Residual tumor volume and patient survival following reoperation for recurrent glioblastoma

Clinical article

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Object

Maximal safe tumor resection is part of the standard of care for patients with newly diagnosed glioblastoma. The role of reoperation in the care of patients with recurrent glioblastoma is less clear, and less than a quarter of patients undergo a second surgery. Previous studies have identified preoperative variables associated with the improved survival of patients following reoperation, and guidelines for the selection of patients for reoperation have been devised and validated. In this study, the authors analyzed the relative survival benefit of maximal safe tumor removal in a series of patients with recurrent glioblastoma who all underwent reoperation.

Methods

In this longitudinal study, the clinical and radiological data of 97 consecutive patients who underwent reoperation for recurrent glioblastoma were prospectively collected. Multiple regression analyses and Kaplan-Meier plotting were performed to identify pre- and postoperative clinical and radiological variables associated with increased survival following reoperation.

Results

The median postoperative survival of all patients following reoperation was 12.4 months (95% confidence interval [CI] 9.0–15.6 months). Multiple Cox regression analysis revealed that patients with large (> 3 cm3) residual tumors following reoperation had significantly decreased survival relative to those with residual tumors that were small (> 0–3 cm3; hazard ratio [HR] = 3.10, 95% CI 1.69–5.70; p < 0.001) or radiologically absent (0 cm3; HR = 5.82, 95% CI 2.98–11.37; p < 0.001). Large residual tumors had faster rates of subsequent regrowth than small (odds ratio [OR] = 4.22, 95% CI 1.19–14.97; p = 0.026) or radiologically absent (OR = 11.00, 95% CI 2.79–43.43; p = 0.001) residual tumors, and a faster regrowth rate was significantly associated with decreased survival (HR = 4.01, 95% CI 2.26–7.14; p < 0.001).

Conclusions

The overall survival of patients with recurrent glioblastoma who underwent reoperations increased with decreasing postoperative residual tumor volumes. For patients meeting prognostic criteria for reoperation, the surgical goal should be to minimize residual tumor volume to maximize overall survival. Clinical trial registration no.: NCT00060541 (ClinicalTrials.gov).

Abbreviations used in this paper:AUC = area under the curve; CI = confidence interval; HR = hazard ratio; KPS = Karnofsky Performance Scale; MCA = middle cerebral artery; MGMT = O6-methylguanine-DNA methyltransferase; OR = odds ratio.

Object

Maximal safe tumor resection is part of the standard of care for patients with newly diagnosed glioblastoma. The role of reoperation in the care of patients with recurrent glioblastoma is less clear, and less than a quarter of patients undergo a second surgery. Previous studies have identified preoperative variables associated with the improved survival of patients following reoperation, and guidelines for the selection of patients for reoperation have been devised and validated. In this study, the authors analyzed the relative survival benefit of maximal safe tumor removal in a series of patients with recurrent glioblastoma who all underwent reoperation.

Methods

In this longitudinal study, the clinical and radiological data of 97 consecutive patients who underwent reoperation for recurrent glioblastoma were prospectively collected. Multiple regression analyses and Kaplan-Meier plotting were performed to identify pre- and postoperative clinical and radiological variables associated with increased survival following reoperation.

Results

The median postoperative survival of all patients following reoperation was 12.4 months (95% confidence interval [CI] 9.0–15.6 months). Multiple Cox regression analysis revealed that patients with large (> 3 cm3) residual tumors following reoperation had significantly decreased survival relative to those with residual tumors that were small (> 0–3 cm3; hazard ratio [HR] = 3.10, 95% CI 1.69–5.70; p < 0.001) or radiologically absent (0 cm3; HR = 5.82, 95% CI 2.98–11.37; p < 0.001). Large residual tumors had faster rates of subsequent regrowth than small (odds ratio [OR] = 4.22, 95% CI 1.19–14.97; p = 0.026) or radiologically absent (OR = 11.00, 95% CI 2.79–43.43; p = 0.001) residual tumors, and a faster regrowth rate was significantly associated with decreased survival (HR = 4.01, 95% CI 2.26–7.14; p < 0.001).

Conclusions

The overall survival of patients with recurrent glioblastoma who underwent reoperations increased with decreasing postoperative residual tumor volumes. For patients meeting prognostic criteria for reoperation, the surgical goal should be to minimize residual tumor volume to maximize overall survival. Clinical trial registration no.: NCT00060541 (ClinicalTrials.gov).

