Predictive models for postoperative hydrocephalus in pediatric patients with posterior fossa tumors

Hendrik-Jan MijderwijkDepartment of Neurosurgery, Heinrich Heine University, Medical Faculty, Düsseldorf, Germany; and

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Thomas BeezDepartment of Neurosurgery, Heinrich Heine University, Medical Faculty, Düsseldorf, Germany; and

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Daniel HänggiDepartment of Neurosurgery, Heinrich Heine University, Medical Faculty, Düsseldorf, Germany; and

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Daan NieboerDepartment of Public Health, Erasmus MC, University Medical Center, Rotterdam, The Netherlands

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Publication Date:
21 Oct 2022
Page Range:
92–94
Volume/Issue:
Volume 31: Issue 1
DOI link:
https://doi.org/10.3171/2022.6.PEDS21582
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Cover Journal of Neurosurgery: Pediatrics

Volume 31: Issue 1 (Jan 2023)

in Journal of Neurosurgery: Pediatrics

Figure from Candela-Cantó et al. (pp 61–70).

Contributor Notes

Correspondence Hendrik-Jan Mijderwijk: hendrik-jan.mijderwijk@med.uni-duesseldorf.de.

INCLUDE WHEN CITING Published online October 21, 2022; DOI: 10.3171/2022.6.PEDS21582.

Disclosures The authors report no conflict of interest.

ACCOMPANYING EDITORIAL DOI: 10.3171/2022.8.PEDS22253.

Page Count:
3
  • 1

    Riva-Cambrin J, Detsky AS, Lamberti-Pasculli M, et al. Predicting postresection hydrocephalus in pediatric patients with posterior fossa tumors. J Neurosurg Pediatr. 2009;3(5):378–385.

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  • 2

    Foreman P, McClugage S III, Naftel R, et al. Validation and modification of a predictive model of postresection hydrocephalus in pediatric patients with posterior fossa tumors. J Neurosurg Pediatr. 2013;12(3):220–226.

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    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    Pitsika M, Fletcher J, Coulter IC, Cowie CJA. A validation study of the modified Canadian Preoperative Prediction Rule for Hydrocephalus in children with posterior fossa tumors. J Neurosurg Pediatr. 2021;28(2):121–127.

    • Search Google Scholar
    • Export Citation
  • 4

    Mijderwijk HJ, Steiger HJ. Predictive analytics in clinical practice: advantages and disadvantages. Acta Neurochir Suppl. 2022;134:263–268.

  • 5

    Mijderwijk HJ, Steyerberg EW, Steiger HJ, Fischer I, Kamp MA. Fundamentals of clinical prediction modeling for the neurosurgeon. Neurosurgery. 2019;85(3):302–311.

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    • Search Google Scholar
    • Export Citation
  • 6

    Mijderwijk HJ, Beez T, Hänggi D, Nieboer D. Application of clinical prediction modeling in pediatric neurosurgery: a case study. Childs Nerv Syst. 2021;37(5):1495–1504.

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    • Search Google Scholar
    • Export Citation
  • 7

    Debray TPA, Vergouwe Y, Koffijberg H, Nieboer D, Steyerberg EW, Moons KGM. A new framework to enhance the interpretation of external validation studies of clinical prediction models. J Clin Epidemiol. 2015;68(3):279–289.

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    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Moons KGM, Altman DG, Reitsma JB, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1–W73.

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    • Search Google Scholar
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  • 9

    Steyerberg EW, Vickers AJ, Cook NR, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21(1):128–138.

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    • Search Google Scholar
    • Export Citation
  • 10

    Maria NUH, Siddiq QUA, Fatima NUA. Canadian Preoperative Prediction Rule for Hydrocephalus: suggestions to improve validity. Letter. J Neurosurg Pediatr. 2021;29(1):122–123.

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    • Search Google Scholar
    • Export Citation
  • 11

    Mijderwijk HJ, van Beek S, Nieboer D. Updating clinical prediction models: an illustrative case study. Acta Neurochir Suppl. 2022;134:109–113.

  • 12

    Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. 2006;26(6):565–574.

  • 13

    Mijderwijk HJ, Nieboer D. Is my clinical prediction model clinically useful? A primer on decision curve analysis. Acta Neurochir Suppl. 2022;134:115–118.

  • 14

    Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMC Med. 2015;13(1):1–10.

    • Crossref
    • Search Google Scholar
    • Export Citation

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