Can low-dose intravenous bevacizumab be as effective as high-dose bevacizumab for cerebral radiation necrosis?

Although intravenous bevacizumab (IVBEV) is the most promising treatment for cerebral radiation necrosis (CRN), there is no conclusion on the optimal dosage. Our retrospective study aimed to compare the efficacy and safety of high-dose with low-dose IVBEV in treating CRN associated with radiotherapy for brain metastases (BMs). This paper describes 75 patients who were diagnosed with CRN secondary to radiotherapy for BMs, treated with low-dose or high-dose IVBEV and followed up for a minimum of 6 months. The clinical data collected for this study include changes in brain MRI, clinical symptoms, and corticosteroid usage before, during, and after IVBEV treatment. At the 3-month mark following administration of IVBEV, a comparison of two groups revealed that the median percentage decreases in CRN volume on T2-weighted fluid-attenuated inversion recovery and T1-weighted gadolinium contrast-enhanced image (T1CE), as well as the signal ratio reduction on T1CE, were 65.8% versus 64.8% (p = 0.860), 41.2% versus 51.9% (p = 0.396), and 37.4% versus 35.1% (p = 0.271), respectively. Similarly, at 6 months post-IVBEV, the median percentage reductions of the aforementioned parameters were 59.5% versus 62.0% (p = 0.757), 39.1% versus 31.3% (p = 0.851), and 35.4% versus 28.2% (p = 0.083), respectively. Notably, the incidence of grade ≥3 adverse events was higher in the high-dose group (n = 4, 9.8%) than in the low-dose group (n = 0). Among patients with CRN secondary to radiotherapy for BMs, the administration of high-dose IVBEV did not demonstrate superiority over low-dose IVBEV. Moreover, the use of high-dose IVBEV was associated with a higher incidence of grade ≥3 adverse events compared with low-dose IVBEV.

A PET/CT radiomics model for predicting distant metastasis in early-stage non-small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study

OBJECTIVES

Stereotactic body radiotherapy (SBRT) is a treatment option for patients with early-stage non-small cell lung cancer (NSCLC) who are unfit for surgery. Some patients may experience distant metastasis. This study aimed to develop and validate a radiomics model for predicting distant metastasis in patients with early-stage NSCLC treated with SBRT.

METHODS

Patients at five institutions were enrolled in this study. Radiomics features were extracted based on the PET/CT images. After feature selection in the training set (from Tianjin), CT-based and PET-based radiomics signatures were built. Models based on CT and PET signatures were built and validated using external datasets (from Zhejiang, Zhengzhou, Shandong, and Shanghai). An integrated model that included CT and PET radiomic signatures was developed. The performance of the proposed model was evaluated in terms of its discrimination, calibration, and clinical utility. Multivariate logistic regression was used to calculate the probability of distant metastases. The cutoff value was obtained using the receiver operator characteristic curve (ROC), and the patients were divided into high- and low-risk groups. Kaplan-Meier analysis was used to evaluate the distant metastasis-free survival (DMFS) of different risk groups.

RESULTS

In total, 228 patients were enrolled. The median follow-up time was 31.4 (2.0-111.4) months. The model based on CT radiomics signatures had an area under the curve (AUC) of 0.819 in the training set (n = 139) and 0.786 in the external dataset (n = 89). The PET radiomics model had an AUC of 0.763 for the training set and 0.804 for the external dataset. The model combining CT and PET radiomics had an AUC of 0.835 for the training set and 0.819 for the external dataset. The combined model showed a moderate calibration and a positive net benefit. When the probability of distant metastasis was greater than 0.19, the patient was considered to be at high risk. The DMFS of patients with high- and low-risk was significantly stratified (P < 0.001).

CONCLUSIONS

The proposed PET/CT radiomics model can be used to predict distant metastasis in patients with early-stage NSCLC treated with SBRT and provide a reference for clinical decision-making. In this study, the model was established by combining CT and PET radiomics signatures in a moderate-quantity training cohort of early-stage NSCLC patients treated with SBRT and was successfully validated in independent cohorts. Physicians could use this easy-to-use model to assess the risk of distant metastasis after SBRT. Identifying subgroups of patients with different risk factors for distant metastasis is useful for guiding personalized treatment approaches.

Identification of Plasma Biomarkers in Drug-Naïve Schizophrenia Using Targeted Metabolomics

OBJECTIVE

Schizophrenia (SCZ) is a severe psychiatric disorder with unknown etiology and lacking specific biomarkers. Herein, we aimed to explore plasma biomarkers relevant to SCZ using targeted metabolomics.

METHODS

Sixty drug-naïve SCZ patients and 36 healthy controls were recruited. Psychotic symptoms were assessed using the Positive and Negative Syndrome Scale. We analyzed the levels of 271 metabolites in plasma samples from all subjects using targeted metabolomics, and identified metabolites that differed significantly between the two groups. Then we evaluated the diagnostic power of the metabolites based on receiver operating characteristic curves, and explored metabolites associated with the psychotic symptoms in SCZ patients.

RESULTS

Twenty-six metabolites showed significant differences between SCZ patients and healthy controls. Among them, 12 metabolites were phosphatidylcholines and cortisol, ceramide (d18:1/22:0), acetylcarnitine, and γ-aminobutyric acid, which could significantly distinguish SCZ from healthy controls with the area under the curve (AUC) above 0.7. Further, a panel consisting of the above 4 metabolites had an excellent performance with an AUC of 0.867. In SCZ patients, phosphatidylcholines were positively related with positive symptoms, and cholic acid was positively associated with negative symptoms.

CONCLUSION

Our study provides insights into the metabolite alterations associated with SCZ and potential biomarkers for its diagnosis and symptom severity assessment.