With a median survival of less than 15 months from the time of diagnosis, patients with glioblastoma, the most common malignant primary brain tumor, have among the worst prognoses of all cancer patients.6,11 The standard of care therapy for newly diagnosed tumors consists of maximal resection followed by temozolomide chemotherapy, given concomitantly with and following radiation therapy.7,11 Despite these measures, disease progression or recurrence is virtually inevitable and occurs at a median of 6.9 months.11 For patients with tumor recurrence, a standard of care regimen has yet to be established and individualized therapeutic strategies are often used. Common systemic options include temozolomide rechallenge, nitrosoureas, or antiangiogenic agents such as bevacizumab, each either alone or in combination with other experimental therapies. To date, however, none of these regimens has resulted in clear survival increases and outcomes are uniformly unfavorable.12

Reoperation is considered in approximately 1 in 4 patients.12 The NIH Recurrent Glioblastoma Scale is a previously devised and validated scoring system that uses only preoperatively available information to identify patients with recurrent glioblastoma who are more likely to benefit from reoperation. Patients with a Karnofsky Performance Scale (KPS) score > 80%, a tumor located in a noneloquent/noncritical brain region, and a tumor < 50 cm3 in size have a median survival of 10.8 months (95% confidence interval [CI] 8.9–16.7 months) following reoperation, while the median survival of those who meet only 1 or 2 of these criteria is 4.5 months (95% CI 2.7–6.1 months). Neither the time interval between initial diagnosis and reoperation nor the administration of systemic therapies following reoperation has a significant effect on survival.8 This study, however, did not address what intraoperative factors, such as volumetric extent of resection, might further influence survival outcome.

In this current study, we sought to determine the relative survival benefit of greater tumor removal during reoperation for recurrent glioblastoma. Using multiple regression models to account for preoperative clinical and radiological variables previously shown to influence survival, we found that decreased residual tumor volume following reoperation was significantly associated with increased overall survival, and possible explanations for this finding were examined. The goal of the study was to develop recommendations for the optimal management of patients with recurrent glioblastoma selected for reoperation.

Methods

Study Design and Participants

The enrollment criteria for this study included a histologically confirmed diagnosis of glioblastoma (WHO Grade IV astrocytoma) at the time of initial tumor resection, initial treatment with radiation and temozolomide, and a first-time radiological recurrence of tumor. Between November 2002 and April 2012, 97 consecutive patients who requested surgery at the NIH Clinical Center and fulfilled these criteria were enrolled into our evaluation and treatment of neurosurgical disorders protocol (ClinicalTrials.gov registration no. NCT00060541 [http://clinicaltrials.gov]) and included in this study. Patients with gliomatosis or recurrent tumors involving deep brain regions such as the basal ganglia, thalamus, or brainstem were excluded. Following enrollment, clinical histories and contrast-enhanced brain MRI studies were obtained from all patients. Patients then underwent reoperation with the goal of resecting a maximal volume of recurrent tumor tissue, defined as the tissue that enhanced following contrast administration on T1-weighted MRI. Combinations of neuronavigation, intraoperative MRI, and ultrasonography, cortical and subcortical motor mapping, and expressive and receptive speech testing were used as necessary. All patients underwent a repeat contrast-enhanced brain MRI study within 24 hours following reoperation. Eighty-seven of the patients had subsequent serial follow-up MRI studies at the NIH. This study was approved by the CNS Institutional Review Board of the NIH, and all patients provided informed written consent for their participation.

Data Acquisition

Within this study, the terms “preoperative” and “postoperative” are relative to a patient's reoperation procedure for a recurrent glioblastoma, not to his or her initial operation for a newly diagnosed glioblastoma. Information regarding age, sex, previous treatment history, pathological diagnosis, preoperative KPS score, postoperative complications, and postoperative adjuvant treatments were prospectively collected. The date of death or the continued survival of all patients was accounted for.

Preoperative MRI studies for all patients were reviewed independently by 3 neurosurgeons (R.L.Y, K.A.Z., and J.K.P.), and tumors were classified as eloquent if they involved 1 or more eloquent or critical brain regions, defined as the cortical or subcortical receptive or expressive speech areas, the primary motor cortex or subcortical motor tracts, and the proximal segments (M1 and/or M2) of the middle cerebral artery (MCA).8 Discordant judgments on tumor eloquence, which occurred in 10 of the 97 cases, were resolved by consensus. There were 619 postoperative MRI studies and the median number of studies per patient was 4 (range 1–51 studies).

