification proposed by the International Association for the Study of Lung Cancer (iaslc) to screen for patients with pathologic N2 (pN2) non-small-cell lung cancer (nsclc) who might benefit from postoperative radiotherapy (port). Methods: The study enrolled 440 patients with pN2 nsclc who received complete surgical resection and allocated them to one of three groups: N2a1 (single-station skip mediastinal lymph node metastasis), N2a2 (single-station non-skip mediastinal lymph node metastasis), and N2b (multi-station mediastinal lymph node metastasis). Rates of local recurrence at first recurrence in patients receiving and not receiving port were compared using the chi-square test. Overall (os) and disease-free survival (dfs) were then compared using Kaplan–Meier survival analysis with log-rank test. In addition, the factors potentially influencing os and dfs were analyzed using univariate and multivariate Cox regression. Results: The rate of local recurrence for the N2a2 and N2b groups was significantly lower in patients receiving port (p = 0.044 and p = 0.043 respectively). The log-rank test revealed that, for the N2a1 group, differences in os and dfs were not statistically significant between the patients who did and did not receive port (p = 0.304 and p = 0.197 respectively). For the N2a2 group, os and dfs were markedly superior in patients who received port compared with those who did not (p = 0.001 and p = 0.014 respectively). For the N2b group, os was evidently better in patients who received port compared with those who did not (p = 0.025), but no statistically significant difference in dfs was observed (p = 0.134). Multivariate regression analysis revealed that, in the N2a1 group, port was significantly associated with poor os [hazard ratio (hr): 2.618; 95% confidence interval (ci): 1.185 to 5.785; p = 0.017]; in the N2a2 group, port was associated with improved os (hr: 0.481; 95% ci: 0.314 to 0.736; p = 0.001) and dfs (hr: 0.685; 95% ci: 0.479 to 0.980; p = 0.039). Conclusions: For patients with pN2 nsclc who receive complete resection, port might be beneficial only for patients with single-station non-skip metastasis (N2a2). Patients with single-station skip metastasis (N2a1) and multi-station metastasis (N2b) might not currently benefit from port.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.062
GPT teacher head0.375
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2020
Admission routes1
Has abstractyes

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