Participation rate and yield of two home-based screening methods to detect increased albuminuria in the general population in the Netherlands (THOMAS): a prospective, randomised, open-label implementation study
Chronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased albuminuria defines the early stages of CKD and is among the strongest risk factors for progressive CKD and cardiovascular disease. The value of population screen...
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Published in | The Lancet (British edition) Vol. 402; no. 10407; pp. 1052 - 1064 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
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London
Elsevier Ltd
23.09.2023
Elsevier Limited |
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Abstract | Chronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased albuminuria defines the early stages of CKD and is among the strongest risk factors for progressive CKD and cardiovascular disease. The value of population screening for albuminuria to detect CKD in an early phase has yet to be studied. We aimed to evaluate the effectiveness of two home-based albuminuria population screening methods.
Towards Home-based Albuminuria Screening (THOMAS) was a prospective, randomised, open-label implementation study that invited Dutch adults aged 45–80 years for albuminuria screening. Individuals were randomly assigned (1:1) to screening by applying either a urine collection device (UCD) that was sent by post to a central laboratory for measurement of the albumin-to-creatinine ratio (ACR) by immunoturbidimetry or to screening via a smartphone application that measures the ACR with a dipstick method at home. Randomisation was done with a four-block method via a web-based system and was stratified by age, sex, and socioeconomic status. If two or more individuals per household were invited to participate, these individuals were randomly assigned to the same group. In case of confirmed increased albuminuria at home, participants were invited for an elaborate screening in a regional hospital (Amphia Hospital, Breda, Netherlands) for CKD and cardiovascular risk factors. When abnormalities were found, participants were referred to their general practitioner for treatment. The primary outcomes were the participation rate and yield of the home-based screening and elaborate screening. Participation rate was assessed in the intention-to-screen population (ie, all participants who were invited for the home-based screening or elaborate screening). Yield was assessed in the per-protocol population (ie, all individuals who participated in the home-based screening or elaborate screening). An exploratory analysis assessed the sensitivity and specificity of both home-based screening methods. To this end, an additional quantitative ACR test was performed among people participating in the elaborate screening, and a substudy was performed among participants with a first negative home-based screening test, who were invited for an additional test. The study is registered with ClinicalTrials.gov, NCT04295889.
15 074 participants were enrolled between Nov 14, 2019, and March 19, 2021. 7552 (50·1%) were randomly assigned to home-based albuminuria screening by the UCD method and 7522 (49·9%) were assigned to albuminuria screening by the smartphone application method. The participation rate of the home-based screening was 4484 (59·4% [95% CI 58·3–60·5]) of the 7552 invited individuals for the UCD method and 3336 (44·3% [43·2–45·5]) of 7522 invited individuals for the smartphone application method (p<0·0001). Increased ACR was confirmed by home-based testing in 150 (3·3% [95% CI 2·9–3·9]) of 4484 individuals for the UCD method and 171 (5·1% [4·4–5·9]) of 3336 indivduals for the smartphone application method. 124 (82·7% [95% CI 75·8–87·9]) of 150 individuals assigned to the UCD method and 142 (83·0% [76·7–87·9]) of 171 participants assigned to the smartphone application method attended the elaborate screening. Sensitivity to detect increased ACR was 96·6% (95% CI 91·5–99·1) for the UCD method and 98·1% (89·9–99·9) for the smartphone application method, and specificity was 97·3% (94·7–98·8) for the UCD method and 67·9% (62·0–73·3) for the smartphone application method, indicating that the test characteristics of only the UCD method were sufficient for screening. Albuminuria, hypertension, hypercholesterolaemia, and decreased kidney function were newly diagnosed in 77 (62·1%), 44 (35·5%), 30 (24·2%), and 27 (21·8%) of 124 participants for the UCD method, respectively. Of the 124 participants assigned to the UCD method who completed elaborate screening, 111 (89·5%) were referred to their general practitioner for treatment because of newly diagnosed CKD or cardiovascular disease risk factors or known risk factors outside the target range.
