Background: Chordomas are rare but challenging neoplasms involving the skull base. A preoperative grading system will be useful to identify both areas for treatment and risk factors, and correlate to the degree of resection, complications, and recurrence.
Objective: To propose a new grading system for cranial chordomas designed by the senior author. Its purpose is to enable comparison of different tumors with a similar pathology to clivus chordoma, and statistically correlate with postoperative outcomes.
Methods: The numerical grading system included tumor size, site of the tumor, vascular encasement, intradural extension, brainstem invasion, and recurrence of the tumor either after surgery or radiotherapy with a range of 2 to 25 points; it was used in 42 patients with cranial chordoma. The grading system was correlated with number of operations for resection, degree of resection, number and type of complications, recurrence, and survival.
Results: We found 3 groups: low-risk 0 to 7 points, intermediate-risk 8 to 12 points, and high-risk ≥13 points in the grading system. The 3 groups were correlated with the following: extent of resection (partial, subtotal, or complete; P < .002); number of operative stages to achieve removal (P < .014); tumor recurrence (P = .03); postoperative Karnofsky Performance Status (P < .001); and with successful outcome (P = .005). The grading system itself correlated with the outcome (P = .005).
Conclusion: The proposed chordoma grading system can help surgeons to predict the difficulty of the case and know which areas of the skull base will need attention to plan further therapy.
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http://dx.doi.org/10.1093/neuros/nyx423 | DOI Listing |
Asian Pac J Cancer Prev
January 2025
D1 S.P. Botkin City Clinical Hospital, Moscow, Russia.
Objectives: To study the predictive role of tumor-associated neutrophils in early luminal HER2-negative breast cancer.
Materials And Methods: This is a retrospective study conducted on 60 women cases aged from 31 to 79 years underwent surgery for luminal HER2-negative ductal breast cancer in tertiary care cancer centre. We first estimated basic morphological signs: tumor size, tumor grade (by Nottingham Histologic Score), tumor infiltrating lymphocytes (TILs), Lymphovascular invasion, hormonal receptors status, proliferative index, and regional lymph nodes metastasis.
Asian Pac J Cancer Prev
January 2025
Department of Pathology, Phramongkutklao College of Medicine, Thailand.
Objective: To determine the correlation among five different types of tumor regression grading (TRG) systems. Test-retest reliability analyses were conducted at two time points to assess the internal validity and consistency of these five TRG systems.
Methods: A test-retest study was performed in 34 pathologically confirmed rectal adenocarcinoma specimens.
Acta Orthop Traumatol Turc
December 2024
Department of Orthopedics, !e Second People's Hospital of Xiangcheng District, Suzhou, China.
Objective: The aim of this study was to examine if tranexamic acid (TXA) can assist in improving outcomes of arthroscopic rotator cu! repair (RCR).
Methods: The databases of PubMed, Embase, Web of Science, CENTRAL, and Scopus were searched for all types of studies examining the e"cacy of TXA for arthroscopic RCR. Twelve studies, 10 randomized controlled trials (RCTs), and 2 retrospective studies were considered eligible.
Disabil Rehabil
January 2025
Department of Physiotherapy, University of Murcia, Murcia, Spain.
Purpose: To synthesize evidence regarding psychometric properties of the Mini-Balance Evaluation Systems Test (Mini-BESTest) in assessing postural control.
Method: Six databases were searched until October 15th, 2024. Two authors independently assessed the methodological quality and results of studies using the COSMIN checklist and Terweés criteria.
J Dent Sci
January 2025
First Clinical Division, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, Beijing, China.
Background/purpose: Artificial intelligence (AI) can assist in medical diagnosis owing to its high accuracy and efficiency. This study aimed to develop a diagnostic system for automatically determining the degree of tooth wear (TW) using intraoral photographs with deep learning.
Materials And Methods: The study included 388 intraoral photographs.
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