Risk assessment in relation to the detection of small pulmonary nodules

Impact of surgery versus follow-up on psychological distress in patients with indeterminate pulmonary nodules: A prospective observational study

PURPOSE

To investigate whether surgery is more effective than follow-up in reducing psychological distress for patients with observable indeterminate pulmonary nodules (IPNs) and to assess if psychological distress can serve as a potential surgical indication for IPNs.

METHODS

This prospective observational study included 341 patients with abnormal psychometric results, as measured by the Hospital Anxiety and Depression Scale (HADS). Of these, 262 patients opted for follow-up and 79 chose surgery. Initial psychological assessments (HADS1) were conducted at enrollment following nodule detection, with a second assessment (HADS2) one year later. A comparative analysis of dynamic psychological changes (ΔHADS: HADS2-HADS1) between the follow-up and surgical groups was performed.

RESULTS

Both groups showed reductions in HADS-A [- 3 (IQR, - 7 to - 1) for follow-up and - 3 (IQR, - 6 to - 1) for surgery] and HADS-D scores [- 2 (IQR, - 4 to 0) for follow-up and - 3 (IQR, - 7 to 0) for surgery]. Univariate analysis revealed that the surgical group had a significantly greater reduction in HADS-D scores compared to the follow-up group (Z = - 2.08, P = 0.037), but there were no significant differences in the changes in HADS-A scores between the groups (Z = - 1.04, P = 0.300). However, in multivariable analysis, surgery did not significantly improve the alleviation of depressive symptoms compared to follow-up (β = - 0.72, 95% CI: - 1.57 to 0.14, P = 0.101). Within the surgical group, female patients reported less relief from anxiety than male patients (Z = - 2.32, P = 0.021), and symptomatic patients experienced less relief from both anxiety (Z = - 2.14, P = 0.032) and depression (Z = - 3.01, P = 0.003).

CONCLUSIONS

Surgery does not provide additional psychological benefits over follow-up. This study does not support using psychological distress as a criterion for surgical intervention in IPNs from a psychological perspective. Trial registry ClinicalTrials.gov (NCT04857333).

An artificial intelligence-assisted diagnostic system for the prediction of benignity and malignancy of pulmonary nodules and its practical value for patients with different clinical characteristics

Objectives

This study aimed to explore the value of an artificial intelligence (AI)-assisted diagnostic system in the prediction of pulmonary nodules.

Methods

The AI system was able to make predictions of benign or malignant nodules. 260 cases of solitary pulmonary nodules (SPNs) were divided into 173 malignant cases and 87 benign cases based on the surgical pathological diagnosis. A stratified data analysis was applied to compare the diagnostic effectiveness of the AI system to distinguish between the subgroups with different clinical characteristics.

Results

The accuracy of AI system in judging benignity and malignancy of the nodules was 75.77% (p < 0.05). We created an ROC curve by calculating the true positive rate (TPR) and the false positive rate (FPR) at different threshold values, and the AUC was 0.755. Results of the stratified analysis were as follows. (1) By nodule position: the AUC was 0.677, 0.758, 0.744, 0.982, and 0.725, respectively, for the nodules in the left upper lobe, left lower lobe, right upper lobe, right middle lobe, and right lower lobe. (2) By nodule size: the AUC was 0.778, 0.771, and 0.686, respectively, for the nodules measuring 5-10, 10-20, and 20-30 mm in diameter. (3) The predictive accuracy was higher for the subsolid pulmonary nodules than for the solid ones (80.54 vs. 66.67%).

Conclusion

The AI system can be applied to assist in the prediction of benign and malignant pulmonary nodules. It can provide a valuable reference, especially for the diagnosis of subsolid nodules and small nodules measuring 5-10 mm in diameter.

