Literature DB >> 35873847

Risk Factors Associated with Malignant Transformation of Astrocytoma: Competing Risk Regression Analysis.

Thara Tunthanathip1, Surasak Sangkhathat2,3, Kanet Kanjanapradit4.   

Abstract

Background  Malignant transformation (MT) of low-grade astrocytoma (LGA) triggers a poor prognosis in benign tumors. Currently, factors associated with MT of LGA have been inconclusive. The present study aims to explore the risk factors predicting LGA progressively differentiated to malignant astrocytoma. Methods  The study design was a retrospective cohort study of medical record reviews of patients with LGA. Using the Fire and Gray method, the competing risk regression analysis was performed to identify factors associated with MT, using both univariate and multivariable analyses. Hence, the survival curves of the cumulative incidence of MT of each covariate were constructed following the final model. Results  Ninety patients with LGA were included in the analysis, and MT was observed in 14.4% of cases in the present study. For MT, 53.8% of patients with MT transformed to glioblastoma, while 46.2% differentiated to anaplastic astrocytoma. Factors associated with MT included supratentorial tumor (subdistribution hazard ratio [SHR] 4.54, 95% confidence interval [CI] 1.08-19.10), midline shift > 1 cm (SHR 8.25, 95% CI 2.18-31.21), and nontotal resection as follows: subtotal resection (SHR 5.35, 95% CI 1.07-26.82), partial resection (SHR 10.90, 95% CI 3.13-37.90), and biopsy (SHR 11.10, 95% CI 2.88-42.52). Conclusion  MT in patients with LGA significantly changed the natural history of the disease to an unfavorable prognosis. Analysis of patients' clinical characteristics from the present study identified supratentorial LGA, a midline shift more than 1 cm, and extent of resection as risk factors associated with MT. The more extent of resection would significantly help to decrease tumor burden and MT. In addition, future molecular research efforts are warranted to explain the pathogenesis of MT. Asian Congress of Neurological Surgeons. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Entities:  

Keywords:  diffuse astrocytoma; high-grade glioma; low-grade glioma; malignant transformation

Year:  2022        PMID: 35873847      PMCID: PMC9298577          DOI: 10.1055/s-0042-1748789

Source DB:  PubMed          Journal:  Asian J Neurosurg


Introduction

Astrocytomas are divided into four grades based on the 2016 World Health Organization (WHO) central nervous system (CNS) tumor classification. These tumors are usually categorized as low-grade (LGAs) and high-grade astrocytomas. LGAs, including pilocytic astrocytoma (WHO I) and diffuse astrocytoma (WHO II), are benign tumors that have a prognosis significantly longer than high-grade tumors. The median survival time of diffuse astrocytoma ranges from 44 to 57 months, while anaplastic astrocytoma (WHO III) and glioblastoma prognosis (WHO IV) had a median survival time ranging from 15 to 24 months and 11 to 14 months, respectively. 1 2 3 Malignant transformation (MT) of low-grade gliomas, including fibrillary astrocytoma, diffuse astrocytoma, oligodendroglioma, mixed oligoastrocytoma, and ganglioglioma, has been reported in 19.5 to 21% cases. 4 5 6 7 In addition, Broniscer et al revealed the 10-year cumulative incidence of MT was 3.8%, and the median time of MT was 5.1 years. 7 Although the pathogenesis of MT has been unknown, factors associated with this rare event have been reported. Murphy et al reported older age, male gender, multiple tumors, chemotherapy alone, and the extent of resection were potential predictors of MT, whereas common genetic profiling of MT was TP53 overexpression, deletions of RB1 , CDKN2A , and PTEN pathway abnormalities. 6 7 However, the heterogeneity of the study population was observed from previous studies. Oligodendroglioma, mixed oligoastrocytoma, and other gliomas were included in the study. 4 5 6 7 In addition, benign tumors can develop to malignancy when patients have to wait for long-term follow-ups. If death occurs before MT during the follow-up period, the MT rate will be changed from another competing event. 8 From this concept, we performed a competing risk regression to evaluate clinical characteristics associated with MT in LGA patients.

