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The impact of rare kidney diseases on kidney failure
Wong and colleagues’ findings highlight the fact that rare kidney disease patients, although a smaller portion of the CKD population (5–10%), constitute a substantial fraction (at least 25%) of those receiving kidney replacement therapy due to a lower mortality rate, higher risk of kidney failure, a...
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Published in: | The Lancet (British edition) 2024-03, Vol.403 (10433), p.1211-1213 |
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description | Wong and colleagues’ findings highlight the fact that rare kidney disease patients, although a smaller portion of the CKD population (5–10%), constitute a substantial fraction (at least 25%) of those receiving kidney replacement therapy due to a lower mortality rate, higher risk of kidney failure, and better survival on dialysis. [...]addressing the unmet need for effective therapies in rare kidney diseases could substantially reduce the long-term demand for kidney replacement therapy and the associated economic impact on health-care systems. Peakstock/Science Photo Library Furthermore, the study highlights the importance of distinguishing patients with rare kidney diseases from those with more common causes of CKD, to facilitate early specialist referral and treatment aimed at delaying the progression to kidney failure as recommended by the National Institute for Health and Care Excellence guideline for CKD.6 Early diagnosis of rare kidney diseases requires increased education and awareness among health-care providers and more extensive use of genetic or advanced diagnostic testing, particularly in patients with unexplained CKD. Clinicians might find the insights from the RaDaR data on the natural history of individual rare diseases valuable for discussions about care and trial participation with patients and their caregivers.7 However, it is essential to recognise that the findings represent the prognosis in the context of the standard of care at the time of the study. [...]the prognosis will probably improve with the wider implementation of supportive kidney therapies, such as SGLT2 inhibitors,8 and the development of novel treatments such as cell and gene therapies for specific rare kidney diseases.9 The application of big data analytics—including machine-learning algorithms for the analyses of data collected by registries such as RaDaR and the European Rare Kidney Disease Registry—could provide valuable insights into rare kidney diseases and facilitate personalised medicine in future.10 OLA declares consulting fees from Innovate UK, Merck, and GlaxoSmithKline outside the submitted work and receives funding from the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, NIHR Applied Research Collaboration West Midlands, NIHR Blood and Transplant Research Unit in Precision Transplant and Cellular Therapeutics at the University of Birmingham, University Hospitals Birmingham NHS Foundation, Innovate UK (part of UK Re |
doi_str_mv | 10.1016/S0140-6736(24)00198-3 |
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[...]addressing the unmet need for effective therapies in rare kidney diseases could substantially reduce the long-term demand for kidney replacement therapy and the associated economic impact on health-care systems. Peakstock/Science Photo Library Furthermore, the study highlights the importance of distinguishing patients with rare kidney diseases from those with more common causes of CKD, to facilitate early specialist referral and treatment aimed at delaying the progression to kidney failure as recommended by the National Institute for Health and Care Excellence guideline for CKD.6 Early diagnosis of rare kidney diseases requires increased education and awareness among health-care providers and more extensive use of genetic or advanced diagnostic testing, particularly in patients with unexplained CKD. Clinicians might find the insights from the RaDaR data on the natural history of individual rare diseases valuable for discussions about care and trial participation with patients and their caregivers.7 However, it is essential to recognise that the findings represent the prognosis in the context of the standard of care at the time of the study. [...]the prognosis will probably improve with the wider implementation of supportive kidney therapies, such as SGLT2 inhibitors,8 and the development of novel treatments such as cell and gene therapies for specific rare kidney diseases.9 The application of big data analytics—including machine-learning algorithms for the analyses of data collected by registries such as RaDaR and the European Rare Kidney Disease Registry—could provide valuable insights into rare kidney diseases and facilitate personalised medicine in future.10 OLA declares consulting fees from Innovate UK, Merck, and GlaxoSmithKline outside the submitted work and receives funding from the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, NIHR Applied Research Collaboration West Midlands, NIHR Blood and Transplant Research Unit in Precision Transplant and Cellular Therapeutics at the University of Birmingham, University Hospitals Birmingham NHS Foundation, Innovate UK (part of UK Research and Innovation), Gilead Sciences, Anthony Nolan, and Sarcoma UK.