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Background: The overall survival (OS) for patients with recurrent glioma is meager. Also, the effect of radionecrosis and prognostic factors for recurrent glioma remains controversial. In this regard, developing effective predictive models and guiding clinical care is crucial for these patients. Methods: We screened patients with recurrent glioma after radiotherapy and those who received surgery between August 1, 2013, and December 31, 2020. Univariate and multivariate Cox regression analyses determined the independent prognostic factors affecting the prognosis of recurrent glioma. Moreover, nomograms were constructed to predict recurrent glioma risk and prognosis. Statistical methods were used to determine the prediction accuracy and discriminability of the nomogram prediction model based on the area under the curve (AUC), the C-index, the decision curve analysis (DCA), and the calibration curve. In order to distinguish high-risk and low-risk groups for OS, the X-Tile and Kaplan-Meier (K-M) survival curves were employed, and the nomogram prediction model was further validated by the X-Tile and K-M survival curves. Results: According to a Cox regression analysis, independent prognostic factors of recurrent glioma after radiotherapy with radionecrosis were World Health Organization (WHO) grade and gliosis percentage. We utilized a nomogram prediction model to analyze results visually. The C-index was 0.682 (95% CI: 0.616–0.748). According to receiver operating characteristic (ROC) analysis, calibration plots, and DCA, the nomogram prediction model was found to have a high-performance ability, and all patients were divided into low-risk and high-risk groups based on OS (P <.001). Conclusion: WHO grade and gliosis percentage are prognostic factors for recurrent glioma with radionecrosis, and a nomogram prediction model was established based on these two variables. Patients could be divided into high- and low-risk groups with different OS by this model, and it will provide individualized clinical decisions for future treatment. [ABSTRACT FROM AUTHOR]

Introduction: The prognosis of acute lymphoblastic leukemia (ALL) in adolescents and adults is poor, and recurrence is an important cause of their death. Changes of genetic information play a vital role in the pathogenesis and recurrence of ALL; however, the impact of molecular genetic mutations on disease diagnosis and prognosis remains unexplored. This study aimed to explore the frequency spectrum of gene mutations and their prognostic significance, along with the minimal residual disease (MRD) level and hematopoietic stem cell transplantation (HSCT), in adolescent and adult patients aged ≥15 years with ALL. Methods: The basic characteristics, cytogenetics, molecular genetics, MRD level, treatment regimen, and survival outcome of patients with untreated ALL (≥15 years) were collected, and the correlation and survival analysis were performed using the SPSS 25.0 and R software. Results: This study included 404 patients, of which 147 were selected for next-generation sequencing (NGS). NGS results revealed that 91.2% of the patients had at least one mutation, and 67.35% had multiple (≥2) mutations. NOTCH1, PHF6, RUNX1, PTEN, JAK3, TET2, and JAK1 were the most common mutations in T-ALL, whereas FAT1, TET2, NARS, KMT2D, FLT3, and RELN were the most common mutations in B-ALL. Correlation analysis revealed the mutation patterns, which were significantly different between T-ALL and B-ALL. In the prognostic analysis of 107 patients with B-ALL, multivariate analysis showed that the number of mutations ≥5 was an independent risk factor for overall survival and the RELN mutation was an independent poor prognostic factor for event-free survival. Discussion: The distribution of gene mutations and the co-occurrence and repulsion of mutant genes in patients with ALL were closely related to the immunophenotype of the patients. The number of mutations ≥5 and the RELN mutation were significantly associated with poor prognosis in adolescent and adult patients with ALL. [ABSTRACT FROM AUTHOR]