Prognostic Factors for Survival in Adult Patients With Recurrent Glioma Enrolled Onto the New Approaches to Brain Tumor Therapy CNS Consortium Phase I and II Clinical Trials
Publication: Journal of Clinical Oncology
Abstract
Purpose
Prognostic factor analyses have proven useful in predicting outcome in patients with newly diagnosed malignant glioma. Similar analyses in patients with recurrent glioma could affect the design and conduct of clinical trials substantially.
Patients and Methods
Between 1995 and 2002, 333 adults with recurrent gliomas were enrolled onto 10 phase I or II trials of systemic or local therapy. The studies had similar inclusion criteria and were conducted within the New Approaches to Brain Tumor Therapy CNS Consortium. Ninety-three percent of the patients have died. Cox proportional hazards (PH) regression and recursive partitioning analysis (RPA) were performed to identify prognostic factors.
Results
Factors associated with an increased risk of death were increased age, lower Karnofsky performance score (KPS), initial and on-study histologies of glioblastoma multiforme (GBM), corticosteroid use, shorter time from original diagnosis to recurrence, and tumor outside frontal lobe. The final PH model included initial histology of GBM (relative risk [RR] = 2.01), 10-year increase in age (RR = 1.23), KPS less than 80 (RR = 1.54), and corticosteroid use (RR = 1.49). RPA resulted in seven classes. Median survival time was poorest in non-GBM patients with KPS less than 80 or GBM patients, age ≥ 50 years, corticosteroid use (4.4 months; 95% CI, 3.6 to 5.4 months); median survival was best in patients with initial histology other than GBM with KPS ≥ 80 and tumor confined to the frontal lobe (25.7 months; 95% CI, 18.7 to 52.5), and was 7.0 months (95% CI, 6.2 to 8.0 months) for all patients.
Conclusion
Initial histology, age, KPS, and corticosteroid use are prognostic for survival in recurrent glioma patients. To allow comparisons across phase II trials, enrollment criteria may need to be restricted.
Introduction
The prognosis for patients with recurrent glioma is poor and few therapies have been found to be efficacious.1-3 Novel therapies for this patient population are tested frequently in uncontrolled or historically controlled phase II trials with the assumption that the patients in these trials are homogeneous. However, the patients may differ on several characteristics, including age, performance status, initial or on-study histology, time from initial diagnosis to recurrence, location of tumor and whether it is resectable, number and type of prior therapies, and use of concomitant medications (eg, corticosteroids, anticonvulsants).
Prognostic factor analyses have proven useful in predicting outcome in patients with newly diagnosed malignant glioma. Factors such as age, Karnofsky performance score (KPS), and extent of resection have been shown to be prognostic for survival in newly diagnosed patients in the Radiation Therapy Oncology Group recursive partitioning analysis (RPA).4 Given that these prognostic factors have more impact on survival than the currently available therapies, randomized prospective clinical trials in newly diagnosed high-grade gliomas are now stratified to account for these differences. Likewise, phase II studies in this patient population are analyzed using published RPA data so results can be compared fairly with other uncontrolled trials. If this were not done, studies enrolling patients with more favorable prognostic factors would appear superior even if the therapy were ineffective.
Few studies have examined prognostic factors in patients with recurrent high-grade gliomas and the findings have not been consistent. Given that most novel agents and approaches are studied in patients with recurrent high-grade gliomas before they are administered to patients who have just been diagnosed, a similar RPA analysis in patients with recurrent disease would be extremely important in deciding which novel therapies should be pursued and which should be abandoned. The objective of our study was to determine whether baseline demographic and clinical characteristics are prognostic for survival in patients with recurrent glioma using RPA.
