Plasma D-Dimer Level Correlates with Age, Metastasis, Recurrence, Tumor-Node-Metastasis Classification (TNM), and Treatment of Non-Small-Cell Lung Cancer (NSCLC) Patients

Prognostic Significance of Pretreatment Plasma D-dimer Levels in EGFR-Positive Advanced Non-Small Cell Lung Cancer Patients Receiving Osimertinib: A Multicentre Retrospective Study

Purpose

This study examined the association between plasma D-dimer levels and overall survival (OS) in advanced non-small cell lung cancer (NSCLC) patients treated with osimertinib.

Methods

In this multicenter study, 88 patients with advanced non-small cell lung cancer (NSCLC) carrying epidermal growth factor receptor (EGFR) mutations and receiving osimertinib were enrolled. The target independent and dependent variables were the D-dimer levels before osimertinib treatment and OS time, respectively. The t-test or chi-square test was utilized to analyze the variances among various groups. The predictive significance of D-dimer for overall survival (OS) was assessed using Kaplan-Meier survival analysis and the Cox proportional hazard regression model.

Results

The selected patients had an average age of 58.01±10.72 years, with females comprising 54.55%. Based on their D-dimer levels, the patients were categorized into three groups: low-level (< 0.6 mg/L), middle-level (0.6 ~ 2 mg/L), and high-level (≥ 2 mg/L). After accounting for possible confounding variables, the Cox proportional hazard model showed that increased D-dimer levels were linked to a greater likelihood of death (HR 2.28, 95% CI = 1.09 ~ 4.76, p = 0.029). Importantly, there was a significant trend indicating that as D-dimer levels rose, the risk of mortality also increased (p for trend, HR 1.15, 95% CI = 1.03 ~ 1.28, p = 0.012). Consistently comparable outcomes were noted in the majority of subcategories. Patients with low-middle and high D dimer levels had a median OS of 28.6 and 17 months, respectively (p =0.014).

Conclusion

In conclusion, elevated levels of D-dimer in the bloodstream were found to have a significant negative correlation with the overall survival (OS) of patients with EGFR-positive non-small cell lung cancer (NSCLC) who underwent treatment with osimertinib.

Thromboelastography (TEG) parameters as potential predictors of malignancy and tumor progression in colorectal cancer

PURPOSE

The purpose of this study was to investigate the use of thromboelastography (TEG) in patients with colorectal cancer and to examine whether the TEG parameters can be used as potential markers for disease screening and prediction of disease severity.

METHODS

One-hundred fifteen healthy controls (HC), 43 patients with benign adenoma (BA), and 387 patients with colorectal cancers (CRC) were included in the study. TEG parameters (reaction time, R; clot kinetics, K; alpha angle, α-angle; maximum amplitude, MA), conventional laboratory parameters, and clinical information were collected and analyzed among the HC, BA, and CRC groups. Receiver operating characteristics (ROC) were used for differential analysis. The correlation between TEG parameters and pathological information of CRC (differentiation degree, vaso-nerve infiltration, TNM stage) was analyzed. The differences in TEG parameters at different stages of disease and pre-/post operation were compared.

RESULTS

Shorter K and higher α-angle/MA were found in patients with CRC compared with HC and BA (P < 0.001). TEG parameters demonstrated moderate diagnostic value (distinguish CRC from HC + BA: K-AUC = 0.693, α-angle-AUC = 0.687, MA-AUC = 0.700) in CRC but did not outperform traditional laboratory parameters. TEG hypercoagulability was closely associated with tumor markers (carcinoma embryonic antigen and carbohydrate antigen 19-9) and pathological information (differentiation degree, vaso-nerve infiltration, and TNM stage) (P < 0.05). Trend analysis showed that K decreased, but α-angle/MA increased gradually as the tumor progressed (P < 0.001). K- and α-angle showed slightly better sensitivity in predicting advanced tumors compared to traditional laboratory parameters. In CRC patients, 3-6 months after tumor resection, K [from 1.8 (1.5, 2.3) to 1.9 (1.6, 2.6)], α-angle [from 65.3 (59.0, 68.6) to 63.7 (56.6, 68.5)], and MA [from 61.0 (58.2, 66.0) to 58.9 (55.8, 61.3)] exhibited modest improvements compared to their preoperative values (P < 0.05).

