| Literature DB >> 35062885 |
Melanie Barz1, Stefanie Bette2,3, Insa Janssen4,5, A Kaywan Aftahy4, Thomas Huber6, Friederike Liesche-Starnecker7, Yu-Mi Ryang4,8, Benedikt Wiestler2, Stephanie E Combs9,10,11, Bernhard Meyer4, Jens Gempt4.
Abstract
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.Entities:
Keywords: Age-adjusted Charlson comorbidity index; Prognostic factor; Recurrent glioblastoma; Surgery
Mesh:
Year: 2022 PMID: 35062885 PMCID: PMC8780246 DOI: 10.1186/s12883-021-02532-x
Source DB: PubMed Journal: BMC Neurol ISSN: 1471-2377 Impact factor: 2.474
Fig. 1Flowchart of patient-selection process
Fig. 2Roc curve analysis and use of Youden index: ACCI > = 6.5 there is a specificity of 96.9% and a sensitivity of 9.9
Baseline patient and tumor characteristics
| Age | 57 years (±10.6) |
|---|---|
| Sex, female | 43/123 |
| KPSS preoperative | 80.0 (IR 70.0–90.0) |
| KPSS postoperative | 70.0 (IR 60.0–90.0) |
| right | 58/123 |
| left | 55/123 |
| avialable | 123,123 |
| median | 4.0 (CI 3–6) |
| intraoperative neuromonitoring | 87/123 |
| 5-ALA | 44/123 |
| neuronavigation | 109/123 |
| complete resection | 45/123 |
| incomplete resection | 78/123 |
| Stupp scheme | 25/123 |
| radiotherapy only | 20/123 |
| chemotherapy only | 24/123 |
normally distributed variables shown as mean +/− standard deviation, non-normally distributed as median (interquartile range)
KPSS Karnofsky Performance Status Scale
Fig. 3OS according to adjuvant therapy
Fig. 4OS according to the age-adjusted Charlson Comorbidity Index (here as an example with cut-off of 3) as well as in relation to the KPSS in GB patients
Multivariate Cox analysis using ACCI as a categorical variable as well as in dichotomised form
| Age (> = 65 vs. < 65) | 0.62 | 0.34–1.13 | 0.12 |
| Postoperative KPSS (< 80 vs. > = 80)* | 2.00 | 1.25–3.22 | 0.004 |
| Resection (complete/incomplete) | 1.61 | 1.04–2.51 | 0.034 |
| ACCI | 0.94 | 0.80–1.11 | 0.467 |
| Age (> = 65 vs. < 65) | 0.74 | 0.41–1.32 | 0.306 |
| ACCI | 0.98 | 0.84–1.15 | 0.84 |
| Resection (complete/incomplete) * | 1.74 | 1.12–2.67 | 0.013 |
| Age (> = 65 vs. < 65) | 0.80 | 0.50–1.29 | 0.363 |
| Resection (complete/incomplete) * | 1.83 | 1.17–2.85 | 0.008 |
| ACCI 6.5 | 0.64 | 0.31–1.31 | 0.219 |
| Age (> = 65 vs. < 65) | 0.75 | 0.46–1.21 | 0.236 |
| Resection (complete/incomplete) * | 1.68 | 1.07–2.64 | 0.023 |
| ACCI 6.5 | 0.71 | 0.34–1.48 | 0.359 |
| Postoperative KPS (< 80 vs. > = 80)* | 1.88 | 1.18–3.01 | 0.008 |
CI Confidence Interval; *P=0.05
A Subanalysis without KPSS; B Subanalysis with the ACCI cut-off of 6.5; C Subanalysis with the ACCI cut-off of 6.5 and KPSS