The study aimed at evaluating the diagnostic accuracy of combining Virtual Touch Tissue Quantification (VTQ) results with chemokine expression levels of CXCL13 in the diagnosis of lung tumors. To ensure that the study was adequately powered to detect the hypothesized effects, a priori power analysis was performed. The priori power analysis involved estimating the effect size, determining the sample size required to achieve a desired level of statistical power, and selecting the appropriate statistical test.

The sample size was determined based on the number of patients with malignant pleural effusion (n=30) and the number of patients with benign thoracic nodules and pleural effusion (n=30). The desired level of statistical power was set at 0.8, meaning that the study had an 80% chance of detecting a significant difference between the two groups if such a difference existed. The effect size was estimated based on previous research studies that investigated the diagnostic accuracy of VTQ and CXCL13 expression levels in lung tumor diagnosis.

The statistical test used for the priori power analysis was the two-sample t-test, which is appropriate for comparing the means of two independent groups. The analysis was performed using a statistical software program, such as R or SAS, which allows for the calculation of sample size and power based on the desired effect size, significance level, and level of power.

The results of the priori power analysis determined the sample size required to achieve the desired level of statistical power and provided confidence in the study’s ability to detect a significant difference between the two groups if such a difference existed. By conducting the priori power analysis, the researchers were able to ensure that the study was designed to have sufficient statistical power to detect meaningful differences and reduce the risk of type II errors, or false negatives.

Thirty pleural effusion specimens were collected from newly diagnosed patients with pulmonary malignant tumors and pleural effusion. These patients were admitted to the 82nd Army Group Military Hospital and the Affiliated Hospital of Hebei University from November 2021 to July 2022 and all of the specimens showed the presence of tumor cells. The collection process was performed under sterile conditions, where 10 ml of pleural effusion was collected from each patient. The supernatant was then separated and collected after 10 minutes of centrifugation at 2000 rpm and 4°C. The collected supernatant was stored in -80°C in 1.5 ml eppendorf tubes until further treatment.

The pathological types of the specimens were classified according to the World Health Organization’s histological classification standards for malignant tumors and the staging was performed following the UICC eighth edition TNM staging system. The inclusion criteria for the specimens included the following:

The following laboratory equipment and supplies were used in this study:

The Siemens ACUSON S2000 color ultrasonic diagnostic instrument, equipped with VTQ (Virtual Touch Quantification) technology, was utilized in the investigation of lung tumors. A convex array probe was selected for the experiment, and the frequency was set to a range of 3.5-5 MHz. The patients were asked to remain seated in a quiet environment, and the VTQ function was activated to capture the relevant data.

To thoroughly examine the lung tumors, various parameters such as size, margins, internal parenchymal echoes, and blood flow were analyzed using the VTQ technology. A total of five successful measurements were taken, and to reduce the impact of outliers, the maximum and minimum values were removed. The average value of the remaining measurements was then calculated and recorded for statistical analysis.

In addition to the VTQ results, the expression level of chemokine CXCL13 was determined through ELISA (Enzyme-Linked Immunosorbent Assay). To obtain an accurate measurement, the pleural effusion specimens were taken out from the -80 oC freezer, thawed to room temperature, and analyzed. The relative expression of chemokine CXCL13 was determined through ELISA, which provides a quantitative measurement of the protein’s concentration in the sample. Figure 1 summarizes the workflow.

The statistical software SPSS19.0 was used to process the data collected in the study. The data was expressed in different ways depending on whether it followed a normal distribution or not. Measurement data that followed a normal distribution were expressed as the mean ± standard deviation ( ± s), while non-normally distributed data were presented as the median (interquartile range).

The non-parametric rank-sum test, also known as the Mann-Whitney Test, was used to compare two independent samples of non-normally distributed measurement data. Unlike the t-test, which assumes that the data follows a normal distribution, the Mann-Whitney Test does not make this assumption, making it a suitable test for comparing two samples of non-normally distributed data.

To examine the relationship between the relative expression level of the chemokine CXCL13 and various clinical characteristics in the non-small cell lung cancer (NSCLC) group, the Mann-Whitney Test was employed. The receiver operating characteristic (ROC) curve was used to determine the optimal diagnostic threshold and corresponding sensitivity and specificity of tumor markers in pleural effusion. The ROC curve plots the true positive rate against the false positive rate for various diagnostic thresholds, allowing for the selection of the threshold that provides the best balance between sensitivity and specificity.

The multivariate ROC was utilized to assess the significance of combined diagnoses based on two or more different indicators. This type of analysis allows for the evaluation of the combined diagnostic power of multiple markers, which may provide a more accurate diagnosis than relying on a single marker alone. A p-value of less than 0.05 was considered statistically significant, meaning that the results observed were unlikely to have occurred by chance.

Our study found that the relative expression levels of CXCL13 and the VTQ values in the lung cancer group were significantly higher compared to those in the control group (P < 0.05). Figure 2 displays the results of the VTQ measurements.