The volume of contrast-enhancing tumor present in each pre- and postoperative T1-weighted MRI study was calculated using the Medical Imaging Processing and Visualization program (MIPAV; http://mipav.cit.nih.gov) using the instructions provided on the website. Briefly, for each tumor containing an MR image slice, a 2D region of interest corresponding to the area of enhancing tumor tissue was segmented semiautomatically and adjusted manually as needed. The regions of interest across all tumor-containing slices were then summed to determine a volume of interest corresponding to the volume of enhancing tumor tissue. Tumor volumes were independently calculated by 3 observers (N.M., M.J.S., and M.A.B.) who were blinded to the clinical histories of the patients, and mean volumes were used in the analyses.

Statistical Analysis

The primary outcome variable, overall survival, was defined as the length of time from date of reoperation to date of death or October 1, 2012, whichever occurred first. Other variables included in the survival analysis were sex, age (dichotomized into 2 categories [younger and older] with a cutoff age of 40 years), tumor location (eloquent vs noneloquent), KPS score (dichotomized into 2 categories [lower vs higher] with a cutoff value of 90%), preoperative tumor size (categorized into 3 ordered categories [small, medium, and large] with cutoff sizes of 8 cm3 and 30 cm3, respectively), postoperative residual tumor size (categorized into 3 ordered categories [radiologically absent, small, and large] with cutoff sizes of 0 cm3 and 3 cm3, respectively) and postoperative regrowth rate (dichotomized into 2 categories [faster and slower] with a cutoff value of 5 cm3). The cutoff values for the categorization of continuous variables were established by determining the values that resulted in the greatest statistically significant differences between the ordered categories.

The postoperative regrowth rate was determined using standardized area under the curve (AUC) analysis. For each patient, the actual tumor volume present in each postoperative MRI study was plotted as a function of time. The actual area under the resulting plot line was calculated using the trapezoidal rule in which the total area was first divided into a series of contiguous trapezoids, and then the areas of the individual trapezoids were summed. To obtain the standardized AUC, the rectangular area under a plot line extended horizontally from the actual tumor volume at time = Day 0 was subtracted from the actual AUC. The regrowth rate was defined as the standardized AUC divided by the number of months of follow-up.

The CIs of median overall survival were estimated by a distribution-free method. Survival curves were drawn by the Kaplan-Meier product-limit method. Simple and multiple Cox regression analyses were performed to evaluate the effects of sex, age, tumor location, KPS score, pre- and postoperative tumor size, and postoperative regrowth rate on overall survival. Simple and multiple logistic regression analyses were performed to evaluate the effects of age, KPS score, and pre- and postoperative tumor size on postoperative regrowth rate. Simple and multiple ordered logistic regression analyses were used to evaluate the effects of sex, age, KPS score, and preoperative tumor size on postoperative tumor size. In the multiple regression analysis, a significance level of 0.1 was used for model selection. All statistical analyses described above were performed using SAS version 9.2.1

Results

Patients and Surgical Outcomes

Ninety-seven patients were enrolled in the study. The median age of the patients was 49.0 years with a range of 23–74 years, and 69 patients (71.1%) were female. Forty-four patients (45.4%) had tumors involving eloquent brain regions, and 87 (89.7%) had a preoperative KPS score of 90% or 100% (range 40%–100%). The median preoperative and postoperative tumor volumes were 18.92 cm3 (range 0.50–91.34 cm3) and 0.18 cm3 (range 0–39.85 cm3), respectively, and a radiologically complete resection (0 cm3 residual tumor) was achieved in 38 patients (39.2%). The clinical and radiological criteria used to classify patients for subsequent analyses are described in Methods and shown in Table 1. Also provided in Table 1 are the median survivals of patients classified using these criteria. There were no intraoperative deaths, but 2 patients with preoperative KPS scores of 40% and 60% died at 1.0 and 0.9 months, respectively, following surgery. Major postoperative complications included a right MCA stroke with resulting permanent left hemiparesis in a patient with a tumor that encircled the right MCA, and a subdural hematoma over the left cerebral hemisphere that occurred 2 months following surgery in a patient with a right temporal tumor. This latter patient underwent surgical drainage 1 month thereafter. Additional complications in 2 patients included an asymptomatic hemorrhage into a tumor resection cavity that was detected on the immediate postoperative MRI study and was treated conservatively in 1 patient, and postoperative motor deficits that resolved within 1 month following surgery in another patient. The overall complication rate was therefore 7.2% (7 patients).

