- Email: [email protected]
66 DEMENTIA RESEARCH GROUP COHORT STUDIES
Podium Presentations: Sunday, July 16, 2017 O1-04-06
MORTALITY AMONG OLDER ADULTS WITH DEMENTIA IN LOW- AND MIDDLEINCOME COUNTRIES: THE 10/66 DEMENTIA RESEARCH GROUP COHORT STUDIES
Ronaldo D. Piovezan1, Nicole Arias2, Daisy Acosta3, Jose C. Galduroz1, Danusa de Almeida Machado4, Jerson Laks5,6, Martin J. Prince7, Cleusa Pinheiro Ferri7,8, 1Universidade Federal de S~ao Paulo, S~ao Paulo, Brazil; 2King’s College London, London, United Kingdom; 3Universidad Nacional Pedro Henriquez Ure~na, Santo Domingo, Dominican Republic; 4 Universidade Federal de Sao Paulo - UNIFESP, Sao Paulo, Brazil; 5Center for Alzheimer’s Disease and Related Disorders, Institute of Psychiatry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; 6Universidade do Grande Rio (Unigranrio), Caxias, Brazil; 7Institute of Psychiatry, and Neuroscience King’s College, London, United Kingdom; 8Universidade Federal de Sao Paulo, Sao Paulo, Brazil. Contact e-mail: rdpiovezan@ gmail.com Background: With the rapid population aging in Low and Middle-Income Countries (LMIC), dementia is becoming a healthcare priority. Monitoring mortality-related indicators among people with dementia (PWD) contributes to defining service provision. However, few studies have investigated mortality rates and predictors among PWD in LMIC. This study aimed to estimate mortality rates and determine mortality risk factors among PWD in 8 LMIC. Methods: The vital status of 1477 older PWD from 8 LMIC was determined after three years. Total, and age and gender-specific mortality rates per 1,000 person-years at risk, as well as total, and age and gender adjusted mortality rates were estimated for each country. Cox’s proportional hazard regressions, conducted by country and pooled using meta-analysis, estimated the effect of potential mortality risk factors. Results: Vital status was determined in 1304 participants (87.6%), with 593 (45.5%) being deceased. The proportion of deceased subjects was highest in China (65.9%) and lowest in Venezuela (26.9%). Mean age at death was highest in Puerto Rico (87.1) and lowest in India (76.1). Dementia severity was classified as mild in 42.8%, moderate in 49.4% and severe in 7.8% of participants. Undernutrition was identified in 16.2% of the participants (highest in India (48.1%)). Mortality risk was higher among males (HR¼1.57, 95%CI 1.32-1.87) and increased with age (HR¼1.04, 95%CI 1.03-1.06). A higher NPI score (HR¼1.03, 95%CI 1.01-1.05), lower Cogscore (HR 1.03, 95%CI 1.02-1.04), undernutrition (HR¼1.55, 95%CI 1.192.02), number of physical impairments (HR¼1.15, 95%CI 1.03-1.29) and disease severity (HR¼1.52, 95%CI 1.33-1.74) increased mortality risk. Education, number of assets, cardiovascular risk factors, depression, dementia subtypes, and having received treatment related to the circumstances of death were not associated to mortality risk. Conclusions: This study described mortality rates in a wide ranging elderly populationbased cohort in LMIC. The large sample size allowed the setting of major mortality predictors in PWD (age, male gender, dementia severity related factors, physical impairments and undernutrition). Our results may support public health plans aimed at reducing morbimortality in PWD where healthcare resources might be scarce. With the increasing number of PWD in LMIC, more studies focusing on dementia-related mortality in these countries are required.
