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Record W4409282773 · doi:10.3390/curroncol32040217

Low-Malignant-Potential Adenocarcinoma: A Histological Category with a Significantly Better Prognosis than Other Solid Adenocarcinomas at IA Stage

2025· article· en· W4409282773 on OpenAlexvenueno aff
Marco Chiappetta, Alessandra Cancellieri, Filippo Lococo, Elisa Meacci, Carolina Sassorossi, Maria Teresa Congedo, Qianqian Zhang, Diomira Tabacco, Isabella Sperduti, Stefano Margaritora

Bibliographic record

VenueCurrent Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdenocarcinomaStage (stratigraphy)LungCancerPathologyInternal medicineRadiology

Abstract

fetched live from OpenAlex

Introduction: Low-malignant-potential adenocarcinoma has been defined as a type of non-mucinous tumor, which has a total tumor size measuring ≤ 3 cm, exhibits ≥ 15% lepidic growth, lacks non-predominant high-grade patterns (≥10% cribriform, ≥5% micropapillary, ≥5% solid), has an absence of angiolymphatic or visceral pleural invasion, spread through air spaces (STAS), necrosis and >1 mitosis per 2 mm2. The aim of this study is to validate, with regard to cancer-specific survival (CSS) and disease-free survival (DFS), the proposed definition of LMP adenocarcinoma in an independent external cohort of lung adenocarcinoma patients having undergone surgical resection, and having presented with a long follow-up period. Methods: Clinicopathological characteristics of patients who underwent lung resection for adenocarcinoma from 1 January 2005 to 31 December 2014 were retrospectively analyzed. Patients with ground-glass opacity (GGO) and part-solid tumors, minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), tumors ≥5 cm in size, nodal involvement and/or distant metastases, patients who underwent neoadjuvant treatment, and those who had an incomplete follow-up or a follow-up shorter than 60 months were excluded. The proposed criteria for low-malignant-potential adenocarcinoma (LMPA) were tumor size ≤ 3 cm, invasive size ≥ 0,5 cm, lepidic growth ≥ 15%, and absence of the following: mitosis (>1 per 2 mm2), mucinous subtype, angiolymphatic invasion, visceral pleural invasion, spread through air spaces (STAS) and tumor necrosis. End points were disease-free survival (DFS) and cancer-specific survival (CSS). The log-rank test was used to assess differences between subgroups. Results: Out of 80 patients meeting the proposed criteria, 14 (17.5%) had the LMPA characteristics defined. The mean follow-up time was 67 ± 39 months. A total of 19 patients died, all in the non-LMPA category, and 33 patients experienced recurrence: 4 (28.5%) with LMPA and 29 (43.9%) with non-LMPA. Log-rank analysis showed 100% 10-year CSS for patients with LMPA and 77.4% for patients without LMPA, with this difference being statistically significant (p-value = 0.047). Univariate analysis showed a significant association with the cStage (AJCC eighth edition), both for CSS (p value = 0.005) and DFS (p-value = 0.003). LMPA classification did not show a statistically significant impact on CSS and DFS, likely due to the limited number of events (CSS p-value = 0.232 and DFS p-value = 0.213). No statistical association was found for CSS and DFS with pT, the number of resected nodes (< or >10) or the number of resected N2 stations (< or >2). Conclusions: Our study confirmed the prognostic role of LMPA features, with a low risk of recurrence and a good CSS and DFS. The criteria for diagnosis are replicable and feasible for application. The clinical implications of these findings, such as pre-operative prediction and surveillance scheduling, may be the topic of future prospective studies.

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)0.000
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.046
GPT teacher head0.354
Teacher spread0.308 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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