Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: To retrospectively compare the safety and efficacy of ultrasound-guided radiofrequency ablation (RFA) with parotidectomy for superficial pleomorphic adenoma (PA). Materials and Methods: From March 2022 to October 2023, 88 patients diagnosed with superficial parotid PA underwent either RFA (n = 12; mean age, 47.1 years) or parotidectomy (n = 76; mean age, 47.8 years). Patients in the RFA group were matched to those in the surgery group in a 1:1 ratio using propensity scores based on age, sex, tumor volume, diameter, location, and comorbidities. Ultrasound characteristics, cosmetic scores (0–4), numerical rating scale scores (0–10), and complications were assessed before the procedures and at 1-, 3-, and 6-month follow-ups. Outcomes were compared between baseline and follow-up in the RFA group and between the RFA and surgery groups. Results: In the RFA group, significant reductions in tumor volume were observed between baseline (median, 2.02 cm 3 ) and the 1-month follow-up (median, 1.21 cm 3 ; P = 0.015), between the 1-month and 3-month follow-ups (median, 0.53 cm 3 ; P= 0.002), and between the 3- and 6-month follow-ups (median, 0.23 cm 3 ; P = 0.003). The volume reduction ratios at 1, 3, and 6 months were 39.7%, 79.9%, and 88.0%, respectively. The cosmetic score was significantly lower at 3- and 6-month followup compared to baseline (median 1 and 1 vs. 4, P = 0.04). The numerical rating scale scores did not differ significantly from baseline throughout follow-up. In the propensity score-matched analysis (12 patients per group), RFA was associated with a shorter median procedure time (61.5 vs. 253.3 minutes; P < 0.001), shorter hospital stay (0 vs. 4 days; P < 0.001), and lower cost (1859.9 vs. 3512.4 USD; P < 0.001) than parotidectomy, with no significant difference in overall complication rates (33.3% [4/12] vs. 41.7% [5/12]; P = 1.000). Conclusion RFA may be a safe and effective alternative to surgery for superficial parotid PA, offering a shorter median procedure time, shorter hospital stay, and lower costs.

Objective: To retrospectively compare the safety and efficacy of ultrasound-guided radiofrequency ablation (RFA) with parotidectomy for superficial pleomorphic adenoma (PA). Materials and Methods: From March 2022 to October 2023, 88 patients diagnosed with superficial parotid PA underwent either RFA (n = 12; mean age, 47.1 years) or parotidectomy (n = 76; mean age, 47.8 years). Patients in the RFA group were matched to those in the surgery group in a 1:1 ratio using propensity scores based on age, sex, tumor volume, diameter, location, and comorbidities. Ultrasound characteristics, cosmetic scores (0–4), numerical rating scale scores (0–10), and complications were assessed before the procedures and at 1-, 3-, and 6-month follow-ups. Outcomes were compared between baseline and follow-up in the RFA group and between the RFA and surgery groups. Results: In the RFA group, significant reductions in tumor volume were observed between baseline (median, 2.02 cm 3 ) and the 1-month follow-up (median, 1.21 cm 3 ; P = 0.015), between the 1-month and 3-month follow-ups (median, 0.53 cm 3 ; P= 0.002), and between the 3- and 6-month follow-ups (median, 0.23 cm 3 ; P = 0.003). The volume reduction ratios at 1, 3, and 6 months were 39.7%, 79.9%, and 88.0%, respectively. The cosmetic score was significantly lower at 3- and 6-month followup compared to baseline (median 1 and 1 vs. 4, P = 0.04). The numerical rating scale scores did not differ significantly from baseline throughout follow-up. In the propensity score-matched analysis (12 patients per group), RFA was associated with a shorter median procedure time (61.5 vs. 253.3 minutes; P < 0.001), shorter hospital stay (0 vs. 4 days; P < 0.001), and lower cost (1859.9 vs. 3512.4 USD; P < 0.001) than parotidectomy, with no significant difference in overall complication rates (33.3% [4/12] vs. 41.7% [5/12]; P = 1.000). Conclusion RFA may be a safe and effective alternative to surgery for superficial parotid PA, offering a shorter median procedure time, shorter hospital stay, and lower costs.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: Colorectal cancer (CRC) often spreads to the liver, necessitating surgical treatment for CRC liver metastasis (CRLM). Iron-deficiency anemia is common in CRC patients and is associated with fatigue and weakness. This study investigated the effects of iron-deficiency anemia on the outcomes of surgical resection of CRLM. Methods: This population-based, retrospective study evaluated data from adults ≥20 years old with CRLM who underwent hepatic resection. All patient data were extracted from the 2005–2018 US National (Nationwide) Inpatient Sample (NIS) database. The outcome measures were in-hospital outcomes including 30-day mortality, unfavorable discharge, and prolonged length of hospital stay (LOS), and short-term complications such as bleeding and infection. Associations between iron-deficiency anemia and outcomes were determined using logistic regression analysis. Results: Data from 7,749 patients (representing 37,923 persons in the United States after weighting) were analyzed. Multivariable analysis revealed that iron-deficiency anemia was significantly associated with an increased risk of prolonged LOS (adjusted odds ratio [aOR], 2.76; 95% confidence interval [CI], 2.30–3.30), unfavorable discharge (aOR, 2.42; 95% CI, 1.83–3.19), bleeding (aOR, 5.05; 95% CI, 2.92–8.74), sepsis (aOR, 1.60; 95% CI, 1.04–2.46), pneumonia (aOR, 2.54; 95% CI, 1.72–3.74), and acute kidney injury (aOR, 1.71; 95% CI, 1.24–2.35). Subgroup analyses revealed consistent associations between iron-deficiency anemia and prolonged LOS across age, sex, and obesity status categories. Conclusion In patients undergoing hepatic resection for CRLM, iron-deficiency anemia is an independent risk factor for prolonged LOS, unfavorable discharge, and several critical postoperative complications. These findings underscore the need for proactive anemia management to optimize surgical outcomes.