In health technology assessment (HTA), decision criteria are considered relevant to support the complex deliberative process that requires simultaneous consideration of multiple factors. The aim was to identify and analyze the decision criteria that have been used by the National Health Technology Assessment Commission (CONITEC) when recommending the incorporation of technologies for the treatment of cancer. Descriptive study, based on reports from CONITEC, between 2012 and 2018, on oncology technologies. The data were collected in a specific extraction form and analyzed using descriptive statistics. 39 reports were analyzed, 15 of them did not present any explicit decision criteria. Medicines were the most frequently evaluated type of technology. The most frequent types of cancers were: breast cancer, head and neck cancer, colorectal cancer, non-Hodgkin's lymphoma and lung cancer. The most frequently considered criteria were: financial impact and effectiveness. The study identified the decision criteria that have been most used in the area of oncology, however, the lack of transparency in relation to the weight of these criteria makes it difficult to understand their influence on the result of the decisions taken.
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http://dx.doi.org/10.1590/1413-81232022277.14242021 | DOI Listing |
Ann Surg Oncol
January 2025
Department of Surgery, Duke University Medical Center, Durham, NC, USA.
Background: Bilateral risk-reducing mastectomies (RRMs) have been proven to decrease the risk of breast cancer in patients at high risk owing to family history or having pathogenic genetic mutations. However, few resources with consolidated data have detailed the patient experience following surgery. This systematic review features patient-reported outcomes for patients with no breast cancer history in the year after their bilateral RRM.
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January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
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January 2025
Department of Mathematics, Dambi Dollo University, Dambi Dollo, Oromia, Ethiopia.
A novel method for solving the multiple-attribute decision-making problem is proposed using the complex Diophantine interval-valued Pythagorean normal set (CDIVPNS). This study aims to discuss aggregating operations and how they are interpreted. We discuss the concept of CDIVPN weighted averaging (CDIVPNWA), CDIVPN weighted geometric (CDIVPNWG), generalized CDIVPN weighted averaging (CGDIVPNWA) and generalized CGDIVPN weighted geometric (CGDIVPNWG).
View Article and Find Full Text PDFActa Vet Scand
January 2025
Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 2, 1870, Frederiksberg C, Denmark.
Background: Prevention of iron deficiency in suckling piglets by intramuscular injection of a standardized amount of iron dextran or gleptoferron in the first days of life can lead to over- or underdosage with respective health risks. Currently, combined iron products containing an active substance against coccidia are also used on farms. When using a combination product targeting two diseases, an adjustment of the necessary amount of iron to prevent anaemia in the frame of a farm-specific treatment protocol is not possible.
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January 2025
Logistics Education (LEED) at Kühne Foundation, Hamburg, Germany.
Background: To ensure the complete traceability of healthcare commodities, robust end-to-end data management protocols are needed for the supply chain. In Ethiopia, digital tools like Dagu-2 are used in the lower levels of the healthcare supply chain. However, there is a lack of information regarding the implementation status, factors, and challenges of Dagu-2, as it is a recent upgrade from the offline Dagu-1 application.
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