- Email: [email protected]
EFFECTS ON FAMILIES OF OLDER ADULTS EXPERIENCING COGNITIVE TESTING (EFECT): A PILOT STUDY
Poster Presentations: Tuesday, July 26, 2016 Table Criterion Validity of Different Formulations of an Algorithmic MCI Diagnosis by Dataset: Results from the Preclinical AD Consortium (N¼1,767) Variable BIOCARD Algorithmic MCI, Cognition only (psycog) Algorithmic MCI, CDR only (psycdr) Algorithmic MCI, Cognition and CDR (psymci) ACS Algorithmic MCI, Cognition only (psycog) Algorithmic MCI, CDR only (psycdr) Algorithmic MCI, Cognition and CDR (psymci) WRAP Algorithmic MCI, Cognition only (psycog) Algorithmic MCI, CDR only (psycdr) Algorithmic MCI, Cognition and CDR (psymci) BLSA Algorithmic MCI, Cognition only (psycog) Algorithmic MCI, CDR only (psycdr) Algorithmic MCI, Cognition and CDR (psymci) AIBL Algorithmic MCI, Cognition only (psycog) Algorithmic MCI, CDR only (psycdr) Algorithmic MCI, Cognition and CDR (psymci)
AUC
Sensitivity
Specificity
0.804
0.77
0.84
0.938 0.865
0.96 0.74
0.91 0.99
0.547
0.96
0.13
0.991 0.972
0.98 0.94
1.00 1.00
0.892
1.00
0.78
0.930 0.976
1.00 1.00
0.86 0.95
0.814
1.00
0.63
0.781 0.844
0.80 0.80
0.76 0.89
0.750
0.99
0.51
0.943 0.945
0.92 0.92
0.96 0.97
follow-up. We identified cognitive tests in common among studies (five memory and eight non-memory), evaluated measurement noninvariance of the tests by study to verify their equivalence across datasets, and defined impairment on each test as 1 standard deviation below a sample-specific mean. We then evaluated correspondence between each study’s clinical diagnosis and different combinations of algorithmic diagnoses based on (1) cognitive impairment only in 2+ tests, (2) CDR0.5 only, and (3) both. Results: An algorithmic diagnosis only based on cognitive tests provided poor specificity (13%-84%) in each dataset (see Table). Using only the CDR revealed subtle differences across studies in how the CDR is used. Requiring cognitive impairment on 2+ tests and CDR0.5 provided the optimal balance of sensitivity and specificity (area under the curve: 0.84 to 0.97). Conclusions: Our data suggest both cognitive tests and CDR should be combined to obtain a reliable algorithmic diagnosis with high specificity and sensitivity in these cohorts. This algorithm can be used to examine relationships with biomarkers collected in the same individuals, such as those derived from CSF, MRI and PET.
P3-206
EFFECT OF DEPRESSION SEVERITY ON FUNCTIONAL IMPAIRMENTS IN PATIENTS WITH MILD COGNITIVE IMPAIRMENT
Sheng-Min Wang, Seoul St Mary Hospital, Seoul, The Republic of Korea. Contact e-mail: [email protected]
P903
Background: Although depression is a common co-morbid disorder in patients with mild cognitive impairment (MCI), not all patients with MCI exhibit depressive symptoms. This study aimed to investigate the effect of depression on cognitive and functional decline in MCI. Methods: 300 patients with amnestic MCI (aMCI) defined by 0.5 score on Clinical Dementia Rating were included in the study. Patients were divided in to three groups based on their Geriatric Depression Scale (GDS) scores: aMCI without depression (GDS<10, n¼55), aMCI with mild depression (GDS10w19, n¼127), and aMCI with severe depression (GDS>20, n¼118). Cognitive function tests (verbal fluency, trail making test-A, and verbal learning test) and Blessed Dementia Scale-Activities of Daily Living (BDS-ADL) were measured. Group differences were analyzed using an analysis of variance (ANOVA). Correlation between GDS scores and BDS-ADL were analyzed. Results: An ANOVA test showed that activities of daily living differed significantly across groups (F(2, 297) ¼ 13.58, p<0.001). Post-hoc analysis showed aMCI with severe depression had a significantly higher mean BDS-ADL score compared with both aMCI without depression and aMCI with mild depression (both, p<0.001). Correlation analysis showed significant positive correlation between GDS and BDS-ADL (r¼0.321, p<0.001). However, mean scores of various cognitive function tests (verbal fluency, verbal learning and TMT-A) were not different among three groups. Conclusions: The present study suggests that co-morbid depressive symptoms may have negative effect on functional impairments rather than cognitive impairments in patients with MCI. This may further suggest the importance of evaluation and treatment of depressive symptoms in patients with MCI. P3-207
