Impact of treatment decision algorithms on treatment costs in recurrent glioblastoma: a health economic study | Zendy

Cdric M. Panje | Zendy; Paul Martin Putora | Zendy; Thomas Hundsberger | Zendy; Andreas F. Hottinger | Zendy; Ulrich Roelcke | Zendy; Gianfranco Pesce | Zendy; Evelyn Herrmann | Zendy; Klazien MatterWalstra | Zendy

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Impact of treatment decision algorithms on treatment costs in recurrent glioblastoma: a health economic study

Author(s) -

Cdric M. Panje,

Paul Martin Putora,

Thomas Hundsberger,

Andreas F. Hottinger,

Ulrich Roelcke,

Gianfranco Pesce,

Evelyn Herrmann,

Klazien MatterWalstra

Publication year - 2019

Publication title -

schweizerische medizinische wochenschrift

Language(s) - English

Resource type - Journals

ISSN - 0036-7672

DOI - 10.4414/smw.2019.20153

Subject(s) - medicine , univariate , univariate analysis , glioblastoma , probabilistic logic , cost–benefit analysis , health care , multivariate analysis , machine learning , artificial intelligence , multivariate statistics , computer science , ecology , cancer research , biology , economics , economic growth

Institutional treatment algorithms can be used to estimate the average treatment costs per patient, which are, however, highly sensitive to probability changes of individual decision criteria. Our study demonstrates a high variability in treatment costs for recurrent GBM among eight Swiss neuro-oncology centres based on individual institutional treatment algorithms.

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