TABLE 1:

Demographic, clinical, and radiological characteristics of the patients

VariableNo.%Median Survival (mos)95% CI (mos)*
all patients9710012.49.0–15.6
age (yrs)
 younger (≤40)2828.918.010.2–44.8
 older (>40)6971.110.67.8–14.2
sex
 female6971.112.38.9–16.3
 male2828.914.26.6–20.2
brain location of tumor
 eloquent4445.48.86.0–14.2
 noneloquent5354.616.310.8–23.0
KPS score
 lower (≤80%)1010.33.01.0–10.6
 higher (≥90%)8789.714.210.2–17.4
preop tumor size (cm3)
 small (0.5–8)2828.924.116.3–35.4
 medium (>8–30)3536.112.48.6–15.3
 large (>30)3435.16.85.2–12.4
postop residual tumor size (cm3)
 none (0)3839.219.912.7–28.4
 small (>0–3)3738.110.68.6–16.3
 large (>3)2222.75.13.4–12.4

Distribution-free confidence limits.

Radiologically absent on contrast-enhanced T1-weighted MRI.

Factors Associated With Postoperative Survival

The median postoperative survival of all patients following reoperation was 12.4 months (95% CI 9.0–15.6). In a simple Cox regression analysis (Table 2), older age (> 40 years), eloquent tumor location, lower KPS score (≤ 80%), progressively larger preoperative tumor volume, and progressively larger postoperative residual tumor volume were all significantly associated with decreased survival (all p < 0.05), while patient sex was not (p = 0.752). Kaplan-Meier plotting with log-rank testing confirmed these associations (Fig. 1). In a multiple Cox regression analysis (Table 2), only older age (hazard ratio [HR] = 2.66, 95% CI 1.41–5.02; p = 0.003), lower KPS score (HR = 6.08, 95% CI 2.72–13.61; p < 0.001), and progressively larger postoperative residual tumor volume (p < 0.001) remained significantly associated with decreased survival. Patients with large (> 3 cm3) residual tumors following reoperation had significantly decreased survival relative to those with small (> 0–3 cm3; HR = 3.10, 95% CI 1.69–5.70; p < 0.001) or radiologically absent (0 cm3; HR = 5.82, 95% CI 2.98–11.37; p < 0.001) residual tumors. However, the survival of patients with small residual tumors did not significantly differ from that of those with radiologically absent tumors (HR = 1.88, 95% CI 0.98–3.58; p = 0.056). Tumor location in eloquent brain regions and preoperative tumor size were not, by themselves, significantly associated with postoperative survival in a multiple regression analysis because they were each highly associated with residual tumor volume (p < 0.001 for both, Fisher's exact test), and preoperative tumor size was also highly associated with KPS score (p = 0.031, Fisher's exact test).

TABLE 2:

Cox regression analyses of overall survival after reoperation

VariableSimple RegressionMultiple Regression
HR95% CIp ValueHR95% CIp Value
sex (male vs female)0.752>0.1
age (older vs younger)2.451.30–4.590.0052.661.41–5.020.003
tumor location (eloquent vs noneloquent)2.461.48–4.100.001>0.1
KPS score (lower vs higher)6.463.00–13.93<0.0016.082.72–13.61<0.001
preop tumor size<0.001>0.1
 large vs medium1.791.04–3.110.037
 medium vs small3.471.59–7.580.002
 large vs small6.222.91–13.31<0.001
postop residual tumor size<0.001<0.001
 large vs small2.461.37–4.440.0033.101.69–5.70<0.001
 small vs none*2.181.16–4.120.0161.880.98–3.580.056
 large vs none*5.372.78–10.37<0.0015.822.98–11.37<0.001

None defined as radiologically absent on contrast-enhanced T1-weighted MRI

Fig. 1.
Fig. 1.Fig. 1.