EFFECTS ON FAMILIES OF OLDER ADULTS EXPERIENCING COGNITIVE TESTING (EFECT): A PILOT STUDY
Nicole R. Fowler1, Amanda M. Harrawood2, Malaz A. Boustani3, 1Indiana University, Indianapolis, IN, USA; 2Regenstrief Institute, Indianapolis, IN, USA; 3Indiana University Center for Aging Research, Indianapolis, IN, USA. Contact e-mail: [email protected] Background: More than 2 million adults with Alzheimer’s disease and related dementias in the United States never receive a formal diagnosis. More than 70% of people with Alzheimer’s disease live in the community and receive care from their family. There is a tremendous psychological, physical, and financial burden of the syndrome borne by patients and family caregivers. This burden may be exacerbated by a delayed diagnosis. The potential risks and benefits screening for Alzheimer’s disease for family members are unknown. Methods: In preparation for a randomized controlled trial to assess the potential benefits and harms of dementia screening on family members of older adults, we: (1) tested the feasibility of recruiting family members of older adults who are part of a dementia screening trial, and (2) measured family members concerns about cognition and screening. Results: 65% of eligible family members agreed to be in the study (n¼96). 33% were a spouse, 51% an adult child, and 16% another relative. The mean age of the family member was 56.8 years. 94.7% live within 50 miles of the patient and endorsed seeing them in-person at least weekly 90% of the time. There was no difference in enrollment rate between family members of patients who were screened for Alzheimer’s disease vs. not screened. When asked about concerns regarding screening for Alzheimer’s disease, 84% endorsed being moderately or extremely concerned if their family member does not have any problems with memory or thinking, but tests positive. 61% endorsed being
P904
Poster Presentations: Tuesday, July 26, 2016
moderately or extremely concerned if a family member had problems with memory and thinking, but tests negative. 95% endorsed being moderately or extremely concerned if a family member had problems with memory and thinking and tests positive, and 25% endorsed being moderately or extremely concerned if a family member does not have any problems with memory and thinking and tests negative. Conclusions: Family members of older adults endorse high levels of concern regarding their family members risk of have Alzheimer’s disease and express willingness to participate in trials measuring the potential benefits and harms of dementia screening on family members of older adults. P3-208
EQUIVALENCE OF IPAD AND PAPER VERSION OF THE BEHAVIOURAL NEUROLOGY ASSESSMENTREVISED
David F. Tang-Wai1,2,3, Larry Leach4, Robert Partridge1, Robyn Spring5, Nima Nourhaghighi3,6, Tom Gee3,7, Stephen C. Strother7,8,9, Barry D. Greenberg1,3, Ellie Aghdassi1,3, Yael Goldberg7, Kathryn A. Stokes7, Mohammad Alhaj10, Alita Fernandez7, Michelle Gyenes7, Josh Kirstein7, Jordana L. Waserman7, Sandra E. Black3,6,11, Morris Freedman2,3,12, 1University Health Network, Toronto, ON, Canada; 2University of Toronto, Toronto, ON, Canada; 3 Toronto Dementia Research Alliance, Toronto, ON, Canada; 4York University, Toronto, ON, Canada; 5Baycrest Health Sciences Centre, Toronto, ON, Canada; 6Sunnybrook Health Sciences Centre, Toronto, ON, Canada; 7Baycrest Health Sciences, Toronto, ON, Canada; 8Rotman Research Institute, Baycrest, Toronto, ON, Canada; 9Toronto Dementia Research Alliance, Toronto, ON, Canada; 10Canada International Scientific Exchange Program, Toronto, ON, Canada; 11Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 12Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada. Contact e-mail: David.Tang-Wai@ uhn.ca Background: The Behavioural Neurology Assessment (BNA)-