Advances in liquid biopsy-based markers in NSCLC

Lung cancer is the second most-frequently occurring cancer and the leading cause of cancer-associated deaths worldwide. Non-small cell lung cancer (NSCLC), the most common type of lung cancer is often diagnosed in middle or advanced stages and have poor prognosis. Diagnosis of disease at an early stage is a key factor for improving prognosis and reducing mortality, whereas, the currently used diagnostic tools are not sufficiently sensitive for early-stage NSCLC. The emergence of liquid biopsy has ushered in a new era of diagnosis and management of cancers, including NSCLC, since analysis of circulating tumor-derived components, such as cell-free DNA (cfDNA), circulating tumor cells (CTCs), cell-free RNAs (cfRNAs), exosomes, tumor-educated platelets (TEPs), proteins, and metabolites in blood or other biofluids can enable early cancer detection, treatment selection, therapy monitoring and prognosis assessment. There have been great advances in liquid biopsy of NSCLC in the past few years. Hence, this chapter introduces the latest advances on the clinical application of cfDNA, CTCs, cfRNAs and exosomes, with a particular focus on their application as early markers in the diagnosis, treatment and prognosis of NSCLC.

Lung cancer-associated T cell repertoire as potential biomarker for early detection of stage I lung cancer

BACKGROUND

Early detection of lung cancer in asymptomatic patients remains challenging, especially for stage I. Considering the substantial interaction with tumor immunogenicity, we hypothesized that lung cancer-associated TCR (LC-aTCR) may serve as potential biomarker in early detection of stage I lung cancer.

METHODS

Individuals who received low-dose computed tomography (LDCT) screening were enrolled in the study. Surgical tissues and peripheral blood specimens were collected and performed with DNA-based T cell repertoire (TCR) sequencing. The motif-based algorithm was used to deconstruct specific lung cancer-associated TCRs (LC-aTCRs).

RESULTS

A total of 146 individuals participating in the real-world LDCT screening project were enrolled in this study, including 52 patients with pathologically-confirmed stage I lung cancer and 94 non-cancer controls. We developed a motif-based algorithm to define 80 LC-aTCRs in the training cohort. Moreover, in the validation cohort, high sensitivity and specificity was showed in stage I lung cancer with 72% and 91% respectively, and the AUC of the ROC curve was 0.91 (95% CI: 0.85 ∼ 0.96).

CONCLUSION

This work provides inspiration for stage I lung cancer detection by using blood TCR profiling data. The combination of TCR-based assay and routine screening deserves further testing in larger cohorts.

Computed Tomography Scanning for Early Detection of Lung Cancer

Parallel and often unrelated developments in health care and technology have all been necessary to bring about early detection of lung cancer and the opportunity to decrease mortality from lung cancer through early detection of the disease by computed tomography. Lung cancer screening programs provide education for patients and clinicians, support smoking cessation as primary prevention for lung cancer, and facilitate health care for tobacco-associated diseases, including cardiovascular and chronic lung diseases. Guidelines for lung cancer screening will need to continue to evolve as additional risk factors and screening tests are developed. Data collection from lung cancer screening programs is vital to the further development of fiscally responsible guidelines to increase detection of lung cancer, which may include small groups with elevated risk for reasons other than tobacco exposure.

Prognostic indicators of pulmonary metastasis in patients with renal cell carcinoma who have undergone radical nephrectomy

The aim of the present study was to validate prognostic indicators of pulmonary metastasis in patients with renal cell carcinoma (RCC) that have undergone nephrectomy treatment. The data from 356 patients who underwent nephrectomy were investigated and subsequently divided into 2 groups, according to the pulmonary metastasis status. The risk factors for pulmonary metastasis were examined in all patients. In the subgroup analysis, the risk factors were additionally verified in patients with pulmonary nodules using univariate and multivariate logistic regression analyses. The status of pulmonary nodules and pulmonary metastasis were confirmed through preoperative chest radiography by two radiologists. Pulmonary metastasis was observed in 33 (9.3%) patients with a median follow-up time of 54.4 months (interquartile range, 38.8-71.8). Patients with pulmonary nodules indicated significantly increased rates of pulmonary metastasis, compared with patients without pulmonary nodules (24.2 vs. 6.1%; P<0.001). In multivariate analysis, the presence of pulmonary nodules [hazard ratio (HR)=3.15; P=0.0262], albumin (HR=0.42; P=0.0490) and pTstage (HR=3.63; P=0.0475) were indicated to be independent prognostic markers for pulmonary metastasis. In subgroup analysis, pTstage was the only independent prognostic indicator for pulmonary metastasis in these patients (HR=9.81; P=0.0033). In patients with RCC, the presence of pulmonary nodules was associated with pulmonary metastasis. Furthermore, pTstage is a negative prognostic indicator in patients with pulmonary nodules. Therefore, a chest radiologic short-term follow-up is required for these patients.