Patients and Methods
Between 1995 and 2002, 333 adult patients were enrolled onto 10 phase I or II clinical trials for the treatment of recurrent glioma conducted within the New Approaches to Brain Tumor Therapy (NABTT) CNS Consortium.5 These trials are described in Appendix Table A1 (online only). Six of the trials involved systemic chemotherapy treatment: 9-aminocamptothecin (9-AC),6 suramin,7 phenylbutyrate,8 aprinocarsen,9 irinotecan,10,11 and oral procarbazine.12 The other four were trials of local chemotherapy or brachytherapy: carmustine wafer (Gliadel wafer, Guilford Pharmaceuticals; Baltimore, MD),13 the alternative temporary brachytherapy technique, GliaSite (CYTYC, Palo Alto, CA) Radiation Therapy System (RTS),14 Onyx-015 (Onyx Pharmaceuticals, Redmond, CA),15 and carmustine wafer and intravenous O6-benzylguanine.16 The trials were approved by the Cancer Therapy Evaluation Program at the National Cancer Institute and the institutional review boards at each NABTT CNS Consortium participating site. The sites that participated in at least one of these trials were the University of Alabama (Birmingham, AL), Brown University (Providence, RI), the Cleveland Clinic (Cleveland, OH), Columbia University (New York, NY), Emory University (Atlanta, GA), Henry Ford Hospital (Detroit, MI), the Johns Hopkins University (Baltimore, MD), Massachusetts General Hospital (Boston, MA), Moffitt Cancer Center (Tampa, FL), Northwestern University (Chicago, IL), the University of Pennsylvania (Philadelphia, PA), the University of Texas at San Antonio (San Antonio, TX), Wake Forest University (Winston-Salem, NC), and Washington University (St. Louis, MO). None of the treatments in the phase II trials were found to be efficacious.
The studies had similar inclusion criteria. Eligible patients were at least 18 years of age, had histologically proven malignant glioma (anaplastic astrocytoma (AA), anaplastic oligodendroglioma, or glioblastoma multiforme [GBM]), had progression or recurrence, and had a KPS ≥ 60. Three of the studies (9-AC, RTS, and phenylbutyrate) did not require previous radiation therapy (RT), and there was no minimum elapsed time between RT and enrollment for carmustine wafer, a minimum of only 28 days between RT and enrollment for phenylbutyrate, and a minimum 2 months between RT and enrollment for 9-AC. The other studies required prior RT and ≥ 3 months since completion. The phenylbutyrate, carmustine wafer, RTS, and O6-benzylguanine protocols did not limit the number of prior chemotherapies allowed, but the other protocols limited them to one or two. Other eligibility criteria included ≥ 3 weeks since last dose of non-nitrosourea chemotherapy, ≥ 6 weeks since a nitrosourea chemotherapy, and hematologic and biochemical parameters within an acceptable range. In addition, patients could not be pregnant or breast-feeding and needed to have a minimum life expectancy of ≥ 2 months. All patients gave informed consent.
Prognostic Factors
Patient prognostic factor data were collected at the baseline visit as part of each study. Demographic factors were age at entry, sex, and race. Clinical factors assessed were KPS, initial histology, time from initial histology until study entry, histology at study entry, site of tumor, and hemoglobin level. Treatment factors included corticosteroid use, anticonvulsant use, surgical resection as part of study, and number of prior chemotherapies, surgeries, and radiation therapies.
Twelve patients were enrolled onto two of the studies and are included in the analysis twice. However, the demographic, clinical characteristics, and survival data are specific to the respective study, and therefore these are treated as independent observations. Although this may not be ideal, excluding the patients’ data from either or both of the studies also could introduce a bias.
Survival
All enrolled patients, even if off treatment or off study, were observed routinely for survival. Overall survival time was calculated from date of start of treatment on the present study until the date of death as a result of any cause. Patients still alive or lost to follow-up were censored at the date of last follow-up. At the time of analysis, 308 of the 333 patients (93%) had died.
Statistical Considerations
Continuous data were summarized with medians and ranges, and categoric data were summarized with frequencies and percentages. Some factors were recoded into dichotomies because of infrequent values. These included race, recoded as white and nonwhite; histology (both initial and on study), recoded as GBM and non-GBM; prior chemotherapies, recoded as less than one and ≥ one, and also less than two and ≥ two; prior surgeries, recoded as less than two and ≥ two; and prior RT courses, recoded as less than two and ≥ two. Tumor site was dichotomized into tumor confined to the frontal lobe and at least some tumor outside of the frontal lobe because previous studies have shown a reduced risk of death when the tumor is confined to the frontal lobe.17,18 Age and KPS were analyzed as continuous measures and were also dichotomized. Age was dichotomized at the median (50 years) and also at 40 and 60 years. KPS was dichotomized at less than 80 and at less than 90.
