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Douglas G Altman - One of the best experts on this subject based on the ideXlab platform.
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a guide to systematic review and meta analysis of Prognostic Factor studies
BMJ, 2019Co-Authors: Richard D Riley, Douglas G Altman, Karel G M Moons, Kym I E Snell, Joie Ensor, Lotty Hooft, Jill A Hayden, Gary S Collins, Thomas P A DebrayAbstract:Prognostic Factors are associated with the risk of future health outcomes in individuals with a particular health condition or some clinical start point (eg, a particular diagnosis). Research to identify genuine Prognostic Factors is important because these Factors can help improve risk stratification, treatment, and lifestyle decisions, and the design of randomised trials. Although thousands of Prognostic Factor studies are published each year, often they are of variable quality and the findings are inconsistent. Systematic reviews and meta-analyses are therefore needed that summarise the evidence about the Prognostic value of particular Factors. In this article, the key steps involved in this review process are described.
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overinterpretation and misreporting of Prognostic Factor studies in oncology a systematic review
British Journal of Cancer, 2018Co-Authors: Emmanuelle Kempf, Marialena Trivella, Jennifer A De Beyer, Jonathan Cook, Jane Holmes, S B Mohammed, Trilong Nguyen, Iveta Simera, Douglas G AltmanAbstract:Cancer Prognostic biomarkers have shown disappointing clinical applicability. The objective of this study was to classify and estimate how study results are overinterpreted and misreported in Prognostic Factor studies in oncology. This systematic review focused on 17 oncology journals with an impact Factor above 7. PubMed was searched for primary clinical studies published in 2015, evaluating Prognostic Factors. We developed a classification system, focusing on three domains: misleading reporting (selective, incomplete reporting, misreporting), misleading interpretation (unreliable statistical analysis, spin) and misleading extrapolation of the results (claiming irrelevant clinical applicability, ignoring uncertainty). Our search identified 10,844 articles. The 98 studies included investigated a median of two Prognostic Factors (Q1–Q3, 1–7). The Prognostic Factors’ effects were selectively and incompletely reported in 35/98 and 24/98 full texts, respectively. Twenty-nine articles used linguistic spin in the form of strong statements. Linguistic spin rejecting non-significant results was found in 34 full-text results and 15 abstract results sections. One in five articles had discussion and/or abstract conclusions that were inconsistent with the study findings. Sixteen reports had discrepancies between their full-text and abstract conclusions. Our study provides evidence of frequent overinterpretation of findings of Prognostic Factor assessment in high-impact medical oncology journals.
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microvessel density as a Prognostic Factor in non small cell lung carcinoma a meta analysis of individual patient data
Lancet Oncology, 2007Co-Authors: Marialena Trivella, Francesco Pezzella, Ugo Pastorino, Adrian L Harris, Douglas G AltmanAbstract:Summary Background Angiogenesis is a potential Prognostic Factor that has been investigated in patients with non-small-cell lung carcinoma. However, published studies of the role of angiogenesis as a Prognostic Factor are inconclusive. We aimed to collect individual patient data to assess microvessel-density counts (ie, a measure of angiogenesis) as a Prognostic Factor in non-small-cell lung carcinoma. Methods We obtained published and unpublished datasets and extracted appropriate data, taking particular care to ensure data quality. Detailed information was obtained for the laboratory methods used by every research centre that generated the data. The outcome of interest was overall survival. We did a meta-analysis to estimate the Prognostic role of microvessel density by combining separately estimated hazard ratios (HR) from every study, which were adjusted for tumour stage and age. Analyses were done separately for studies that used the Chalkley method or for those that counted all microvessels. Findings 17 centres provided data for 3200 patients, 2719 of which were included in the analysis. All but three centres (datasets 9, 10, and 13–367 cases) had already published their findings, and six had updated follow-up information (datasets 1, 2, 3, 6, 7, and 8–1273 cases). For all but three centres (datasets 4, 11, and 13) some data corrections were necessary. For microvessel density counts obtained by the Chalkley method, the HR for death per extra microvessel was 1·05 (95% CI 1·01–1·09, p=0·03) when analysed as a continuous variable. For microvessel density counts obtained by the all vessels method, the HR for death per ten extra microvessels was 1·03 (0.97–1·09, p=0·3) when analysed as a continuous variable. Interpretation Microvessel density does not seem to be a Prognostic Factor in patients with non-metastatic surgically treated non-small-cell lung carcinoma. This conclusion contradicts the results of a meta-analysis of published data only. Therefore, the methodology used to assess Prognostic Factors should be assessed carefully.
So Yeon Park - One of the best experts on this subject based on the ideXlab platform.