Kaplan-Meier estimates of survival following reoperation. Patients were grouped by age, KPS score, or postoperative residual tumor volume using values defined in Table 1. Shaded areas represent the corresponding 95% CIs, and the number of patients at risk in each group are shown on the bottom. A: Younger (≤ 40 years; blue) versus older (> 40 years; red) age (p = 0.004, log-rank test). B: Higher (≤ 90%; blue) versus lower (≥ 80%; red) KPS score (p < 0.001, log-rank test). C: No (blue) versus small (red) versus large (green) residual tumor (p < 0.001, log-rank test).

Postoperative Tumor Volume, Regrowth Rate, and Survival

As an explanation for the greater postoperative survival of patients with less postoperative residual tumor volume (Tables 1 and 2), we hypothesized that the rate of regrowth of residual tumors correlates with their volume. To test this hypothesis, we used AUC analysis to determine the tumor regrowth rate in 87 patients who had MRI studies subsequent to the immediate postoperative study (332 total scans; Fig. 2 upper). Associations of tumor regrowth rate with KPS score, age, and pre- and postoperative tumor volume were then sought using simple logistic regression analysis, and the only significant correlations were with pre- and postoperative tumor volume (Table 3). In a multiple logistic regression analysis, only postoperative residual volume remained significantly associated with tumor regrowth rate (p = 0.003). Large residual tumors had a significantly increased rate of regrowth relative to small (odds ratio [OR] = 4.22, 95% CI 1.19–14.97; p = 0.026) and radiologically absent (OR = 11.00, 95% CI 2.79–43.43; p = 0.001) residual tumors. However, the regrowth rate of small residual tumors did not significantly differ from that of radiologically absent tumors (OR = 2.61, 95% CI 0.85–8.00; p = 0.094). Consistent with the relationship between postoperative residual tumor volume and subsequent regrowth rate, substitution of the former with the latter in simple and multiple Cox regression models of survival demonstrated that faster regrowth rate was significantly associated with decreased postoperative survival (HR = 4.01, 95% CI 2.26–7.14; p < 0.001; Table 4, Fig. 2 lower).

Fig. 2.
Fig. 2.

Analysis of tumor regrowth over time (upper) and survival (lower). Upper: Standardized AUC of representative tumors with fast (standardized AUC = 12.26 cm3, red) and slow (standardized AUC = 0.89 cm3, blue) regrowth rates. Lower: Kaplan-Meier estimate of survival following reoperation for patients grouped by tumor regrowth rate, comparing standardized AUC < 5 cm3 (red) with standardized AUC > 5 cm3 (blue; p < 0.001, log-rank test). Shaded areas represent the corresponding 95% CIs, and the number of patients at risk in each group are shown on the bottom.

TABLE 3:

Logistic regression analyses of tumor regrowth rate (faster vs slower)*

VariableSimple RegressionMultiple Regression
OR95% CIp ValueOR95% CIp Value
age (older vs younger)0.249>0.1
KPS score (lower vs higher)1>0.1
preop tumor size0.024>0.1
 large vs medium1.500.54–4.180.438
 medium vs small4.751.19–19.010.028
 large vs small7.121.72–29.460.007
postop residual tumor size0.0030.003
 large vs small4.221.19–14.970.0264.221.19–14.970.026
 small vs none2.610.85–8.000.0942.610.85–8.000.094
 large vs none11.002.79–43.430.00111.002.79–43.430.001

In 87 patients who had MRI studies subsequent to the immediate postoperative study.

TABLE 4:

Cox regression analyses of overall survival following reoperation*

VariableSimple RegressionMultiple Regression
HR95% CIp ValueHR95% CIp Value
age (older vs younger)2.211.14–4.280.0182.461.28–4.730.007
KPS score (lower vs higher)4.801.80–12.780.0027.732.67–20.67<0.001
regrowth rate (faster vs slower)3.171.82–5.50<0.0014.012.26–7.14<0.001

In 87 patients who had MRI studies subsequent to the immediate postoperative study.

Regrowth rate (standardized AUC): slower < 5 cm3, faster > 5 cm3.

Factors Associated With Residual Tumor Following Reoperation

Given the goal of radiologically complete recurrent tumor resections, we sought to identify potential causes for incomplete resections. In a simple logistic regression analysis, tumor location in an eloquent brain region, lower KPS score, and progressively larger preoperative tumor volumes were significantly associated with larger postoperative residual tumor volume, while patient sex and age were not (Table 5). In the multiple regression analysis, only eloquent tumor location (OR = 16.00, 95% CI 4.98–51.47; p < 0.001) and larger preoperative tumor volume remained significantly associated (p < 0.001). Specifically, the odds of having greater postoperative residual tumor volume were not significantly greater for large versus medium preoperative tumors (OR = 2.59, 95% CI 0.90–7.48; p = 0.078) but were for medium versus small tumors (OR = 11.69, 95% CI 3.05–44.81; p < 0.001) and even greater for large versus small tumors (OR = 30.33, 95% CI 7.20–127.74; p < 0.001).

