Marc Salzberg’s research while affiliated with Tufts University and other places

Aim: To estimate the mean lifetime survival benefit, an essential component of health economic evaluations in oncology, of adding tumor treating fields (TTFields) to maintenance temozolomide (TMZ) for newly diagnosed glioblastoma patients. Methods: We integrated EF-14 trial data with glioblastoma epidemiology data. The model provided for an evidence-based approach to estimate lifetime survival for the material number of EF-14 trial patients still alive at 5 years. Results & conclusion: Patients treated with TTFields and TMZ had an incremental mean lifetime survival of 1.8 years (TTFields/TMZ: 4.2 vs TMZ alone: 2.4). Patients alive at year 2 after starting TTFields had a 20.7% probability of surviving to year 10. The results presented here provide the required incremental survival benefit necessary for a future assessment of the incremental cost–effectiveness of TTFields.

BACKGROUND Glioblastoma (GBM) is the most aggressive form of primary brain cancer. The EF-14 trial for GBM patients reported a 5-year survival rate of 12.8%, the first report from a large randomized controlled trial of 5-year survival greater than 10%. The increased survival compared to previous studies was achieved by adding tumor treating fields (TTFields) to the existing standard of care of radiochemotherapy. An understanding of the predicted long-term prognosis for GBM patients is important to facilitate good clinical, personal and policy decision-making, as survival at 5 years continues to improve. OBJECTIVE To estimate the mean lifetime survival benefit for GBM patients of adding TTFields to the existing standard of care. METHODS Standard regression-based parametric extrapolations of overall survival were constructed and were fit to the EF-14 trial data. These models underestimated the reported long-term GBM survival rates. Parametric models assume a constant hazard function, which was not observed in the EF-14 trial or epidemiological data, resulting in the underestimation. Survival was instead modelled using a previously described method that synthesized EF-14 trial data with GBM epidemiological data and general population survival rates. RESULTS The estimated mean lifetime survival from initiation of adjuvant treatment was 4.2 years with TTFields and 2.4 years without it, an increase of 1.8 years. The estimated incremental life years gained (LYG) was 1.3 years when a 3% discount rate was applied to future survival benefits. TTFields-treated survivors who survived to 2 years were estimated to have a 20.7% chance of surviving to 10 years. CONCLUSIONS The analysis indicated that treating GBM patients with TTFields substantially increased mean lifetime survival, consistent with the clinical findings of the EF-14 trial. Current GBM treatment strategies offer improved prognoses compared to past therapies, and should be considered by physicians, patients and payers in GBM treatment decisions.

Background: Glioblastoma is the most common and aggressive primary brain tumor. Survival times for GBM have improved significantly since 2005. Researchers in 2005 demonstrated that adding TMZ, an oral alkylating agent, to surgery and radiation extended median overall survival from 12 to 15 months, and 2-year survival rates from 11% to 27%. More recently the addition of Tumor Treating Fields (TTFields), a loco-regionally delivered anti-mitotic treatment, to TMZ demonstrated an increase in median overall survival of 5 months, and survival rates of 43% and 17% at 2-years and 4-years respectively. Trial data for TMZ and TTFields both demonstrated increasing conditional probabilities of survival as patients survived longer from diagnosis. Increasing conditional probability of surviving GBM has also been reported in epidemiological literature. Accordingly, standard parametric survival models based on regression analysis will not provide reliable estimates of lifetime survival benefits and an alternative modelling method is provided here. Clinicians and policy makers need to understand the lifetime survival estimates for GBM patients, as the rate of GBM patients surviving to 4-years and 5-years is now significant. Methods: Lifetime patient survival was simulated using a synthesis of parametric survival curves fit to the recently completed EF-14 Trial’s 4-year follow-up data and conditional survival probabilities from a SEER state cancer registries database analysis. The 4-year parametric curves were extrapolated to estimate 5-year survival. We then used GBM-specific conditional survival estimates to model patient survival at 10 and 15 years given survival to year 5, and assumed patients surviving beyond 15 years had survival equivalent to population averages. We performed one-way and probabilistic sensitivity analyses to assess result uncertainty due to parameter variability. Results: Our modeled analysis showed that TTFields plus TMZ resulted in 3.63 (95% credible range [CR], 3.32 to 3.93) life-years versus 2.53 (95% CR, 2.36 to 2.69) life-years for TMZ monotherapy, a difference of 1.10 years (95% CR, 0.96 to 1.23) discounted; the difference was 1.56 years (95% CR, 1.33 to 1.80) undiscounted. The results were most sensitive to uncertainty in the 10- and 15- year survival estimates conditional on survival to years 5 and 10, respectively. Conclusions. This analysis presents a new approach to model lifetime survival benefits of adding TTFields to TMZ for GBM by combining long-term clinical trial data and epidemiological data. The model demonstrates that adding TTFields to TMZ for GBM increases lifetime survival substantially. Citation Format: Greg Guzauskas, Bruce Wang, Marc Salzberg. Modeling long-term survival outcomes in glioblastoma patients treated with TTFields plus temozolomide and temolozomide monotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr CT160. doi:10.1158/1538-7445.AM2017-CT160