P197
SUNDAY, JULY 16, 2017 ORAL SESSION O1-05 BIOMARKERS: METHOD DEVELOPMENT AND/OR QUALITY CONTROL O1-05-01
CLINICAL VALIDATION OF DIAGNOSING ALZHEIMER’S DISEASE BY ASSAYING PLASMA AMYLOIDS AND TAU PROTEIN VIA IMMUNOMAGNETIC REDUCTION
Shieh-Yueh Yang1, Ming-Jang Chiu2, Ta-Fu Chen3, Chaur-Jong Hu4, SuiHing Yan5, Yu Sun6, Bing-Hsien Liu1, Che-Chuan Yang1, 1MagQu Co., Ltd., New Taipei City, Taiwan; 2National Taiwan University Hospital, Taipei, Taiwan; 3Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan; 4Taipei Medical University Shuang-Ho Hospital, Taipei, Taiwan; 5Renai Branch, Taipei City Hospital, Taipei, Taiwan; 6 Department of Neurology, En Chu Kong Hospital, Taipei, Taiwan. Contact e-mail: [email protected] Background: In order to demonstrate the validity of assaying
plasma beta-amyloid and tau protein for diagnosing Alzheimer’s disease (AD), two independent cohorts were recruited in Taiwan. The first cohort (or referred as to reference cohort), including 96 healthy controls, 24 patients with mild cognitive impairment (MCI) due to AD, and 60 AD patients, has been enrolled at National Taiwan University from 2009 to 2014. The second cohort (or referred as to validation cohort) including 134 healthy controls, 34 patients with MCI due to AD, and 74 AD patients, was enrolled at four hospitals in Taiwan in 2015 and 2016. Methods: All subjects were performed with clinical diagnosis according to 2011 NIA-AA guideline, and were assayed blindly for plasma beta-amyloid and tau protein using immunomagnetic reduction. Through ROC-curve analysis for the measured biomarkers of the reference cohort, the cut-off values, sensitivities, specificities, and are under the curve (AUC) by using beta-amyloid-40, betaamyloid-42, tau protein or combinations of these biomarkers for discriminating healthy controls and patients are obtained. By applying the cut-off values of biomarkers obtained from the reference cohort to the validation cohort, the positive percent agreement, negative percent agreement, and overall percent agreement (or accuracy) for discriminating healthy controls form MCI-due-to-AD patients, or differentiating MCI-due-to AD patients from AD patients are clarified. Results: With the measured biomarkers of the reference cohort, the cut-off value of concentration product of beta-amyloid-42 and tau protein in plasma for differentiating healthy controls from MCI due to AD is 455 (pg/ml)2, which results in the AUC higher than 90%. Furthermore, the cut-off value of concentration product of beta-amyloid-42 and tau protein in plasma for differentiating MCI due to AD from AD is 642 (pg/ml)2, which results in the AUC higher than 80%. By applying the cut-off value 455 (pg/ml)2 to discriminate healthy controls from MCI due to AD of the validation cohort, the accuracy is higher than 80%. Moreover, by applying the cut-off value 642 (pg/ml)2 to differentiate MCI due to AD from AD of the validation cohort, the accuracy is also higher than 80%. Conclusions: These results reveal the promising feasibility to diagnose AD via plasma assay using immunomagnetic reduction.
MORTALITY AMONG OLDER ADULTS WITH DEMENTIA IN LOW- AND MIDDLEINCOME COUNTRIES: THE 10/66 DEMENTIA RESEARCH GROUP COHORT STUDIES
Ronaldo D. Piovezan1, Nicole Arias2, Daisy Acosta3, Jose C. Galduroz1, Danusa de Almeida Machado4, Jerson Laks5,6, Martin J. Prince7, Cleusa Pinheiro Ferri7,8, 1Universidade Federal de S~ao Paulo, S~ao Paulo, Brazil; 2King’s College London, London, United Kingdom; 3Universidad Nacional Pedro Henriquez Ure~na, Santo Domingo, Dominican Republic; 4 Universidade Federal de Sao Paulo - UNIFESP, Sao Paulo, Brazil; 5Center for Alzheimer’s Disease and Related Disorders, Institute of Psychiatry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; 6Universidade do Grande Rio (Unigranrio), Caxias, Brazil; 7Institute of Psychiatry, and Neuroscience King’s College, London, United Kingdom; 8Universidade Federal de Sao Paulo, Sao Paulo, Brazil. Contact e-mail: rdpiovezan@ gmail.com Background: With the rapid population aging in Low and Middle-Income Countries (LMIC), dementia is becoming a healthcare priority. Monitoring mortality-related indicators among people with dementia (PWD) contributes to defining service provision. However, few studies have investigated mortality rates and predictors among PWD in LMIC. This study aimed to estimate mortality rates and determine mortality risk factors among PWD in 8 LMIC. Methods: The vital status of 1477 older PWD from 8 LMIC was determined after three years. Total, and age and gender-specific mortality rates per 1,000 person-years at risk, as well as total, and age and gender adjusted mortality rates were estimated for each country. Cox’s proportional hazard regressions, conducted by country and pooled using meta-analysis, estimated the effect of potential mortality risk factors. Results: Vital status was determined in 1304 participants (87.6%), with 593 (45.5%) being deceased. The proportion of deceased subjects was highest in China (65.9%) and lowest in Venezuela (26.9%). Mean age at death was highest in Puerto Rico (87.1) and lowest in India (76.1). Dementia severity was classified as mild in 42.8%, moderate in 49.4% and severe in 7.8% of participants. Undernutrition was identified in 16.2% of the participants (highest in India (48.1%)). Mortality risk was higher among males (HR¼1.57, 95%CI 1.32-1.87) and increased with age (HR¼1.04, 95%CI 1.03-1.06). A higher NPI score (HR¼1.03, 95%CI 1.01-1.05), lower Cogscore (HR 1.03, 95%CI 1.02-1.04), undernutrition (HR¼1.55, 95%CI 1.192.02), number of physical impairments (HR¼1.15, 95%CI 1.03-1.29) and disease severity (HR¼1.52, 95%CI 1.33-1.74) increased mortality risk. Education, number of assets, cardiovascular risk factors, depression, dementia subtypes, and having received treatment related to the circumstances of death were not associated to mortality risk. Conclusions: This study described mortality rates in a wide ranging elderly populationbased cohort in LMIC. The large sample size allowed the setting of major mortality predictors in PWD (age, male gender, dementia severity related factors, physical impairments and undernutrition). Our results may support public health plans aimed at reducing morbimortality in PWD where healthcare resources might be scarce. With the increasing number of PWD in LMIC, more studies focusing on dementia-related mortality in these countries are required.