Materials and Methods

Study Population

According to the primary objective, the sample size was calculated using the log-rank test formula. 9 Using data from the study of Murphy et al, 6 total resection was significantly associated with MT (hazard ratio [HR] 0.47, 95% confidence interval [95% CI] 0.31–0.72) and proportion of total resection group was found in 34.9%. Therefore, these parameters were performed for sample size estimation at α of 0.05 and β of 0.2 via Web-based calculator. 10 The sample size comprised at least 61 patients for testing the hypothesis. The study was conducted with a medical record review and included all patients newly diagnosed with pilocytic astrocytoma and diffuse astrocytoma between January 2003 and December 2018 in the tertiary hospital of southern Thailand. Some patients were part of the multicenter CNS tumor registry of Thailand, which was published and had the endpoint of study with death. 1 The histological diagnosis was confirmed by a pathologist, according to the 2016 WHO classification of CNS tumors. 11 The exclusion criteria were as follows: patients with mixed oligoastrocytoma or other gliomas and unavailable imaging. Moreover, patients who obtained tissue for diagnosis by free-hand biopsy or ultrasound-guided biopsy were excluded, whereas patients with a stereotactic biopsy were not excluded in the present study. Preoperative, postoperative, and follow-up magnetic resonance imaging (MRI) were reviewed by a neurosurgeon, such as tumor size, location, side, and midline shift. Moreover, a tumor volume calculation was performed based on a prior study of Tunthanathip and Madteng. 12 The extent of resection was assessed from postoperative imaging and was divided into four groups as follows: total resection (no visible residual tumor both enhanced and unenhanced portions), subtotal resection (≥ 90% of resection), partial resection (> 50% of resection), and biopsy (< 5%). 13 14 In our institute, the postoperative MRIs were routinely performed every 3 to 6 months for the follow-up purpose. We assess each visit's outcome according to the revised Response Evaluation Criteria in Solid Tumors guidelines (version 1.1). In detail, progressive disease was defined as an increased size of tumors of at least 20%, the absolute growth of tumors of at least 5 mm, or the appearance of one or more new lesions. 15 MT was defined as a tumor progressively differentiated to high-grade astrocytoma with histology-confirmed evidence of at least WHO III astrocytoma. 4 5 6 7 Besides, patients' death status was assessed from the Office of Central Civil-Registration on June 30, 2020. A human research ethics committee approved the present study. The present study did not require informed consent from patients because the study design was the retrospective approach. Besides, the patients' identification numbers were encoded before analysis.

Statistical Analysis

The endpoint of the study was the MT from which the starting date was the date of diagnosis of LGA and the endpoint of the study was the date of histology-confirmed diagnosis of MT by a pathologist or until June 2020 as the exiting date. Descriptive statistics were used for describing the baseline characteristics of the patients. Kaplan–Meier curve and log-rank test were performed for comparing prognosis between the MT group and non-MT group. Using Cox regression analysis, the effect of MT on survival time was analyzed and reported as a HR with 95% CI. Using Nelson–Aalen estimator, nonparametric test was performed to describe MT's overall cumulative hazard rate function. Because death is another event that affects the rate at which MT events occur, we use Fine and Gray's competing risk regression analysis to assess the risk associated with MT. 16 17 The subdistribution HR (SHR) was used instead of HR to report MT's risk in both univariate and multivariable analyses. For fitting the model, candidate variables that had a p -value of 0.1 or less in univariate analysis were analyzed in a multivariable model with backward stepwise selection. The proposed model was considered by the Akaike information criterion (AIC). After fitting the model, each covariate's survival curve was plotted for estimating the cumulative incidence of MT in each covariate. 18 19 Statistical analysis was performed using Stata v16 (StataCorp, Texas, United States, SN 401606310234).

Results

Initially, 101 patients who were newly diagnosed with LGA were reviewed. Eleven patients were excluded with unavailable imaging and final diagnosis of mixed glioma. Therefore, 90 patients were analyzed, and baseline clinical characteristics were summarized, as shown in Table 1 .
Table 1

Baseline characteristics of patients newly diagnosed low-grade astrocytoma ( N  = 90)

