Preoperative assessment of lung cancer patients: Evaluating guideline compliance (re-audit)

A clinical-information-free method for early diagnosis of lung cancer from the patients with pulmonary nodules based on backpropagation neural network model

Lung cancer is the main cause of cancer-related deaths worldwide. Due to lack of obvious clinical symptoms in the early stage of the lung cancer, it is hard to distinguish between malignancy and pulmonary nodules. Understanding the immune responses in the early stage of malignant lung cancer patients may provide new insights for diagnosis. Here, using high-through-put sequencing, we obtained the TCRβ repertoires in the peripheral blood of 100 patients with Stage I lung cancer and 99 patients with benign pulmonary nodules. Our analysis revealed that the usage frequencies of TRBV, TRBJ genes, and V-J pairs and TCR diversities indicated by D50s, Shannon indexes, Simpson indexes, and the frequencies of the largest TCR clone in the malignant samples were significantly different from those in the benign samples. Furthermore, reduced TCR diversities were correlated with the size of pulmonary nodules. Moreover, we built a backpropagation neural network model with no clinical information to identify lung cancer cases from patients with pulmonary nodules using 15 characteristic TCR clones. Based on the model, we have created a web server named "Lung Cancer Prediction" (LCP), which can be accessed at http://i.uestc.edu.cn/LCP/index.html.

The Application and Value of 3T Magnetic Resonance Imaging in the Display of Pulmonary Nodules

Objective

The aim of this study was to evaluate the sensitivity and accuracy of multi-sequence 3T magnetic resonance imaging (MRI) in the detection of different types of pulmonary nodules.

Methods

A total of 68 patients with pulmonary nodules identified using computed tomography (CT) subsequently underwent MRI. Using CT images with a slice thickness of 1 mm as the gold standard, the sensitivity of three MRI sequences in detecting different types of pulmonary nodules was calculated, and the image quality was also evaluated. Nodule types included solid nodules, ground glass nodules (GGN), and part-solid nodules (PSN). Statistical analyses of data were conducted using the software SPSS 21.0. The intra-class correlation coefficient was calculated in order to compare the consistency of nodule size in both MRI and CT.

Results

CT detected 188 pulmonary nodules in 68 patients, including 87 solid nodules and 101 sub-solid nodules, the latter comprising 46 PSNs and 55 GGNs. The average nodule diameter was approximately 7.7 mm. The sensitivity of MRI in detecting nodules ≥ 6 mm in diameter and those of > 8 mm in diameter was 92% and 100%, respectively, and the sequence with the highest detection rate was T2-BLADE. In relation to solid nodules, the sequence with the highest detection rate was T1 Star-VIBE, while the T2-BLADE sequence demonstrated the highest detection rate of sub-solid nodules. The image quality of the T1 Star-VIBE sequence was better than that of both the T2-HASTE and the T2-BLADE sequences. The consistency of CT and MRI sequences for nodule size was high with a consistency coefficient of 0.94–0.98.

Conclusion

The detection rate of MRI for nodules with a diameter of > 8 mm was 100%. The T2-BLADE sequence had the highest detection sensitivity. The sequence with the best image quality was the T1 Star-VIBE.

Surgical Compliance and Survival Outcomes for Patients with Stage T1-2 Non-Small-Cell Lung Cancer

Introduction

Our aim was to determine the relationship between surgical compliance and survival outcomes in patients with stage T1-2 non-small-cell lung cancer (NSCLC).

Methods

Patients with T1-2 NSCLC who were diagnosed between 2004 and 2015 were identified from the SEER database. Multivariate logistic regression was used to analyse factors associated with surgical compliance. Kaplan-Meier curves and Cox regression were used to analyse the effects of surgical compliance on overall survival (OS) and cancer-specific survival (CSS).

Results

Of the 221,704 eligible T1-2 NSCLC patients, 106,668 patients recommended surgery. Among them, 99,672 (93.4%) patients were surgical compliance group, and 6996 (6.6%) were surgical noncompliance group. Poor surgical compliance was associated with earlier diagnosis time, old age, male, black race, unmarried status, main bronchus site, poor grade/stage, and lower household income. Patients' compliance was an independent prognostic factor for OS and CSS of T1-2 NSCLC patients. Multivariate Cox regression showed that surgical noncompliance individuals showed lower OS (hazard ratio [HR] 2.494; 95% confidence interval [CI] 2.423-2.566, p < 0.001) and lower CSS (HR 2.877; 95% CI 2.782-2.974, p < 0.001) compared with surgical compliance patients. In addition, results in the non-surgical group were observed to be similar to those of the surgical noncompliance group.

Conclusion

We found that patients' compliance was an independent prognostic factor for survival in T1-2 NSCLC patients. Poor surgical compliance was associated with earlier diagnosis time, old age, male, black race, unmarried status, main bronchus site, poor grade/stage, and lower household income.