P197
SUNDAY, JULY 16, 2017 ORAL SESSION O1-05 BIOMARKERS: METHOD DEVELOPMENT AND/OR QUALITY CONTROL O1-05-01
CLINICAL VALIDATION OF DIAGNOSING ALZHEIMER’S DISEASE BY ASSAYING PLASMA AMYLOIDS AND TAU PROTEIN VIA IMMUNOMAGNETIC REDUCTION
Shieh-Yueh Yang1, Ming-Jang Chiu2, Ta-Fu Chen3, Chaur-Jong Hu4, SuiHing Yan5, Yu Sun6, Bing-Hsien Liu1, Che-Chuan Yang1, 1MagQu Co., Ltd., New Taipei City, Taiwan; 2National Taiwan University Hospital, Taipei, Taiwan; 3Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan; 4Taipei Medical University Shuang-Ho Hospital, Taipei, Taiwan; 5Renai Branch, Taipei City Hospital, Taipei, Taiwan; 6 Department of Neurology, En Chu Kong Hospital, Taipei, Taiwan. Contact e-mail: [email protected] Background: In order to demonstrate the validity of assaying
plasma beta-amyloid and tau protein for diagnosing Alzheimer’s disease (AD), two independent cohorts were recruited in Taiwan. The first cohort (or referred as to reference cohort), including 96 healthy controls, 24 patients with mild cognitive impairment (MCI) due to AD, and 60 AD patients, has been enrolled at National Taiwan University from 2009 to 2014. The second cohort (or referred as to validation cohort) including 134 healthy controls, 34 patients with MCI due to AD, and 74 AD patients, was enrolled at four hospitals in Taiwan in 2015 and 2016. Methods: All subjects were performed with clinical diagnosis according to 2011 NIA-AA guideline, and were assayed blindly for plasma beta-amyloid and tau protein using immunomagnetic reduction. Through ROC-curve analysis for the measured biomarkers of the reference cohort, the cut-off values, sensitivities, specificities, and are under the curve (AUC) by using beta-amyloid-40, betaamyloid-42, tau protein or combinations of these biomarkers for discriminating healthy controls and patients are obtained. By applying the cut-off values of biomarkers obtained from the reference cohort to the validation cohort, the positive percent agreement, negative percent agreement, and overall percent agreement (or accuracy) for discriminating healthy controls form MCI-due-to-AD patients, or differentiating MCI-due-to AD patients from AD patients are clarified. Results: With the measured biomarkers of the reference cohort, the cut-off value of concentration product of beta-amyloid-42 and tau protein in plasma for differentiating healthy controls from MCI due to AD is 455 (pg/ml)2, which results in the AUC higher than 90%. Furthermore, the cut-off value of concentration product of beta-amyloid-42 and tau protein in plasma for differentiating MCI due to AD from AD is 642 (pg/ml)2, which results in the AUC higher than 80%. By applying the cut-off value 455 (pg/ml)2 to discriminate healthy controls from MCI due to AD of the validation cohort, the accuracy is higher than 80%. Moreover, by applying the cut-off value 642 (pg/ml)2 to differentiate MCI due to AD from AD of the validation cohort, the accuracy is also higher than 80%. Conclusions: These results reveal the promising feasibility to diagnose AD via plasma assay using immunomagnetic reduction.