The comparability of survival times for each protocol was assessed in two ways. First, the hazard rate, calculated as the number of deaths divided by the total patient-years of follow-up, and 95% CI were computed for each protocol. Then Cox proportional hazards (PH) regression analysis19 was used to compare survival from each protocol with the combined data from the other protocols.
Univariate PH regression analysis was performed to identify possible prognostic factors associated with an increased risk of death. Factors identified as being possible predictors in the univariate analysis, defined as P < .20, were then included in a backward stepwise multivariate analysis. The least significant factor was dropped from the model, and the model was refit. This process was repeated until only significant factors (P < .05) remained. Because some factors had missing data, a forward analysis was also performed to confirm the final model.
RPA was performed based on the log-likelihood ratios from the PH regressions.20 Data were partitioned on the factor with the greatest log likelihood, then univariable PH regressions were refit on the partitioned data. This process continued until either no more factors were significant at the P < .05 level or the remaining sample size was less than 20. Kaplan-Meier survival estimates21 were obtained for each of the RPA classes and tested for inequality with the Wilcoxon test. Amalgamation of classes with similar survival times was then performed and the curves were plotted.
CIs were calculated using standard methods. Analyses were performed using SAS version 9 (SAS Institute, Cary, NC). All reported P values are two sided.
Results
Demographic and clinical characteristics of the patients by trial are presented in Table 1 and for all patients combined in Table 2. The hazard rate and 95% CI for each protocol are shown in Figure 1. Only one protocol was significantly different from the others for survival on PH regression analysis. The phase II study of aprinocarsen exhibited an increased risk when compared with the combined data from the other trials (risk ratio [RR] = 1.62, 95% CI, 1.02 to 2.56). Grossman et al9 propose that the integrity of the blood-brain barrier could be a possible reason for this increased risk of death. However, there were only 21 patients in this trial and differences in known prognostic factors, such as KPS and histology, cannot be ruled out as the cause. Therefore, we included these patients in our primary analysis reported here. We then excluded these patients, repeated the analysis, and obtained nearly identical results.
The results of the univariate PH regression analysis are listed in Table 3. The factors that were at least marginally associated with an increased risk of death (P < .20) included increased age, lower KPS, initial and on-study histologies of GBM, corticosteroid use, shorter time from initial diagnosis, and tumor located outside of the frontal lobe. These factors were included in the multivariate PH regression analysis. The final multivariate regression model included initial histology of GBM versus other (RR = 2.01; 95% CI, 1.50 to 2.70; P < .0001), decade increase in age (RR = 1.23; 95% CI, 1.10 to 1.37; P = .0002), KPS of 60 to 70 versus 80 to 100 (RR = 1.54; 95% CI, 1.18 to 2.00; P = .001), and corticosteroid use (RR = 1.49; 95% CI, 1.13 to 1.96; P = .005).
The RPA, displayed in Figure 2, resulted in seven terminal nodes (or classes). The first partition was initial histology. For the non-GBM patients, the next split was KPS, dichotomized at less than 80 and ≥ 80. For the partition with poorer KPS, no additional variables were prognostic for survival. For the better KPS group, an additional partition of tumor location was prognostic. For the GBM patients, age dichotomized as younger than 50 and ≥ 50 years was the next split. KPS, dichotomized as less than 90 and ≥ 90 was the final partition for patients younger than age 50 years. For patients who were ≥ 50 years of age, corticosteroid use was the final partition.
Median survival time for these seven RPA classes ranged from 3.8 to 25.7 months. The survival times for class 3 compared with class 7 and for class 5 compared with class 6 were not significant on the Wilcoxon test for inequalities, so these classes were combined and the resulting Kaplan-Meier survival curves were plotted (Fig 3). The median overall survival for all patients was 7.0 months (95% CI, 6.2 to 8.0). Median survival was poorest in non-GBM patients with KPS less than 80 or GBM patients, age ≥ 50 years, and taking corticosteroids (4.4 months; 95% CI, 3.6 to 5.4), and was best in patients with initial histology other than GBM with KPS ≥ 80 and tumor confined to the frontal lobe (25.7 months; 95% CI, 18.7 to 52.5 months).
