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Published on: October 26, 2017
Prediction of high-risk factor in early-stage lung cancer: micropapillary adenocarcinoma
Linhui Yang1,2, Ping Zhou3, Jiarui Zhang1,2
1Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Objective:
To identify independent risk factors for micropapillary adenocarcinoma (MPA) in lung adenocarcinoma, a subtype often associated with poor prognosis, in order to support preoperative risk assessment and treatment planning.
Methods:
Patients diagnosed with lung adenocarcinoma were classified into the micropapillary adenocarcinoma (MPA) group or the non-MPA group based on pathological findings. Clinical, pathological, and imaging data were collected for both groups. Patients were followed up through outpatient visits or telephone interviews. The primary outcome was disease-free survival (DFS). Independent risk factors for MPA were identified using univariate and multivariate logistic regression analyses. A preoperative predictive model and corresponding nomogram were developed. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff value and the Hosmer-Lemeshow test and bootstrap - corrected calibration curves were used to evaluate the model's predictive performance.
Results:
The recurrence rate was significantly higher in the MPA group compared to the non-MPA group. Independent risk factors for MPA included smoking history, CT-diameter (≥22.5 mm), partially-solid nodule (PSN), solid nodule (SN), lobulation, spiculation, presence of vacuoles, and volume doubling time (VDT) (≤310 days). Guided by the multivariable analysis, we constructed a clinically oriented nomogram to provide an intuitive and practical tool for predicting MPA. The nomogram demonstrated excellent discrimination for predicting MPA, with an area under the ROC curve (AUC) of 0.923.
Conclusion:
MPA predicts worse prognosis. The developed nomogram provides improved stratification of patients and supports informed clinical management.
Insights
Micropapillary adenocarcinoma (MPA) in lung cancer is linked to higher recurrence. Key risk factors include smoking, nodule characteristics, and volume doubling time, aiding preoperative prediction.
Area of Science:
- Pulmonary Medicine
- Oncology
- Radiology
Background:
- Lung adenocarcinoma (LUAD) is a common cancer.
- Micropapillary adenocarcinoma (MPA) is a LUAD subtype with a poor prognosis.
- Accurate preoperative identification of MPA is crucial for treatment planning.
Purpose of the Study:
- To identify independent risk factors for MPA in LUAD.
- To develop a predictive model for MPA to aid in preoperative risk assessment.
- To support personalized treatment strategies for LUAD patients.
Main Methods:
- Classification of LUAD patients into MPA and non-MPA groups based on pathology.
- Collection and analysis of clinical, pathological, and imaging data.
- Development of a preoperative predictive nomogram using logistic regression and ROC analysis.
Main Results:
- MPA group showed significantly higher recurrence rates.
- Independent risk factors for MPA included smoking history, CT-diameter (≥22.5 mm), partially-solid nodule, solid nodule, lobulation, spiculation, vacuoles, and VDT (≤310 days).
- The developed nomogram demonstrated excellent predictive performance with an AUC of 0.923.
Conclusions:
- MPA is associated with a worse prognosis in LUAD.
- The developed nomogram is a valuable tool for predicting MPA preoperatively.
- Improved patient stratification and informed clinical management are facilitated by this predictive model.
