Acute progression of untreated incidental WHO Grade II glioma to glioblastoma in an asymptomatic patient

WHO Grade II glioma (low-grade glioma [LGG]) is increasingly diagnosed as an incidental finding in patients undergoing MRI for many conditions. Recent data have demonstrated that such incidental LGGs are progressive tumors that undergo clinical transformation and ultimately become malignant. Although asymptomatic LGG seems to represent an earlier step in the natural course of a glioma than the symptomatic LGG, it is nonetheless impossible to predict at the individual level when the tumor will become malignant. The authors report the case of a 43-year-old woman with a right operculo-insular LGG that was incidentally diagnosed because of headaches. No treatment was proposed, and repeated MRI scans were performed for 6 years in another institution. Due to a slow but continuous growth of the lesion, the patient was finally referred to our center to undergo surgery. Interestingly, objective calculation of the velocity of the tumor’s diametric expansion demonstrated a sudden acceleration of the growth rate within the 5 months preceding surgery, with the development of contrast enhancement. Remarkably, the patient was still asymptomatic. An awake resection was performed with intraoperative electrical mapping. There was no functional worsening following surgery, as assessed on postoperative neuropsychological examination. Removal of 92% of signal abnormality on FLAIR MRI was achieved, with complete resection of the area of contrast enhancement. Neuropathological examination revealed a glioblastoma, and the patient was subsequently treated with concomitant radiotherapy and chemotherapy. Although a “wait and see” attitude has been advocated by some authors with respect to incidental LGG, our original case demonstrates that acute transformation to glioblastoma may nonetheless occur, even before the onset of any symptoms. Therefore, because the lack of symptoms does not protect from malignant transformation, we propose consideration of earlier resection in a more systematic manner in cases of incidental LGG.

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The effect of the addition of chemotherapy to radiotherapy on cognitive function in patients with low-grade glioma: Secondary analysis of RTOG 98-02.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.2047 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. 2047-2047

Author(s):

Roshan Sudhir Prabhu ◽

Minhee Won ◽

Edward G. Shaw ◽

Meihua Wang ◽

David Brachman ◽

...

Keyword(s):

Cognitive Function ◽

Mmse Score ◽

Low Grade Glioma ◽

Subtotal Resection ◽

Low Grade ◽

Who Grade ◽

Term Survival ◽

Who Grade Ii Glioma ◽

Grade Ii ◽

Grade Ii Glioma

2047 Background: The addition of PCV chemotherapy to radiotherapy (RT) for patients with WHO grade II glioma improves progression free survival (PFS) and overall survival (OS), for patients surviving at least 2 years (Shaw, J Clin Oncol 26: 2008). The effect of therapy intensification on cognitive function (CF) remains a concern in this population with substantial long term survival. Methods: 251patients with WHO grade II glioma and age > 40 with any extent of resection, or age < 40 with subtotal resection/biopsy were randomized to RT (54Gy) or RT + PCV. 111 patients with age < 40 and gross total resection were observed. CF was assessed by mini-mental status exam (MMSE)at baseline and years 1, 3, and 5 for patients without progression. Change in MMSE score from baseline of > 3 points was considered clinically significant. Results: Overall, very few patients experienced significant decline in MMSE score, with a median follow-up time of 9.7 years for alive patients. There were no significant differences in the proportion of patients experiencing MMSE decline between study arms at any time point. The table below summarizes MMSE change from baseline over time. Neither baseline MMSE score nor change in MMSE at year 1 significantly predicted for OS or PFS, but there was a trend towards worse OS for patients with MMSE loss of ≥ 2 points [HR 1.73, 95% CI (0.86, 3.47), p=0.12]. Conclusions: The MMSE is a relatively insensitive tool that has not been validated in patients receiving cranial RT, and subtle changes in CF may have been missed. However, the addition of PCV to RT for low grade glioma did not result in significantly higher rates of MMSE decline than RT alone or observation. There was a trend towards an MMSE decline of ≥ 2 points at year 1 predicting for worse OS. [Table: see text]

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P10.03 Establishment and validation of clinical prediction model in WHO grade II glioma

Neuro-Oncology ◽

10.1093/neuonc/noab180.096 ◽

2021 ◽

Vol 23 (Supplement_2) ◽

pp. ii28-ii28

Author(s):

X Xue ◽

Q Gao

Keyword(s):

Prediction Model ◽

Training Group ◽

Clinical Prediction ◽

Validation Group ◽

Who Grade ◽

Clinical Prediction Model ◽

Cox Regression Analysis ◽

Who Grade Ii Glioma ◽

Grade Ii ◽

Grade Ii Glioma

Abstract OBJECTIVE WHO grade II glioma has the characteristics of heterogeneity, and this disease progresses rapidly in some patients, in whom the malignant degree is equivalent to that of high-grade glioma. In order to accurately predict the prognosis of patients, an effective clinical prediction model based on relevant risk factors is needed which could provide a theoretical basis for optimization of clinical individualized treatment. METHODS According to the inclusion and exclusion criteria, eligible patients from January 2010 to December 2018 in our hospital were selected, and those who met the criteria were randomly assigned 4:1 to the training group and the validation group, respectively. The predictors were screened by univariate and multivariate Cox regression analysis, the prediction model was established, and the model was verified and evaluated. RESULTS A total of 258 patients with WHO grade II glioma were recruited, including 208 patients as the training group and 50 patients as the validation group. Six independent risk factors, including patient age, preoperative Karnofsky performance status (KPS) score, preoperative seizure symptoms, surgical resection range, tumor size and IDH status, were selected and included into the prediction model by univariate and multivariate Cox regression analysis, and were visualized in the form of Nomogram. The concordance index (C index) was used to evaluate the predictive ability of the model. Results showed that the C-index was 0.832 in the training group and 0.853 in the validation group, respectively, indicating good performance for the prediction model. The calibration charts were drawn in both groups respectively, which showed that the calibration lines were in good agreement with the standard lines, indicating good consistency between the two groups. CONCLUSIONS In this study, a clinical prediction model for WHO grade II glioma was established, and it was verified that the model has good predictive ability, which may be beneficial for clinical work.

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