E-ISSN: 1019-5157
ISSN: 2651-5024
Research
NOMOGRAM FOR PREDICTING SURVIVAL OF GRADE 4 DIFFUSE GLIOMAS
Hui Liu✉ ,
Lun Peng ,
Zhao Jihu ,
Sun Peng
DOI: 10.5137/1019-5149.JTN.47174-24.2
Article in Press
Corresponding Author:
Hui Liu (forever860722@163.com)
Abstract
Aim
Grade 4 diffuse gliomas is a highly malignant tumor with considerable health implications. Studies have investigated the immunohistochemical molecules associated with glioblastoma development. However, grade 4 diffuse gliomas in Ki-67 positive patients have not been conclusively investigated.
Material and Methods
We retrospectively extracted data for 146 patients with Ki-67 positive grade 4 diffuse gliomas. The data were analyzed using the R software. Statistically significant indicators were identified by COX regression analysis and used to establish the nomogram. The nomogram was corrected by C-index, area under the curve (AUC), calibration curve and decision curve analyses (DCA). Finally, the model was externally validated using the Chinese Glioma Genome Atlas (CGGA) database.
Results
Age, treatment and IDH were found to be significant. The models C-index was 0.743 while the area under the curve (AUC) value of the time-dependent ROC curve at 3- and 6-months were 0.832 and 0.829, respectively. These findings imply a good discriminatory ability. Finally, a nomogram was constructed and validated using validation and DCA curves.
Conclusion
Three risk factors (age, treatment and IDH) were identified to be independent prognostic factors in Ki-67 positive grade 4 diffuse gliomas patients. The model can be used to accurately assess the disease-specific survival rates of these patients and inform on treatment options.
Grade 4 diffuse gliomas is a highly malignant tumor with considerable health implications. Studies have investigated the immunohistochemical molecules associated with glioblastoma development. However, grade 4 diffuse gliomas in Ki-67 positive patients have not been conclusively investigated.
Material and Methods
We retrospectively extracted data for 146 patients with Ki-67 positive grade 4 diffuse gliomas. The data were analyzed using the R software. Statistically significant indicators were identified by COX regression analysis and used to establish the nomogram. The nomogram was corrected by C-index, area under the curve (AUC), calibration curve and decision curve analyses (DCA). Finally, the model was externally validated using the Chinese Glioma Genome Atlas (CGGA) database.
Results
Age, treatment and IDH were found to be significant. The models C-index was 0.743 while the area under the curve (AUC) value of the time-dependent ROC curve at 3- and 6-months were 0.832 and 0.829, respectively. These findings imply a good discriminatory ability. Finally, a nomogram was constructed and validated using validation and DCA curves.
Conclusion
Three risk factors (age, treatment and IDH) were identified to be independent prognostic factors in Ki-67 positive grade 4 diffuse gliomas patients. The model can be used to accurately assess the disease-specific survival rates of these patients and inform on treatment options.
Keywords
grade 4 diffuse gliomas
Ki-67 positive
nomogram
survival
the time-dependent receiver operating characteristic (ROC)