CONCLUSION

TEG parameters possess moderate diagnostic value in CRC diagnosis and predicting advanced tumors, and they are closely linked to surgical interventions. Although TEG parameters do not significantly outperform traditional laboratory parameters, they still hold promise as potential alternative indicators in CRC patients.

The effectiveness of blood-activating and stasis-transforming traditional Chinese medicines (BAST) in lung cancer progression-a comprehensive review

ETHNOPHARMACOLOGICAL RELEVANCE

Blood-activating and stasis-transforming traditional Chinese medicines (BAST) are a class of herbs that have the effect of dilating blood vessels and dispersing stagnation. Modern pharmaceutical research has demonstrated that they are capable of improving hemodynamics and micro-flow, resist thrombosis and promote blood flow. BAST contain numerous active ingredients, which can theoretically regulate multiple targets at the same time and have a wide range of pharmacological effects in the treatment of diseases including human cancers. Clinically, BAST have minimal side effects and can be used in combination with Western medicine to improve patients' quality of life, lessen adverse effects and minimize the risk of recurrence and metastasis of cancers.

AIM OF THE REVIEW

We aimed to summarize the research progression of BAST on lung cancer in the past five years and present a prospect for the future. Particularly, this review further analyzes the effects and molecular mechanisms that BAST inhibit the invasion and metastasis of lung cancer.

MATERIALS AND METHODS

Relevant studies about BSAT were collected from PubMed and Web of science.

RESULTS

Lung cancer is one of the malignant tumors with the highest mortality rate. Most patients with lung cancer are diagnosed at an advanced stage and are highly susceptible to metastasis. Recent studies have shown that BAST, a class of traditional Chinese medicine (TCM) with the function of opening veins and dispersing blood stasis, significantly improve hemodynamics and microcirculation, prevent thrombosis and promote blood flow, and thereby inhibiting the invasion and metastasis of lung cancer. In the current review, we analyzed 51 active ingredients extracted from BAST. It was found that BAST and their active ingredients contribute to the prevention of invasion and metastasis of lung cancer through multiple mechanisms, such as regulation of EMT process, specific signaling pathway and metastasis-related genes, tumor blood vessel formation, immune microenvironment and inflammatory response of tumors.

CONCLUSIONS

BSAT and its active ingredients have showed promising anticancer activity and significantly inhibit the invasion and metastasis of lung cancer. A growing number of studies have realized their potential clinical significance in the therapy of lung cancer, which will provide substantial evidences for the development of new TCM for lung cancer therapy.

Construction of a mortality risk prediction model for elderly people at risk of lobectomy for NSCLC

Background

An increasing number of lung cancer patients are opting for lobectomy for oncological treatment. However, due to the unique organismal condition of elderly patients, their short-term postoperative mortality is significantly higher than that of non-elderly patients. Therefore, there is a need to develop a personalised predictive tool to assess the risk of postoperative mortality in elderly patients.

Methods

Information on the diagnosis and survival of 35,411 older patients with confirmed lobectomy NSCLC from 2009 to 2019 was screened from the SEER database. The surgical group was divided into a high-risk mortality population group (≤90 days) and a non-high-risk mortality population group using a 90-day criterion. Survival curves were plotted using the Kaplan-Meier method to compare the differences in overall survival (OS) and lung cancer-specific survival (LCSS) between the two groups. The data set was split into modelling and validation groups in a ratio of 7.5:2.5, and model risk predictors of postoperative death in elderly patients with NSCLC were screened using univariate and multifactorial logistic regression. Columnar plots were constructed for model visualisation, and the area under the subject operating characteristic curve (AUC), DCA decision curve and clinical impact curve were used to assess model predictiveness and clinical utility.

