Dataset Information

A User-Friendly, Web-Based Integrative Tool (ESurv) for Survival Analysis: Development and Validation Study.

ABSTRACT: BACKGROUND:Prognostic genes or gene signatures have been widely used to predict patient survival and aid in making decisions pertaining to therapeutic actions. Although some web-based survival analysis tools have been developed, they have several limitations. OBJECTIVE:Taking these limitations into account, we developed ESurv (Easy, Effective, and Excellent Survival analysis tool), a web-based tool that can perform advanced survival analyses using user-derived data or data from The Cancer Genome Atlas (TCGA). Users can conduct univariate analyses and grouped variable selections using multiomics data from TCGA. METHODS:We used R to code survival analyses based on multiomics data from TCGA. To perform these analyses, we excluded patients and genes that had insufficient information. Clinical variables were classified as 0 and 1 when there were two categories (for example, chemotherapy: no or yes), and dummy variables were used where features had 3 or more outcomes (for example, with respect to laterality: right, left, or bilateral). RESULTS:Through univariate analyses, ESurv can identify the prognostic significance for single genes using the survival curve (median or optimal cutoff), area under the curve (AUC) with C statistics, and receiver operating characteristics (ROC). Users can obtain prognostic variable signatures based on multiomics data from clinical variables or grouped variable selections (lasso, elastic net regularization, and network-regularized high-dimensional Cox-regression) and select the same outputs as above. In addition, users can create custom gene signatures for specific cancers using various genes of interest. One of the most important functions of ESurv is that users can perform all survival analyses using their own data. CONCLUSIONS:Using advanced statistical techniques suitable for high-dimensional data, including genetic data, and integrated survival analysis, ESurv overcomes the limitations of previous web-based tools and will help biomedical researchers easily perform complex survival analyses.

SUBMITTER: Pak K

PROVIDER: S-EPMC7238095 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe application of technology in the area of dietary assessment has resulted in the development of an array of tools, which are often specifically designed for a particular country or region.ObjectiveThe aim of this study was to describe the development, validation, and user evaluation of a Web-based dietary assessment tool "Foodbook24."MethodsFoodbook24 is a Web-based, dietary assessment tool consisting of a 24-hour dietary recall (24HDR) and food frequency questionnaire (FFQ) alongside supplementary questionnaires. Validity of the 24HDR component was assessed by 40 participants, who completed 3 nonconsecutive, self-administered 24HDR using Foodbook24 and a 4-day semi-weighed food diary at separate time points. Participants also provided fasted blood samples and 24-hour urine collections for the identification of biomarkers of nutrient and food group intake during each recording period. Statistical analyses on the nutrient and food group intake data derived from each method were performed in SPSS version 20.0 (SPSS Inc). Mean nutrient intakes (and standard deviations) recorded using each method of dietary assessment were calculated. Spearman and Pearson correlations, Wilcoxon Signed Rank and Paired t test were used to investigate the agreement and differences between the nutritional output from Foodbook24 (test method) and the 4-day semi-weighed food diary (reference method). Urinary and plasma biomarkers of nutrient intake were used as an objective validation of Foodbook24. To investigate the user acceptability of Foodbook24, participants from different studies involved with Foodbook24 were asked to complete an evaluation questionnaire.ResultsFor nutrient intake, correlations between the dietary assessment methods were acceptable to very good in strength and statistically significant (range r=.32 to .75). There were some significant differences between reported mean intakes of micronutrients recorded by both methods; however, with the exception of protein (P=.03), there were no significant differences in the reporting of energy or macronutrient intake. Of the 19 food groups investigated in this analysis, there were significant differences between 6 food groups reported by both methods. Spearman correlations for biomarkers of nutrient and food group intake and reported intake were similar for both methods. A total of 118 participants evaluated the acceptability of Foodbook24. The tool was well-received and the majority, 67.8% (80/118), opted for Foodbook24 as the preferred method for future dietary intake assessment when compared against a traditional interviewer led recall and semi-weighed food diary.ConclusionsThe results of this study demonstrate the validity and user acceptability of Foodbook24. The results also highlight the potential of Foodbook24, a Web-based dietary assessment method, and present a viable alternative to nutritional surveillance in Ireland.

Project description:BackgroundIn the United States, the tuberculosis (TB) disease burden and associated factors vary substantially across states. While public health agencies must choose how to deploy resources to combat TB and latent tuberculosis infection (LTBI), state-level modeling analyses to inform policy decisions have not been widely available.MethodsWe developed a mathematical model of TB epidemiology linked to a web-based user interface - Tabby2. The model is calibrated to epidemiological and demographic data for the United States, each U.S. state, and the District of Columbia. Users can simulate pre-defined scenarios describing approaches to TB prevention and treatment or create their own intervention scenarios. Location-specific results for epidemiological outcomes, service utilization, costs, and cost-effectiveness are reported as downloadable tables and customizable visualizations. To demonstrate the tool's functionality, we projected trends in TB outcomes without additional intervention for all 50 states and the District of Columbia. We further undertook a case study of expanded treatment of LTBI among non-U.S.-born individuals in Massachusetts, covering 10% of the target population annually over 2025-2029.ResultsBetween 2022 and 2050, TB incidence rates were projected to decline in all states and the District of Columbia. Incidence projections for the year 2050 ranged from 0.03 to 3.8 cases (median 0.95) per 100,000 persons. By 2050, we project that majority (> 50%) of TB will be diagnosed among non-U.S.-born persons in 46 states and the District of Columbia; per state percentages range from 17.4% to 96.7% (median 83.0%). In Massachusetts, expanded testing and treatment for LTBI in this population was projected to reduce cumulative TB cases between 2025 and 2050 by 6.3% and TB-related deaths by 8.4%, relative to base case projections. This intervention had an incremental cost-effectiveness ratio of $180,951 (2020 USD) per quality-adjusted life year gained from the societal perspective.ConclusionsTabby2 allows users to estimate the costs, impact, and cost-effectiveness of different TB prevention approaches for multiple geographic areas in the United States. Expanded testing and treatment for LTBI could accelerate declines in TB incidence in the United States, as demonstrated in the Massachusetts case study.

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A User-Friendly, Web-Based Integrative Tool (ESurv) for Survival Analysis: Development and Validation Study.

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