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diversity index as a novel Prognostic Factor in breast cancer
Oncotarget, 2017Co-Authors: Yul Ri Chung, Mee Soo Chang, Ki Tae Hwang, So Yeon ParkAbstract:// Yul Ri Chung 1, 2 , Hyun Jeong Kim 2 , Young A. Kim 3 , Mee Soo Chang 1, 3 , Ki-Tae Hwang 4 and So Yeon Park 1, 2 1 Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea 2 Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Gyeonggi, Republic of Korea 3 Department of Pathology, Seoul National University Boramae Hospital, Seoul, Republic of Korea 4 Department of Surgery, Seoul National University Boramae Hospital, Seoul, Republic of Korea Correspondence to: So Yeon Park, email: sypmd@snu.ac.kr Keywords: heterogeneity, Shannon index, c-MYC, FGFR1, copy number variation Received: June 08, 2017 Accepted: August 28, 2017 Published: September 28, 2017 ABSTRACT Intratumoral genetic heterogeneity leads to tumor progression and therapeutic resistance. However, due to the difficulty associated with its assessment, the use of this heterogeneity as a Prognostic or predictive marker remains limited. To investigate the significance of the Shannon diversity index of gene copy number variation as a tool for measuring genetic heterogeneity in breast cancer, we performed fluorescence in situ hybridization of c-MYC in two sets of invasive breast cancer samples and correlated the Shannon index of c -MYC copy number variation with clinicopathologic features and patient survival. The Shannon index was correlated with average c-MYC copy number and was higher in tumors in which c-MYC was amplified and in those with c-MYC genetic or regional heterogeneity. A high Shannon index was associated with adverse pathologic features including high histologic grade, lymphovascular invasion, p53 overexpression, high Ki-67 proliferation index and negative hormone receptor status. It was also associated with poor disease-free survival in the whole group, in a subgroup excluding c-MYC- amplified cases, and in the hormone receptor-positive subgroup of both a test and a validation set. A high Shannon index for FGFR1 gene copy number variation was also an independent adverse Prognostic Factor. Our findings suggest that the Shannon diversity index is a measure of intratumoral heterogeneity and can be used as a Prognostic Factor in breast cancer.
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an increase in cancer stem cell population after primary systemic therapy is a poor Prognostic Factor in breast cancer
British Journal of Cancer, 2011Co-Authors: Suyeon Choi, Eunyoung Kang, Il Yong Chung, Yunshik Choi, So Yeon ParkAbstract:An increase in cancer stem cell population after primary systemic therapy is a poor Prognostic Factor in breast cancer
Ardalan Ebrahimi - One of the best experts on this subject based on the ideXlab platform.
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lymph node ratio as an independent Prognostic Factor in oral squamous cell carcinoma
Head and Neck-journal for The Sciences and Specialties of The Head and Neck, 2011Co-Authors: Ardalan Ebrahimi, Jonathan R Clark, Wan Jing Zhang, Michel S Elliott, Chris Milross, Kerwin ShannonAbstract:BACKGROUND: We aimed to validate the lymph node ratio (LNR) as an independent Prognostic Factor in oral squamous cell carcinoma (OSCC) and compare its utility with the current nodal staging system. METHODS: We conducted a retrospective analysis of 313 patients with OSCC undergoing neck dissection. The LNR was adjusted by relevant covariates in a multivariable Cox regression model. RESULTS: LNR displaced conventional nodal staging and was shown to be an independent predictor of regional failure (p = .020), disease-specific (p = .003) and overall survival (p = .001). Patients with an LNR of 2.5% to 7.5%, 7.5% to 20%, and >20% had 2.6, 3.7, and 4.4 times the risk of death from OSCC, respectively, when compared with patients with an LNR <2.5%. CONCLUSIONS: The LNR is an independent Prognostic Factor in OSCC and may be used in conjunction with the current TNM staging to enable better risk stratification and selection for adjuvant therapy.
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lymph node ratio as an independent Prognostic Factor in oral squamous cell carcinoma
Head and Neck-journal for The Sciences and Specialties of The Head and Neck, 2011Co-Authors: Ardalan Ebrahimi, Jonathan R Clark, Wan Jing Zhang, Michel S Elliott, Chris Milross, Kan Gao, Kerwin F ShannonAbstract:Background We aimed to validate the lymph node ratio (LNR) as an independent Prognostic Factor in oral squamous cell carcinoma (OSCC) and compare its utility with the current nodal staging system. Methods We conducted a retrospective analysis of 313 patients with OSCC undergoing neck dissection. The LNR was adjusted by relevant covariates in a multivariable Cox regression model. Results LNR displaced conventional nodal staging and was shown to be an independent predictor of regional failure (p = .020), disease-specific (p = .003) and overall survival (p = .001). Patients with an LNR of 2.5% to 7.5%, 7.5% to 20%, and >20% had 2.6, 3.7, and 4.4 times the risk of death from OSCC, respectively, when compared with patients with an LNR <2.5%. Conclusions The LNR is an independent Prognostic Factor in OSCC and may be used in conjunction with the current TNM staging to enable better risk stratification and selection for adjuvant therapy. © 2010 Wiley Periodicals, Inc. Head Neck, 2010
Richard D Riley - One of the best experts on this subject based on the ideXlab platform.