The RPA analysis selected different prognostic factors for the GBM and non-GBM strata. To validate this finding, we stratified the patients by initial histology and ran separate PH models on each stratum. For the non-GBM stratum, the final multivariate PH model included KPS of 60 to 70 versus 80 to 100 (RR = 3.38; 95% CI, 1.94 to 5.86; P < .0001), age ≥ 60 versus younger than 60 (RR = 2.45; 95% CI, 1.16 to 5.17; P = .02) and tumor outside frontal lobe versus confined to frontal lobe (RR = 2.04; 95% CI, 1.09 to 3.82; P = .03). This model contains all of the factors that were significant in the RPA and the additional prognostic factor of age dichotomized at 60 years. For the GBM stratum, the final PH model included age ≥ 50 versus younger than 50 years (RR = 1.51; 95% CI, 1.13 to 2.03; P = .006), 10 point increase in KPS (RR = 1.13; 95% CI, 1.01 to 1.27; P = .04) and corticosteroid use (RR = 1.42; 95% CI, 1.01 to 1.99; P = .04). The factors in this model were the same as in the RPA, although the cut points were different for age and KPS.
Tumor grade was available for 94 of the 98 patients who had initial histology other than GBM; 17 (18%) were low-grade and 77 (82%) were high-grade gliomas. All 17 of the patients with low-grade glioma had died and 47% of them had on-study histology of GBM. The percentage of patients with low-grade glioma at initial histology in RPA class 1 was 26%, 16% in RPA class 2, and 18% in RPA class 3.
Although a large number of factors were tested in the RPA analysis, the significance level was set at P < .05. If a more stringent requirement of P < .01 were used, most of the partitions would remain. Only the partition of tumor location (P = .03) in the non-GBM stratum and the partition of KPS (P = .03) for the GBM, age younger than 50 years stratum would not have been made. The comparison of the RPA nodes would reflect these same results: RPA classes 1 and 2 would not be significantly different (P = .03), and the RPA classes 2 and 4 would not be significantly different (P = .02).
Discussion
Our data suggest that patients with recurrent gliomas entering clinical trials have widely variable outcomes based on baseline demographic and clinical characteristics. The most significant of these prognostic factors are initial histology, KPS, age, and corticosteroid use. The differences seen in the median survival time between our seven RPA classes are larger than the treatment effects being evaluated in many studies. RPA classes 1 and 2, for which the initial histology was other than GBM and KPS was ≥ 80, consisted of 20% of the patients in our database. Their median survival time was greater than 17 months. Compared with the 7.0-month median survival time for our entire cohort of patients, this survival difference is quite large. If the analysis were restricted to those patients whose initial diagnosis was GBM, the median survival times for the nodes varies from 4.9 to 10.4 months.
Many phase II studies in recurrent glioma restrict enrollment to GBM or GBM and AA, but they do not restrict enrollment to those who had an initial diagnosis of high-grade glioma. Our results suggest that this may be inappropriate if the goal is to have a relatively homogeneous population that could be compared with other similarly constructed trials. Although a few of the studies in the present analysis allowed on-study diagnoses of anaplastic oligodendroglioma, there were relatively few patients with this diagnosis. Excluding these patients from the analysis did not reduce the median survival time for RPA nodes 1 and 2 by more than 0.3 months.
The finding of age, KPS, and extent of resection being prognostic for survival in recurrent glioma is not unexpected. They have been shown to be powerful prognostic factors for survival in newly diagnosed patients using RPA.4 Other studies suggest that corticosteroid dose was prognostic for survival in newly diagnosed gliomas.22-24 The study by Hohwieler Schloss et al22 included patients with all histologic grades and found that the 15 patients with less corticosteroid dependency had a median survival time of 29 months compared with 5 months for the 29 patients with greater corticosteroid dependency.