FactorN (%)
Gender
 Male47 (52.2)
 Female43 (47.8)
Mean age, year (SD)35.7 (19.3)
Signs and symptoms
 Seizure46 (51.1)
 Progressive headache37 (41.1)
 Weakness20 (22.2)
 Visual disturbance9 (10.0)
 Ataxia6 (6.7)
 Behavior change1 (1.1)
Preoperative Karnofsky Performance Status score
 < 8028 (31.1)
 ≥ 8062 (68.9)
Location
 Frontal lobe33 (36.7)
 Temporal lobe16 (17.8)
 Corpus callosum10 (11.1)
 Cerebellum9 (10.0)
 Sellar/suprasellar area6 (6.7)
 Parietal lobe4 (4.4)
 Brainstem3 (3.3)
 Basal ganglion3 (3.3)
 Thalamus3 (3.3)
 Occipital lobe1 (1.1)
 Periventricular area1 (1.1)
 Pineal gland1 (1.1)
Site of tumor
 Left33 (36.7)
 Right33 (36.7)
 Midline22 (24.4)
 Bilateral sites (for multiple lesions)2 (2.2)
Mean maximum diameter of tumor, cm (SD)5.5 (2.0)
Mean tumor volume, cm 3 (SD) 58.0 (48.0)
Eloquent area35 (38.9)
Preoperative hydrocephalus24 (26.7)
Preoperative leptomeningeal dissemination5 (5.6)
Preoperative multiple lesions4 (4.4)
Mean preoperative midline shift, cm (SD)4 (4.4)
Extent of resection
 Total resection13 (14.4)
 Subtotal resection17 (18.9)
 Partial resection26 (28.9)
 Stereotactic biopsy34 (37.8)
Postoperative radiotherapy58 (64.4)
Postoperative chemotherapy
 No87 (95.6)
 Temozolomide2 (2.2)
 Vincristine and cyclophosphamide2 (2.2)
Postoperative Karnofsky Performance Status score
 < 8036 (40.0)
 ≥ 8054 (60.0)
Histology of the first diagnosis
 Pilocytic astrocytoma14 (15.6)
 Diffuse astrocytoma72 (80.0)
 Gemistocytic astrocytoma2 (2.2)
 Pleomorphic xanthoastrocytoma2 (2.2)

Abbreviation: SD, standard deviation.

Abbreviation: SD, standard deviation. There were nearly equal proportions of males and females, 52.2 and 47.8%, respectively. Seizure, progressive headache, and hemiparesis were the first and third common clinical presentation of the eligible patients. The typical location of pilocytic astrocytoma was the cerebellum and suprasellar region of 7/14 (50.0%) and 5/14 (35.7%), while the frontal lobe, temporal lobe, and corpus callosum were the common location of diffuse astrocytoma in 32/72 (44.4%), 16/72 (22.2%), and 8 (11.1%), respectively. Moreover, 91% of astrocytoma with WHO grade II were in the supratentorial location, while more than half (58.1%) of WHO grade I astrocytoma were placed in the infratentorial location (chi-square test, p -value < 0.001). All eligible patients underwent an operation for histological diagnosis. Therefore, the first diagnosis was diffuse astrocytoma (80%), pilocytic astrocytoma (15.6%), gemistocytic astrocytoma (2.2%), and pleomorphic xanthoastrocytoma (2.2%). Total tumor resection was observed in 14.4%, and more than two-thirds of patients received postoperative adjuvant radiotherapy. Also, five patients received postoperative chemotherapy. MT occurred in 14.4% of the study population when the median time of follow-up was 20 months (interquartile range [IQR] 36 months), and median time of MT was 13 months (IQR 21.5 months). The clinical characteristics of patients who developed MT during the follow-up period are listed in Table 2 . More than half of MT was transformed into glioblastoma, whereas 46.2% of MT turned to anaplastic astrocytoma, as shown in Fig. 1A–F and Fig. 2A–D . Moreover, almost all patients with MT had never been exposed to radiotherapy before, and all of MT patients had never received adjuvant chemotherapy before MT.
Table 2

Characteristics of patients with malignant transformation ( N  = 13)

FactorN (%)
MT13/90 (14.4)
Progressive disease without MT36/90 (40.0)
Extent of resection at MT
 Subtotal resection6 (46.2)
 Partial resection6 (46.2)
 Biopsy1 (7.7)
History of exposure RT
 No12 (92.3)
 Radiotherapy before MT1 (7.7)
Histology at MT
 Anaplastic astrocytoma6 (46.2)
 Glioblastoma7 (53.8)

Abbreviations: MT, malignant transformation; RT, radiotherapy.