TABLE 5:

Ordered logistic regression analyses of postoperative tumor volume (large vs small vs none)*

VariableSimple RegressionMultiple Regression
OR95% CIp ValueOR95% CIp Value
sex (male vs female)0.167>0.1
age (older vs younger)0.827>0.1
tumor location (eloquent vs noneloquent)19.016.85–52.74<0.00116.004.98–51.47<0.001
KPS score (lower vs higher)4.591.28–16.420.019>0.1
preop tumor size<0.001<0.001
 large vs medium6.872.49–18.95<0.0012.590.90–7.480.078
 medium vs small6.932.26–21.310.00111.693.05–44.81<0.001
 large vs small47.6113.14–172.52<0.00130.337.20–127.74<0.001

Proportional odds assumption was met.

Discussion

Despite the lack of a randomized clinical trial demonstrating its efficacy, maximal safe tumor resection is an important component of the standard of care for newly diagnosed glioblastoma tumors. Resection of > 78% to > 98% of the contrast-enhancing portion of a tumor on MRI is associated with increased survival, and the majority of patients with good functional status and tumors located in noneloquent brain regions therefore undergo attempted gross-total resections.7,10 At the time of tumor recurrence, which occurs within 24 months for almost 90% of patients,11 reoperation is not routinely recommended and is performed in only 12.3% to 28% of cases.2,5,12 In the present study, we evaluated the factors associated with increased survival within a cohort of patients who all underwent reoperation. Using multiple Cox regression analyses, we found that along with younger age and higher KPS score, progressively smaller residual tumor volume following reoperation was significantly associated with increased survival. As a possible explanation for this association, smaller tumors had slower rates of regrowth and, consistent with a transitive relation, patients with slower regrowing tumors had increased postoperative survival (Fig. 3). To our knowledge, this is the first detailed analysis of the rate of regrowth of recurrent glioblastoma tumors.

Fig. 3.
Fig. 3.

Transitive relation of residual tumor size, regrowth rate, and survival. Smaller residual tumor size was significantly associated with increased survival as well as a slower rate of tumor regrowth. Slower rate of tumor regrowth was significantly associated with increased survival.

Due to their unproven prognostic significance in patients with recurrent glioblastoma, molecular markers were not included as variables in our analyses. The best studied marker, O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation, has been shown in numerous studies to have both prognostic and predictive value in patients with newly diagnosed glioblastoma, but the significance of MGMT promoter methylation in recurrent tumors is controversial.4,13 Studies examining various temozolomide administration schedules have not demonstrated a strong predictive effect of MGMT promoter methylation on tumor response or outcome. Although patients with MGMT-methylated tumors did show some improved survival in these series, no such effect was noted in a more recent study that specifically examined this question.9,13

Many patients with recurrent glioblastoma may not meet criteria to be considered viable candidates for reoperation. It remains unclear, however, whether more patients would be offered reoperation if validated prognostic criteria, such as the NIH Recurrent Glioma Scale,5 were uniformly applied. In patients who do meet these criteria, the present study provides strong evidence that aggressive resections should be offered to maximize survival. Patients with larger tumors or those located in eloquent brain locations should be informed that a radiologically complete resection is less likely given the association of those properties with increased residual postoperative volume (Table 5). The expectation of an incomplete resection should not, however, deter patients from considering reoperation altogether, as small residual tumors, in contrast to large residual tumors, neither regrow significantly faster nor associate more closely with shorter survival than radiologically absent tumors (Tables 2 and 3). The median postoperative survival of all patients in this study was 12.4 months (95% CI 9.0–15.6 months), and that of selected subgroups such as those with small preoperative tumor volumes and radiologically complete resections was 24.1 months (95% CI 16.3–35.4 months) and 19.9 months (95% CI 12.7–28.4 months), respectively.

