Purpose: Preference-based quality of life measures (PBMs) are used to generate quality-adjusted life years (QALYs) in economic evaluations. A PBM consists of (1) a health state classification system and (2) a utility value set that allows the instrument responses to be converted to QALYs. A new, oral health-specific classification system, the Early Childhood Oral Health Impact Scale-4D (ECOHIS-4D) has recently been developed. The aim of this study was to generate an Australian utility value set for the ECOHIS-4D.
Methods: A discrete choice experiment with duration (DCE) was used as the preference elicitation technique. An online survey was administered to a representative sample of Australian adults over 18 years. Respondents were given 14 choice tasks (10 tasks from the DCE design of 50 choice sets blocked into five blocks, 2 practice tasks, a repeated and a dominant task). Data were analyzed using the conditional logit model.
Results: A total of 1201 respondents from the Australian general population completed the survey. Of them, 69% (n = 829) perceived their oral health status to be good, very good, or excellent. The estimated coefficients from the conditional logit models were in the expected directions and were statistically significant (p < 0.001). The utility values for health states defined by the ECOHIS-4D ranged from 0.0376 to 1.0000.
Conclusions: This newly developed utility value set will enable the calculation of utility values for economic evaluations of interventions related to oral diseases such as dental caries among young children. This will facilitate more effective resource allocation for oral health services.
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http://dx.doi.org/10.1007/s10198-022-01542-x | DOI Listing |
Diabetol Metab Syndr
January 2025
First Central Clinical Medical Institute, Tianjin Medical University, Tianjin, China.
Background: To identify the relationship between BMI or lipid metabolism and diabetic neuropathy using a Mendelian randomization (MR) study.
Methods: Body constitution-related phenotypes, namely BMI (kg/m), total cholesterol (TC), and triglyceride (TG), were investigated in this study. Despite the disparate origins of these data, all were accessible through the IEU OPEN GWAS database ( https://gwas.
Biomark Res
January 2025
Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, P.R. China.
Background: Disease progression within 24 months (POD24) significantly impacts overall survival (OS) in patients with follicular lymphoma (FL). This study aimed to develop a robust predictive model, FLIPI-C, using a machine learning approach to identify FL patients at high risk of POD24.
Methods: A cohort of 1,938 FL patients (FL1-3a) from seventeen centers nationwide in China was randomly divided into training and internal validation sets (2:1 ratio).
BMC Cancer
January 2025
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Objective: Rapid on-site evaluation (ROSE) of respiratory cytology specimens is a critical technique for accurate and timely diagnosis of lung cancer. However, in China, limited familiarity with the Diff-Quik staining method and a shortage of trained cytopathologists hamper utilization of ROSE. Therefore, developing an improved deep learning model to assist clinicians in promptly and accurately evaluating Diff-Quik stained cytology samples during ROSE has important clinical value.
View Article and Find Full Text PDFJ Food Drug Anal
December 2024
Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan.
This study was aimed to evaluate the cost-effectiveness of pembrolizumab with chemotherapy (pembrolizumab combination therapy) and compare it with standard-of-care platinum-based chemotherapy (chemotherapy alone) as a first-line treatment for metastatic nonsquamous NSCLC from the perspective of Taiwan's third-party-payer public health-care system. We used a partitioned survival model with an estimated time horizon of 10 years. The partitioned survival model uses Kaplan-Meier estimates of progression-free and overall survival from the KEYNOTE-189 clinical trial.
View Article and Find Full Text PDFJ Psychosom Res
December 2024
Badminton Technical and Tactical Analysis and Diagnostic Laboratory, National Academy of Badminton, Guangzhou Sport University, Guangzhou 510500, China. Electronic address:
Purpose: This study aims to harness machine learning techniques, particularly the Random Survival Forest (RSF) model, to assess the impact of depression on cardiovascular disease (CVD) mortality among hypertensive patients. A key objective is to elucidate the interplay between mental health, lifestyle, and physical activity while comparing the effectiveness of the RSF model against the traditional Cox proportional hazards model in predicting CVD mortality.
Methods: Data from the National Health and Nutrition Examination Survey (NHANES) spanning 2007 to 2014 were used for comprehensive depression screening.
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