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Zhou S, Wu S, Li Z, Wang X. Construction and Validation of Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Patients with Primary Anaplastic Oligodendroglioma. World Neurosurg 2024; 187:e472-e484. [PMID: 38677647 DOI: 10.1016/j.wneu.2024.04.111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 04/29/2024]
Abstract
OBJECTIVE Anaplastic oligodendroglioma (AOD) is a rare high-grade central nervous system tumor. The current research on prognostic prediction of AOD remains limited. This study aimed to identify prognostic factors and establish the nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with AOD. METHODS Patients diagnosed with AOD between 1992 and 2020 were extracted from the Surveillance, Epidemiology, and End Result database. We performed univariate and multivariate Cox regression analyses to identify independent prognostic factors based on the training group. Kaplan-Meier survival curves were used to compare the impact of various independent factors on patient prognosis. For OS and CSS, the nomograms were constructed and verified by the validation group. Harrell''s concordance index, receiver operating characteristic curves, calibration curves, and decision curve analyses were used to assess the discrimination, consistency, and clinical value of the nomograms. RESULTS A total of 1202 AOD patients were enrolled, being randomly divided into training (n = 841) and validation (n = 361) groups (7:3 ratio). Univariate and multivariate Cox analysis identified 4 significant independent factors (tumor site, age, surgery, and chemotherapy). For OS and CSS, Harrell''s concordance index were 0.731 (0.705-0.757) and 0.728 (0.701-0.754) in the training group, 0.688 (0.646-0.731) and 0.684 (0.639-0.729) in the validation group, respectively. Receiver operating characteristic curves and Calibration curves showed good discrimination and consistency, respectively. In addition, the decision curve analyses curves showed the nomograms have good clinical benefits. CONCLUSIONS We successfully established the nomograms to predict the OS and CSS for AOD patients. The nomograms showed good performance in prognostic prediction, assisting clinicians in evaluating patient prognosis and personalizing treatment plans.
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Affiliation(s)
- Shuoming Zhou
- Department of Neurosurgery, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Shuaishuai Wu
- Department of Neurosurgery, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zhaoming Li
- Department of Neurosurgery, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Xiangyu Wang
- Department of Neurosurgery, The First Affiliated Hospital of Jinan University, Guangzhou, China.
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McAleenan A, Kelly C, Spiga F, Kernohan A, Cheng HY, Dawson S, Schmidt L, Robinson T, Brandner S, Faulkner CL, Wragg C, Jefferies S, Howell A, Vale L, Higgins JPT, Kurian KM. Prognostic value of test(s) for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation for predicting overall survival in people with glioblastoma treated with temozolomide. Cochrane Database Syst Rev 2021; 3:CD013316. [PMID: 33710615 PMCID: PMC8078495 DOI: 10.1002/14651858.cd013316.pub2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Glioblastoma is an aggressive form of brain cancer. Approximately five in 100 people with glioblastoma survive for five years past diagnosis. Glioblastomas that have a particular modification to their DNA (called methylation) in a particular region (the O6-methylguanine-DNA methyltransferase (MGMT) promoter) respond better to treatment with chemotherapy using a drug called temozolomide. OBJECTIVES To determine which method for assessing MGMT methylation status best predicts overall survival in people diagnosed with glioblastoma who are treated with temozolomide. SEARCH METHODS We searched MEDLINE, Embase, BIOSIS, Web of Science Conference Proceedings Citation Index to December 2018, and examined reference lists. For economic evaluation studies, we additionally searched NHS Economic Evaluation Database (EED) up to December 2014. SELECTION CRITERIA Eligible studies were longitudinal (cohort) studies of adults with diagnosed glioblastoma treated with temozolomide with/without radiotherapy/surgery. Studies had to have related MGMT status in tumour tissue (assessed by one or more method) with overall survival and presented results as hazard ratios or with sufficient information (e.g. Kaplan-Meier curves) for us to estimate hazard ratios. We focused mainly on studies comparing two or more methods, and listed brief details of articles that examined a single method of measuring MGMT promoter methylation. We also sought economic evaluations conducted alongside trials, modelling studies and cost analysis. DATA COLLECTION AND ANALYSIS Two review authors independently undertook all steps of the identification and data extraction process for multiple-method studies. We assessed risk of bias and applicability using our own modified and extended version of the QUality In Prognosis Studies (QUIPS) tool. We compared different techniques, exact promoter regions (5'-cytosine-phosphate-guanine-3' (CpG) sites) and thresholds for interpretation within studies by examining hazard ratios. We performed meta-analyses for comparisons of the three most commonly examined methods (immunohistochemistry (IHC), methylation-specific polymerase chain reaction (MSP) and pyrosequencing (PSQ)), with ratios of hazard ratios (RHR), using an imputed value of the correlation between results based on the same individuals. MAIN RESULTS We included 32 independent cohorts involving 3474 people that compared two or more methods. We found evidence that MSP (CpG sites 76 to 80 and 84 to 87) is more prognostic than IHC for MGMT protein at varying thresholds (RHR 1.31, 95% confidence interval (CI) 1.01 to 1.71). We also found evidence that PSQ is more prognostic than IHC for MGMT protein at various thresholds (RHR 1.36, 95% CI 1.01 to 1.84). The data suggest that PSQ (mainly at CpG sites 74 to 78, using various thresholds) is slightly more prognostic than MSP at sites 76 to 80 and 84 to 87 (RHR 1.14, 95% CI 0.87 to 1.48). Many variants of PSQ have been compared, although we did not see any strong and consistent messages from the results. Targeting multiple CpG sites is likely to be more prognostic than targeting just one. In addition, we identified and summarised 190 articles describing a single method for measuring MGMT promoter methylation status. AUTHORS' CONCLUSIONS PSQ and MSP appear more prognostic for overall survival than IHC. Strong evidence is not available to draw conclusions with confidence about the best CpG sites or thresholds for quantitative methods. MSP has been studied mainly for CpG sites 76 to 80 and 84 to 87 and PSQ at CpG sites ranging from 72 to 95. A threshold of 9% for CpG sites 74 to 78 performed better than higher thresholds of 28% or 29% in two of three good-quality studies making such comparisons.
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Affiliation(s)
- Alexandra McAleenan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Claire Kelly
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Francesca Spiga
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ashleigh Kernohan
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hung-Yuan Cheng
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sarah Dawson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) , University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Lena Schmidt
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tomos Robinson
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Sebastian Brandner
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Division of Neuropathology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Claire L Faulkner
- Bristol Genetics Laboratory, Pathology Sciences, Southmead Hospital, Bristol, UK
| | - Christopher Wragg
- Bristol Genetics Laboratory, Pathology Sciences, Southmead Hospital, Bristol, UK
| | - Sarah Jefferies
- Department of Oncology, Addenbrooke's Hospital, Cambridge, UK
| | - Amy Howell
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Luke Vale
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Julian P T Higgins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) , University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Kathreena M Kurian
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Medical School: Brain Tumour Research Centre, Public Health Sciences, University of Bristol, Bristol, UK
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Prognostic Nomograms for Primary High-Grade Glioma Patients in Adult: A Retrospective Study Based on the SEER Database. BIOMED RESEARCH INTERNATIONAL 2020; 2020:1346340. [PMID: 32775408 PMCID: PMC7397389 DOI: 10.1155/2020/1346340] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 06/13/2020] [Accepted: 06/23/2020] [Indexed: 12/14/2022]
