The clinical and public health significance of nonalcoholic fatty liver disease (NAFLD) is not well established. We investigated the long-term effect of NAFLD on mortality. This analysis utilized the National Health and Nutrition Examination Survey conducted in 1988-1994 and subsequent follow-up data for mortality through December 31, 2006. NAFLD was defined by ultrasonographic detection of hepatic steatosis in the absence of other known liver diseases. The presence and severity of hepatic fibrosis in subjects with NAFLD was determined by the NAFLD fibrosis score (NFS), the aspartate aminotransferase to platelet ratio index (APRI), and FIB-4 score. Of 11,154 participants, 34.0% had NAFLD—the majority (71.7%) had NFS consistent with lack of significant fibrosis (NFS <−1.455), whereas 3.2% had a score indicative of advanced fibrosis (NFS >0.676). After a median follow-up of 14.5 years, NAFLD was not associated with higher mortality (age- and sex-adjusted hazard ratio [HR]: 1.05; 95% confidence interval [CI]: 0.93-1.19). In contrast, there was a progressive increase in mortality with advancing fibrosis scores. Compared to subjects without fibrosis, those with a high probability of advanced fibrosis had a 69% increase in mortality (for NFS: HR, 1.69, 95% CI: 1.09-2.63; for APRI: HR, 1.85, 95% CI: 1.02-3.37; for FIB-4: HR, 1.66, 95% CI: 0.98-2.82) after adjustment for other known predictors of mortality. These increases in mortality were almost entirely from cardiovascular causes (for NFS: HR, 3.46, 95% CI: 1.91-6.25; for APRI: HR, 2.53, 95% CI: 1.33-4.83; for FIB-4: HR, 2.68, 95% CI: 1.44-4.99). Conclusions : Ultrasonography-diagnosed NAFLD is not associated with increased mortality. However, advanced fibrosis, as determined by noninvasive fibrosis marker panels, is a significant predictor of mortality, mainly from cardiovascular causes, independent of other known factors.

Radiomics, which involves the use of high-dimensional quantitative imaging features for predictive purposes, is a powerful tool for developing and testing medical hypotheses. Radiologic and statistical challenges in radiomics include those related to the reproducibility of imaging data, control of overfitting due to high dimensionality, and the generalizability of modeling. The aims of this review article are to clarify the distinctions between radiomics features and other omics and imaging data, to describe the challenges and potential strategies in reproducibility and feature selection, and to reveal the epidemiological background of modeling, thereby facilitating and promoting more reproducible and generalizable radiomics research.

Baek S, et al. Korean J Radiol. 2015 Mar-Apr;16(2):286-296. http://dx.doi.org/10.3348/kjr.2015.16.2.286

Introduction: Metformin use has recently been observed to decrease both the rate and mortality of breast cancer. Our study was aim to determine whether metformin use is associated with survival in diabetic breast cancer patients by breast cancer subtype and systemic treatment. Methods: Data from the Asan Medical Center Breast Cancer Database from 1997 to 2007 were analyzed. The study cohort comprised 6,967 nondiabetic patients, 202 diabetic patients treated with metformin, and 184 diabetic patients that did not receive metformin. Patients who were divided into three groups by diabetes status and metformin use were also divided into four subgroups by hormone receptor and HER2-neu status. Results: In Kaplan-Meier analysis, the metformin group had a significantly better overall and cancer specific survival outcome compared with non metformin diabetic group (P <0.005 for both). There was no difference in survival between the nondiabetic and metformin groups. In multivariate analysis, Compared with metformin group, patients who did not receive metformin tended to have a higher risk of metastasis with HR 5.37 (95 % CI, 1.88 to 15.28) and breast cancer death with HR 6.51 (95 % CI, 1.88 to 15.28) on the hormone receptor-positive and HER2-negative breast cancer. The significant survival benefit of metformin observed in diabetic patients who received chemotherapy and endocrine therapy (HR for disease free survival 2.14; 95 % CI 1.14 to 4.04) was not seen in diabetic patients who did not receive these treatments. Conclusion: Patients receiving metformin treatment when breast cancer diagnosis show a better prognosis only if they have hormone receptor-positive, HER2-positive tumors. Metformin treatment might provide a survival benefit when added to systemic therapy in diabetic patients.

Chung S, et al. J Korean Med Sci. 2021 Nov;36(47):e319. https://doi.org/10.3346/jkms.2021.36.e319

Background: The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) is the instrument most frequently used to measure quality of life in cancer patients, whereas the EQ-5D is widely used to measure and evaluate general health status. Although the EORTC QLQ-C30 has been mapped to EQ-5D utilities, those studies were limited to patients with a single type of cancer. The present study aimed to develop a mapping relationship between the EORTC QLQ-C30 and EQ-5D-based utility values at the individual level. Methods: The model was derived using patients with different types of cancer who were receiving chemotherapy. The external validation set comprised outpatients with colon cancer. Ordinary least squares regression was used to estimate the EQ-5D index from the EORTC QLQ-C30 results. The predictability, goodness of fit, and signs of the estimated coefficients of the model were assessed. Predictive ability was determined by calculating the mean absolute error, the estimated proportions with absolute errors > 0.05 and > 0.1, and the root-mean-squared error (RMSE). Results: A model that included global health, physical, role, emotional functions, and pain was optimal, with a mean absolute error of 0.069 and an RMSE of 0.095 (normalized RMSE, 8.1%). The explanatory power of this model was 51.6%. The mean absolute error was higher for modeled patients in poor health. Conclusions: This mapping algorithm enabled the EORTC QLQ-C30 to be converted to the EQ-5D utility index to assess cancer patients in Korea.