Results

Multi-factor logistic regression results showed that sex, age, race, histology and grade were independent predictors of the risk of postoperative death in elderly patients with NSCLC. The above factors were imported into R software to construct a line graph model for predicting the risk of postoperative death in elderly patients with NSCLC. The AUCs of the modelling and validation groups were 0.711 and 0.713 respectively, indicating that the model performed well in terms of predictive performance. The DCA decision curve and clinical impact curve showed that the model had a high net clinical benefit and was of clinical application.

Conclusion

The construction and validation of a predictive model for death within 90 days of lobectomy in elderly patients with lung cancer will help the clinic to identify high-risk groups and give timely intervention or adjust treatment decisions.

Construction and Validation of a Recurrent Risk Nomogram Model for Non-Small Cell Lung Cancer within 1 Year after Radical Resection

Objective

To explore the risk factors of recurrence within 1 year after radical resection of non-small cell lung cancer (NSCLC) and construct the nomogram model.

Methods

The clinical data of 186 patients with NSCLC treated with radical surgery in Affiliated Hospital of Youjiang Medical University for Nationalities of Baise were retrospectively analyzed. Multivariate logistic regression was applied to analyze the risk factors of recurrence within 1 year after radical resection of NSCLC. The R language (R 4.0.3 software package) was used in constructing the nomogram model, and the predictive value of the model was evaluated.

Results

The recurrence rate of 186 patients within 1 year after radical surgery was 29.57%. After multivariate logistic regression analysis, pathological stage, number of lymph node metastasis, chronic obstructive pulmonary disease (COPD), postoperative plasma D-dimer, and carcinoembryonic antigen were independent factors for recurrence within 1 year after radical resection of NSCLC (P < 0.05). Based on the above independent risk factors, a nomogram model was established, with the distinction of AUC = 0.891 (95% CI: 0.819–0.964) and sensitivity and specificity of 70.3% and 97.8%, respectively. The calibration curve was close to the ideal curve. External validation of the model showed AUC = 0.801 (95% CI: 0.674–0.928), and sensitivity and specificity were 66.7% and 84.2%, respectively.

Conclusion

The recurrence of NSCLC within 1 year after radical surgery was related to a variety of factors, and the nomogram model constructed based on risk factors had good goodness of fit, calibration, consistency of prediction, and prediction efficiency.

Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients

Background and Purpose

On the basis of the promising clinical study results, thoracic radiotherapy (TRT)¹ has become an integral part of treatment of synchronous oligometastatic non–small cell lung cancer (SOM-NSCLC). However, some of them experienced rapid disease progression after TRT and showed no significant survival benefit. How to screen out such patients is a more concerned problem at present. In this study, we developed a risk-prediction model by screening hematological and clinical data of patients with SOM-NSCLC and identified patients who would not benefit from TRT.

Materials and Methods

We investigated patients with SOM-NSCLC between 2011 and 2019. A formula named Risk-Total was constructed using factors screened by LASSO-Cox regression analysis. Stabilized inverse probability treatment weight analysis was used to match the clinical characteristics between TRT and non-TRT groups. The primary endpoint was overall survival (OS).

Results

We finally included 283 patients divided into two groups: 188 cases for the training cohort and 95 for the validation cohort. Ten prognostic factors included in the Risk-Total formula were age, N stage, T stage, adrenal metastasis, liver metastasis, sensitive mutation status, local treatment status to metastatic sites, systemic inflammatory index, CEA, and Cyfra211. Patients were divided into low- and high-risk groups based on risk scores, and TRT was found to have improved the OS of low-risk patients (46.4 vs. 31.7 months, P = 0.083; 34.1 vs. 25.9 months, P = 0.078) but not that of high-risk patients (14.9 vs. 11.7 months, P = 0.663; 19.4 vs. 18.6 months, P = 0.811) in the training and validation sets, respectively.

Conclusion

We developed a prediction model to help identify patients with SOM-NSCLC who would not benefit from TRT, and TRT could not improve the survival of high-risk patients.