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a guide to systematic review and meta analysis of Prognostic Factor studies
BMJ, 2019Co-Authors: Richard D Riley, Douglas G Altman, Karel G M Moons, Kym I E Snell, Joie Ensor, Lotty Hooft, Jill A Hayden, Gary S Collins, Thomas P A DebrayAbstract:Prognostic Factors are associated with the risk of future health outcomes in individuals with a particular health condition or some clinical start point (eg, a particular diagnosis). Research to identify genuine Prognostic Factors is important because these Factors can help improve risk stratification, treatment, and lifestyle decisions, and the design of randomised trials. Although thousands of Prognostic Factor studies are published each year, often they are of variable quality and the findings are inconsistent. Systematic reviews and meta-analyses are therefore needed that summarise the evidence about the Prognostic value of particular Factors. In this article, the key steps involved in this review process are described.
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prognosis research strategy progress 2 Prognostic Factor research
PLOS Medicine, 2013Co-Authors: Richard D Riley, Jill A Hayde, Ewou W Steyerberg, Karel G M Moons, Keith R Abrams, Panayiotis A Kyzas, Nuria Malats, Andrew Iggs, Sara Schrote, Douglas G AltmaAbstract:Prognostic Factor research aims to identify Factors associated with subsequent clinical outcome in people with a particular disease or health condition. In this article, the second in the PROGRESS series, the authors discuss the role of Prognostic Factors in current clinical practice, randomised trials, and developing new interventions, and explain why and how Prognostic Factor research should be improved.
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individual participant data meta analysis of Prognostic Factor studies state of the art
BMC Medical Research Methodology, 2012Co-Authors: Ghada Abozaid, Willi Sauerbrei, Richard D RileyAbstract:Background: Prognostic Factors are associated with the risk of a subsequent outcome in people with a given disease or health condition. Meta-analysis using individual participant data (IPD), where the raw data are synthesised from multiple studies, has been championed as the gold-standard for synthesising Prognostic Factor studies. We assessed the feasibility and conduct of this approach. Methods: A systematic review to identify published IPD meta-analyses of Prognostic Factors studies, followed by detailed assessment of a random sample of 20 articles published from 2006. Six of these 20 articles were from the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials in traumatic brain injury) collaboration, for which additional information was also used from simultaneously published companion papers. Results: Forty-eight published IPD meta-analyses of Prognostic Factors were identified up to March 2009. Only three were published before 2000 but thereafter a median of four articles exist per year, with traumatic brain injury the most active research field. Availability of IPD offered many advantages, such as checking modelling assumptions; analysing variables on their continuous scale with the possibility of assessing for non-linear relationships; and obtaining results adjusted for other variables. However, researchers also faced many challenges, such as large cost and time required to obtain and clean IPD; unavailable IPD for some studies; different sets of Prognostic Factors in each study; and variability in study methods of measurement. The IMPACT initiative is a leading example, and had generally strong design, methodological and statistical standards. Elsewhere, standards are not always as high and improvements in the conduct of IPD meta-analyses of Prognostic Factor studies are often needed; in particular, continuous variables are often categorised without reason; publication bias and availability bias are rarely examined; and important methodological details and summary results are often inadequately reported. Conclusions: IPD meta-analyses of Prognostic Factors are achievable and offer many advantages, as displayed most expertly by the IMPACT initiative. However such projects face numerous logistical and methodological obstacles, and their conduct and reporting can often be substantially improved.
Kerwin Shannon - One of the best experts on this subject based on the ideXlab platform.
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lymph node ratio as an independent Prognostic Factor in oral squamous cell carcinoma
Head and Neck-journal for The Sciences and Specialties of The Head and Neck, 2011Co-Authors: Ardalan Ebrahimi, Jonathan R Clark, Wan Jing Zhang, Michel S Elliott, Chris Milross, Kerwin ShannonAbstract:BACKGROUND: We aimed to validate the lymph node ratio (LNR) as an independent Prognostic Factor in oral squamous cell carcinoma (OSCC) and compare its utility with the current nodal staging system. METHODS: We conducted a retrospective analysis of 313 patients with OSCC undergoing neck dissection. The LNR was adjusted by relevant covariates in a multivariable Cox regression model. RESULTS: LNR displaced conventional nodal staging and was shown to be an independent predictor of regional failure (p = .020), disease-specific (p = .003) and overall survival (p = .001). Patients with an LNR of 2.5% to 7.5%, 7.5% to 20%, and >20% had 2.6, 3.7, and 4.4 times the risk of death from OSCC, respectively, when compared with patients with an LNR <2.5%. CONCLUSIONS: The LNR is an independent Prognostic Factor in OSCC and may be used in conjunction with the current TNM staging to enable better risk stratification and selection for adjuvant therapy.