Fig. 1

Illustrative cases of malignant transformation of diffuse astrocytoma. ( A ) Preoperative T1W postcontrast magnetic resonance imaging (MRI) showing left frontal mass. ( B ) Hematoxylin and eosin (H&E) stain showing moderate cellularity with nuclear atypia of astrocytes. ( C ) T1W postcontrast MRI at 4 months later showing progressive left frontal mass with corpus callosum involvement. ( D ) H&E stain showing an anaplastic transformation, including astrocytes with pleomorphism. ( E ) T1W postcontrast MRI at 8 months later showing left frontal tumor crossing to the right side. ( F ) H&E stain showing glioblastoma multiforme (GBM) features, including hypercellularity of astrocytes and endothelial proliferation ( arrow ).

Fig. 2

Anaplastic transformation illustrative case of pilocytic astrocytoma. ( A ) Preoperative T1W postcontrast magnetic resonance imaging (MRI) showing an enhanced suprasellar mass. ( B ) Hematoxylin and eosin (H&E) stain showing astrocytic cells neoplastic astrocytes in the glial fibrillary background, with numerous Rosenthal fibers ( arrows ). ( C ) T1W postcontrast MRI at 3 years later showing the larger residual tumor. ( D ) H&E stain showing an anaplastic transformation, including increased cellularity and pleomorphism of tumor cells with multinucleated cells ( circle ) and mitoses ( arrows ).

Abbreviations: MT, malignant transformation; RT, radiotherapy. Illustrative cases of malignant transformation of diffuse astrocytoma. ( A ) Preoperative T1W postcontrast magnetic resonance imaging (MRI) showing left frontal mass. ( B ) Hematoxylin and eosin (H&E) stain showing moderate cellularity with nuclear atypia of astrocytes. ( C ) T1W postcontrast MRI at 4 months later showing progressive left frontal mass with corpus callosum involvement. ( D ) H&E stain showing an anaplastic transformation, including astrocytes with pleomorphism. ( E ) T1W postcontrast MRI at 8 months later showing left frontal tumor crossing to the right side. ( F ) H&E stain showing glioblastoma multiforme (GBM) features, including hypercellularity of astrocytes and endothelial proliferation ( arrow ). Anaplastic transformation illustrative case of pilocytic astrocytoma. ( A ) Preoperative T1W postcontrast magnetic resonance imaging (MRI) showing an enhanced suprasellar mass. ( B ) Hematoxylin and eosin (H&E) stain showing astrocytic cells neoplastic astrocytes in the glial fibrillary background, with numerous Rosenthal fibers ( arrows ). ( C ) T1W postcontrast MRI at 3 years later showing the larger residual tumor. ( D ) H&E stain showing an anaplastic transformation, including increased cellularity and pleomorphism of tumor cells with multinucleated cells ( circle ) and mitoses ( arrows ). As shown in Fig. 3 , MT of LGA was significantly associated with poor prognosis (log-rank test, p  = 0.006). The median survival time of patients without MT was 78 months (95% CI: 55.2–100.7), whereas patients with MT had a median survival time of 32.0 months (95% CI: 11.3–52.6). Using Cox regression analysis, MT significantly affected shortening survival time with HR of 2.46 (95% CI: 1.26–4.80, p -value 0.008).
Fig. 3

Kaplan–Meier curve showing malignant transformation group had a significantly poorer prognosis than nonmalignant transformation (log-rank test, p  = 0.006).

Kaplan–Meier curve showing malignant transformation group had a significantly poorer prognosis than nonmalignant transformation (log-rank test, p  = 0.006). MT was the failure event in the present study that is likely to occur over time, as shown in Fig. 4A . Patients with LGA risk to MT were 8.2% in 1-year probability, and the 2-year risk of MT in patients was 16.6%. The MT risk was steady at 19.4% when patients were followed-up in the third year, as shown in Table 3 .
Fig. 4

Survival curve of the cumulative incidence of malignant transformation (MT) for each factor. ( A ) Nelson–Aalen estimator of the cumulative hazard function. ( B ) Supratentorial tumor. ( C ) Midline shift on preoperative imaging. ( D ) The extent of resection.

Table 3

Risk of malignant transformation in patients with low-grade astrocytoma overtime

Follow-up time (mo)Proportion of risk to malignant transformation (95% CI)
 128.2% (3.7–1.8)
 2416.1% (8.7–31.4)
 3619.7% (10.6–36.7)
 4819.7% (10.6–36.7)
 6019.7% (10.6–36.7)

Abbreviation: CI, confidence interval.

