The impact of survivorship bias in glioblastoma research

Francesco Pasqualetti; Alessandro Barberis; Sofia Zanotti; Nicola Montemurro; Gian Luca De Salvo; Riccardo Soffietti; Chiara Maria Mazzanti; Tamara Ius; Maria Caffo; Fabiola Paiar; Guido Bocci; Giuseppe Lombardi; Adrian L Harris; Francesca M Buffa

doi:10.1016/j.critrevonc.2023.104065

The impact of survivorship bias in glioblastoma research

Crit Rev Oncol Hematol. 2023 Aug:188:104065. doi: 10.1016/j.critrevonc.2023.104065. Epub 2023 Jun 29.

Authors

Affiliations

¹ Department of Oncology, University of Oxford, Oxford, UK; Radiation Oncology, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy. Electronic address: [email protected].
² Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
³ Anatomic Pathology Unit, IRCCS Humanitas University Research Hospital, Milan, Italy.
⁴ Department of Neurosurgery, Azienda Ospedaliero Universitaria Pisana (AOUP), Pisa, Italy.
⁵ Istituto Oncologico Veneto-IRCCS, Padua, Italy.
⁶ Division of Neuro-Oncology, Department of Neuroscience, University and City of Health and Science University Hospital, Turin, Italy.
⁷ Fondazione Pisana per la Scienza, Pisa, Italy.
⁸ Neurosurgery Unit, Head-Neck and NeuroScience Department University Hospital of Udine, p.le S. Maria della Misericordia 15, 33100 Udine, Italy.
⁹ Unit of Neurosurgery, Department of Biomorphology and Dental Sciences and Morfophunctional Imaging, University Hospital "G. Martino", Messina, Italy.
¹⁰ Radiation Oncology, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy.
¹¹ Department of Clinical and Experimental Medicine, University of Pisa, I-56126 Pisa, Italy.
¹² Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy.
¹³ Department of Oncology, University of Oxford, Oxford, UK.
¹⁴ Department of Oncology, University of Oxford, Oxford, UK; Department of Computing Sciences, Bocconi University, Milan, Italy; Institute for Data Science and Analytics, Bocconi University, Milano, Italy.

PMID: 37392899
DOI: 10.1016/j.critrevonc.2023.104065

Abstract

Despite advances in the therapy of Central Nervous System (CNS) malignancies, treatment of glioblastoma (GB) poses significant challenges due to GB resistance and high recurrence rates following post-operative radio-chemotherapy. The majority of prognostic and predictive GB biomarkers are currently developed using tumour samples obtained through surgical interventions. However, the selection criteria adopted by different neurosurgeons to determine which cases are suitable for surgery make operated patients not representative of all GB cases. Particularly, geriatric and frail individuals are excluded from surgical consideration in some cancer centers. Such selection generates a survival (or selection) bias that introduces limitations, rendering the patients or data chosen for downstream analyses not representative of the entire community. In this review, we discuss the implication of survivorship bias on current and novel biomarkers for patient selection, stratification, therapy, and outcome analyses.

Keywords: Biomarkers; Glioblastoma; Liquid biopsy; Methodology; O6-methylguanine-DNA methyltransferase (MGMT) methylation; Research; Selection bias; Translational research.

Publication types

Review

MeSH terms

Aged
Biomarkers, Tumor / metabolism
Brain Neoplasms* / diagnosis
Brain Neoplasms* / genetics
Brain Neoplasms* / therapy
DNA Methylation
DNA Repair Enzymes / genetics
DNA Repair Enzymes / metabolism
DNA Repair Enzymes / therapeutic use
Dacarbazine
Glioblastoma* / drug therapy
Humans
Prognosis
Survivorship
Temozolomide / therapeutic use

Substances

Temozolomide
Dacarbazine
Biomarkers, Tumor
DNA Repair Enzymes

Grants and funding

23969/CRUK_/Cancer Research UK/United Kingdom