Age-adjusted Charlson comorbidity index in recurrent glioblastoma: a new prognostic factor?


Journal

BMC neurology
ISSN: 1471-2377
Titre abrégé: BMC Neurol
Pays: England
ID NLM: 100968555

Informations de publication

Date de publication:
21 Jan 2022
Historique:
received: 02 11 2020
accepted: 22 12 2021
entrez: 22 1 2022
pubmed: 23 1 2022
medline: 27 1 2022
Statut: epublish

Résumé

For recurrent glioblastoma (GB) patients, several therapy options have been established over the last years such as more aggressive surgery, re-irradiation or chemotherapy. Age and the Karnofsky Performance Status Scale (KPSS) are used to make decisions for these patients as these are established as prognostic factors in the initial diagnosis of GB. This study's aim was to evaluate preoperative patient comorbidities by using the age-adjusted Charlson Comorbidity Index (ACCI) as a prognostic factor for recurrent GB patients. In this retrospective analysis we could include 123 patients with surgery for primary recurrence of GB from January 2007 until December 2016 (43 females, 80 males, mean age 57 years (range 21-80 years)). Preoperative age, sex, ACCI, KPSS and adjuvant treatment regimes were recorded for each patient. Extent of resection (EOR) was recorded as a complete/incomplete resection of the contrast-enhancing tumor part. Median overall survival (OS) was 9.0 months (95% CI 7.1-10.9 months) after first re-resection. Preoperative KPSS > 80% (P < 0.001) and EOR (P = 0.013) were associated with significantly improved survival in univariate analysis. Including these factors in multivariate analysis, preoperative KPSS < 80 (HR 2.002 [95% CI: 1.246-3.216], P = 0.004) and EOR are the only significant prognostic factor (HR 1.611 [95% CI: 1.036-2.505], P = 0.034). ACCI was not shown as a prognostic factor in univariate and multivariate analyses. For patients with surgery for recurrent glioblastoma, the ACCI does not add further information about patient's prognosis besides the well-established KPSS and extent of resection.

Sections du résumé

BACKGROUND BACKGROUND
For recurrent glioblastoma (GB) patients, several therapy options have been established over the last years such as more aggressive surgery, re-irradiation or chemotherapy. Age and the Karnofsky Performance Status Scale (KPSS) are used to make decisions for these patients as these are established as prognostic factors in the initial diagnosis of GB. This study's aim was to evaluate preoperative patient comorbidities by using the age-adjusted Charlson Comorbidity Index (ACCI) as a prognostic factor for recurrent GB patients.
METHODS METHODS
In this retrospective analysis we could include 123 patients with surgery for primary recurrence of GB from January 2007 until December 2016 (43 females, 80 males, mean age 57 years (range 21-80 years)). Preoperative age, sex, ACCI, KPSS and adjuvant treatment regimes were recorded for each patient. Extent of resection (EOR) was recorded as a complete/incomplete resection of the contrast-enhancing tumor part.
RESULTS RESULTS
Median overall survival (OS) was 9.0 months (95% CI 7.1-10.9 months) after first re-resection. Preoperative KPSS > 80% (P < 0.001) and EOR (P = 0.013) were associated with significantly improved survival in univariate analysis. Including these factors in multivariate analysis, preoperative KPSS < 80 (HR 2.002 [95% CI: 1.246-3.216], P = 0.004) and EOR are the only significant prognostic factor (HR 1.611 [95% CI: 1.036-2.505], P = 0.034). ACCI was not shown as a prognostic factor in univariate and multivariate analyses.
CONCLUSION CONCLUSIONS
For patients with surgery for recurrent glioblastoma, the ACCI does not add further information about patient's prognosis besides the well-established KPSS and extent of resection.

Identifiants

pubmed: 35062885
doi: 10.1186/s12883-021-02532-x
pii: 10.1186/s12883-021-02532-x
pmc: PMC8780246
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

32

Informations de copyright

© 2022. The Author(s).

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Auteurs

Melanie Barz (M)

Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany. melanie.barz@tum.de.

Stefanie Bette (S)

Department of Neuroradiology, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.
Department of Radiology and Neuroradiology, University of Augsburg, Augsburg, Germany.

Insa Janssen (I)

Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.
Department of Neurosurgery, Hôpitaux Universitaires de Genève, Geneva, Switzerland.

A Kaywan Aftahy (AK)

Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.

Thomas Huber (T)

Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Friederike Liesche-Starnecker (F)

Department of Neuropathology, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Institute of Pathology, Munich, Germany.

Yu-Mi Ryang (YM)

Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.
Department of Neurosurgery, Helios Klinikum Berlin Buch, Berlin, Germany.

Benedikt Wiestler (B)

Department of Neuroradiology, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.

Stephanie E Combs (SE)

Department of Radiation Oncology, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.
Department of Radiation Sciences (DRS) Helmholtz Zentrum Munich, Institute of Innovative Radiotherapy (iRT), Munich, Germany.
German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.

Bernhard Meyer (B)

Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.

Jens Gempt (J)

Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany.

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