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Introduction: The aim of the study was to analyze monosomal karyotype (MK) occurrence and the relationship between MKs and complex karyotypes (CKs) and to determine the prognostic significance of MKs in MDS patients based on conventional cytogenetic (CC) and fluorescence in situ hybridization (FISH) analyses. Methods: CC and FISH analyses were conducted for 216 primary MDS patients. Follow‐ups and statistical analysis were conducted. Results: A total of 25 (11.6%) patients with MKs were identified by FISH and CC analyses, and 23 (92%) of these MKs were also CKs. Only 19 patients (8.8%) with MKs were identified by CC analysis. Patients with MKs had higher bone marrow (BM) blast counts (P = 0.006), incidence of very high risk according to International Prognostic Scoring System‐Revised (IPSS‐R) (P < 0.001), leukemic transformation (P = 0.003,) and death rates (P < 0.001) than those without MKs. Overall survival (OS) and progression‐free survival (PFS) of MK or CK patients which were additionally detected by FISH and CC analyses had no statistical significance with those MK or CK patients detected by CC analyses separately. Multivariate analysis indicated that MK (P < 0.001), blast in BM (P < 0.001) and age (P = 0.028) were inferior independent prognostic factors in OS, whereas CK (P = 0.003) was the inferior independent prognostic factor in PFS. Conclusion: The MDS FISH panel may provide additional information for defining MKs beyond CC analysis. MK was an important indicator of OS in MDS patients, and CK indicated inferior disease progression but did not influence OS according to CC and FISH analyses. [ABSTRACT FROM AUTHOR]

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]