Home-based screening of the general population for increased ACR using a UCD had a high participation rate and correctly identified individuals with increased albuminuria and yet unknown or known but outside target range CKD and cardiovascular risk factors. By contrast, the smartphone application method had a lower at-home participation rate than the UCD method and the test specificity was too low to accurately assess individuals for risk factors during the elaborate screening. The UCD screening strategy could allow for an early start of treatment to prevent progressive kidney function loss and cardiovascular disease in patients with CKD.
Dutch Kidney Foundation, Top Sector Life Sciences & Health of the Dutch Ministry of Economic Affairs. |
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AbstractList | Summary Background Chronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased albuminuria defines the early stages of CKD and is among the strongest risk factors for progressive CKD and cardiovascular disease. The value of population screening for albuminuria to detect CKD in an early phase has yet to be studied. We aimed to evaluate the effectiveness of two home-based albuminuria population screening methods. Methods Towards Home-based Albuminuria Screening (THOMAS) was a prospective, randomised, open-label implementation study that invited Dutch adults aged 45–80 years for albuminuria screening. Individuals were randomly assigned (1:1) to screening by applying either a urine collection device (UCD) that was sent by post to a central laboratory for measurement of the albumin-to-creatinine ratio (ACR) by immunoturbidimetry or to screening via a smartphone application that measures the ACR with a dipstick method at home. Randomisation was done with a four-block method via a web-based system and was stratified by age, sex, and socioeconomic status. If two or more individuals per household were invited to participate, these individuals were randomly assigned to the same group. In case of confirmed increased albuminuria at home, participants were invited for an elaborate screening in a regional hospital (Amphia Hospital, Breda, Netherlands) for CKD and cardiovascular risk factors. When abnormalities were found, participants were referred to their general practitioner for treatment. The primary outcomes were the participation rate and yield of the home-based screening and elaborate screening. Participation rate was assessed in the intention-to-screen population (ie, all participants who were invited for the home-based screening or elaborate screening). Yield was assessed in the per-protocol population (ie, all individuals who participated in the home-based screening or elaborate screening). An exploratory analysis assessed the sensitivity and specificity of both home-based screening methods. To this end, an additional quantitative ACR test was performed among people participating in the elaborate screening, and a substudy was performed among participants with a first negative home-based screening test, who were invited for an additional test. The study is registered with ClinicalTrials.gov, NCT04295889. Findings 15 074 participants were enrolled between Nov 14, 2019, and March 19, 2021. 7552 (50·1%) were randomly assigned to home-based albuminuria screening by the UCD method and 7522 (49·9%) were assigned to albuminuria screening by the smartphone application method. The participation rate of the home-based screening was 4484 (59·4% [95% CI 58·3–60·5]) of the 7552 invited individuals for the UCD method and 3336 (44·3% [43·2–45·5]) of 7522 invited individuals for the smartphone application method (p<0·0001). Increased ACR was confirmed by home-based testing in 150 (3·3% [95% CI 2·9–3·9]) of 4484 individuals for the UCD method and 171 (5·1% [4·4–5·9]) of 3336 indivduals for the smartphone application method. 