Nevertheless, very few studies have directly addressed prognostic factors in recurrent gliomas. Wong et al25 performed RPA in recurrent glioma, using histology at recurrence as a prognostic factor and limiting the sample to those with recurrent GBM or AA. Similar to our study, histology was the first split in their RPA, and for the AA subgroup, the next split was KPS. However, they had no additional significant splits in their analysis. Perhaps that is due to the younger age of their patients (median 45 years compared with median 50 years in the present study), and that they were testing age dichotomized at 40 years. A second study found no association of tumor grade, and only KPS was prognostic for survival in recurrent glioma.26
Our study focused on prognostic factors related to survival rather than on progression-free survival (PFS). There are several reasons for this. First, the NABTT CNS Consortium studies included in this analysis had formal end points that were either response rate or survival. Second, the survival end point is unequivocal in contrast to the frequently used 6-month PFS. This measure uses bimonthly MRIs, which are a measure of blood-brain barrier dysfunction rather than true tumor size. Furthermore, it is subjective, susceptible to manipulations of glucocorticoid dose or therapies (which may increase or decrease blood-brain barrier dysfunction), and has an artificial 6-month cutoff even if in retrospect that patient had been experiencing slow progression. Finally, given the huge effect that prognostic factors have on survival in patients with recurrent gliomas as shown in this study, it is highly likely that the same results would apply to PFS as Wong et al25 reported in their study.
There are a few limitations to our study. First, the resulting algorithm has not been validated in a different data set. We plan to validate the algorithm when sufficient patients have been treated on other phase I and II NABTT recurrent glioma trials. Second, no data were collected on subsequent therapies that patients received after going off the study included here. However, this is frequently the case in many trials, and thus contributes to the generalizability of the results. Data from both phase I and II studies were included. However, none of the phase II studies were found to be efficacious, and we first compared the survival times for each study. Lastly, there is some variation in the patient eligibility criteria between studies.
Phase II trials play a critical role in the assessment of novel therapeutic approaches in patients with high-grade gliomas. Given that it would be far too costly and inefficient to conduct large, randomized, prospective trials of all novel treatment concepts, estimated response rates, 6-month PFS, and overall survival from phase II trials are compared to decide which therapies should be studied further. From the data presented in this article, it is clear that patients with recurrent gliomas have strikingly different prognoses depending on their initial histology, age, KPS, and corticosteroid use. The RPA data from this study will permit investigators to design studies with more homogeneous patient populations or to adjust outcome data retrospectively, thereby improving investigators’ abilities to compare outcomes across phase II studies appropriately.
Authors’ Disclosures of Potential Conflicts of Interest
The author(s) indicated no potential conflicts of interest.
Author Contributions
Conception and design: Kathryn A. Carson, Stuart A. Grossman, Joy D. Fisher, Edward G. Shaw
