Is age an additional factor in the treatment of elderly patients with glioblastoma? A new stratification model: an Italian Multicenter Study

  • Tamara Ius
    Neurosurgery Unit, Department of Neurosciences, Santa Maria della Misericordia University Hospital, Udine;
  • Teresa Somma
    Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples;
  • Roberto Altieri
    Department of Medical and Surgical Sciences and Advanced Technologies (G.F. Ingrassia); Neurological Surgery, Policlinico “G. Rodolico - San Marco” University Hospital, University of Catania;
  • Filippo Flavio Angileri
    Division of Neurosurgery, BIOMORF Department, University of Messina;
  • Giuseppe Maria Barbagallo
    Department of Medical and Surgical Sciences and Advanced Technologies (G.F. Ingrassia); Neurological Surgery, Policlinico “G. Rodolico - San Marco” University Hospital, University of Catania;
  • Paolo Cappabianca
    Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples;
  • Francesco Certo
    Department of Medical and Surgical Sciences and Advanced Technologies (G.F. Ingrassia); Neurological Surgery, Policlinico “G. Rodolico - San Marco” University Hospital, University of Catania;
  • Fabio Cofano
    Department of Neuroscience “Rita Levi Montalcini,” Neurosurgery Unit, University of Turin;
  • Alessandro D’Elia
    Department of Neurosurgery “Giampaolo Cantore”–IRCSS Neuromed, Pozzilli;
  • Giuseppe Maria Della Pepa
    Institute of Neurosurgery, Fondazione Policlinico Gemelli, Catholic University, Rome;
  • Vincenzo Esposito
    Department of Neurosurgery “Giampaolo Cantore”–IRCSS Neuromed, Pozzilli;
  • Marco Maria Fontanella
    Division of Neurosurgery, Department of Surgical Specialties, Radiological Sciences and Public Health, University of Brescia;
  • Antonino Germanò
    Division of Neurosurgery, BIOMORF Department, University of Messina;
  • Diego Garbossa
    Department of Neuroscience “Rita Levi Montalcini,” Neurosurgery Unit, University of Turin;
  • Miriam Isola
    Department of Medicine, University of Udine;
  • Giuseppe La Rocca
    Institute of Neurosurgery, Fondazione Policlinico Gemelli, Catholic University, Rome;
  • Francesco Maiuri
    Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples;
  • Alessandro Olivi
    Institute of Neurosurgery, Fondazione Policlinico Gemelli, Catholic University, Rome;
  • Pier Paolo Panciani
    Division of Neurosurgery, Department of Surgical Specialties, Radiological Sciences and Public Health, University of Brescia;
  • Fabrizio Pignotti
    Department of Neurosurgery, Mater Olbia Hospital, Olbia, Italy
  • Miran Skrap
    Neurosurgery Unit, Department of Neurosciences, Santa Maria della Misericordia University Hospital, Udine;
  • Giannantonio Spena
    Department of Neurosurgery, Alessandro Manzoni Hospital, Lecco; and
  • Giovanni Sabatino
    Institute of Neurosurgery, Fondazione Policlinico Gemelli, Catholic University, Rome;

抄録

<jats:sec><jats:title>OBJECTIVE</jats:title><jats:p>Approximately half of glioblastoma (GBM) cases develop in geriatric patients, and this trend is destined to increase with the aging of the population. The optimal strategy for management of GBM in elderly patients remains controversial. The aim of this study was to assess the role of surgery in the elderly (≥ 65 years old) based on clinical, molecular, and imaging data routinely available in neurosurgical departments and to assess a prognostic survival score that could be helpful in stratifying the prognosis for elderly GBM patients.</jats:p></jats:sec><jats:sec><jats:title>METHODS</jats:title><jats:p>Clinical, radiological, surgical, and molecular data were retrospectively analyzed in 322 patients with GBM from 9 neurosurgical centers. Univariate and multivariate analyses were performed to identify predictors of survival. A random forest approach (classification and regression tree [CART] analysis) was utilized to create the prognostic survival score.</jats:p></jats:sec><jats:sec><jats:title>RESULTS</jats:title><jats:p>Survival analysis showed that overall survival (OS) was influenced by age as a continuous variable (p = 0.018), <jats:italic>MGMT</jats:italic> (p = 0.012), extent of resection (EOR; p = 0.002), and preoperative tumor growth pattern (evaluated with the preoperative T1/T2 MRI index; p = 0.002). CART analysis was used to create the prognostic survival score, forming six different survival groups on the basis of tumor volumetric, surgical, and molecular features. Terminal nodes with similar hazard ratios were grouped together to form a final diagram composed of five classes with different OSs (p < 0.0001). EOR was the most robust influencing factor in the algorithm hierarchy, while age appeared at the third node of the CART algorithm. The ability of the prognostic survival score to predict death was determined by a Harrell’s c-index of 0.75 (95% CI 0.76–0.81).</jats:p></jats:sec><jats:sec><jats:title>CONCLUSIONS</jats:title><jats:p>The CART algorithm provided a promising, thorough, and new clinical prognostic survival score for elderly surgical patients with GBM. The prognostic survival score can be useful to stratify survival risk in elderly GBM patients with different surgical, radiological, and molecular profiles, thus assisting physicians in daily clinical management. The preliminary model, however, requires validation with future prospective investigations. Practical recommendations for clinicians/surgeons would strengthen the quality of the study; e.g., surgery can be considered as a first therapeutic option in the workflow of elderly patients with GBM, especially when the preoperative estimated EOR is greater than 80%.</jats:p></jats:sec>

収録刊行物

  • Neurosurgical Focus

    Neurosurgical Focus 49 (4), E13-, 2020-10

    Journal of Neurosurgery Publishing Group (JNSPG)

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