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

Author

Pak, Kyoungjune, Oh, Sae-Ock, Goh, Tae Sik, Heo, Hye Jin, Han, Myoung-Eun, Jeong, Dae Cheon, Lee, Chi-Seung, Sun, Hokeun, Kang, Junho, Choi, Suji, Lee, Soohwan, Kwon, Eun Jung, Kang, Ji Wan, and Kim, Yun Hak

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundPrognostic 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. ObjectiveTaking 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. MethodsWe 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). ResultsThrough 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. ConclusionsUsing 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.

Published
2020
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21. Glucose metabolism and radiodensity of abdominal adipose tissue: A 5‐year longitudinal study in a large PET cohort.

Author

Pak, Kyoungjune, Santavirta, Severi, Shin, Seunghyeon, Nam, Hyun‐Yeol, De Maeyer, Sven, and Nummenmaa, Lauri

Subjects
*ABDOMINAL adipose tissue, *GLUCOSE metabolism, *RADIOPACITY, *POSITRON emission tomography, *BLOOD sugar
Abstract

Objective Design, Patients and Measurements Results Conclusions 18F‐Fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) allows noninvasive assessment of glucose metabolism and radiodensity in visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). We aimed to address the effects of ageing and metabolic factors on abdominal adipose tissue.We retrospectively analyzed data from 435 healthy men (mean 42.8 years) who underwent a health check‐up programme twice, at baseline and the 5‐year follow‐up. The mean standardized uptake value (SUV) was measured using SAT and VAT and divided by the liver SUV. The mean Hounsfield units (HU) of the SAT and VAT were measured from the CT scans. The effects of clinical variable clusters on SUVR were investigated using Bayesian hierarchical modelling; metabolic cluster (BMI, waist‐to‐hip ratio, fat percentage, muscle percentage*−1, HOMA‐IR), blood pressure (systolic, diastolic), glucose (fasting plasma glucose level, HbA1c) and C‐reactive protein.All the clinical variables changed during the 5‐year follow‐up period. The SUVR and HU of the VAT increased during follow‐up; however, those of the SAT did not change. SUVR and HU were positively correlated with both VAT and SAT. SAT and VAT SUVR were negatively associated with metabolic clusters.Ageing led to increased glucose metabolism and radiodensity in VAT, but not in SAT. VAT may reflect the ageing process more directly than SAT. Glucose metabolism was higher and radiodensity was lower in VAT than in SAT, probably owing to differences in gene expression and lipid density. Both glucose metabolism and radiodensity of VAT and SAT reflect metabolic status. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Anorexia nervosa is associated with higher brain mu-opioid receptor availability

Author

Pak, Kyoungjune, primary, Tuisku, Jouni, additional, Karlsson, Henry K., additional, Hirvonen, Jussi, additional, Rebelos, Eleni, additional, Pekkarinen, Laura, additional, Sun, Lihua, additional, Latva-Rasku, Aino, additional, Helin, Semi, additional, Rajander, Johan, additional, Karukivi, Max, additional, Nuutila, Pirjo, additional, and Nummenmaa, Lauri, additional

Published
2024
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