Survival curve of the cumulative incidence of malignant transformation (MT) for each factor. ( A ) Nelson–Aalen estimator of the cumulative hazard function. ( B ) Supratentorial tumor. ( C ) Midline shift on preoperative imaging. ( D ) The extent of resection. Abbreviation: CI, confidence interval.

Factor Associated with MT by the Competing Risk Regression Analysis

Various clinical factors were analyzed in the univariate analysis by competing risk regression. Significant factors comprised supratentorial tumor (SHR 7.68, 95% CI: 1.78–33.1), midline shift of more than 1 cm from preoperative imaging (SHR 10.29, 95% CI: 2.89–35.67), and nontotal resection as follows: subtotal resection (SHR 12.51, 95% CI: 2.59–60.44), partial resection (SHR 21.20, 95% CI: 7.02–64.27), and biopsy (SHR 16.57, 95% CI: 4.68–58.40). In addition, tumors with WHO grade II tended to risk MT. For multivariable analysis, candidate factors were analyzed with backward stepwise selection. The model which had the least AIC comprised supratentorial tumor (SHR 4.54, 95% CI: 1.08–19.10), midline shift of more than 1 cm from preoperative imaging (SHR 8.25, 95% CI: 2.18–31.21), and nontotal resection as follows: subtotal resection (SHR 5.35, 95% CI: 1.07–26.82), partial resection (SHR 10.90, 95% CI: 3.13–37.90), and biopsy (SHR 11.10, 95% CI: 2.88–42.52), as shown in Table 4 . Subsequently, the significant covariates in the model have constructed the survival curve for estimating the cumulative incidence of MT in each covariate, as shown in Fig. 4B–D .
Table 4

Univariate and multivariable analysis for malignant transformation of low-grade astrocytoma

FactorUnivariate analysisMultivariable analysis
SHR (95% CI)p -Value SHR (95% CI)p -Value
Age, y
  < 40Ref
 ≥ 400.75 (0.24–2.34)0.62
Gender
 MaleRef
 Female1.22 (0.41–3.57)0.36
Seizure
 NoRef
 Yes0.55 (1.87–1.61)0.27
Preoperative KPS
 < 80Ref
 ≥ 801.03 (0.33–3.20)0.95
Location
 Frontal lobe a 2.46 (0.81–7.43)0.12
 Temporal lobe a 0.73 (0.17–3.01)0.67
 Corpus callosum a 2.19 (0.45–10.66)0.32
 Eloquent area a 0.88 (0.29–2.63)0.82
 Sellar/suprasellar area a 1.44 (0.22–9.29)0.69
 Supratentorial tumor a 7.68 (1.78–33.1)< 0.0014.54 (1.08–19.10)< 0.001
WHO grade I a 0.54 (0.06–4.23)0.101.14 (0.10–12.92)0.91
Midline shift, cm
 0–0.50RefRef
 0.51–1.001.39 (0.34–5.57)0.631.18 (0.30–4.53)0.80
 > 1.0010.29 (2.89–35.67)< 0.0018.25 (2.18–31.21)0.002
Extent of resection
 Total resectionRefRef
 Subtotal resection12.51 (2.59–60.44)0.0015.35 (1.07–26.82)< 0.001
 Partial resection21.20 (7.02–64.27)0.00110.90 (3.13–37.90)< 0.001
 Biopsy16.57 (4.68–58.40)0.00111.10 (2.88–42.52)< 0.001
Postoperative RT a 1.03 (0.31–3.36)0.96
Postoperative KPS
 < 80Ref
 ≥ 800.51 (0.06–3.96)0.52

Abbreviations: CI, confidence interval; KPS: Karnofsky Performance Status; RT, radiotherapy; SHR, subdistribution hazard ratio; WHO, World Health Organization.

Data show only “yes group” while reference groups (no group) are hidden.

Abbreviations: CI, confidence interval; KPS: Karnofsky Performance Status; RT, radiotherapy; SHR, subdistribution hazard ratio; WHO, World Health Organization. Data show only “yes group” while reference groups (no group) are hidden.

