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Polasek TM, Peck RW. Beyond Population-Level Targets for Drug Concentrations: Precision Dosing Needs Individual-Level Targets that Include Superior Biomarkers of Drug Responses. Clin Pharmacol Ther 2024; 116:602-612. [PMID: 38328977 DOI: 10.1002/cpt.3197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 01/17/2024] [Indexed: 02/09/2024]
Abstract
The purpose of precision dosing is to increase the chances of therapeutic success in individual patients. This is achieved in practice by adjusting doses to reach precision dosing targets determined previously in relevant populations, ideally with robust supportive evidence showing improved clinical outcomes compared with standard dosing. But is this implicit assumption of translatable population-level precision dosing targets correct and the best for all patients? In this review, the types of precision dosing targets and how they are determined are outlined, problems with the translatability of these targets to individual patients are identified, and ways forward to address these challengers are proposed. Achieving improved clinical outcomes to support precision dosing over standard dosing is currently hampered by applying population-level targets to all patients. Just as "one-dose-fits-all" may be an inappropriate philosophy for drug treatment overall, a "one-target-fits-all" philosophy may limit the broad clinical benefits of precision dosing. Defining individual-level precision dosing targets may be needed for greatest therapeutic success. Superior future precision dosing targets will integrate several biomarkers that together account for the multiple sources of drug response variability.
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Affiliation(s)
- Thomas M Polasek
- Centre for Medicine Use and Safety, Monash University, Melbourne, Victoria, Australia
- CMAX Clinical Research, Adelaide, South Australia, Australia
| | - Richard W Peck
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
- Pharma Research & Development (pRED), Roche Innovation Center Basel, Basel, Switzerland
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Garbelli M, Bellocchio F, Baro Salvador ME, Chermisi M, Rincon Bello A, Godoy IB, Perez SO, Shkolenko K, Perez AS, Toro DS, Apel C, Petrovic J, Stuard S, Barbieri C, Mari F, Neri L. The Use of Anemia Control Model Is Associated with Improved Hemoglobin Target Achievement, Lower Rates of Inappropriate Erythropoietin Stimulating Agents, and Severe Anemia among Dialysis Patients. Blood Purif 2024; 53:405-417. [PMID: 38382484 DOI: 10.1159/000536181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/29/2023] [Indexed: 02/23/2024]
Abstract
INTRODUCTION The Anemia Control Model (ACM) is a certified medical device suggesting the optimal ESA and iron dosage for patients on hemodialysis. We sought to assess the effectiveness and safety of ACM in a large cohort of hemodialysis patients. METHODS This is a retrospective study of dialysis patients treated in NephroCare centers between June 1, 2013 and December 31, 2019. We compared patients treated according to ACM suggestions and patients treated in clinics where ACM was not activated. We stratified patients belonging to the reference group by historical target achievement rates in their referral centers (tier 1: <70%; tier 2: 70-80%; tier 3: >80%). Groups were matched by propensity score. RESULTS After matching, we obtained four groups with 85,512 patient-months each. ACM had 18% higher target achievement rate, 63% smaller inappropriate ESA administration rate, and 59% smaller severe anemia risk compared to Tier 1 centers (all p < 0.01). The corresponding risk ratios for ACM compared to Tier 2 centers were 1.08 (95% CI: 1.08-1.09), 0.49 (95% CI: 0.47-0.51), and 0.64 (95% CI: 0.61-0.68); for ACM compared to Tier 3 centers, 1.01 (95% CI: 1.01-1.02), 0.66 (95% CI: 0.63-0.69), and 0.94 (95% CI: 0.88-1.00), respectively. ACM was associated with statistically significant reductions in ESA dose administration. CONCLUSION ACM was associated with increased hemoglobin target achievement rate, decreased inappropriate ESA usage and a decreased incidence of severe anemia among patients treated according to ACM suggestion.
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Affiliation(s)
- Mario Garbelli
- Global Medical Office - Clinical Advanced Analytics - Data Science - EMEA, APAC, LATAM region, Fresenius Medical Care Italia spa, Vaiano Cremasco, Italy,
| | - Francesco Bellocchio
- Global Medical Office - Clinical Advanced Analytics - Data Science - EMEA, APAC, LATAM region, Fresenius Medical Care Italia spa, Vaiano Cremasco, Italy
| | | | - Milena Chermisi
- Global Medical Office - Clinical Advanced Analytics - Data Science - EMEA, APAC, LATAM region, Fresenius Medical Care Italia spa, Vaiano Cremasco, Italy
| | - Abraham Rincon Bello
- Country Medical Office - NephroCare Spain, Fresenius Medical Care, Madrid, Spain
| | - Isabel Berdud Godoy
- Country Medical Office - NephroCare Spain, Fresenius Medical Care, Madrid, Spain
| | - Sofia Ortego Perez
- Country Medical Office - NephroCare Spain, Fresenius Medical Care, Madrid, Spain
| | - Kateryna Shkolenko
- Country Medical Office - NephroCare Spain, Fresenius Medical Care, Madrid, Spain
| | - Alicia Sobrino Perez
- Country Medical Office - NephroCare Spain, Fresenius Medical Care, Madrid, Spain
| | - Diana Samaniego Toro
- Country Medical Office - NephroCare Spain, Fresenius Medical Care, Madrid, Spain
| | - Christian Apel
- Health Economics and Market Access, Fresenius Medical Care, Bad Homburg, Germany
| | - Jovana Petrovic
- Health Economics and Market Access, Fresenius Medical Care, Bad Homburg, Germany
| | - Stefano Stuard
- Global Medical Office - Clinical and Therapeutic Governance EMEA, Fresenius Medical Care, Bad Homburg, Germany
| | - Carlo Barbieri
- Global Digital Transformation and Innovation, Clinical Digital Center of Excellence, Fresenius Medical Care, Vaiano Cremasco, Italy
| | - Flavio Mari
- Global Digital Transformation and Innovation, Clinical Digital Center of Excellence, Fresenius Medical Care, Vaiano Cremasco, Italy
| | - Luca Neri
- Global Medical Office - Clinical Advanced Analytics - Data Science - EMEA, APAC, LATAM region, Fresenius Medical Care Italia spa, Vaiano Cremasco, Italy
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Kotanko P, Zhang H, Wang Y. Artificial Intelligence and Machine Learning in Dialysis: Ready for Prime Time? Clin J Am Soc Nephrol 2023; 18:803-805. [PMID: 36795031 PMCID: PMC10278848 DOI: 10.2215/cjn.0000000000000089] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Peter Kotanko
- Renal Research Institute, New York, New York
- Icahn School of Medicine at Mount Sinai, New York, New York
| | | | - Yuedong Wang
- Department of Statistics & Applied Probability, University of California at Santa Barbara, Santa Barbara, California
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