Patient characteristics in each of the seven trials are listed in the Data Supplement. For the combined group, the median age was 54 years (range, 19 to 77 years), and the median baseline KPS was 90 (range, 60 to 100). Sixty-three percent of the patients were men, and 91% were white. Twelve percent of the patients had biopsy only before starting protocol treatment, 70% had subtotal resection, and the remaining 19% underwent gross total resection.
The estimated median survival and the survival rates at 26, 52, and 78 weeks for the pre-TMZ studies and for each recent UCSF study separately are listed in the Data Supplement. At the time of this analysis, 26 of 370 patients in the pre-TMZ trials were censored for survival with a median follow-up of 225 weeks (range, 1 to 881 weeks). One patient in RTRT was censored for survival at week 134, four patients in TTRT were censored with a median follow-up of 192 weeks (range, 146 to 243 weeks), and nine patients in OTRT were censored with a median follow-up of 250 weeks (range, 209 to 285 weeks). The latest study, OTRT, which combined the use of TMZ with erlotinib (an orally active selective inhibitor of the tyrosine kinase EGFR) during and after radiotherapy, was the only trial that successfully demonstrated prolonged survival when compared with its historical control, which consisted of TTRT and RTRT. In particular, this treatment combination was associated with the highest estimated survival at each time point that we investigated, with a median survival of 84 weeks. The estimated median survival for pre-TMZ trials, TTRT, and RTRT were 58, 70, and 57 weeks, respectively. A presents the Kaplan-Meier curves for survival separately for each post-TMZ protocol. The OTRT study showed significant survival advantage compared with the other two trials (OTRT v TTRT P = .025; OTRT v RTRT P < .001). No statistically significant survival difference was found between TTRT and RTRT protocols (P = .07). B shows the Kaplan-Meier curves of the pre-TMZ trials compared with the data combining TTRT and RTRT, suggesting that the survival distributions of these two cohorts of patients were comparable (P = .34). On the basis of these reasons, the pre-TMZ trials were combined with TTRT and RTRT for the conditional probability estimation. OTRT was reported separately because of its superior survival outcome. In general, survival probability seemed to decrease most rapidly in the first 2 years after initial diagnosis (B). The second column of gives the estimated survival probabilities separately for the combined data (pre-TMZ data + TTRT + RTRT) and OTRT; the observed 6-month and 1-, 2-, 3-, and 4-year survival rates were 80%, 58%, 20%, 10%, and 7%, respectively, for the combined data and 92%, 68%, 32%, 23%, and 16%, respectively, for OTRT.
Fig 2. Kaplan-Meier curves for survival in (A) three post-temozolomide (TMZ) studies on the basis of the Stupp regimen (OTRT v TTRT, P = .025; OTRT v RTRT, P < .001; TTRT v RTRT, P = .07; all adjusting for age, Karnofsky performance score [KPS], and (more ...)
Conditional Probabilities of Survival at Various Time Points
Conditional Probabilities of Survival
gives the conditional probabilities of survival at various time points for the cohort combining pre-TMZ data, TTRT, and RTRT (top) and OTRT (bottom) separately. For example, the conditional probability of surviving to 4 years after survival to 2 years (ie, surviving an additional 2 years) in the combined cohort was 34% (95% CI, 24% to 44%). This was markedly higher than the observed 4-year survival rate of 7% (95% CI, 5% to 10%). Conditional probabilities of other time points can be obtained similarly. A presents the probabilities of survival to 4 years post diagnosis for this cohort as the number of months after diagnosis increases.
Fig 3. (A) Conditional probability of survival at 4 years given survival to various time points, and (B) conditional probability of surviving an additional year at various time points. Note that these data combine pre-temozolomide, TTRT, and RTRT trials. The (more ...)
The conditional probability of survival also gives a prediction of surviving the next year for GBM survivors. For example, in the combined cohort of patients on pre-TMZ, TTRT, and RTRT, the conditional probabilities of surviving an additional year given survival to 1, 2, 3, and 4 years after diagnosis were 35%, 49%, 69%, and 93%, respectively. B depicts the conditional probabilities of living an additional year given survival at various time points after diagnosis. Interestingly, compared with the unconditional probability of surviving 1 year after diagnosis (58%), there appears to be first a decrease in the conditional probability of surviving an additional year at 6 months and 1 year, followed by an increasing trend after 1.5 years. At 3 years, the conditional probability of surviving an additional year (69%) has exceeded the unconditional 1-year survival rate. This indicates that the estimated 1-year survival rate for a patient who had already lived for 3 years may be higher than a patient who was recently diagnosed.
Assessment of Prognostic Values of Patient Factors According to the 1-Year Landmark
By using three recent UCSF trials, we evaluated whether putative prognostic variables, such as age, KPS, and progression status, were predictive of subsequent survival at the 1-year landmark. At the 1-year time point, KPS was available for 85 patients. Seventy (82%) of these patients had a KPS of 70 or higher. Ten of these patients died around the 1-year landmark (KPS = 0). Patients who died or were lost to follow-up within 1 year post diagnosis were excluded from the analysis, and survival was measured from the 1-year time point. presents the results of the Cox proportional hazards models side-by-side with clinical factors at baseline (left) and at the 1-year time point (right). As expected, baseline KPS and age were both significantly predictive of survival (KPS HR, 0.98; KPS P = .04; age [10 years] HR, 1.34; age [10 years] P < .001). At the 1-year landmark, lower KPS and prior progression were significantly associated with higher risk of death (P < .001 for both variables). However, age did not reach statistical significance (HR [10 years], 1.22; P = .25). The test of interaction indicated that the HR of age at baseline was significantly different from that at the 1-year landmark (P = .001). Although the extent of resection was not predictive of survival at both time points, we note the drastic difference in the HR estimates comparing biopsy to subtotal resection at the two time points (baseline HR, 1.52; 1-year HR, 0.4). Although the reason for this reversed effect is unclear, this difference is less persuasive on the basis of the marginally significant P value (test of interaction P = .04) and the limited sample size available in the biopsy category at the 1-year landmark (n = 7).
Multivariable Cox Proportional Hazards Analysis of Survival at Baseline and at 1-Year Landmark on the Basis of Three Recent UCSF Post-TMZ Trials
Test for Constant Hazard of Death Assumption (Exponential Distribution)
The likelihood ratio test comparing the Weibull and the exponential distributions indicated that the Weibull distribution fits the data significantly better (P = .02), demonstrating the violation of the constant hazard assumption. presents the comparison of the Kaplan-Meier curve and a survival curve on the basis of the exponential distribution assumption. The departure of the Kaplan-Meier curve from the curve that is based on the exponential distribution illustrates the nature of this difference in this population.