Revised (BNA-R) is a revision of the original BNA to enhance its detection of mild cognitive impairment. It serves as an in-depth cognitive assessment that is intermediate between short screening tests and lengthy neuropsychological assessments, and can be administered by any health professional. It is comprised of subtests within 7 cognitive domains: orientation, immediate verbal recall, delayed verbal and visual recall, delayed verbal and visual recognition, visuospatial function, working memory/attention/executive control, and language. Using a paper version, a normative database was developed testing 303 people between the ages of 50-89 years, with 75 participants per decade. We developed an iPad version of the BNA-R (iBNA-R) and compared participant performance on the iPad to the paper version. Methods: Thirty-two participants, who did not receive the paper version of the BNA-R, were administered the iBNA-R (original n¼36, 4 were excluded - 2 due to inability to complete the serial 7’s subtest and 2 due to scores deemed abnormally low compared to compiled norms) and were compared to 5 independent random samples of approximate sample size of 40, drawn from the normative database (age: M¼69.8; SD¼10.9). Using SPSS Version 23, analysis of the results obtained from the iPad and paper versions of the BNA-R included one-way ANOVA of the age, education, and the raw total score (SUM) of the BNA-R. Results: There was no significant group effect for age, F(5, 186)¼.16, p¼.98 or for education, F(5,186)¼.33, p¼.89. A univariate ANOVA revealed a marginally significant group effect on the mean SUM scores (F(5, 186)¼2.23, p¼.053) likely due to random differences in sample selection than a systematic bias of the medium by which subject responses are scored. No between group comparisons with Bonferonni corrections were significant.
Conclusions: Administration of the BNA-R by a trained examiner using either standard paper records or iPad to record subject responses were equivalent. The iBNA-R can be used reliably in the clinical setting to assess cognition. P3-209
IMPACT OF BIOMARKERS ON DIAGNOSTIC CONFIDENCE IN CLINICAL ASSESSMENT OF PATIENTS WITH SUSPECTED ALZHEIMER’S DISEASE AND HIGH DIAGNOSTIC UNCERTAINTY: AN EADC STUDY
Paolo Bosco1, Alberto Redolfi1, Martina Bocchetta2,3, Clarissa Ferrari1, Anna Mega1, Samantha Galluzzi2, Frederic Assal4, Mircea Balasa5, Christine Bastin6, Anastasia Bougea7, Derya Durusu Emek-Savas8, Sebastiaan Engelborghs9,10, Panteleimon Giannakopoulos11, Gabriel Gold12, Timo Grimmer13, Galina Grosu14, Milica G. Kramberger15, Brian Lawlor16, Gorana Mandic Stojmenovic17, Mihaela Marinescu14, Patrizia Mecocci18, Jose Luis Molinuevo19, Ricardo Morais20, Ellis Niemantsverdriet9, Flavio Nobili21, Konstantinos Ntovas22, Sarah O’Dwyer16, George Paraskevas23, Luca Pelini24, Agnese Picco25, Eric Salmon26, Isabel Santana27, Oscar Sotolongo-Grau28, Luiza Spiru29,30, Elka Stefanova31, Katarina Surlan Popovic32, Magda Tsolaki22, G€orsev Yener8, Dina Zekry4, Giovanni B. Frisoni2,33, 1IRCCS Fatebenefratelli, Brescia, Italy; 2IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; 3University College London, London, United Kingdom; 4University Hospitals and University of Geneva, Geneva, Switzerland; 5Hospital Clinic i Universitari, Barcelona, Spain; 6Cyclotron Research Centre, University of Liege, Liege, Belgium; 