Methods of computed tomography screening and management of lung cancer in Tianjin: design of a population-based cohort study

Objective

European lung cancer screening studies using computed tomography (CT) have shown that a management protocol based on measuring lung nodule volume and volume doubling time (VDT) is more specific for early lung cancer detection than a diameter-based protocol. However, whether this also applies to a Chinese population is unclear. The aim of this study is to compare the diagnostic performance of a volume-based protocol with a diameter-based protocol for lung cancer detection and optimize the nodule management criteria for a Chinese population.

Methods

This study has a population-based, prospective cohort design and includes 4000 participants from the Hexi district of Tianjin, China. Participants will undergo low-dose chest CT at baseline and after 1 year. Initially, detected lung nodules will be evaluated for diameter and managed according to a routine diameter-based protocol (Clinical Practice Guideline in Oncology for Lung Cancer Screening, Version 2.2018). Subsequently, lung nodules will be evaluated for volume and management will be simulated according to a volume-based protocol and VDT (a European lung nodule management protocol). Participants will be followed up for 4 years to evaluate lung cancer incidence and mortality. The primary outcome is the diagnostic performance of the European volume-based protocol compared to diameter-based management regarding lung nodules detected using low-dose CT.

Results

The diagnostic performance of volume- and diameter-based management for lung nodules in a Chinese population will be estimated and compared.

Conclusions

Through the study, we expect to improve the management of lung nodules and early detection of lung cancer in Chinese populations.

Lung cancer risk to personalise annual and biennial follow-up computed tomography screening

BACKGROUND

All lung cancer CT screening trials used fixed follow-up intervals, which may not be optimal. We developed new lung cancer risk models for personalising screening intervals to 1 year or 2 years, and compared these with existing models.

METHODS

We included participants in the CT arm of the National Lung Screening Trial (2002-2010) who underwent a baseline scan and a first annual follow-up scan and were not diagnosed with lung cancer in the first year. True and false positives and the area under the curve of each model were calculated. Internal validation was performed using bootstrapping.

RESULTS

Data from 24 542 participants were included in the analysis. The accuracy was 0.785, 0.693, 0.697, 0.666 and 0.727 for the polynomial, patient characteristics, diameter, Patz and PanCan models, respectively. Of the 24 542 participants included, 174 (0.71%) were diagnosed with lung cancer between the first and the second annual follow-ups. Using the polynomial model, 2558 (10.4%, 95% CI 10.0% to 10.8%), 7544 (30.7%, 30.2% to 31.3%), 10 947 (44.6%, 44.0% to 45.2%), 16 710 (68.1%, 67.5% to 68.7%) and 20 023 (81.6%, 81.1% to 92.1%) of the 24 368 participants who did not develop lung cancer in the year following the first follow-up screening round could have safely skipped it, at the expense of delayed diagnosis of 0 (0.0%, 0.0% to 2.7%), 8 (4.6%, 2.2% to 9.2%), 17 (9.8%, 6.0% to 15.4%), 44 (25.3%, 19.2% to 32.5%) and 70 (40.2%, 33.0% to 47.9%) of the 174 lung cancers, respectively.

CONCLUSIONS

The polynomial model, using both patient characteristics and baseline scan morphology, was significantly superior in assigning participants to 1-year or 2-year screening intervals. Implementing personalised follow-up intervals would enable hundreds of participants to skip a screening round per lung cancer diagnosis delayed.