348 research outputs found

    Deep learning-based survival prediction for multiple cancer types using histopathology images

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    Prognostic information at diagnosis has important implications for cancer treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and clinical variables can provide useful prognostic insights, improving risk stratification remains an active research area. We developed a deep learning system (DLS) to predict disease specific survival across 10 cancer types from The Cancer Genome Atlas (TCGA). We used a weakly-supervised approach without pixel-level annotations, and tested three different survival loss functions. The DLS was developed using 9,086 slides from 3,664 cases and evaluated using 3,009 slides from 1,216 cases. In multivariable Cox regression analysis of the combined cohort including all 10 cancers, the DLS was significantly associated with disease specific survival (hazard ratio of 1.58, 95% CI 1.28-1.70, p<0.0001) after adjusting for cancer type, stage, age, and sex. In a per-cancer adjusted subanalysis, the DLS remained a significant predictor of survival in 5 of 10 cancer types. Compared to a baseline model including stage, age, and sex, the c-index of the model demonstrated an absolute 3.7% improvement (95% CI 1.0-6.5) in the combined cohort. Additionally, our models stratified patients within individual cancer stages, particularly stage II (p=0.025) and stage III (p<0.001). By developing and evaluating prognostic models across multiple cancer types, this work represents one of the most comprehensive studies exploring the direct prediction of clinical outcomes using deep learning and histopathology images. Our analysis demonstrates the potential for this approach to provide prognostic information in multiple cancer types, and even within specific pathologic stages. However, given the relatively small number of clinical events, we observed wide confidence intervals, suggesting that future work will benefit from larger datasets

    Discovery and saturation analysis of cancer genes across 21 tumour types

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    Although a few cancer genes are mutated in a high proportion of tumours of a given type (>20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600–5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics

    Efficacy and safety of a two-step method of skin preparation for peripheral intravenous catheter insertion: a prospective multi-centre randomised trial

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    We have developed a two-step procedure for preparing the skin before peripheral venous catheter (PVC) insertions. This procedure involves two successive swabbings with wipes soaked in alcoholic antiseptic. We investigated whether this two-step procedure was as effective and safe as the standard four-step procedure – washing with detergent, rinsing, drying, applying antiseptic – by carrying out a multicentre randomised equivalence study comparing the frequency of precursor signs of infection at the site of insertion for the two skin preparation procedures. The study was carried out over an eight-month period, and 248 PVC insertion sites were evaluated. The two-step procedure was used for 130 subjects and the standard procedure for 118. Taking into account all the confounding factors predisposing patients to the complications studied, the characteristics of the two groups of patients were found to be similar, with no significant differences noted. The incidence of precursor signs of infection was 11 % 24 hours after PVC insertion (27/248), 25 % at 48 hours (50/203) and at 29 % at 72 hours (34/119). Eleven patients had complications necessitating the withdrawal of the PVC: sensitivity of the insertion site, with redness and/or slight swelling and/or a palpable venous cord. No major complications were observed in this study. The frequency of local complications associated with PVCs reported in this study, whether simple or severe, was not affected by the skin preparation procedure used for PVC insertion (two-step or four-step procedure)

    Exome sequencing of pleuropulmonary blastoma reveals frequent biallelic loss of TP53 and two hits in DICER1 resulting in retention of 5p-derived miRNA hairpin loop sequences

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    Pleuropulmonary blastoma is a rare childhood malignancy of lung mesenchymal cells that can remain dormant as epithelial cysts or progress to high-grade sarcoma. Predisposing germline loss-of-function DICER1 variants have been described. We sought to uncover additional contributors through whole exome sequencing of 15 tumor/normal pairs, followed by targeted resequencing, miRNA analysis and immunohistochemical analysis of additional tumors. In addition to frequent biallelic loss of TP53 and mutations of NRAS or BRAF in some cases, each case had compound disruption of DICER1: a germline (12 cases) or somatic (3 cases) loss-of-function variant plus a somatic missense mutation in the RNase IIIb domain. 5p-Derived microRNA (miRNA) transcripts retained abnormal precursor miRNA loop sequences normally removed by DICER1. This work both defines a genetic interaction landscape with DICER1 mutation and provides evidence for alteration in miRNA transcripts as a consequence of DICER1 disruption in cancer

    Fragmentation of care threatens patient safety in peripheral vascular catheter management in acute care--a qualitative study.

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    BACKGROUND: The use of peripheral vascular catheters (PVCs) is an extremely common and necessary clinical intervention, but inappropriate PVC care poses a major patient safety risk in terms of infection. Quality improvement initiatives have been proposed to reduce the likelihood of adverse events, but a lack of understanding about factors that influence behaviours of healthcare professionals limits the efficacy of such interventions. We undertook qualitative interviews with clinical staff from a large group of hospitals in order to understand influences on PVC care behaviors and subsequent patient safety. METHODS: Ten doctors, ten clinical pharmacists, 18 nurses and one midwife at a National Health Service hospital group in London (United Kingdom) were interviewed between December 2010 and July 2011 using qualitative methods. Responses were analysed using a thematic framework. RESULTS: FOUR KEY THEMES EMERGED: 1) Fragmentation of management and care, demonstrated with a lack of general overview and insufficient knowledge about expected standards of care or responsibility of different professionals; 2) feelings of resentment and frustration as a result of tensions in the workplace, due to the ambiguity about professional responsibilities; 3) disregard for existing hospital policy due to perceptions of flaws in the evidence used to support it; and 4) low-risk perception for the impact of PVC use on patient safety. CONCLUSION: Fragmentation of practice resulted in ill-defined responsibilities and interdisciplinary resentment, which coupled with a generally low perception of risk of catheter use, appeared to result in lack of maintaining policy PVC standards which could reduced patient safety. Resolution of these issues through clearly defining handover practice, teaching interdisciplinary duties and increasing awareness of PVC risks could result in preventing thousands of BSIs and other PVC-related infections annually
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