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Outcome prediction in brain tumor surgery: a literature review on the influence of nonmedical factors

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Abstract

The purpose of the present study was to review the existing data on preoperative nonmedical factors that are predictive of outcome in brain tumor surgery. Our hypothesis was that also the individual characteristics (e.g., emotional state, cognitive status, social relationships) could influence the postoperative course in addition to clinical factors usually investigated in brain tumor surgery. PubMed, Embase, and Scopus were searched from 2008 to 2018 using terms relating to brain tumors, craniotomy, and predictors. All types of outcome were considered: clinical, cognitive, and psychological. Out of 6.288 records identified, 16 articles were selected for analysis and a qualitative synthesis of the prognostic factors was performed. The following nonmedical factors were found to be predictive of surgical outcomes: socio-demographic (age, marital status, type of insurance, gender, socio-economic status, type of hospital), cognitive (preoperative language and cognitive deficits, performance at TMT-B test), and psychological (preoperative depressive symptoms, personality traits, autonomy for daily activities, altered mental status). This review showed that nonmedical predictors of outcome exist in brain tumor surgery. Consequently, individual characteristics (e.g., emotional state, cognitive status, social relationships) can influence the postoperative course in addition to clinical factors.

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References

  1. Altman DG (2001) Systematic reviews of evaluations of prognostic variables. BMJ 323:224–228

    Article  CAS  Google Scholar 

  2. Ambekar S, Sharma M, Madhugiri VS, Nanda A (2013) Trends in intracranial meningioma surgery and outcome: a Nationwide Inpatient Sample database analysis from 2001 to 2010. J Neuro-Oncol 114:299–307

    Article  Google Scholar 

  3. Bekelis K, Bakhoum SF, Desai A, Mackenzie TA, Roberts DW (2013) Outcome prediction in intracranial tumor surgery: the National Surgical Quality Improvement Program 2005-2010. J Neuro-Oncol 113:57–64

    Article  Google Scholar 

  4. Bunevicius A, Tamasauskas S, Deltuva V, Tamasauskas A, Radziunas A, Bunevicius R (2014) Predictors of health-related quality of life in neurosurgical brain tumor patients: focus on patient-centered perspective. Acta Neurochir 156:367–374

    Article  Google Scholar 

  5. Bunevicius A (2018) Personality traits, patient centered health status and prognosis of brain tumor patients. J Neuro-Oncol 137:593–600

  6. Bunevicius A, Deltuva VP, Tamasauskas A (2017) Association of pre-operative depressive and anxiety symptoms with five-year survival of glioma and meningioma patients: a prospective cohort study. Oncotarget 8:57543–57551

    Article  Google Scholar 

  7. Chaichana K, Parker S, Olivi A, Quiñones-Hinojosa A (2010) A proposed classification system that projects outcomes based on preoperative variables for adult patients with glioblastoma multiforme. J Neurosurg 112:997–1004

    Article  Google Scholar 

  8. Davis FG, McCarthy BJ, Freels S, Kupelian V, Bondy ML (1999) The conditional probability of survival of patients with primary malignant brain tumors: surveillance, epidemiology, and end results (SEER) data. Cancer 85:485–491

    Article  CAS  Google Scholar 

  9. de Rooij NK, Rinkel GJ, Dankbaar JW, Frijns CJ (2013) Delayed cerebral ischemia after subarachnoid hemorrhage: a systematic review of clinical, laboratory, and radiological predictors. Stroke 44:43–54

    Article  Google Scholar 

  10. Drewes C, Sagberg LM, Jakola AS, Solheim O (2018) Perioperative and postoperative quality of life in patients with glioma-a longitudinal cohort study. World Neurosurg 117:e465–e474

    Article  Google Scholar 

  11. Gulati S, Jakola AS, Johannesen TB, Solheim O (2012) Survival and treatment patterns of glioblastoma in the elderly: a population-based study. World Neurosurg 78:518–526

    Article  Google Scholar 

  12. Hooten KG, Neal D, Lovaton Espadin RE, Gil JN, Azari H, Rahman M (2015) Insurance status influences the rates of reportable quality metrics in brain tumor patients: a nationwide inpatient sample study. Neurosurgery 76:239–247 discussion 247-248

    Article  Google Scholar 

  13. Ilmberger J, Ruge M, Kreth FW, Briegel J, Reulen HJ, Tonn JC (2008) Intraoperative mapping of language functions: a longitudinal neurolinguistic analysis. J Neurosurg 109:583–592

    Article  Google Scholar 

  14. Jakola AS, Unsgård G, Solheim O (2011) Quality of life in patients with intracranial gliomas: the impact of modern image-guided surgery. J Neurosurg 114:1622–1630

    Article  Google Scholar 

  15. Lacroix M, Abi-Said D, Fourney DR, Gokaslan ZL, Shi W, DeMonte F, Lang FF, McCutcheon I, Hassenbusch SJ, Holland E, Hess K, Michael C, Miller D, Sawaya R (2001) A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J Neurosurg 95:190–198

    Article  CAS  Google Scholar 

  16. Lee ST, Park CK, Kim JW, Park MJ, Lee H, Lim JA, Choi SH, Kim TM, Lee SH, Park SH, Kim IH, Lee KM (2015) Early cognitive function tests predict early progression in glioblastoma. Neurooncol Pract 2:137–143

