In Asian countries, ultrasound has been proposed as a possible alternative for mammography in breast cancer screening because of its superiority in dense breasts, accessibility and low costs. This research aimed to meta-analyze the evidence for the diagnostic performance of ultrasound compared to mammography for breast cancer screening in Asian women. PubMed, Web of Science, and China National Knowledge Infrastructure databases were searched for studies that concurrently compared mammography and ultrasound in 2000–2019. Data extraction and risk of bias were performed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) statement. The primary outcome was the sensitivity and specificity. Bivariate random models were used to generate pooled estimates of diagnostic parameters and 95% confidence intervals (95% CI). In total, 4424 studies were identified of which six studies met the inclusion criteria with a sample size of 124,425 women. The pooled mean prevalence of the included studies was 3.7‰ (range: 1.2–5.7‰). The pooled sensitivity of mammography was significantly higher than that of ultrasound (0.81 [95% CI 0.71–0.88] versus 0.65 [95% CI 0.58–0.72], p = 0.03), but no significant differences were found in specificity (0.98 [95% CI: 0.94–1.00] versus 0.99 [95% CI: 0.97–1.00], p = 0.65). In conclusion, based on the currently available data on sensitivity alone, there is no indication that ultrasound can replace mammography in breast cancer screening in Asian women.

Objectives: The role of Vitamin D (VD) in calcium balance and bone health makes VD a vital factor in osteoarthritis (OA). Studies that have evaluated the effect of VD on OA patients have mainly been performed on a short-term basis. In this analysis, we aimed to evaluate whether VD was associated with mortality, a long-term outcome, in OA patients. Methods: Participants with self-reported OA from NHANES III and NHANES 2001–2018 were included. Associations of 25(OH)D concentrations with mortality risk were assessed continuously using restricted cubic splines and by categories (i.e., <25.0, 25.0–49.9, 50.0–74.9, and ≥75.0 nmol/L) using the Cox regression model. Sensitivity and stratified analyses were performed to evaluate the robustness of the results. Results: A total of 4570 patients were included, of which 1388 died by 31 December 2019. An L-shaped association was observed between 25(OH)D concentrations and all-cause mortality, whereas an inverse association was found for cardiovascular disease (CVD) mortality. The adjusted hazard ratios (95% confidence intervals) across four categories were 1.00 (reference), 0.49 (0.31, 0.75), 0.45 (0.29, 0.68), and 0.43 (0.27, 0.69) for all-cause mortality and 1.00 (reference), 0.28 (0.14, 0.59), 0.25 (0.12, 0.51), and 0.24 (0.11, 0.49) for CVD-specific mortality; no significant associations were found for cancer-specific mortality. Similar results were observed when stratified and sensitivity analyses were performed. Conclusions: Compared with patients with insufficient or deficient serum 25(OH)D, those with sufficient 25(OH)D concentrations had a lower risk of all-cause and CVD mortality, supporting a beneficial role of VD on a long-term basis.

Background: Instead of a single value for mammographic sensitivity, a sensitivity function based on tumor size more realistically reflects mammography's detection capability. Because previous models may have overestimated size-specific sensitivity, we aimed to provide a novel approach to improve sensitivity estimation as a function of tumor size. Methods: Using aggregated data on interval and screen-detected cancers, observed tumor sizes were back-calculated to the time of screening using an exponential tumor growth model and a follow-up time of 4 years. From the observed number of detected cancers and an estimation of the number of false-negative cancers, a model for the sensitivity as a function of tumor size was determined. A univariate sensitivity analysis was conducted by varying follow-up time and tumor volume doubling time (TVDT). A systematic review was conducted for external validation of the sensitivity model. Results: Aggregated data of 22,915 screen-detected and 10,670 interval breast cancers from the Dutch screening program were used. The model showed that sensitivity increased from 0 to 85% for tumor sizes from 2 to 20 mm. When TVDT was set at the upper and lower limits of the confidence interval, sensitivity for a 20-mm tumor was 74% and 93%, respectively. The estimated sensitivity gave comparable estimates to those from two of three studies identified by our systematic review. Conclusion: Derived from aggregated breast screening outcomes data, our model's estimation of sensitivity as a function of tumor size may provide a better representation of data observed in screening programs than other models. (C) 2020 The Authors. Published by Elsevier Ltd.

A specialized large language model (LLM) for report summarization had better performance than GPT-4o (OpenAI), a general-purpose LLM, in generating CT and MRI radiology report summaries.