Administrative support: Joy D. Fisher
Provision of study materials or patients: Stuart A. Grossman, Joy D. Fisher, Edward G. Shaw
Collection and assembly of data: Kathryn A. Carson, Stuart A. Grossman, Joy D. Fisher, Edward G. Shaw
Data analysis and interpretation: Kathryn A. Carson, Stuart A. Grossman, Joy D. Fisher, Edward G. Shaw
Manuscript writing: Kathryn A. Carson, Stuart A. Grossman, Joy D. Fisher, Edward G. Shaw
Final approval of manuscript: Kathryn A. Carson, Stuart A. Grossman, Joy D. Fisher, Edward G. Shaw
Appendix
| Characteristic | NABTT Trial | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 9-AC | Suramin | Phenylbutyrate | Aprinocarsen | CPT-11 | Procarbazine | Carmustine Wafer | GliaSite | O6-BG | Onyx | ||||||||||
| Sex, % male | 60 | 100 | 67 | 71 | 59 | 76 | 72 | 71 | 67 | 71 | |||||||||
| Race, % nonwhite | 7 | 0 | 19 | 0 | 9 | 8 | 2 | 29 | 14 | 0 | |||||||||
| Age, median years | 47 | 55 | 51 | 46 | 48 | 56 | 48 | 48 | 52 | 52 | |||||||||
| KPS | |||||||||||||||||||
| Median | 90 | 80 | 80 | 80 | 90 | 80 | 80 | 80 | 90 | 90 | |||||||||
| % 60-80 | 49 | 64 | 61 | 67 | 45 | 65 | 57 | 62 | 45 | 33 | |||||||||
| % 60-70 | 37 | 27 | 33 | 38 | 28 | 29 | 24 | 33 | 29 | 25 | |||||||||
| Initial histology, % GBM | 56 | 73 | 58 | 67 | 72 | 56 | 70 | 71 | 81 | 73 | |||||||||
| On-study histology, % GBM | 62 | 91 | 76 | 76 | 79 | 70 | 77 | 86 | 90 | 83 | |||||||||
| Time from initial dx, median months | 12.8 | 10.7 | 10.2 | 9.4 | 11.0 | 11.5 | 9.1 | 9.5 | 10.3 | 13.6 | |||||||||
| Tumor outside frontal lobe, % yes | 80 | 91 | 89 | 95 | 91 | 81 | 85 | 67 | 80 | 70 | |||||||||
| Corticosteroid use, % yes | 60 | 82 | 84 | 75 | 70 | 58 | 81 | 86 | 71 | 61 | |||||||||
| Anticonvulsant use, % yes | 69 | 91 | 84 | 81 | 72 | 86 | 12 | 67 | 88 | 68 | |||||||||
| Hemoglobin, median | 14.0 | 13.8 | 12.7 | 12.9 | 13.2 | 14.2 | 14.1 | * | 13.8 | 14.5 | |||||||||
| Prior chemotherapy, % > 0 | 69 | 91 | 74 | 86 | 88 | 71 | 56 | 57 | 69 | 91 | |||||||||
| Prior chemotherapy, % > 1 | 10 | 36 | 37 | 38 | 7 | 4 | 17 | 14 | 21 | 32 | |||||||||
| Prior surgery, % > 1 | 71 | 64 | 47 | 52 | 47 | 51 | 30 | 29 | 38 | 9 | |||||||||
| Prior RT, % > 1 | 19 | 27 | 21 | 5 | 3 | 0 | 0 | 14 | 0 | 5 | |||||||||
Abbreviations: NABTT, New Approaches to Brain Tumor Therapy; O6-BG, O6-benzylguanine; 9-AC, 9-aminocamptothecin; CPT-11, irinotecan; KPS, Karnofsky performance score; GBM, glioblastoma multiforme; dx, diagnosis; RT, radiation therapy.
*
No hemoglobin data were available for this study.
| Characteristic | Total No. of Patients | No. of Patients | % | |
|---|---|---|---|---|
| Sex, male | 333 | 228 | 68.5 | |
| Race, nonwhite | 333 | 29 | 8.7 | |
| Age, years | 333 | |||
| Median | 49.8 | |||
| Range | 18.5-75.0 | |||
| KPS | 321 | |||
| Median | 80 | |||
| Range | 60-100 | |||
| 60-80 | 321 | 171 | 53.3 | |
| 60-70 | 321 | 95 | 29.6 | |
| Initial histology, GBM | 325 | 219 | 67.4 | |
| On-study histology, GBM | 329 | 255 | 77.5 | |
| Time from initial dx, months | 325 | |||
| Median | 10.7 | |||
| Range | 3.2-231.1 | |||
| Tumor outside frontal lobe | 307 | 255 | 83.1 | |
| Corticosteroid use | 322 | 227 | 70.5 | |
| Anticonvulsant use | 328 | 227 | 69.2 | |
| Hemoglobin | 246 | |||
| Median | 13.8 | |||
| Range | 9.6-17.5 | |||
| Prior chemotherapy, > 0 | 326 | 241 | 73.9 | |
| Prior chemotherapy, > 1 | 326 | 55 | 16.9 | |
| Prior surgery, > 1 | 328 | 146 | 44.5 | |
| Prior RT, > 1 | 328 | 22 | 6.7 | |
| Surgical protocol | 333 | 130 | 39.0 | |
Abbreviations: KPS, Karnofsky performance score; GBM, glioblastoma multiforme; dx, diagnosis; RT, radiation therapy.
