19 research outputs found

    A validated integrated clinical and molecular glioblastoma long-term survival-predictive nomogram.

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    Background: Glioblastoma (GBM) is the most common primary malignant brain tumor in adulthood. Despite multimodality treatments, including maximal safe resection followed by irradiation and chemotherapy, the median overall survival times range from 14 to 16 months. However, a small subset of GBM patients live beyond 5 years and are thus considered long-term survivors. Methods: A retrospective analysis of the clinical, radiographic, and molecular features of patients with newly diagnosed primary GBM who underwent treatment at The University of Texas MD Anderson Cancer Center was conducted. Eighty patients had sufficient quantity and quality of tissue available for next-generation sequencing and immunohistochemical analysis. Factors associated with survival time were identified using proportional odds ordinal regression. We constructed a survival-predictive nomogram using a forward stepwise model that we subsequently validated using The Cancer Genome Atlas. Results: Univariate analysis revealed 3 pivotal genetic alterations associated with GBM survival: both high tumor mutational burden ( Conclusions: Our newly devised long-term surviva

    Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging

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    Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid (<90< 90 seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas. DeepGlioma is trained using a multimodal dataset that includes stimulated Raman histology (SRH); a rapid, label-free, non-consumptive, optical imaging method; and large-scale, public genomic data. In a prospective, multicenter, international testing cohort of patients with diffuse glioma (n=153n=153) who underwent real-time SRH imaging, we demonstrate that DeepGlioma can predict the molecular alterations used by the World Health Organization to define the adult-type diffuse glioma taxonomy (IDH mutation, 1p19q co-deletion and ATRX mutation), achieving a mean molecular classification accuracy of 93.3±1.6%93.3\pm 1.6\%. Our results represent how artificial intelligence and optical histology can be used to provide a rapid and scalable adjunct to wet lab methods for the molecular screening of patients with diffuse glioma.Comment: Paper published in Nature Medicin

    Single Center Review of Femoral Arteriovenous Grafts for Hemodialysis

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    It is unclear how to manage high risk hemodialysis patients who present with an indwelling catheter. The National Kidney Foundation Practice Guidelines urge prompt removal of the catheter, but the guidelines do not specifically address the problem of patients whose only option is a femoral arteriovenous (AV) graft.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41306/1/268_2005_Article_62.pd

    A road map for the treatment of pediatric diffuse midline glioma

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    Objectives:Traditional journal clubs have been shown to be insufficient in improving residents\u27 scholarly productivity, often due to the inability to sustain residents\u27 interest and participation. Additionally, the 2019 novel coronavirus (COVID-19) pandemic restrictions caused a decline in academic scholarly productivity across residency programs. We evaluated the impact of a resident-led research club called \u27journal café\u27 on residents\u27 scholarly productivity by comparing scholarly output between the journal café members and non-members during the COVID-19 pandemic. Methods: The journal café was established in the 2012/2013 academic year by internal medicine residents of a university residency program in Atlanta, Georgia, to foster self-directed collaboration among residents based on shared interests in academic research. The journal café runs independently of the residency program\u27s journal club. We categorized IM residents at our institution into journal café members and non-members and collected data on their research productivity during residency training and the COVID-19 pandemic. The survey was conducted between April and June 2021 and analyzed data presented using frequencies, tables, and appropriate charts. Results: Sixty-eight residents (29 journal café members and 39 non-members) completed the survey (response rate of 85%). A significantly higher number of journal café members reported having five or more research publications (55.1% vs 7.1%, P \u3c .001) and scientific presentations (48.3% vs 2.6%, P \u3c .001) compared with non-members. Additionally, more journal café members published COVID-19-related research in peer-reviewed journals compared with non-members (68% vs 32%, n = 19). Finally, most of the residents cited the opportunity of a platform to share and brainstorm on research ideas as the reason for joining the journal café. Conclusion: We found an association between journal café participation and increased scholarly activity, particularly during the COVID-19 pandemic. Independent resident-led research clubs supported by the residency program may complement the traditional journal clubs and enhance residents\u27 participation in research

    A validated integrated clinical and molecular glioblastoma long-term survival-predictive nomogram

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    BackgroundGlioblastoma (GBM) is the most common primary malignant brain tumor in adulthood. Despite multimodality treatments, including maximal safe resection followed by irradiation and chemotherapy, the median overall survival times range from 14 to 16 months. However, a small subset of GBM patients live beyond 5 years and are thus considered long-term survivors.MethodsA retrospective analysis of the clinical, radiographic, and molecular features of patients with newly diagnosed primary GBM who underwent treatment at The University of Texas MD Anderson Cancer Center was conducted. Eighty patients had sufficient quantity and quality of tissue available for next-generation sequencing and immunohistochemical analysis. Factors associated with survival time were identified using proportional odds ordinal regression. We constructed a survival-predictive nomogram using a forward stepwise model that we subsequently validated using The Cancer Genome Atlas.ResultsUnivariate analysis revealed 3 pivotal genetic alterations associated with GBM survival: both high tumor mutational burden (P = .0055) and PTEN mutations (P = .0235) negatively impacted survival, whereas IDH1 mutations positively impacted survival (P &lt; .0001). Clinical factors significantly associated with GBM survival included age (P &lt; .0001), preoperative Karnofsky Performance Scale score (P = .0001), sex (P = .0164), and clinical trial participation (P &lt; .0001). Higher preoperative T1-enhancing volume (P = .0497) was associated with shorter survival. The ratio of TI-enhancing to nonenhancing disease (T1/T2 ratio) also significantly impacted survival (P = .0022).ConclusionsOur newly devised long-term survival-predictive nomogram based on clinical and genomic data can be used to advise patients regarding their potential outcomes and account for confounding factors in nonrandomized clinical trials
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