</description><identifier>ISSN: 0140-6736</identifier><identifier>ISSN: 1474-547X</identifier><identifier>EISSN: 1474-547X</identifier><identifier>DOI: 10.1016/S0140-6736(24)00198-3</identifier><identifier>PMID: 38492577</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Algorithms ; Big Data ; Colleges & universities ; Data analysis ; Dialysis ; Economic impact ; Failure ; Gene therapy ; Health care ; Humans ; Impact analysis ; Kidney ; Kidney diseases ; Kidney Diseases - complications ; Kidneys ; Machine learning ; Medical prognosis ; Medical research ; Mortality ; Patients ; Precision medicine ; Prognosis ; Radar ; Radar data ; Rare Diseases ; Renal failure ; Renal Insufficiency - etiology ; Renal replacement therapy ; Research facilities ; Sarcoma ; Steroids</subject><ispartof>The Lancet (British edition), 2024-03, Vol.403 (10433), p.1211-1213</ispartof><rights>2024 Elsevier Ltd</rights><rights>2024. Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c341t-d416a0ba1dc4c00471dcd9521360b5fc05c1be292e977f1a2a9e06bdefa082a13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38492577$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Aiyegbusi, Olalekan Lee</creatorcontrib><creatorcontrib>Fenton, Anthony</creatorcontrib><title>The impact of rare kidney diseases on kidney failure</title><title>The Lancet (British edition)</title><addtitle>Lancet</addtitle><description>Wong and colleagues’ findings highlight the fact that rare kidney disease patients, although a smaller portion of the CKD population (5–10%), constitute a substantial fraction (at least 25%) of those receiving kidney replacement therapy due to a lower mortality rate, higher risk of kidney failure, and better survival on dialysis. [...]addressing the unmet need for effective therapies in rare kidney diseases could substantially reduce the long-term demand for kidney replacement therapy and the associated economic impact on health-care systems. Peakstock/Science Photo Library Furthermore, the study highlights the importance of distinguishing patients with rare kidney diseases from those with more common causes of CKD, to facilitate early specialist referral and treatment aimed at delaying the progression to kidney failure as recommended by the National Institute for Health and Care Excellence guideline for CKD.6 Early diagnosis of rare kidney diseases requires increased education and awareness among health-care providers and more extensive use of genetic or advanced diagnostic testing, particularly in patients with unexplained CKD. Clinicians might find the insights from the RaDaR data on the natural history of individual rare diseases valuable for discussions about care and trial participation with patients and their caregivers.7 However, it is essential to recognise that the findings represent the prognosis in the context of the standard of care at the time of the study. [...]the prognosis will probably improve with the wider implementation of supportive kidney therapies, such as SGLT2 inhibitors,8 and the development of novel treatments such as cell and gene therapies for specific rare kidney diseases.9 The application of big data analytics—including machine-learning algorithms for the analyses of data collected by registries such as RaDaR and the European Rare Kidney Disease Registry—could provide valuable insights into rare kidney diseases and facilitate personalised medicine in future.10 OLA declares consulting fees from Innovate UK, Merck, and GlaxoSmithKline outside the submitted work and receives funding from the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, NIHR Applied Research Collaboration West Midlands, NIHR Blood and Transplant Research Unit in Precision Transplant and Cellular Therapeutics at the University of Birmingham, University Hospitals Birmingham NHS Foundation, Innovate UK (part of UK Research and Innovation), Gilead Sciences, Anthony Nolan, and Sarcoma UK.</description><subject>Algorithms</subject><subject>Big Data</subject><subject>Colleges & universities</subject><subject>Data analysis</subject><subject>Dialysis</subject><subject>Economic impact</subject><subject>Failure</subject><subject>Gene therapy</subject><subject>Health care</subject><subject>Humans</subject><subject>Impact analysis</subject><subject>Kidney</subject><subject>Kidney diseases</subject><subject>Kidney Diseases - complications</subject><subject>Kidneys</subject><subject>Machine learning</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Mortality</subject><subject>Patients</subject><subject>Precision medicine</subject><subject>Prognosis</subject><subject>Radar</subject><subject>Radar data</subject><subject>Rare Diseases</subject><subject>Renal failure</subject><subject>Renal Insufficiency - etiology</subject><subject>Renal replacement therapy</subject><subject>Research facilities</subject><subject>Sarcoma</subject><subject>Steroids</subject><issn>0140-6736</issn><issn>1474-547X</issn><issn>1474-547X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkEtLAzEQx4Motj4-grLgpR5WJ4_dbE4ixRcUPFjBW8gms5ja7takK_Tbu30evHiaYfj9Z4YfIRcUbijQ_PYNqIA0lzwfMHENQFWR8gPSp0KKNBPy45D090iPnMQ4AQCRQ3ZMerwQimVS9okYf2LiZ3NjF0lTJcEETL68q3GZOB_RRIxJU-9GlfHTNuAZOarMNOL5tp6S98eH8fA5Hb0-vQzvR6nlgi5SJ2huoDTUWWG727JrnMoY5TmUWWUhs7REphgqKStqmFEIeemwMlAwQ_kpGWz2zkPz3WJc6JmPFqdTU2PTRs1UVjDFC1ihV3_QSdOGuvtOc-BKUiEK6KhsQ9nQxBiw0vPgZyYsNQW90qrXWvXKmWZCr7Vq3uUut9vbcoZun9p57IC7DYCdjh-PQUfrsbbofEC70K7x_5z4BQp4hS0</recordid><startdate>20240330</startdate><enddate>20240330</enddate><creator>Aiyegbusi, Olalekan Lee</creator><creator>Fenton, Anthony</creator><general>Elsevier Ltd</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0TT</scope><scope>0TZ</scope><scope>0U~</scope><scope>3V.