Discussion

MT of LGA is the process by which benign astrocytes turn malignant. When MT developed, the prognosis of patients with LGA accelerated downward and had a significantly shorter survival time than the non-MT group. In the present study, MT of LGA developed in 14.4%, and the median time to MT was 13 months. The results in the present study were in concordance with prior studies. The incidence of MT in low-grade gliomas has been reported in 3.8 to 21%, 6 7 and Chaichana et al reported the median latency of MT ranging from 13 to 66 months. 4 However, various methodologies and definitions from prior studies were observed in the literature review. Heterogeneity of low-grade gliomas such as fibrillary astrocytoma, oligodendroglioma, and mixed glioma may be an influence on MT rate and time to MT, whereas the study population of the present study was focused on astrocytoma. In addition, MT in prior publications included both histology-confirmed MT and imaging characteristic MT, 6 whereas MT in the present study excluded cases without a histological diagnosis. Clinical predictors associated with MT in the present study were observed as follows: supratentorial LGA, a preoperative midline shift of more than 1 cm, and extent of resection. Supratentorial astrocytoma was significantly prone toward MT, these may be related to the WHO grading of LGA. Although the WHO grading was not significantly associated with MT, LGA with WHO grade II tended to be MT's risk factor. Chaichana et al reported that fibrillary astrocytoma, which is WHO grade II, according to the 2007 CNS tumor classification, was significantly associated with MT. 4 Midline shift of more than 1 cm was one of the predictors of MT in the present study. As the author's knowledge, this factor has never been reported as a MT predictor, but several studies observed greater tumor size or volume were associated with MT. 4 20 21 Peritumoral edema has been reported as a typical finding of malignant gliomas and contributed as a prognostic factor. 22 These regions promote tumor cell invasion from the blood–brain barrier impairment that may be the mechanism of MT. 23 24 Therefore, our findings that a midline shift of more than 1 cm increased the risk of MT should be further explored with a larger cohort or meta-analysis in the future. The extent of resection has been considered as a predictor associated with MT in previous studies. Kiliç et al and Murphy et al reported that total tumor resection were risk factors of MT. Total tumor resection is the critical factor that modified the patient's prognosis and MT event because residual tumors could transform over time. 6 25 Moreover, total tumor resection has broadly been known as a prognostic factor for increased survival time. 26 27 28 When patients develop the event of death competing MT event, the probability of MT will be directly interfered. Hence, the new survival analysis concept has been published in several neurosurgical conditions such as meningioma, metastases, and cerebral aneurysms. 29 30 31 Additionally, multiple lesions of low-grade glioma were reported as a preventative factor of MT. 6 The findings may be an effect from competing events of patients with multiple lesions associated with poor prognosis. 32 33 Several variables have been reported as MT predictors, but these are still inconclusive. Tom et al reported that males were associated with MT, while females were a risk factor of MT in the study of Murphy et al. Furthermore, older age was reported as related to MT, 6 whereas Rotariu et al observed that MT frequently was found in younger patients. 34 Although the present study is the first article proposing MT predictors of LGA to the authors' knowledge by Fine and Gray's method, several limitations of the study should be acknowledged. First, the biopsy procedure may cause inadequate tissue diagnosis of MT. We managed this bias by eliminating cases that underwent nonstereotactic biopsy. However, the stereotactic biopsy was accepted in the present study because this procedure has been accepted to take adequate tissue for diagnosis in prior studies. 6 18 35 Secondly, the study design may lead to bias from retrospective studies. However, the prospective study also has limitations by conducting to explore predictors of MT. Because MT does not frequently occur with time-consuming differentiations, a longitudinal follow-up is needed in prospective cohort study design. We used the multivariable analysis to adjust the results and confounders. 36 Moreover, the propensity score approach and meta-analysis are alternative ways to explore focused interventions or predictors. 36 37 38 Third, the present study reported that only clinical predictors of MT and genetic investigation should be conducted. From molecular findings, the pathogenesis of MT has been discovered and explains clinical predictors. Glioma with wild-type IDH was associated with MT in the study of Tom et al, 20 while Broniscer et al studied nine tissue samples of MT and found that the common molecular pathways of MT were TP53 overexpression, alteration of PTEN, RB1 , and CDKN2A . 7 Moreover, Park et al studied in three MT patients with IDH1 -mutated gliomas using next-generation sequencing technology which found an altered genetic expression in U2AF2, TCF12, and ARID1A. 39