    PubMed  PubMed Central  Google Scholar 

  17. Lynch JC, Welling L, Escosteguy C, Pereira AG, Andrade R, Pereira C (2013) Socioeconomic and educational factors interference in the prognosis for glioblastoma multiform. Br J Neurosurg 27:80–83

    Article  Google Scholar 

  18. Marcus HJ, Williams S, Hughes-Hallett A, Camp SJ, Nandi D, Thorne L (2017) Predicting surgical outcome in patients with glioblastoma multiforme using pre-operative magnetic resonance imaging: development and preliminary validation of a grading system. Neurosurg Rev 40:621–631

    Article  Google Scholar 

  19. Mineo JF, Bordron A, Baroncini M, Ramirez C, Maurage CA, Blond S et al (2007) Prognosis factors of survival time in patients with glioblastoma multiforme: a multivariate analysis of 340 patients. Acta Neurochir 149:245–252 [discussion 252–253]

    Article  Google Scholar 

  20. Pan IW, Ferguson SD, Lam S (2015) Patient and treatment factors associated with survival among adult glioblastoma patients: a USA population-based study from 2000-2010. J Clin Neurosci 22:1575–1581

    Article  Google Scholar 

  21. Pirracchio R, Resche-Rigon M, Bresson D, Basta B, Welschbillig S, Heyer L et al (2010) One-year outcome after neurosurgery for intracranial tumor in elderly patients. J Neurosurg Anesthesiol 22:342–346

    Article  Google Scholar 

  22. Sagberg LM, Drewes C, Jakola AS, Solheim O (2017) Accuracy of operating neurosurgeons’ prediction of functional levels after intracranial tumor surgery. J Neurosurg 126:1173–1180

    Article  Google Scholar 

  23. Sanai N, Polley MY, McDermott MW, Parsa AT, Berger MS (2011) An extent of resection threshold for newly diagnosed glioblastomas. J Neurosurg 115:3–8

    Article  Google Scholar 

  24. Senders JT, Staples PC, Karhade AV, Zaki MM, Gormley WB, Broekman MLD et al (2018) Machine learning and neurosurgical outcome prediction: a systematic review. World Neurosurg 109:476–486

    Article  Google Scholar 

  25. Stark AM, van de Bergh J, Hedderich J, Mehdorn HM, Nabavi A (2012) Glioblastoma: clinical characteristics, prognostic factors and survival in 492 patients. Clin Neurol Neurosurg 114:840–845

    Article  Google Scholar 

  26. Trikalinos NA, Kwok Y, Goloubeva O, Mehta M, Sausville E (2016) Socioeconomic status and survival in glioblastoma. Int J Clin Exp Med 9:4131–4136

    CAS  Google Scholar 

  27. Wang X, Li J, Chen J, Fan S, Chen W, Liu F, Chen D, Hu X (2018) Health-related quality of life and posttraumatic growth in low-grade gliomas in China: a prospective study. World Neurosurg 111:e24–e31

    Article  Google Scholar 

  28. Weldring T, Smith SM (2013) Patient-reported outcomes (PROs) and patient-reported outcome measures (PROMs). Health Serv Insights 6:61–68

    PubMed  PubMed Central  Google Scholar 

  29. Wu AS, Witgert ME, Lang FF, Xiao L, Bekele BN, Meyers CA, Ferson D, Wefel JS (2011) Neurocognitive function before and after surgery for insular gliomas. J Neurosurg 115:1115–1125

    Article  Google Scholar 

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Authors and Affiliations

  1. Neurology, Public Health and Disability Unit, Fondazione IRCSS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy

    Silvia Schiavolin, Alberto Raggi, Chiara Scaratti, Claudia Toppo, Fabiola Silvaggi, Davide Sattin & Matilde Leonardi

  2. Division of Neurosurgery II, Fondazione IRCSS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy

    Morgan Broggi & Paolo Ferroli

Authors
  1. Silvia Schiavolin
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  2. Alberto Raggi
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  3. Chiara Scaratti
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  4. Claudia Toppo
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  5. Fabiola Silvaggi
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  6. Davide Sattin
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  7. Morgan Broggi
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  8. Paolo Ferroli
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  9. Matilde Leonardi
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Contributions

Silvia Schiavolin had the idea for this article, performed the literature review and data analysis, and drafted the work. Alberto Raggi, Chiara Scaratti, Claudia Toppo, Fabiola Silvaggi, and Davide Sattin performed literature review and critically revised the work. Morgan Broggi, Paolo Ferroli, and Matilde Leonardi critically revised the work.

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Correspondence to Silvia Schiavolin.

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No ethical approval was required, as this is a literature review.

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This article, being a literature review, does not contain any studies with human participants performed by any of the authors, and is based solely on the analysis of previously published literature.

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Schiavolin, S., Raggi, A., Scaratti, C. et al. Outcome prediction in brain tumor surgery: a literature review on the influence of nonmedical factors. Neurosurg Rev 44, 807–819 (2021). https://doi.org/10.1007/s10143-020-01289-0

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  • DOI: https://doi.org/10.1007/s10143-020-01289-0

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