The prognostic value of circulating lymphocyte counts and ABO blood group in lung cancer stereotactic body radiation therapy: a retrospective study

Background: Clinically, there is a lack of simple and feasible indicators to predict the efficacy of stereotactic body radiation therapy (SBRT). Circulating lymphocyte counts (CLCs) is considered to be related to curative effect in conventional radiotherapy of lung cancer, and blood groups are also associated with the survival. In this study, we investigate the prognostic value of CLCs and ABO blood groups in lung cancer patients treated with SBRT. Methods: We retrospectively analyzed 191 patients who were treated with lung cancer SBRT in Taizhou Hospital of Zhejiang Province from September 2014 to December 2018. The medical record system of Taizhou Hospital was used to collect relevant clinical data, such as stage, CLC, ABO blood groups and other important clinical co-variates. The effects of SBRT were evaluated by patient reexamination image data and telephone follow-up. The RECIST 1.1 standard was used to evaluate the short-term efficacy in the first, third, and sixth months after SBRT. Progression-free survival (PFS) was defined as the time from the day of SBRT to disease progression or death from any cause. Overall survival (OS) was measured from the day of SBRT until the last follow-up or death. Survival curves and univariate, multivariate logistic-regression analyses were used to expound the prognostic factors for local control (LC), PFS, and OS of lung cancer SBRT patients. Results: Univariate and multivariate analysis results showed that post-SBRT CLCs were independent factors for the short-term efficacy 3 and 6 months after lung cancer SBRT [hazard ratio (HR) =0.249, P=0.037; HR =0.347, P=0.012]. Survival analyses showed that the PFS and OS of lung cancer SBRT patients with A blood type was significantly shorter than that in the other three non-A blood groups (PFS: 6.5 vs. 10 months, HR =1.535, P=0.020; OS: 24 vs. 41 months, HR =1.578, P=0.048). Moreover, the patients with high post-SBRT CLCs in the non-A blood group had the longest PFS and OS after lung cancer SBRT (HR =0.551, P=0.043). Conclusions: Lung cancer SBRT patients with high-post-SBRT CLCs and non-A blood groups seem to exhibits best curative effect, which represent a potential opportunity to improve the clinical management of these patients. The mechanisms of this association deserve further verification and investigation

Endostar acts as a pneumonitis protectant in patients with locally advanced non-small cell lung cancer receiving concurrent chemoradiotherapy

Abstract Background CCRT is presently the standard treatment for LA-NSCLC. RP is one of the main obstacles to the completion of thoracic radiation therapy, resulting in limited survival benefits in NSCLC patients. This research aims to explore the role of Endostar in the occurrence of grade≥2 RP and clinical curative effect in LA-NSCLC patients. Methods This study retrospectively analyzed 122 patients with stage III NSCLC who received CCRT from December 2008 to December 2017, or Endostar intravenous drip concurrently with chemoradiotherapy (Endostar + CCRT group). Standard toxicity of the pneumonitis endpoint was also collected by CTCAE V5.0. We further summarized other available studies on the role of Endostar in the prognosis of NSCLC patients and the incidence of RP. Results There were 76 cases in the CCRT group and 46 cases in the CCRT+ Endostar group. In the CCRT+ Endostar group, the occurrence of grade ≥2 RP in patients with V20Gy ≥25% was significantly higher than that in patients with V20Gy < 25% (p = 0.001). In the cohorts with V20Gy < 25%, 0 cases of 29 patients treated with Endostar developed grade ≥2 RP was lower than in the CCRT group (p = 0.026). The re-analysis of data from other available studies indicated that Endostar plus CCRT could be more efficient and safely in the occurrence of grade≥2 RP with LA-NSCLC. Conclusions When receiving CCRT for LA-NSCLC patients, simultaneous combination of Endostar is recommended to enhance clinical benefit and reduce pulmonary toxicity

Mining Personal Context-Aware Preferences for Mobile Users

Abstract—In this paper, we illustrate how to extract personal context-aware preferences from the context-rich device logs (i.e., context logs) for building novel personalized context-aware recommender systems. A critical challenge along this line is that the context log of each individual user may not contain sufficient data for mining his/her context-aware preferences. Therefore, we propose to first learn common context-aware preferences from the context logs of many users. Then, the preference of each user can be represented as a distribution of these common context-aware preferences. Specifically, we develop two approaches for mining common context-aware preferences based on two different assumptions, namely, con-text independent and context dependent assumptions, which can fit into different application scenarios. Finally, extensive experiments on a real-world data set show that both approaches are effective and outperform baselines with respect to mining personal context-aware preferences for mobile users

Predicting the Efficacy of SBRT for Lung Cancer with ¹⁸F-FDG PET/CT Radiogenomics

Purpose: to develop a radiogenomic model on the basis of 18F-FDG PET/CT radiomics and clinical-parameter EGFR for predicting PFS stratification in lung-cancer patients after SBRT treatment. Methods: A total of 123 patients with lung cancer who had undergone 18F-FDG PET/CT examination before SBRT from September 2014 to December 2021 were retrospectively analyzed. All patients’ PET/CT images were manually segmented, and the radiomic features were extracted. LASSO regression was used to select radiomic features. Logistic regression analysis was used to screen clinical features to establish the clinical EGFR model, and a radiogenomic model was constructed by combining radiomics and clinical EGFR. We used the receiver operating characteristic curve and calibration curve to assess the efficacy of the models. The decision curve and influence curve analysis were used to evaluate the clinical value of the models. The bootstrap method was used to validate the radiogenomic model, and the mean AUC was calculated to assess the model. Results: A total of 2042 radiomics features were extracted. Five radiomic features were related to the PFS stratification of lung-cancer patients with SBRT. T-stage and overall stages (TNM) were independent factors for predicting PFS stratification. AUCs under the ROC curve of the radiomics, clinical EGFR, and radiogenomic models were 0.84, 0.67, and 0.86, respectively. The calibration curve shows that the predicted value of the radiogenomic model was in good agreement with the actual value. The decision and influence curve showed that the model had high clinical application values. After Bootstrap validation, the mean AUC of the radiogenomic model was 0.850(95%CI 0.849–0.851). Conclusions: The radiogenomic model based on 18F-FDG PET/CT radiomics and clinical EGFR has good application value in predicting the PFS stratification of lung-cancer patients after SBRT treatment