Conclusion

MT in patients with LGA significantly changed the natural history of the disease to an unfavorable prognosis. Supratentorial LGA, a midline shift of more than 1 cm, and the extent of resection as risk factors associated with MT. Particularly total tumor resection, the more extent of resection would significantly help to decrease tumor burden and MT. In addition, future molecular research efforts are warranted to explain the pathogenesis of MT.
  31 in total

1.  The assessment of prognostic factors in surgical treatment of low-grade gliomas: a prospective study.

Authors:  Krzysztof Majchrzak; Wojciech Kaspera; Barbara Bobek-Billewicz; Anna Hebda; Gabriela Stasik-Pres; Henryk Majchrzak; Piotr Ładziński
Journal:  Clin Neurol Neurosurg       Date:  2012-03-17       Impact factor: 1.876

2.  Malignant Transformation of Molecularly Classified Adult Low-Grade Glioma.

Authors:  Martin C Tom; Deborah Y J Park; Kailin Yang; C Marc Leyrer; Wei Wei; Xuefei Jia; Vamsi Varra; Jennifer S Yu; Samuel T Chao; Ehsan H Balagamwala; John H Suh; Michael A Vogelbaum; Gene H Barnett; Richard A Prayson; Glen H J Stevens; David M Peereboom; Manmeet S Ahluwalia; Erin S Murphy
Journal:  Int J Radiat Oncol Biol Phys       Date:  2019-08-25       Impact factor: 7.038

3.  How definitive treatment affects the rupture rate of unruptured cerebral aneurysms: a competing risk survival analysis.

Authors:  Toshikazu Kimura; Chikayuki Ochiai; Kensuke Kawai; Akio Morita; Nobuhito Saito
Journal:  J Neurosurg       Date:  2019-03-08       Impact factor: 5.115

4.  Sample-size formula for the proportional-hazards regression model.

Authors:  D A Schoenfeld
Journal:  Biometrics       Date:  1983-06       Impact factor: 2.571

5.  Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma.

Authors:  Roger Stupp; Warren P Mason; Martin J van den Bent; Michael Weller; Barbara Fisher; Martin J B Taphoorn; Karl Belanger; Alba A Brandes; Christine Marosi; Ulrich Bogdahn; Jürgen Curschmann; Robert C Janzer; Samuel K Ludwin; Thierry Gorlia; Anouk Allgeier; Denis Lacombe; J Gregory Cairncross; Elizabeth Eisenhauer; René O Mirimanoff
Journal:  N Engl J Med       Date:  2005-03-10       Impact factor: 91.245

6.  Free survival time of recurrence and malignant transformation and associated factors in patients with supratentorial low-grade gliomas.

Authors:  Ittichai Sakarunchai; Rassamee Sangthong; Nakornchai Phuenpathom; Monlika Phukaoloun
Journal:  J Med Assoc Thai       Date:  2013-12

7.  The clinical characteristics and prognostic factors of multiple lesions in glioblastomas.

Authors:  Thara Tunthanathip; Surasak Sangkhathat; Pimwara Tanvejsilp; Kanet Kanjanapradit
Journal:  Clin Neurol Neurosurg       Date:  2020-05-07       Impact factor: 1.876

8.  Recurrence and malignant degeneration after resection of adult hemispheric low-grade gliomas.

Authors:  Kaisorn L Chaichana; Matthew J McGirt; John Laterra; Alessandro Olivi; Alfredo Quiñones-Hinojosa
Journal:  J Neurosurg       Date:  2010-01       Impact factor: 5.115

9.  Multiple glioblastomas: Are they different from their solitary counterparts?

Authors:  Gajendra Singh; Anant Mehrotra; Jayesh Sardhara; Kuntal K Das; Janmejay Jamdar; Lily Pal; Arun K Srivastava; Rabi N Sahu; Awadhesh K Jaiswal; Sanjay Behari
Journal:  Asian J Neurosurg       Date:  2015 Oct-Dec

10.  Recurrence patterns after maximal surgical resection and postoperative radiotherapy in anaplastic gliomas according to the new 2016 WHO classification.

Authors:  Jung Ho Im; Je Beom Hong; Se Hoon Kim; Junjeong Choi; Jong Hee Chang; Jaeho Cho; Chang-Ok Suh
Journal:  Sci Rep       Date:  2018-01-15       Impact factor: 4.379

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