Co-Occurrence Patterns of Pathological High-Risk Factors and Predictive Value of PET Metabolic Features in Lung Adenocarcinoma: A Retrospective Cohort Study of 1292 Cases
- 1Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Abstract
Background/Objectives: Co-occurrence patterns among pathological high-risk factors in lung adenocarcinoma remain poorly characterized, and whether preoperative 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) predicts them is unsettled. We mapped their interrelationships and evaluated the predictive value of preoperative maximum standardized uptake value (SUVmax). Methods: We retrospectively enrolled 1292 consecutive patients with resected invasive lung adenocarcinoma (May 2020–September 2023) and extracted six high-risk factors: spread through air spaces (STAS), visceral pleural invasion (VPI), lymphovascular invasion (LVI), occult lymph node metastasis (OLNM), and solid and micropapillary components. Pairwise co-occurrence was quantified by the Phi coefficient with Bonferroni correction; logistic regression and receiver operating characteristic (ROC) analysis assessed the predictive value of SUVmax. High-risk burden was defined as ≥3 concurrent factors. Results: STAS (29.8%) and the micropapillary component (24.4%) were the most prevalent. All 15 pairwise associations were positive and significant after Bonferroni correction; the strongest enrichment was between LVI and OLNM (observed-to-expected [O/E] ratio 5.85, Phi = 0.41, p < 0.001), with no mutual exclusivity. SUVmax independently predicted all six factors (e.g., solid component, odds ratio [OR] 1.283; STAS, OR 1.225; micropapillary component, OR 1.141; all p < 0.001). For high-risk burden, SUVmax achieved an area under the curve (AUC) of 0.838, which was numerically higher than that for any individual factor. At a cut-off of 3.0, sensitivity was 86.8% and the negative predictive value was 96.8% (bootstrap 95% confidence interval [CI] 0.807–0.865). Conclusions: High-risk pathological factors co-occur rather than segregate. Preoperative SUVmax is independently associated with all six factors but is best positioned to identify high-risk burden rather than individual features, although a clinical benefit remains to be demonstrated.
Related
- Pathological high-risk feature count and survival outcomes in patients with stage I invasive lung adenocarcinoma (≤3 cm): a retrospective cohort study.
- Prediction of pathological complete response to neoadjuvant chemo-immunotherapy in locally advanced lung adenocarcinoma: a multimodal machine learning approach
- Advances in predictive factors for pathological complete response after neoadjuvant therapy in locally advanced rectal cancer
- Impact of postoperative chemotherapy in patients resected for esophagogastric adenocarcinoma with major pathological response after preoperative chemotherapy: a study from the FREGAT database
- Spread through air spaces (STAS) in stage I lung adenocarcinoma under the new IASLC/WHO pathological grading system: research progress on prognostic value-narrative review.
BibTeX
@article{leng2026cooccurrence,
title = {{Co-Occurrence Patterns of Pathological High-Risk Factors and Predictive Value of PET Metabolic Features in Lung Adenocarcinoma: A Retrospective Cohort Study of 1292 Cases}},
author = {Qiuyu Leng and Yu Huang and Bowen Zhao and Zuhan Geng and Chi Zhang and Yongde Liao},
journal = {Cancers},
year = {2026},
month = oct,
doi = {10.3390/cancers18213435},
url = {https://www.mdpi.com/2072-6694/18/21/3435},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Co-Occurrence Patterns of Pathological High-Risk Factors and Predictive Value of PET Metabolic Features in Lung Adenocarcinoma: A Retrospective Cohort Study of 1292 Cases
AU - Qiuyu Leng
AU - Yu Huang
AU - Bowen Zhao
AU - Zuhan Geng
AU - Chi Zhang
AU - Yongde Liao
PY - 2026
DA - 2026/10/23
JO - Cancers
DO - 10.3390/cancers18213435
UR - https://www.mdpi.com/2072-6694/18/21/3435
AB - Background/Objectives: Co-occurrence patterns among pathological high-risk factors in lung adenocarcinoma remain poorly characterized, and whether preoperative 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) predicts them is unsettled. We mapped their interrelationships and evaluated the predictive value of preoperative maximum standardized uptake value (SUVmax). Methods: We retrospectively enrolled 1292 consecutive patients with resected invasive lung adenocarcinoma (May 2020–September 2023) and extracted six high-risk factors: spread through air spaces (STAS), visceral pleural invasion (VPI), lymphovascular invasion (LVI), occult lymph node metastasis (OLNM), and solid and micropapillary components. Pairwise co-occurrence was quantified by the Phi coefficient with Bonferroni correction; logistic regression and receiver operating characteristic (ROC) analysis assessed the predictive value of SUVmax. High-risk burden was defined as ≥3 concurrent factors. Results: STAS (29.8%) and the micropapillary component (24.4%) were the most prevalent. All 15 pairwise associations were positive and significant after Bonferroni correction; the strongest enrichment was between LVI and OLNM (observed-to-expected [O/E] ratio 5.85, Phi = 0.41, p < 0.001), with no mutual exclusivity. SUVmax independently predicted all six factors (e.g., solid component, odds ratio [OR] 1.283; STAS, OR 1.225; micropapillary component, OR 1.141; all p < 0.001). For high-risk burden, SUVmax achieved an area under the curve (AUC) of 0.838, which was numerically higher than that for any individual factor. At a cut-off of 3.0, sensitivity was 86.8% and the negative predictive value was 96.8% (bootstrap 95% confidence interval [CI] 0.807–0.865). Conclusions: High-risk pathological factors co-occur rather than segregate. Preoperative SUVmax is independently associated with all six factors but is best positioned to identify high-risk burden rather than individual features, although a clinical benefit remains to be demonstrated.
SN - 2072-6694
ER -