Daniel Feucht, P. Haas, M. Skardelly, F. Behling, D. Rieger, Paula Bombach, F. Paulsen, E. Hoffmann, Till-Karsten Hauser, Benjamin Bender, M. Renovanz, Maximilian Niyazi, Ghazaleh Tabatabai, M. Tatagiba, Constantin Roder
{"title":"未经治疗的胶质母细胞瘤的术前生长动力学--指数生长类型的描述、相关因素以及与术后存活率的关系","authors":"Daniel Feucht, P. Haas, M. Skardelly, F. Behling, D. Rieger, Paula Bombach, F. Paulsen, E. Hoffmann, Till-Karsten Hauser, Benjamin Bender, M. Renovanz, Maximilian Niyazi, Ghazaleh Tabatabai, M. Tatagiba, Constantin Roder","doi":"10.1093/noajnl/vdae053","DOIUrl":null,"url":null,"abstract":"\n \n \n Little is known about growth dynamics of untreated glioblastoma and its possible influence on postoperative survival. Our aim was to analyze a possible association of preoperative growth dynamics with postoperative survival.\n \n \n \n We performed a retrospective analysis of all adult patients surgically treated for newly diagnosed glioblastoma at our center between 2010 and 2020. By volumetric analysis of data of patients with availability of ≥3 preoperative sequential MRI, a growth pattern was aimed to be identified. Main inclusion criterion for further analysis was the availability of two preoperative MRI scans with a slice thickness of 1mm, at least 7 days apart. Individual growth rates were calculated. Association with overall survival (OS) was examined multivariably.\n \n \n \n Out of 749 patients screened, thirteen had ≥3 preoperative MRI, 70 had two MRI and met the inclusion criteria.\n A curve estimation regression model showed best fit for exponential tumor growth.\n Median tumor volume doubling time (VDT) was 31 days, median specific growth rate (SGR) was 2.2% growth per day. SGR showed negative correlation with tumor size (rho=-0.59, p<0.001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log rank: p=0.010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox-regression model for patients after tumor resection.\n \n \n \n Especially small lesions suggestive for glioblastoma showed exponential tumor growth with variable growth rates and a median VDT of 31 days. SGR was significantly associated with OS in patients with tumor resection in our sample.\n","PeriodicalId":94157,"journal":{"name":"Neuro-oncology advances","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Preoperative growth dynamics of untreated glioblastoma – Description of an exponential growth-type, correlating factors and association with postoperative survival\",\"authors\":\"Daniel Feucht, P. Haas, M. Skardelly, F. Behling, D. Rieger, Paula Bombach, F. Paulsen, E. Hoffmann, Till-Karsten Hauser, Benjamin Bender, M. Renovanz, Maximilian Niyazi, Ghazaleh Tabatabai, M. Tatagiba, Constantin Roder\",\"doi\":\"10.1093/noajnl/vdae053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n Little is known about growth dynamics of untreated glioblastoma and its possible influence on postoperative survival. Our aim was to analyze a possible association of preoperative growth dynamics with postoperative survival.\\n \\n \\n \\n We performed a retrospective analysis of all adult patients surgically treated for newly diagnosed glioblastoma at our center between 2010 and 2020. By volumetric analysis of data of patients with availability of ≥3 preoperative sequential MRI, a growth pattern was aimed to be identified. Main inclusion criterion for further analysis was the availability of two preoperative MRI scans with a slice thickness of 1mm, at least 7 days apart. Individual growth rates were calculated. Association with overall survival (OS) was examined multivariably.\\n \\n \\n \\n Out of 749 patients screened, thirteen had ≥3 preoperative MRI, 70 had two MRI and met the inclusion criteria.\\n A curve estimation regression model showed best fit for exponential tumor growth.\\n Median tumor volume doubling time (VDT) was 31 days, median specific growth rate (SGR) was 2.2% growth per day. SGR showed negative correlation with tumor size (rho=-0.59, p<0.001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log rank: p=0.010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox-regression model for patients after tumor resection.\\n \\n \\n \\n Especially small lesions suggestive for glioblastoma showed exponential tumor growth with variable growth rates and a median VDT of 31 days. SGR was significantly associated with OS in patients with tumor resection in our sample.\\n\",\"PeriodicalId\":94157,\"journal\":{\"name\":\"Neuro-oncology advances\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuro-oncology advances\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.1093/noajnl/vdae053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuro-oncology advances","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1093/noajnl/vdae053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Preoperative growth dynamics of untreated glioblastoma – Description of an exponential growth-type, correlating factors and association with postoperative survival
Little is known about growth dynamics of untreated glioblastoma and its possible influence on postoperative survival. Our aim was to analyze a possible association of preoperative growth dynamics with postoperative survival.
We performed a retrospective analysis of all adult patients surgically treated for newly diagnosed glioblastoma at our center between 2010 and 2020. By volumetric analysis of data of patients with availability of ≥3 preoperative sequential MRI, a growth pattern was aimed to be identified. Main inclusion criterion for further analysis was the availability of two preoperative MRI scans with a slice thickness of 1mm, at least 7 days apart. Individual growth rates were calculated. Association with overall survival (OS) was examined multivariably.
Out of 749 patients screened, thirteen had ≥3 preoperative MRI, 70 had two MRI and met the inclusion criteria.
A curve estimation regression model showed best fit for exponential tumor growth.
Median tumor volume doubling time (VDT) was 31 days, median specific growth rate (SGR) was 2.2% growth per day. SGR showed negative correlation with tumor size (rho=-0.59, p<0.001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log rank: p=0.010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox-regression model for patients after tumor resection.
Especially small lesions suggestive for glioblastoma showed exponential tumor growth with variable growth rates and a median VDT of 31 days. SGR was significantly associated with OS in patients with tumor resection in our sample.