The differences between the two groups were analyzed and the results are presented in Table 2 . The table summarizes the mean values, standard deviations, and statistical significance of the differences in CXCL13 and VTQ values between the lung cancer group and the control group. By comparing these values, we can understand the relationship between the expression levels of CXCL13 and the VTQ results, and how they may be used as indicators of lung cancer.

In our study of the Non-Small Cell Lung Cancer (NSCLC) group, we aimed to examine the relationship between the relative expression level of CXCL13, a chemokine, and various clinical characteristics of the patients. To achieve this, we analyzed the expression levels of CXCL13 and compared them to the TNM staging and tumor differentiation of each patient. Our findings indicated that as the TNM staging of the cancer progressed, meaning the cancer became more advanced, and as the tumor differentiation worsened, meaning the cancer cells were becoming more abnormal, the expression level of CXCL13 increased. Furthermore, our results showed that the expression level of CXCL13 was higher in patients diagnosed with adenocarcinoma compared to those with squamous cell carcinoma. These findings suggest that the expression level of CXCL13 may play a role in the progression of NSCLC and can provide valuable information for understanding the underlying mechanisms of this type of cancer. All of these results are presented in Table 3 for easy reference and further analysis.

The performance of the two biomarkers was evaluated using receiver operating characteristic (ROC) curve analysis, which is a commonly used method to assess the diagnostic accuracy of biomarkers. The ROC curve plots the true positive rate against the false positive rate at various threshold values, and the area under the curve (AUC) provides a single measure of the diagnostic performance.

In this study, the AUC for CXCL13 in diagnosing lung tumors was found to be 0.74 (95% confidence interval [CI]: 0.61-0.86). This indicates that CXCL13 has a good ability to differentiate between patients with lung tumors and those without. The sensitivity and specificity of CXCL13 were 60% and 80%, respectively, which means that 60% of the lung tumor cases were correctly identified, and 80% of the non-tumor cases were correctly identified. The optimal cut-off value, which is the threshold value that provides the best balance between sensitivity and specificity, was found to be 777.82 pg/ml. Similarly, the AUC for VTQ in diagnosing lung tumors was found to be 0.67 (95% CI: 0.53-0.82). This indicates that VTQ also has good diagnostic performance. The sensitivity and specificity of VTQ were 60% and 83.3%, respectively, with an optimal diagnostic cut-off of 3.33 m/s. These results are shown in Figure 3 and Table 4 .

In conclusion, either the VTQ biomarker or the CXCL13 biomarker can serve as an effective individual diagnostic tool for lung tumors.

The study included 60 patients, with 30 cases of lung tumors complicated by malignant pleural effusion in the case group and 30 cases of benign pleural effusion in the control group. The gold standard for diagnosis was based on pathological examination, where malignant cases were coded as 1 and benign cases were coded as 0. Two indicators, VTQ and CXCL13, were measured in each patient and were represented as X1 and X2, respectively (where malignant cases were coded as 1, benign cases were coded as -1, and unknown cases were coded as 0). This is summarized in Table 5 .

SPSS was used to calculate the individual prediction rate (pre-1) of covariate X1 and the combination of both covariates X1 and X2 (pre-2). The ROC curve analysis was used to evaluate the performance of the variables (pre-1, pre-2) and state variables (group). The results showed that the AUC for covariate X1 (pre-1) in diagnosing malignant pleural effusion was 0.674 (95% confidence interval [CI]: 0.53-0.82). However, the combination of both covariates (pre-2) for the diagnosis of thoracic tumors had a much higher AUC of 0.842 (95% CI: 0.74-0.94). This result is summarised in Table 6 and Figure 4 .

In conclusion, the ROC curve analysis using SPSS demonstrated that the combination of VTQ and CXCL13 is a more effective diagnostic tool for lung tumors complicated by malignant pleural effusion compared to the use of either marker alone.

A posteriori power analysis was conducted to evaluate the sample size and statistical power of the study. The results of the study showed that both the expression levels of CXCL13 and VTQ were significantly higher in the lung cancer group compared to the control group (P < 0.05), which suggests that the sample size was sufficient to detect a significant difference between the two groups. However, a larger sample size may have increased the statistical power of the study and improved the precision of the results.

The ROC curve analysis of CXCL13 showed an AUC of 0.74 (0.61, 0.86) with an optimal cut-off value of 777.82 pg/ml, indicating that the test has moderate accuracy for diagnosing lung tumors. The ROC curve analysis of VTQ showed an AUC of 0.67 (0.53, 0.82) with a sensitivity of 60.0% and a specificity of 83.3%, which suggests that the test has limited accuracy for diagnosing lung tumors.

The combination of CXCL13 and VTQ for diagnosing thoracic tumors had an AUC of 0.842 (0.74, 0.94), which was significantly higher than either factor alone. This suggests that the combination of the two tests may be a more accurate tool for diagnosing lung tumors compared to using either test alone.

In conclusion, the sample size of the study was sufficient to detect a significant difference between the two groups, but a larger sample size may have increased the statistical power and precision of the results.