A recent systematic review of reoperation for recurrent glioblastoma concluded that there is a lack of consensus regarding its utility. The authors noted that the studies published to date are limited by their retrospective nature, the use of small sample sizes, and the frequent inclusion of patients with lower-grade tumors such as anaplastic astrocytomas (WHO Grade III astrocytomas). Younger age and higher KPS score did, however, emerge as significant predictors of survival in all studies examined, as it does in this study.3 As with the aforementioned studies, the primary limitation of this study is its nonrandomized nature. A trial in which patients are randomized to reoperation or nonsurgical treatment would best determine the survival benefits of reoperation per se, but accrual to such a trial has been difficult due to the reluctance of patients to be randomized (ClinicalTrials.gov registration no. NCT01413438). An alternative study design would have been to compare patients who underwent reoperation to a “matched” cohort who did not undergo reoperation, but selection bias is inherent in such a design. Therefore, we opted in this study to examine a single cohort of consecutive patients who underwent reoperations and determine the variables associated with improved survival within this cohort. To eliminate technical skill and clinical setting as survival-determining variables, all patients were reoperated on by a single surgeon (J.K.P.) at a single institution. While our study does not determine the value of reoperation versus nonsurgical treatment per se, it does demonstrate a clearly significant inverse relationship between residual tumor volume and overall survival in patients who do undergo reoperation.

Conclusions

Reoperation should be considered as a treatment option in patients with recurrent glioblastoma tumors who have favorable preoperative clinical and radiological characteristics. In patients who do proceed with reoperation, maximal tumor volume resection should be the surgical goal. Further studies are necessary before reoperation can be adopted as a standard of care for recurrent glioblastoma tumors as initial surgery is for newly diagnosed tumors. Because reoperation is not curative, patients should be considered for enrollment in clinical trials of experimental therapies following reoperation.

Disclosure

This work was supported by the Intramural Research Program of the National Institute of Neurological Disorders and Stroke, NIH. The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author contributions to the study and manuscript preparation include the following. Conception and design: J Park. Acquisition of data: J Park, Yong, Mihatov, Shen, Brown, Zaghloul. Analysis and interpretation of data: J Park, Yong, Wu, Mihatov, Shen, Brown, Zaghloul, G Park. Drafting the article: J Park, Yong, Wu, G Park. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: J Park. Statistical analysis: Yong, Wu, G Park. Study supervision: J Park.

This article contains some figures that are displayed in color online but in black-and-white in the print edition.

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  • 13

    Weller MStupp RReifenberger GBrandes AAvan den Bent MJWick W: MGMT promoter methylation in malignant gliomas: ready for personalized medicine?. Nat Rev Neurol 6:39512010

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Article Information

Address correspondence to: John K. Park, M.D., Ph.D., Santa Barbara Neuroscience Institute at Cottage Health System, 400 W. Pueblo St., Santa Barbara, CA 93105. email: jparkmd@outlook.com.

Please include this information when citing this paper: published online July 25, 2014; DOI: 10.3171/2014.6.JNS132038.

© AANS, except where prohibited by US copyright law.

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Figures

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    Kaplan-Meier estimates of survival following reoperation. Patients were grouped by age, KPS score, or postoperative residual tumor volume using values defined in Table 1. Shaded areas represent the corresponding 95% CIs, and the number of patients at risk in each group are shown on the bottom. A: Younger (≤ 40 years; blue) versus older (> 40 years; red) age (p = 0.004, log-rank test). B: Higher (≤ 90%; blue) versus lower (≥ 80%; red) KPS score (p < 0.001, log-rank test). C: No (blue) versus small (red) versus large (green) residual tumor (p < 0.001, log-rank test).

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    Analysis of tumor regrowth over time (upper) and survival (lower). Upper: Standardized AUC of representative tumors with fast (standardized AUC = 12.26 cm3, red) and slow (standardized AUC = 0.89 cm3, blue) regrowth rates. Lower: Kaplan-Meier estimate of survival following reoperation for patients grouped by tumor regrowth rate, comparing standardized AUC < 5 cm3 (red) with standardized AUC > 5 cm3 (blue; p < 0.001, log-rank test). Shaded areas represent the corresponding 95% CIs, and the number of patients at risk in each group are shown on the bottom.

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    Transitive relation of residual tumor size, regrowth rate, and survival. Smaller residual tumor size was significantly associated with increased survival as well as a slower rate of tumor regrowth. Slower rate of tumor regrowth was significantly associated with increased survival.

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