Abstract
Purpose In our study, we aimed to screen the risk factors that affect overall survival (OS) and cancer-specific survival (CSS) in adult glioma patients and to develop and evaluate nomograms. Methods Primary high-grade gliomas patients being retrieved from the surveillance, epidemiology and end results (SEER) database, between 2004 and 2015, then they randomly assigned to a training group and a validation group. Univariate and multivariate Cox analysis models were used to choose the variables significantly correlated with the prognosis of high-grade glioma patients. And these variables were used to construct the nomograms. Next, concordance index (C-index), calibration plot and receiver operating characteristics (ROCs) curve were used to evaluate the accuracy of the nomogram model. In addition, the decision curve analysis (DCA) was used to analyze the benefit of nomogram and prognostic indicators commonly used in clinical practice. Results A total of 6395 confirmed glioma patients were selected from the SEER database, divided into training set (n =3166) and validation set (n =3229). Age at diagnosis, tumor grade, tumor size, histological type, surgical type, radiotherapy and chemotherapy were screened out by Cox analysis model. For OS nomogram, the C-index of the training set was 0.741 (95% CI: 0.751-0.731), and the validation set was 0.738 (95% CI: 0.748-0.728). For CSS nomogram, the C-index of the training set was 0.739 (95% CI: 0.749-0.729), and the validation set was 0.738 (95% CI: 0.748-0.728). The net benefit and net reduction in inverventions of nomograms in the decision curve analysis (DCA) was higher than histological type. Conclusions We developed nomograms to predict 3- and 5-year OS rates and 3- and 5-year CSS rates in adult high-grade glioma patients. Both the training set and the validation set showed good calibration and validation, indicating the clinical applicability of the nomogram and good predictive results.
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Tejada Solís S, Plans Ahicart G, Iglesias Lozano I, de Quintana Schmidt C, Fernández Coello A, Hostalot Panisello C, Ley Urzaiz L, García Romero JC, Díez Valle R, González Sánchez J, Duque S. Glioblastoma treatment guidelines: Consensus by the Spanish Society of Neurosurgery Tumor Section. Neurocirugia (Astur) 2020; 31:289-298. [PMID: 32690400 DOI: 10.1016/j.neucir.2020.06.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 05/20/2020] [Accepted: 06/03/2020] [Indexed: 01/11/2023]
Abstract
INTRODUCTION Glioblastoma (GBM) treatment starts in most patients with surgery, either resection surgery or biopsy, to reach a histology diagnose. Multidisciplinar team, including specialists in brain tumors diagnose and treatment, must make an individualize assessment to get the maximum benefit of the available treatments. MATERIAL AND METHODS Experts in each GBM treatment field have briefly described it based in their experience and the reviewed of the literature. RESULTS Each area has been summarized and the consensus of the brain tumor group has been included at the end. CONCLUSIONS GBM are aggressive tumors with a dismal prognosis, however accurate treatments can improve overall survival and quality of life. Neurosurgeons must know treatment options, indications and risks to participate actively in the decision making and to offer the best surgical treatment in every case.
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Affiliation(s)
- Sonia Tejada Solís
- Departamento de Neurocirugía, Hospital Universitario Fundación Jiménez Díaz, Madrid, España.
| | - Gerard Plans Ahicart
- Departamento de Neurocirugía, Hospital Universitari Bellvitge, L'Hospitalet de Llobregat (Barcelona), España
| | - Irene Iglesias Lozano
- Departamento de Neurocirugía, Hospital Universitario Puerta del Mar, Barcelona, España
| | | | - Alejandro Fernández Coello
- Departamento de Neurocirugía, Hospital Universitari Bellvitge, L'Hospitalet de Llobregat (Barcelona), España
| | | | - Luis Ley Urzaiz
- Departamento de Neurocirugía, Hospital Universitario Ramón y Cajal, Madrid, España
| | | | - Ricardo Díez Valle
- Departamento de Neurocirugía, Hospital Universitario Fundación Jiménez Díaz, Madrid, España
| | - Josep González Sánchez
- Departamento de Neurocirugía, Hospital Clínic y Provincial de Barcelona, Barcelona, España
| | - Sara Duque
- Departamento de Neurocirugía, Hospital Universitario HM Montepríncipe, Majadahonda (Madrid), España
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