124 (82·7% [95% CI 75·8–87·9]) of 150 individuals assigned to the UCD method and 142 (83·0% [76·7–87·9]) of 171 participants assigned to the smartphone application method attended the elaborate screening. Sensitivity to detect increased ACR was 96·6% (95% CI 91·5–99·1) for the UCD method and 98·1% (89·9–99·9) for the smartphone application method, and specificity was 97·3% (94·7–98·8) for the UCD method and 67·9% (62·0–73·3) for the smartphone application method, indicating that the test characteristics of only the UCD method were sufficient for screening. Albuminuria, hypertension, hypercholesterolaemia, and decreased kidney function were newly diagnosed in 77 (62·1%), 44 (35·5%), 30 (24·2%), and 27 (21·8%) of 124 participants for the UCD method, respectively. Of the 124 participants assigned to the UCD method who completed elaborate screening, 111 (89·5%) were referred to their general practitioner for treatment because of newly diagnosed CKD or cardiovascular disease risk factors or known risk factors outside the target range. Interpretation Home-based screening of the general population for increased ACR using a UCD had a high participation rate and correctly identified individuals with increased albuminuria and yet unknown or known but outside target range CKD and cardiovascular risk factors. By contrast, the smartphone application method had a lower at-home participation rate than the UCD method and the test specificity was too low to accurately assess individuals for risk factors during the elaborate screening. The UCD screening strategy could allow for an early start of treatment to prevent progressive kidney function loss and cardiovascular disease in patients with CKD. Funding Dutch Kidney Foundation, Top Sector Life Sciences & Health of the Dutch Ministry of Economic Affairs. BACKGROUNDChronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased albuminuria defines the early stages of CKD and is among the strongest risk factors for progressive CKD and cardiovascular disease. The value of population screening for albuminuria to detect CKD in an early phase has yet to be studied. We aimed to evaluate the effectiveness of two home-based albuminuria population screening methods.METHODSTowards Home-based Albuminuria Screening (THOMAS) was a prospective, randomised, open-label implementation study that invited Dutch adults aged 45-80 years for albuminuria screening. Individuals were randomly assigned (1:1) to screening by applying either a urine collection device (UCD) that was sent by post to a central laboratory for measurement of the albumin-to-creatinine ratio (ACR) by immunoturbidimetry or to screening via a smartphone application that measures the ACR with a dipstick method at home. Randomisation was done with a four-block method via a web-based system and was stratified by age, sex, and socioeconomic status. If two or more individuals per household were invited to participate, these individuals were randomly assigned to the same group. In case of confirmed increased albuminuria at home, participants were invited for an elaborate screening in a regional hospital (Amphia Hospital, Breda, Netherlands) for CKD and cardiovascular risk factors. When abnormalities were found, participants were referred to their general practitioner for treatment. The primary outcomes were the participation rate and yield of the home-based screening and elaborate screening. Participation rate was assessed in the intention-to-screen population (ie, all participants who were invited for the home-based screening or elaborate screening). Yield was assessed in the per-protocol population (ie, all individuals who participated in the home-based screening or elaborate screening). An exploratory analysis assessed the sensitivity and specificity of both home-based screening methods. To this end, an additional quantitative ACR test was performed among people participating in the elaborate screening, and a substudy was performed among participants with a first negative home-based screening test, who were invited for an additional test. The study is registered with ClinicalTrials.gov, NCT04295889.FINDINGS15 074 participants were enrolled between Nov 14, 2019, and March 19, 2021. 7552 (50·1%) were randomly assigned to home-based albuminuria screening by the UCD method and 7522 (49·9%) were assigned to albuminuria screening by the smartphone application method. The participation rate of the home-based screening was 4484 (59·4% [95% CI 58·3-60·5]) of the 7552 invited individuals for the UCD method and 3336 (44·3% [43·2-45·5]) of 7522 invited individuals for the smartphone application method (p<0·0001). Increased ACR was confirmed by home-based testing in 150 (3·3% [95% CI 2·9-3·9]) of 4484 individuals for the UCD method and 171 (5·1% [4·4-5·9]) of 3336 indivduals for the smartphone application method. 