Objective: Social anxiety disorder (SAD) shows relatively delayed responses to pharmacotherapy when compared to other anxiety disorders. Therefore, more effective early therapeutic decisions can be made if the therapeutic response is predictable as early as possible. We studied whether the therapeutic response at 12 weeks is predictable based on the early improvement with escitalopram at 1 week.
Methods: The subjects were 28 outpatients diagnosed with SAD. The subjects took 10-20 mg/day of escitalopram. The results of the Liebowitz social anxiety scale (LSAS), Hamilton anxiety rating scale, and Montgomery-Asberg depression rating scale were evaluated at 0, 1, 4, 8, and 12 weeks of treatment. Early improvement was defined as a ≥10% reduction in the LSAS total at 1 week of treatment, and endpoint response was defined as a ≥35% reduction in the LSAS total score. The correlation between clinical characteristics and therapeutic responses was analyzed by simple linear regression. The correlation between early improvement responses and endpoint responses was analyzed by multivariate logistic regression analysis and receiver operating characteristic curves.
Results: When we adjusted the influence of a ≥35% reduction in the LSAS total endpoint score on a ≥10% reduction of the LSAS total score at 1 week of treatment for the patients' age, the early improvement group at 1 week of treatment was expected to show stronger endpoint responses compared to the group with no early improvement.
Conclusion: The results suggest that a ≥10% reduction in the LSAS total score in a week can predict endpoint treatment response.
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http://dx.doi.org/10.9758/cpn.2016.14.2.161 | DOI Listing |
Asian Pac J Cancer Prev
January 2025
Zanjan Metabolic Diseases Research Center, Zanjan University of Medical Sciences, Zanjan, Iran.
Background: Hepatocellular carcinoma (HCC), the most common form of liver cancer, has a significant mortality rate, largely due to late diagnosis. Recent advances in medical research have demonstrated the potential of biomarkers for early detection. Moreover, the discovery and use of prognostic biomarkers offer a ray of hope in the fight against liver cancer.
View Article and Find Full Text PDFAsian Pac J Cancer Prev
January 2025
Cachar Cancer Hospital and Research Center, NS Avenue, Meherpur, Silchar, Assam, India.
Objective: Cancer remains a leading cause of morbidity and mortality globally, with India experiencing a significant cancer burden. Effective population-based cancer screening is crucial for early detection and reduction of cancer-related deaths. This study aims to develop a mobile application-based Cancer Screening and Surveillance System (CSMS) to enhance the efficiency and effectiveness of population-based cancer screening by community health workers (CHWs).
View Article and Find Full Text PDFJ Assist Reprod Genet
January 2025
Department of Veterinary Medicine, University of Sassari, Via Vienna 2, Sassari, Italy.
Purpose: This study aimed to evaluate the effectiveness of single versus group culture strategies for cumulus-oocyte complexes (COCs) derived from early antral follicles (EAFs), with the goal of optimizing culture conditions to increase oocyte availability for assisted reproductive technologies.
Methods: COCs isolated from EAFs (350-450 µm) from sheep ovaries were cultured in TCM199 medium supplemented with 0.15 µg/mL Zn as zinc sulfate, 10 IU/mL FSH, 10 ng/mL estradiol, 50 ng/mL testosterone, 50 ng/mL progesterone, and 5 µM Cilostamide.
Mikrochim Acta
January 2025
College of Chemistry, Chemical Engineering & Environmental Science, Minnan Normal University, Zhangzhou, 363000, China.
The detection of cysteine (Cys) and homocysteine (Hcy) in biological fluids has great significance for early diagnosis, including Alzheimer's and Parkinson's disease. The simultaneous determination of Cys and Hcy with a single probe is still a huge challenge. To enlarge the differences in space structure (line and ring) and energy (-721.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Laboratory, the Second Hospital of Shanxi Medical University, No. 382, Wuyi Road, Taiyuan, 030001, Shanxi, People's Republic of China.
Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.
Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.
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