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Kunst N, Siu A, Drummond M, Grimm S, Grutters J, Husereau D, Koffijberg H, Rothery C, Wilson ECF, Heath A. Comment on: "Adding Value to CHEERS: New Reporting Standards for Value of Information Analyses". APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2024; 22:265-267. [PMID: 38141116 DOI: 10.1007/s40258-023-00856-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/05/2023] [Indexed: 12/24/2023]
Affiliation(s)
- Natalia Kunst
- Centre for Health Economics, University of York, Heslington, YO10 5DD, York, UK.
- School of Public Health, Yale University, New Haven, CT, USA.
| | - Annisa Siu
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada
| | - Michael Drummond
- Centre for Health Economics, University of York, Heslington, YO10 5DD, York, UK
| | - Sabine Grimm
- Department of Epidemiology and Medical Technology Assessment (KEMTA), Maastricht Health Economics and Technology Assessment (Maastricht HETA) Center, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Janneke Grutters
- Department for Health Evidence, Radboud Institute for Health Sciences, Radboudumc, Nijmegen, The Netherlands
| | - Don Husereau
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
- Institute of Health Economics, Edmonton, AB, Canada
| | - Hendrik Koffijberg
- Department of Health Technology and Services Research, TechMed Centre, University of Twente, Enschede, The Netherlands
| | - Claire Rothery
- Centre for Health Economics, University of York, Heslington, YO10 5DD, York, UK
| | - Edward C F Wilson
- Peninsula Technology Assessment Group, University of Exeter, Exeter, UK
| | - Anna Heath
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Department of Statistical Science, University College London, London, UK
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Foglia E, Ferrario L, Garagiola E, Asperti F, Mazzone A, Gatti F, Varalli L, Ponsiglione C, Cannavacciuolo L. The role of INTERCheckWEB digital innovation in supporting polytherapy management. Sci Rep 2023; 13:5544. [PMID: 37016155 PMCID: PMC10072813 DOI: 10.1038/s41598-023-32844-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 04/03/2023] [Indexed: 04/06/2023] Open
Abstract
The study aims at defining the factors affecting the clinicians' decision of changing or confirming the treatment options for frail patients in polytherapy, supporting prescribing patterns, thus also figuring out if the inclination of the clinicians towards digital solutions (INTERCheckWEB) and specific guidelines, could play a role in their decision. A literature review was performed, revealing the main individual, organizational and decisional factors, impacting on the clinicians' propensity to change the current patients' therapy: the clinician perceptions of support in case of clinical guidelines use or INTERCheckWEB use were studied. A qualitative approach was implemented, and thirty-five clinicians completed a questionnaire, aimed at evaluating fifteen different clinical cases, defining if they would change the patient's current therapy depending on the level of information received. Three methodological approaches were implemented. (1) Bivariate correlations to test the relationships between variables. (2) Hierarchical sequential linear regression model to define the predictors of the clinician propensity to change therapy. (3) Fuzzy Qualitative Comparative Analysis-fsQCA, to figure out the combination of variables leading to the outcome. Patient's age and autonomy (p value = 0.000), as well as clinician's perception regarding IT ease of use (p value = 0.043) and seniority (p value = 0.009), number of drugs assumed by the patients (p value = 0.000) and number of concomitant diseases (p value = 0.000) are factors influencing a potential change in the current therapy. The fsQCA-crisp confirms that the clinical conditions of the patients are the driving factors that prompt the clinicians towards a therapy change.
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Affiliation(s)
- Emanuela Foglia
- LIUC Business School, LIUC- University Cattaneo, Healthcare Datascience LAB, Corso Matteotti 22, 21053, Castellanza, Varese, Italy
| | - Lucrezia Ferrario
- LIUC Business School, LIUC- University Cattaneo, Healthcare Datascience LAB, Corso Matteotti 22, 21053, Castellanza, Varese, Italy.
| | - Elisabetta Garagiola
- LIUC Business School, LIUC- University Cattaneo, Healthcare Datascience LAB, Corso Matteotti 22, 21053, Castellanza, Varese, Italy
| | - Federica Asperti
- LIUC Business School, LIUC- University Cattaneo, Healthcare Datascience LAB, Corso Matteotti 22, 21053, Castellanza, Varese, Italy
| | | | | | - Luca Varalli
- ASST Ovest Milanese Hospital, Legnano, Milano, Italy
| | - Cristina Ponsiglione
- Department of Industrial Engineering, University of Naples Federico II, Naples, Italy
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Wilson LAB, Zajitschek SRK, Lagisz M, Mason J, Haselimashhadi H, Nakagawa S. Sex differences in allometry for phenotypic traits in mice indicate that females are not scaled males. Nat Commun 2022; 13:7502. [PMID: 36509767 PMCID: PMC9744842 DOI: 10.1038/s41467-022-35266-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 11/24/2022] [Indexed: 12/14/2022] Open
Abstract
Sex differences in the lifetime risk and expression of disease are well-known. Preclinical research targeted at improving treatment, increasing health span, and reducing the financial burden of health care, has mostly been conducted on male animals and cells. The extent to which sex differences in phenotypic traits are explained by sex differences in body weight remains unclear. We quantify sex differences in the allometric relationship between trait value and body weight for 363 phenotypic traits in male and female mice, recorded in >2 million measurements from the International Mouse Phenotyping Consortium. We find sex differences in allometric parameters (slope, intercept, residual SD) are common (73% traits). Body weight differences do not explain all sex differences in trait values but scaling by weight may be useful for some traits. Our results show sex differences in phenotypic traits are trait-specific, promoting case-specific approaches to drug dosage scaled by body weight in mice.
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Affiliation(s)
- Laura A. B. Wilson
- grid.1005.40000 0004 4902 0432Evolution & Ecology Research Centre, UNSW Data Science Hub, and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052 Australia ,grid.1001.00000 0001 2180 7477School of Archaeology and Anthropology, The Australian National University, Canberra, ACT 2600 Australia
| | - Susanne R. K. Zajitschek
- grid.1005.40000 0004 4902 0432Evolution & Ecology Research Centre, UNSW Data Science Hub, and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052 Australia ,grid.4425.70000 0004 0368 0654School of Biological and Environmental Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF UK
| | - Malgorzata Lagisz
- grid.1005.40000 0004 4902 0432Evolution & Ecology Research Centre, UNSW Data Science Hub, and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052 Australia
| | - Jeremy Mason
- Melio Healthcare Ltd., City Tower, 40 Basinghall Street, London, EC2V 5DE UK ,European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD UK
| | - Hamed Haselimashhadi
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD UK
| | - Shinichi Nakagawa
- grid.1005.40000 0004 4902 0432Evolution & Ecology Research Centre, UNSW Data Science Hub, and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052 Australia
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