Add like
Add dislike
Add to saved papers

Prognostic Evaluation of Neurological Assessment of the Neuro-Oncology Scale in Glioblastoma Patients.

BACKGROUND: The aims of this study were to investigate the role of the Neurological Assessment of Neuro-Oncology (NANO) scale in predicting the prognosis of patients with glioblastoma, and compare these results to predicted data of the Karnofsky Performance Scale (KPS), and Eastern Cooperative Oncology Group (ECOG)/World Health Organization (WHO) performance status. Additionally, we examined other prognostic factors in glioblastoma patients.

METHODS: The medical records of 76 patients with a new diagnosis of histologically ascertained glioblastoma in the period from January 2002 to December 2015 at the authors' institution were retrospectively reviewed. Clinical factors, including epidemiologic, radiologic, and therapeutic values were reviewed as well as the performance status assessed by the KPS, ECOG/WHO performance status, and NANO scale.

RESULTS: The mean overall survival was 19.8 months (95% confidence interval 15.2-25.4 months). At initial diagnosis, the mean value [±standard deviation (SD)] of KPS score, ECOG/WHO performance status, and NANO scale were 81 (±7.4), 1.3 (±0.6), and 7.3 (±3.8), respectively. Multivariate analysis for predicting survival showed odds ratios of KPS score, ECOG/WHO performance status, and NANO scale were 2.502 (≥80 vs. <80; p=0.024), 1.691 (0-1 vs. 2-5; p=0.047), and 2.763 (0-7 vs. 8-23; p=0.020), respectively. At the time of progression, the mean value (±SD) of KPS score, ECOG/WHO performance status, and NANO scale were 69 (±8.2), 1.6 (±0.7), and 11.4 (±4.2), respectively; multivariate analysis for predicting survival showed that the odd ratios for KPS score, ECOG/WHO performance status, and NANO scale were 2.007 (≥80 vs. <80; p=0.035), 1.321 (0-1 vs. 2-5; p=0.143), and 3.182 (0-7 vs. 8-23; p=0.002), respectively.

CONCLUSION: The NANO scale provided a more detailed and objective measure of neurologic function than that currently used for predicting the prognosis of glioblastoma patients, especially at the time of progression.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app