</scope><scope>7QL</scope><scope>7QP</scope><scope>7RV</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88C</scope><scope>88E</scope><scope>88G</scope><scope>88I</scope><scope>8AF</scope><scope>8AO</scope><scope>8C1</scope><scope>8C2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>ASE</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FPQ</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K6X</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>KB~</scope><scope>LK8</scope><scope>M0R</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2M</scope><scope>M2O</scope><scope>M2P</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>S0X</scope><scope>7X8</scope></search><sort><creationdate>20240330</creationdate><title>The impact of rare kidney diseases on kidney failure</title><author>Aiyegbusi, Olalekan Lee ; Fenton, Anthony</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c341t-d416a0ba1dc4c00471dcd9521360b5fc05c1be292e977f1a2a9e06bdefa082a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Big Data</topic><topic>Colleges & universities</topic><topic>Data analysis</topic><topic>Dialysis</topic><topic>Economic impact</topic><topic>Failure</topic><topic>Gene therapy</topic><topic>Health care</topic><topic>Humans</topic><topic>Impact analysis</topic><topic>Kidney</topic><topic>Kidney diseases</topic><topic>Kidney Diseases - 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Academic</collection><jtitle>The Lancet (British edition)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aiyegbusi, Olalekan Lee</au><au>Fenton, Anthony</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The impact of rare kidney diseases on kidney failure</atitle><jtitle>The Lancet (British edition)</jtitle><addtitle>Lancet</addtitle><date>2024-03-30</date><risdate>2024</risdate><volume>403</volume><issue>10433</issue><spage>1211</spage><epage>1213</epage><pages>1211-1213</pages><issn>0140-6736</issn><issn>1474-547X</issn><eissn>1474-547X</eissn><abstract>Wong and colleagues’ findings highlight the fact that rare kidney disease patients, although a smaller portion of the CKD population (5–10%), constitute a substantial fraction (at least 25%) of those receiving kidney replacement therapy due to a lower mortality rate, higher risk of kidney failure, and better survival on dialysis. [...]addressing the unmet need for effective therapies in rare kidney diseases could substantially reduce the long-term demand for kidney replacement therapy and the associated economic impact on health-care systems. Peakstock/Science Photo Library Furthermore, the study highlights the importance of distinguishing patients with rare kidney diseases from those with more common causes of CKD, to facilitate early specialist referral and treatment aimed at delaying the progression to kidney failure as recommended by the National Institute for Health and Care Excellence guideline for CKD.6 Early diagnosis of rare kidney diseases requires increased education and awareness among health-care providers and more extensive use of genetic or advanced diagnostic testing, particularly in patients with unexplained CKD. Clinicians might find the insights from the RaDaR data on the natural history of individual rare diseases valuable for discussions about care and trial participation with patients and their caregivers.7 However, it is essential to recognise that the findings represent the prognosis in the context of the standard of care at the time of the study. [...]the prognosis will probably improve with the wider implementation of supportive kidney therapies, such as SGLT2 inhibitors,8 and the development of novel treatments such as cell and gene therapies for specific rare kidney diseases.9 The application of big data analytics—including machine-learning algorithms for the analyses of data collected by registries such as RaDaR and the European Rare Kidney Disease Registry—could provide valuable insights into rare kidney diseases and facilitate personalised medicine in future.10 OLA declares consulting fees from Innovate UK, Merck, and GlaxoSmithKline outside the submitted work and receives funding from the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, NIHR Applied Research Collaboration West Midlands, NIHR Blood and Transplant Research Unit in Precision Transplant and Cellular Therapeutics at the University of Birmingham, University Hospitals Birmingham NHS Foundation, Innovate UK (part of UK Research and Innovation), Gilead Sciences, Anthony Nolan, and Sarcoma UK.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>38492577</pmid><doi>10.1016/S0140-6736(24)00198-3</doi><tpages>3</tpages></addata></record> |
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subjects | Algorithms Big Data Colleges & universities Data analysis Dialysis Economic impact Failure Gene therapy Health care Humans Impact analysis Kidney Kidney diseases Kidney Diseases - complications Kidneys Machine learning Medical prognosis Medical research Mortality Patients Precision medicine Prognosis Radar Radar data Rare Diseases Renal failure Renal Insufficiency - etiology Renal replacement therapy Research facilities Sarcoma Steroids |
title | The impact of rare kidney diseases on kidney failure |
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