Browsing by Author "Meng, Yinnan"

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    Efficacy and Failure Patterns of Early SBRT to the Primary Tumor in Advanced EGFR-Mutation-Positive Lung Cancer with EFGR-TKI Treatment: A Prospective, Single Arm, Phase II Study
    (MDPI, 2022-11-22) Shi, Yangyang; Xu, Hailing; Raynor, William Y.; Ding, Jiapei; Lin, Ling; Zhou, Chao; Wang, Wei; Meng, Yinnan; Wu, Xiaomai; Chen, Xiaofeng; Lv, Dongqing; Yang, Haihua; Radiation Oncology, School of Medicine
    Early stereotactic body radiation therapy (SBRT) to the primary tumor combined with epidermal growth factor receptor tyrosine kinase inhibitor (EFGR-TKI) treatment may increase progression-free survival (PFS) by delaying resistance in patients with advanced EGFR-mutant non-small cell lung cancer (NSCLC). In this prospective, single arm, phase II study, patients with advanced NSCLC were treated with EGFR-TKI (icotinib 125 mg tid or gefitinib 250 mg qd) for one month followed by SBRT (40-60 Gy/5-8 F/5-10 d) to the primary tumor with concurrent EGFR-TKI until disease progression. The primary endpoint was PFS and the patterns of failure. Overall survival (OS) and adverse effects (AEs) were secondary endpoints. Overall, 41 advanced NSCLC patients with EGFR mutations received treatment with 24.42 months of median follow-up time. On average, SBRT was initiated 1.49 months after EGFR-TKI administration. Tumors were found to have an average shrinkage rate of 42.50%. Median PFS was 15.23 months (95% CI 13.10-17.36), while median OS was 27.57 months (95% CI 23.05-32.09). Thirty-three patients were found to have disease progression, of which new site failure (NF) (22 patients, 66.66%) was the most common pattern, followed by original site failure (OF) (7 patients, 21.21%) and simultaneous OF/NF (ONF) (4 patients, 12.12%). There were no Aes equal to or greater than grade 3, with the most frequent AE being radiation pneumonitis. Therefore, administering therapy targeted at the primary tumor using early SBRT after EGFR-TKI initiation is a new potentially safe and effective approach to treat EGFR-mutant advanced NSCLC.
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    Enhanced CT-Based Radiomics to Predict Micropapillary Pattern Within Lung Invasive Adenocarcinoma
    (Frontiers Media, 2021-08-27) Xu, Yunyu; Ji, Wenbin; Hou, Liqiao; Lin, Shuangxiang; Shi, Yangyang; Zhou, Chao; Meng, Yinnan; Wang, Wei; Chen, Xiaofeng; Wang, Meihao; Yang, Haihua; Radiation Oncology, School of Medicine
    Objective: We aimed to investigate whether enhanced CT-based radiomics can predict micropapillary pattern (MPP) of lung invasive adenocarcinoma (IAC) in the pre-op phase and to develop an individual diagnostic predictive model for MPP in IAC. Methods: 170 patients who underwent complete resection for pathologically confirmed lung IAC were included in our study. Of these 121 were used as a training cohort and the other 49 as a test cohort. Clinical features and enhanced CT images were collected and assessed. Quantitative CT analysis was performed based on feature types including first order, shape, gray-level co-occurrence matrix-based, gray-level size zone matrix-based, gray-level run length matrix-based, gray-level dependence matrix-based, neighboring gray tone difference matrix-based features and transform types including Log, wavelet and local binary pattern. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to value the ability to identify the lung IAC with MPP using these characteristics. Results: Using quantitative CT analysis, one thousand three hundred and seventeen radiomics features were deciphered from R (https://www.r-project.org/). Then these radiomic features were decreased to 14 features after dimension reduction using the least absolute shrinkage and selection operator (LASSO) method in R. After correlation analysis, 5 key features were obtained and used as signatures for predicting MPP within IAC. The individualized prediction model which included age, smoking, family tumor history and radiomics signature had better identification (AUC=0.739) in comparison with the model consisting only of radiomics features (AUC=0.722). DeLong test showed that the difference in AUC between the two models was statistically significant (P<0.01). Compared with the simple radiomics model, the more comprehensive individual prediction model has better prediction performance. Conclusion: The use of radiomics approach is of great value in the diagnosis of tumors by non-invasive means. The individualized prediction model in the study, when incorporated with age, smoking and radiomics signature, had effective predictive performance of lung IAC with MPP lesions. The combination of imaging features and clinical features can provide additional diagnostic value to identify the micropapillary pattern in IAC and can affect clinical diagnosis and treatment.
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    The prognostic value of circulating lymphocyte counts and ABO blood group in lung cancer stereotactic body radiation therapy: a retrospective study
    (AME, 2022) Chen, Meng; Chen, Kuifei; Li, Shuling; Meng, Yinnan; Shi, Yangyang; Chen, Xiaofeng; Yang, Haihua; Radiation Oncology, School of Medicine
    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.