| Variable | Risk Ratio | 95% CI | P |
|---|---|---|---|
| Sex, male v female | 1.10 | 0.86 to 1.40 | .45 |
| Race, nonwhite v white | 0.87 | 0.58 to 1.31 | .51 |
| Age, years | |||
| Decade increase | 1.29 | 1.17 to 1.42 | < .0001 |
| ≥ 40 v < 40 | 1.59 | 1.20 to 2.11 | .001 |
| ≥ 50 v < 50 | 1.65 | 1.31 to 2.08 | < .0001 |
| ≥ 60 v < 60 | 1.71 | 1.30 to 2.23 | < .0001 |
| KPS | |||
| 10-point increase | 1.33 | 1.21 to 1.46 | < .0001 |
| 60-80 v 90-100 | 1.68 | 1.33 to 2.11 | < .0001 |
| 60-70 v 80-100 | 1.98 | 1.54 to 2.55 | < .0001 |
| Initial histology, GBM v other | 2.36 | 1.81 to 3.09 | < .0001 |
| On-study histology, GBM v other | 2.44 | 1.80 to 3.30 | < .0001 |
| Time from initial dx, 1-year increase | 0.93 | 0.89 to 0.98 | .005 |
| Tumor outside frontal lobe, yes v no | 1.88 | 1.36 to 2.60 | .0001 |
| Corticosteroid use, yes v no | 1.65 | 1.28 to 2.12 | .0001 |
| Anticonvulsant use, yes v no | 0.98 | 0.77 to 1.25 | .87 |
| Hemoglobin, 1 unit increase | 1.07 | 0.98 to 1.17 | .11 |
| Prior chemotherapy | |||
| > 0 v 0 | 0.95 | 0.73 to 1.22 | .67 |
| > 1 v 0-1 | 0.84 | 0.61 to 1.14 | .25 |
| Prior surgery, > 1 v 0-1 | 1.02 | 0.82 to 1.28 | .85 |
| Prior RT, > 1 v 0-1 | 0.97 | 0.62 to 1.53 | .91 |
| Surgical protocol, yes v no | 0.86 | 0.68 to 1.08 | .18 |
Abbreviations: KPS, Karnofsky performance score; GBM, glioblastoma multiforme; dx, diagnosis; RT, radiation therapy.
| NABTT Trial | Phase | No. of Patients | Description of Treatment |
|---|---|---|---|
| 9-Aminocamptothecin | I/II | 22/21 | Administered as a 72-hour IV infusion every 2 weeks; starting dose of 850 μg/m2/24 hours was escalated to 1,611 μg/m2/24 hours for patients taking EIACs |
| Suramin | II | 11 | Fixed doses infused during 1 hour |
| Oral phenylbutyrate | I | 21 | Dose escalations of 9, 18, 27, and 36 g/d administered orally in three equally divided doses |
| Aprinocarsen | II | 21 | Administered as a 21-day infusion at a rate of 2.0 mg/kg/d, followed by 7 days of no treatment, then repeated |
| Irinotecan | I/II | 40/18 | Weekly 90-minute IV infusion for 4 weeks, then repeated every 6 weeks; starting dose was 125 mg/m2/wk, MTD was 117 mg/m2/wk for EIAC-and 411 mg/m2/wk for patients taking EIACs |
| Oral procarbazine | I | 49 | Dose escalation of procarbazine given orally once daily for 5 consecutive days repeated monthly; starting dose was 200 mg/m2/d and MTD was 393 mg/m2/d for patients taking EIACs and ≥ 334 mg/m2/d for patients not taking EIACs |
| Carmustine wafers | I | 43 | Dose escalation study of carmustine polymers from 6.5% to 28% carmustine by weight; MTD was 20% |
| GliaSite RTS | I | 21 | Safety and feasibility study of an implanted inflatable balloon catheter and liquid iodine-125 brachytherapy |
| Onyx-015 | I | 24 | Dose escalation study of an intratumoral injection with an E1B-attenuated adenovirus |
| Carmustine and IV O6-BG | I | 42 | Establish the dose of continuous IV infusion of O6-BG (combined with 3.85% carmustine wafers) that suppresses alkylating–DNA alkyl transferase and escalate duration of infusion |
Abbreviations: NABTT, New Approaches to Brain Tumor Therapy; IV, intravenous; EIAC, enzyme-inducing anticonvulsants; MTD, maximum-tolerated dose; RTS, Radiation Therapy System; O6-BG,O6-benzylguanine.
Supported by NABTT Grant No. CA62475.
Presented in part at the 41st Annual Meeting of the American Society of Clinical Oncology, May 13-17, 2005, Orlando, FL.
Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.
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© 2007 by American Society of Clinical Oncology.
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Published in print: June 20, 2007
Published online: September 21, 2016
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Prognostic Factors for Survival in Adult Patients With Recurrent Glioma Enrolled Onto the New Approaches to Brain Tumor Therapy CNS Consortium Phase I and II Clinical Trials. JCO 25, 2601-2606(2007).
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Journal of Clinical Oncology 2007 25:18, 2601-2606
Journal of Clinical Oncology 2007 25:18, 2601-2606
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