124 (82·7% [95% CI 75·8-87·9]) of 150 individuals assigned to the UCD method and 142 (83·0% [76·7-87·9]) of 171 participants assigned to the smartphone application method attended the elaborate screening. Sensitivity to detect increased ACR was 96·6% (95% CI 91·5-99·1) for the UCD method and 98·1% (89·9-99·9) for the smartphone application method, and specificity was 97·3% (94·7-98·8) for the UCD method and 67·9% (62·0-73·3) for the smartphone application method, indicating that the test characteristics of only the UCD method were sufficient for screening. Albuminuria, hypertension, hypercholesterolaemia, and decreased kidney function were newly diagnosed in 77 (62·1%), 44 (35·5%), 30 (24·2%), and 27 (21·8%) of 124 participants for the UCD method, respectively. Of the 124 participants assigned to the UCD method who completed elaborate screening, 111 (89·5%) were referred to their general practitioner for treatment because of newly diagnosed CKD or cardiovascular disease risk factors or known risk factors outside the target range.INTERPRETATIONHome-based screening of the general population for increased ACR using a UCD had a high participation rate and correctly identified individuals with increased albuminuria and yet unknown or known but outside target range CKD and cardiovascular risk factors. By contrast, the smartphone application method had a lower at-home participation rate than the UCD method and the test specificity was too low to accurately assess individuals for risk factors during the elaborate screening. The UCD screening strategy could allow for an early start of treatment to prevent progressive kidney function loss and cardiovascular disease in patients with CKD.FUNDINGDutch Kidney Foundation, Top Sector Life Sciences & Health of the Dutch Ministry of Economic Affairs. Chronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased albuminuria defines the early stages of CKD and is among the strongest risk factors for progressive CKD and cardiovascular disease. The value of population screening for albuminuria to detect CKD in an early phase has yet to be studied. We aimed to evaluate the effectiveness of two home-based albuminuria population screening methods. Towards Home-based Albuminuria Screening (THOMAS) was a prospective, randomised, open-label implementation study that invited Dutch adults aged 45–80 years for albuminuria screening. Individuals were randomly assigned (1:1) to screening by applying either a urine collection device (UCD) that was sent by post to a central laboratory for measurement of the albumin-to-creatinine ratio (ACR) by immunoturbidimetry or to screening via a smartphone application that measures the ACR with a dipstick method at home. Randomisation was done with a four-block method via a web-based system and was stratified by age, sex, and socioeconomic status. If two or more individuals per household were invited to participate, these individuals were randomly assigned to the same group. In case of confirmed increased albuminuria at home, participants were invited for an elaborate screening in a regional hospital (Amphia Hospital, Breda, Netherlands) for CKD and cardiovascular risk factors. When abnormalities were found, participants were referred to their general practitioner for treatment. The primary outcomes were the participation rate and yield of the home-based screening and elaborate screening. Participation rate was assessed in the intention-to-screen population (ie, all participants who were invited for the home-based screening or elaborate screening). Yield was assessed in the per-protocol population (ie, all individuals who participated in the home-based screening or elaborate screening). An exploratory analysis assessed the sensitivity and specificity of both home-based screening methods. To this end, an additional quantitative ACR test was performed among people participating in the elaborate screening, and a substudy was performed among participants with a first negative home-based screening test, who were invited for an additional test. The study is registered with ClinicalTrials.gov, NCT04295889. 15 074 participants were enrolled between Nov 14, 2019, and March 19, 2021. 7552 (50·1%) were randomly assigned to home-based albuminuria screening by the UCD method and 7522 (49·9%) were assigned to albuminuria screening by the smartphone application method. The participation rate of the home-based screening was 4484 (59·4% [95% CI 58·3–60·5]) of the 7552 invited individuals for the UCD method and 3336 (44·3% [43·2–45·5]) of 7522 invited individuals for the smartphone application method (p<0·0001). Increased ACR was confirmed by home-based testing in 150 (3·3% [95% CI 2·9–3·9]) of 4484 individuals for the UCD method and 171 (5·1% [4·4–5·9]) of 3336 indivduals for the smartphone application method. 