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Maximum resection and immunotherapy improve glioblastoma patient survival: a retrospective single-institution prognostic analysis.

ABSTRACT: Glioblastoma (GBM) is a refractory disease with a poor prognosis and various methods, including maximum resection and immunotherapy, have been tested to improve outcomes. In this retrospective study we analyzed the prognostic factors of 277 newly diagnosed GBM patients over 11 years of consecutive cases at our institution to evaluate the effect of these methods on prognosis. Various data, including the extent of removal (EOR) and type of adjuvant therapy, were examined and prognostic relationships were analyzed. The median overall survival (OS) of the entire 277-case cohort, 200 non-biopsy cases, and 77 biopsy cases was 16.6 months, 19.7 months, and 9.7 months, respectively. Gross total removal (GTR; 100% of EOR) was achieved in 32.9% of the cases. Univariate analysis revealed younger age, right side, higher Karnofsky performance status, GTR, intraoperative magnetic resonance imaging (MRI) use for removal, proton therapy, combination immunotherapy, and discharge to home as good prognostic factors. Intraoperative MRI use and EOR were closely related. In the multivariate analysis, GTR, proton therapy, and a combination of immunotherapies, including autologous formalin-fixed tumor vaccine, were the significant prognostic factors. A multivariate analysis of 91 GTR cases showed that immunotherapy contributed to prognostic improvements. The median OS and 5-year OS % values were 36.9 months and 43.3% in GTR cases receiving immunotherapy. In conclusion, GTR, proton therapy, and immunotherapy were good prognostic factors in single-center GBM cases. Tumor vaccine therapy for GTR cases achieved a notably high median survival time and long-term survival ratio, indicating its usefulness in GTR cases.

SUBMITTER: Ishikawa E

PROVIDER: S-EPMC8287820 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Maximum resection and immunotherapy improve glioblastoma patient survival: a retrospective single-institution prognostic analysis.

Ishikawa Eiichi E Sugii Narushi N Matsuda Masahide M Kohzuki Hidehiro H Tsurubuchi Takao T Akutsu Hiroyoshi H Takano Shingo S Mizumoto Masashi M Sakurai Hideyuki H Matsumura Akira A

BMC neurology 20210719 1

Glioblastoma (GBM) is a refractory disease with a poor prognosis and various methods, including maximum resection and immunotherapy, have been tested to improve outcomes. In this retrospective study we analyzed the prognostic factors of 277 newly diagnosed GBM patients over 11 years of consecutive cases at our institution to evaluate the effect of these methods on prognosis. Various data, including the extent of removal (EOR) and type of adjuvant therapy, were examined and prognostic relationshi ...[more]

PMID: 34281518

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Project description:PurposeApproximately 12,000 glioblastomas are diagnosed annually in the United States. The median survival rate for this disease is 12 months, but individual survival rates can vary with patient-specific factors, including extent of surgical resection (EOR). The goal of our investigation is to develop a reliable strategy for personalized survival prediction and for quantifying the relationship between survival, EOR, and adjuvant chemoradiotherapy.Patients and methodsWe used accelerated failure time (AFT) modeling using data from 721 newly diagnosed patients with glioblastoma (from 1993 to 2010) to model the factors affecting individualized survival after surgical resection, and we used the model to construct probabilistic, patient-specific tools for survival prediction. We validated this model with independent data from 109 patients from a second institution.ResultsAFT modeling using age, Karnofsky performance score, EOR, and adjuvant chemoradiotherapy produced a continuous, nonlinear, multivariable survival model for glioblastoma. The median personalized predictive error was 4.37 months, representing a more than 20% improvement over current methods. Subsequent model-based calculations yield patient-specific predictions of the incremental effects of EOR and adjuvant therapy on survival.ConclusionNonlinear, multivariable AFT modeling outperforms current methods for estimating individual survival after glioblastoma resection. The model produces personalized survival curves and quantifies the relationship between variables modulating patient-specific survival. This approach provides comprehensive, personalized, probabilistic, and clinically relevant information regarding the anticipated course of disease, the overall prognosis, and the patient-specific influence of EOR and adjuvant chemoradiotherapy. The continuous, nonlinear relationship identified between expected median survival and EOR argues against a surgical management strategy based on rigid EOR thresholds and instead provides the first explicit evidence supporting a maximum safe resection approach to glioblastoma surgery.

Project description:BackgroundDurvalumab is approved for the treatment of lung cancer, advanced biliary tract cancers, and is also being evaluated in many other solid organ tumors. The aim of our study is to define the incidence, etiology, and outcomes of liver injury in consecutive patients receiving durvalumab-based immunotherapy.Patients and methodsDurvalumab treated patients between 1/2016 - 7/2020 were identified from the electronic medical record. Liver injury was defined as serum AST or ALT ≥ 5x upper limit of normal (ULN), ALP ≥ 2x ULN, bilirubin ≥ 2.5 mg/dl, or INR ≥ 1.5. Potential drug induced liver injury (DILI) cases were adjudicated using expert opinion scoring and confirmed with Roussel Uclaf Causality Assessment Method (RUCAM).ResultsAmongst 112 patients, 58 (52%) had non-small cell lung cancer, the median age was 65 years, and 60% were male. The 21 (19%) liver injury patients were significantly more likely to harbor hepatic metastases (52% vs 17%, p=<0.001), experience tumor progression (67% vs 32%, p=0.01) or die (48% vs 11%, p<0.001) during follow-up compared to the 91 without liver injury. Using multivariate regression analysis, the development of liver injury during treatment as well as baseline hepatic metastases were independently associated with mortality during follow-up. Six of the 21 (29%) liver injury cases were adjudicated as probable DILI with four attributed to durvalumab and two due to other drugs (paclitaxel, pembrolizumab). Durvalumab was permanently discontinued in two DILI patients, three received corticosteroids, and one was successfully rechallenged. Only one patient with DILI developed jaundice, and none required hospitalization. Liver biochemistries normalized in all 6 DILI cases, while they only normalized in 27% of the 15 non-DILI cases (p=0.002). The 6 DILI patients also had a trend towards improved survival compared to those with other causes of liver injury.ConclusionLiver injury was observed in 19% of durvalumab-treated patients and is associated with a greater likelihood of tumor progression and death during follow-up. The four durvalumab DILI cases were mild and self-limited, highlighting the importance of causality assessment to determine the cause of liver injury in oncology patients receiving immunotherapy.

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Maximum resection and immunotherapy improve glioblastoma patient survival: a retrospective single-institution prognostic analysis.

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Maximum resection and immunotherapy improve glioblastoma patient survival: a retrospective single-institution prognostic analysis.

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