Literature DB >> 27367241

Interrater and intrarater reliability of the Knosp scale for pituitary adenoma grading.

Michael A Mooney1, Douglas A Hardesty1, John P Sheehy1, Robert Bird1, Kristina Chapple1, William L White1, Andrew S Little1.   

Abstract

OBJECTIVE The goal of this study was to determine the interrater and intrarater reliability of the Knosp grading scale for predicting pituitary adenoma cavernous sinus (CS) involvement. METHODS Six independent raters (3 neurosurgery residents, 2 pituitary surgeons, and 1 neuroradiologist) participated in the study. Each rater scored 50 unique pituitary MRI scans (with contrast) of biopsy-proven pituitary adenoma. Reliabilities for the full scale were determined 3 ways: 1) using all 50 scans, 2) using scans with midrange scores versus end scores, and 3) using a dichotomized scale that reflects common clinical practice. The performance of resident raters was compared with that of faculty raters to assess the influence of training level on reliability. RESULTS Overall, the interrater reliability of the Knosp scale was "strong" (0.73, 95% CI 0.56-0.84). However, the percent agreement for all 6 reviewers was only 10% (26% for faculty members, 30% for residents). The reliability of the middle scores (i.e., average rated Knosp Grades 1 and 2) was "very weak" (0.18, 95% CI -0.27 to 0.56) and the percent agreement for all reviewers was only 5%. When the scale was dichotomized into tumors unlikely to have intraoperative CS involvement (Grades 0, 1, and 2) and those likely to have CS involvement (Grades 3 and 4), the reliability was "strong" (0.60, 95% CI 0.39-0.75) and the percent agreement for all raters improved to 60%. There was no significant difference in reliability between residents and faculty (residents 0.72, 95% CI 0.55-0.83 vs faculty 0.73, 95% CI 0.56-0.84). Intrarater reliability was moderate to strong and increased with the level of experience. CONCLUSIONS Although these findings suggest that the Knosp grading scale has acceptable interrater reliability overall, it raises important questions about the "very weak" reliability of the scale's middle grades. By dichotomizing the scale into clinically useful groups, the authors were able to address the poor reliability and percent agreement of the intermediate grades and to isolate the most important grades for use in surgical decision making (Grades 3 and 4). Authors of future pituitary surgery studies should consider reporting Knosp grades as dichotomized results rather than as the full scale to optimize the reliability of the scale.

Entities:  

Keywords:  CS = cavernous sinus; ICA = internal carotid artery; Knosp classification; cavernous sinus; interrater reliability; intrarater reliability; pituitary adenoma; pituitary surgery

Mesh:

Year:  2016        PMID: 27367241     DOI: 10.3171/2016.3.JNS153044

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  14 in total

1.  Tumor T2 signal intensity and stalk angulation correlates with endocrine status in pituitary adenoma patients: a quantitative 7 tesla MRI study.

Authors:  John W Rutland; Puneet Pawha; Puneet Belani; Bradley N Delman; Corey M Gill; Teresa Brown; Khadeen Cheesman; Raj K Shrivastava; Priti Balchandani
Journal:  Neuroradiology       Date:  2020-01-10       Impact factor: 2.804

2.  Rater Reliability of the Hardy Classification for Pituitary Adenomas in the Magnetic Resonance Imaging Era.

Authors:  Michael A Mooney; Douglas A Hardesty; John P Sheehy; C Roger Bird; Kristina Chapple; William L White; Andrew S Little
Journal:  J Neurol Surg B Skull Base       Date:  2017-06-07

3.  Predictors of postoperative biochemical remission in acromegaly.

Authors:  Shun Yao; Wen-Li Chen; Sherwin Tavakol; Farhana Akter; Michael P Catalino; Xiaopeng Guo; Jie Luo; Ai-Liang Zeng; Leo Zekelman; Zhi-Gang Mao; Yong-Hong Zhu; Qing-Zhi Wu; Edward R Laws; Wenya Linda Bi; Hai-Jun Wang
Journal:  J Neurooncol       Date:  2021-01-04       Impact factor: 4.130

4.  A Convolutional Neural Network Model for Detecting Sellar Floor Destruction of Pituitary Adenoma on Magnetic Resonance Imaging Scans.

Authors:  Tianshun Feng; Yi Fang; Zhijie Pei; Ziqi Li; Hongjie Chen; Pengwei Hou; Liangfeng Wei; Renzhi Wang; Shousen Wang
Journal:  Front Neurosci       Date:  2022-07-04       Impact factor: 5.152

5.  Early postoperative growth in non-functioning pituitary adenomas; A tool to tailor safe follow-up.

Authors:  Kristin Astrid Øystese; Manuela Zucknick; Olivera Casar-Borota; Geir Ringstad; Jens Bollerslev
Journal:  Endocrine       Date:  2017-05-17       Impact factor: 3.633

6.  Comparison of Constructive Interference in Steady-State and T1-Weighted MRI Sequence at Detecting Pituitary Adenomas in Cushing's Disease Patients.

Authors:  Min Lang; Ghaith Habboub; Doksu Moon; Abin Bandyopadhyay; Danilo Silva; Laurence Kennedy; Varun R Kshettry; Pablo F Recinos
Journal:  J Neurol Surg B Skull Base       Date:  2018-05-10

7.  Diagnostic value of Knosp grade and modified Knosp grade for cavernous sinus invasion in pituitary adenomas: a systematic review and meta-analysis.

Authors:  Yi Fang; Zhijie Pei; Hongjie Chen; Renzhi Wang; Ming Feng; Liangfeng Wei; Jun Li; Heng Zhang; Shousen Wang
Journal:  Pituitary       Date:  2021-01-25       Impact factor: 4.107

8.  Adverse event detection by medical record review is reproducible, but the assessment of their preventability is not.

Authors:  Dorthe O Klein; Roger J M W Rennenberg; Richard P Koopmans; Martin H Prins
Journal:  PLoS One       Date:  2018-11-29       Impact factor: 3.240

9.  Data Mining in Spine Surgery: Leveraging Electronic Health Records for Machine Learning and Clinical Research.

Authors:  Victor E Staartjes; Martin N Stienen
Journal:  Neurospine       Date:  2019-12-31

10.  Impact of Intraoperative 3-Tesla MRI on Endonasal Endoscopic Pituitary Adenoma Resection and a Proposed New Scoring System for Predicting the Utility of Intraoperative MRI.

Authors:  Masahiro Tanji; Hiroharu Kataoka; Masahiro Kikuchi; Tatsunori Sakamoto; Fumihiko Kuwata; Mami Matsunaga; Takayuki Nakagawa; Yohei Mineharu; Yoshiki Arakawa; Kazumichi Yoshida; Susumu Miyamoto
Journal:  Neurol Med Chir (Tokyo)       Date:  2020-10-21       Impact factor: 1.742

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