124 (82·7% [95% CI 75·8–87·9]) of 150 individuals assigned to the UCD method and 142 (83·0% [76·7–87·9]) of 171 participants assigned to the smartphone application method attended the elaborate screening. Sensitivity to detect increased ACR was 96·6% (95% CI 91·5–99·1) for the UCD method and 98·1% (89·9–99·9) for the smartphone application method, and specificity was 97·3% (94·7–98·8) for the UCD method and 67·9% (62·0–73·3) for the smartphone application method, indicating that the test characteristics of only the UCD method were sufficient for screening. Albuminuria, hypertension, hypercholesterolaemia, and decreased kidney function were newly diagnosed in 77 (62·1%), 44 (35·5%), 30 (24·2%), and 27 (21·8%) of 124 participants for the UCD method, respectively. Of the 124 participants assigned to the UCD method who completed elaborate screening, 111 (89·5%) were referred to their general practitioner for treatment because of newly diagnosed CKD or cardiovascular disease risk factors or known risk factors outside the target range. Home-based screening of the general population for increased ACR using a UCD had a high participation rate and correctly identified individuals with increased albuminuria and yet unknown or known but outside target range CKD and cardiovascular risk factors. By contrast, the smartphone application method had a lower at-home participation rate than the UCD method and the test specificity was too low to accurately assess individuals for risk factors during the elaborate screening. The UCD screening strategy could allow for an early start of treatment to prevent progressive kidney function loss and cardiovascular disease in patients with CKD. Dutch Kidney Foundation, Top Sector Life Sciences & Health of the Dutch Ministry of Economic Affairs. |
Author | van Etten, Ronald W Heerspink, Hiddo J L van Mil, Dominique Kieneker, Lyanne M Thelen, Marc H M Evers-Roeten, Birgitte de Vries, Hanne Hemmelder, Marc H Dorgelo, Annemiek Gansevoort, Ron T |
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CitedBy_id | crossref_primary_10_1007_s11356_024_34201_0 crossref_primary_10_3238_arztebl_m2024_0072 crossref_primary_10_1016_j_eclinm_2023_102414 crossref_primary_10_1016_S0140_6736_23_01140_6 crossref_primary_10_1093_ckj_sfae031 crossref_primary_10_1093_ndt_gfae083 crossref_primary_10_1016_j_medj_2024_03_003 crossref_primary_10_1093_ckj_sfae044 crossref_primary_10_1016_j_semnephrol_2024_151520 crossref_primary_10_1093_ckj_sfad254 crossref_primary_10_7326_L23_0369 |
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Chronic kidney disease testing among primary care patients with type 2 diabetes across 24 U.S. health care organizations publication-title: Diabetes Care doi: 10.2337/dc21-2005 contributor: fullname: Mink – volume: 28 start-page: 2805 year: 2013 ident: 10.1016/S0140-6736(23)00876-0_bib25 article-title: Screening for albuminuria with subsequent screening for hypertension and hypercholesterolaemia identifies subjects in whom treatment is warranted to prevent cardiovascular events publication-title: Nephrol Dial Transplant doi: 10.1093/ndt/gft254 contributor: fullname: Ozyilmaz – ident: 10.1016/S0140-6736(23)00876-0_bib26 contributor: fullname: Leemrijse – volume: 395 start-page: 709 year: 2020 ident: 10.1016/S0140-6736(23)00876-0_bib2 article-title: Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 publication-title: Lancet doi: 10.1016/S0140-6736(20)30045-3 contributor: fullname: Bikbov |
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Snippet | Chronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased albuminuria defines... Summary Background Chronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased... BACKGROUNDChronic kidney disease (CKD) has a rising global prevalence and is expected to become the fifth leading cause of death by 2030. Increased albuminuria... |
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SubjectTerms | Abnormalities Cardiovascular disease Cardiovascular diseases Cholesterol Cost analysis Creatinine Diabetes Disease prevention Health risks Health services Hospitals Hypercholesterolemia Hypertension Kidney diseases Kidneys Labels Methods Participation Randomization Risk factors Sensitivity analysis Smartphones Socioeconomic factors Socioeconomics Urine |
Title | Participation rate and yield of two home-based screening methods to detect increased albuminuria in the general population in the Netherlands (THOMAS): a prospective, randomised, open-label implementation study |
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