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Temporal muscle thickness as an independent prognostic marker in glioblastoma patients-a systematic review and meta-analysis.
Sadhwani, Nidhisha; Aggarwal, Ankita; Mishra, Ayushi; Garg, Kanwaljeet.
Afiliação
  • Sadhwani N; Department of Neurosurgery, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India.
  • Aggarwal A; Department of Radiodiagnosis, VMMC and Safdarjung Hospital, New Delhi, India.
  • Mishra A; Department of Radiodiagnosis, VMMC and Safdarjung Hospital, New Delhi, India.
  • Garg K; Department of Neurosurgery, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India. kanwaljeet84@gmail.com.
Neurosurg Rev ; 45(6): 3619-3628, 2022 Dec.
Article em En | MEDLINE | ID: mdl-36350492
ABSTRACT
Glioblastoma is the most common primary malignant brain tumor in the adult population. It causes the patient to incur a great deal of malady. Even with the advances in management and the Stupp protocol in place, the prognosis remains grim. There are various parameters to evaluate patients' performance status and frailty pre-operatively, but these are mostly subjective and thus suffer from inter-observer variability. Assessment of sarcopenia serves as an objective parameter to assess the patient's performance status pre-operatively. Temporalis muscle thickness serves as a surrogate to assess sarcopenia in patients with glioblastoma. We conducted a literature review and meta-analysis to determine the prognostic implications of temporalis muscle thickness in 3283 patients with primary glioblastoma. The pooled overall survival hazard's ratio of thick versus thin TMT was 0.54. The pooled progression-free survival hazard's ratio of thick versus thin TMT was 0.38. Thus, the main finding of this study is that thicker temporal muscle is associated with better OS and PFS as compared to thinner temporal muscle. We thus conclude that TMT is a viable surrogate for predicting sarcopenia and survival in primary glioblastoma. TMT measurement is extremely easy and can be incorporated as a part of the routine neurosurgical workflow in these patients. Survival prediction will help inform treatment decisions in glioblastoma patients having poor prognosis, at the initial diagnosis itself.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Glioblastoma / Sarcopenia Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Glioblastoma / Sarcopenia Idioma: En Ano de publicação: 2022 Tipo de documento: Article