7Eginition Hospital Kapodistrian University, Medical School of Athens, Athens, Greece; 8Dokuz Eyl€ul University, Izmir, Turkey; 9Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium; 10 Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium; 11University Hospital of Geneva, Geneva, Switzerland; 12Division of Geriatrics, University Hospital of Geneva, Geneva, Switzerland; 13Klinikum Rechts der Isar, Technische Universitaet Muenchen, Munich, Germany; 14Elias University Clinical Hospital, Bucharest, Romania; 15University Medical Centre Ljubljana, Ljubljana, Slovenia; 16Mercer’s Institute for Successful Ageing, St. James’s Hospital, Dublin, Ireland; 17Institute of Neurology, CCS, Belgrade, Serbia; 18University of Perugia, Perugia, Italy; 19ICN Hospital Clinic Universitari and Pasqual Maragall Foundation, Barcelona, Spain; 20Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal; 21 University of Genoa, Italy, Genoa, Italy; 22Aristotle University of Thessaloniki, Thessaloniki, Greece; 23Eginition Hospital Kapodistrian University, Medical School of Athens, Athens, Greece; 24Istituto di Gerontologia e Geriatria, Universita degli Studi di Perugia, Perugia, Italy; 25 Neurology Unit, IRCCS AOU San Martino, University of Genoa, Genoa, Italy; 26GIGA-CRC, University of Liege, Liege, Belgium; 27University of Coimbra, Coimbra, Portugal; 28Fundacio ACE. Barcelona Alzheimer Treatment & Research Center, Barcelona, Spain; 29Carol Davila University of Medicine, Bucharest, Romania; 30Ana Aslan Intl Foundation-Memory Clinic, Bucharest, Romania; 31Neurology Clinic, Clinical Centre Serbia, Belgrade, Serbia; 32Clinical Institute of Radiology University Medical Center Ljubljana, Ljubljana, Slovenia; 33Memory Clinic and LANVIE Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland. Contact e-mail: pbosco@fatebenefratelli. eu Background: NIA-AA and IWG diagnostic criteria for Alzheimer’s Disease (AD) include core structural, functional, and CSF biomarkers. The impact of core biomarkers in clinical settings is still unclear. This study aimed at measuring the impact of core biomarkers on the diagnostic confidence of uncertain AD cases in a routine memory clinic setting. Methods: 356 patients with mild dementia (MMSE ¼ 20) or Mild Cognitive Impairment possibly due to AD were recruited in 17 European Alzheimer’s Disease
AUC
Sensitivity
Specificity
0.804
0.77
0.84
0.938 0.865
0.96 0.74
0.91 0.99
0.547
0.96
0.13
0.991 0.972
0.98 0.94
1.00 1.00
0.892
1.00
0.78
0.930 0.976
1.00 1.00
0.86 0.95
0.814
1.00
0.63
0.781 0.844
0.80 0.80
0.76 0.89
0.750
0.99
0.51
0.943 0.945
0.92 0.92
0.96 0.97
follow-up. We identified cognitive tests in common among studies (five memory and eight non-memory), evaluated measurement noninvariance of the tests by study to verify their equivalence across datasets, and defined impairment on each test as 1 standard deviation below a sample-specific mean. We then evaluated correspondence between each study’s clinical diagnosis and different combinations of algorithmic diagnoses based on (1) cognitive impairment only in 2+ tests, (2) CDR0.5 only, and (3) both. Results: An algorithmic diagnosis only based on cognitive tests provided poor specificity (13%-84%) in each dataset (see Table). Using only the CDR revealed subtle differences across studies in how the CDR is used. Requiring cognitive impairment on 2+ tests and CDR0.5 provided the optimal balance of sensitivity and specificity (area under the curve: 0.84 to 0.97). Conclusions: Our data suggest both cognitive tests and CDR should be combined to obtain a reliable algorithmic diagnosis with high specificity and sensitivity in these cohorts. This algorithm can be used to examine relationships with biomarkers collected in the same individuals, such as those derived from CSF, MRI and PET.
P3-206
EFFECT OF DEPRESSION SEVERITY ON FUNCTIONAL IMPAIRMENTS IN PATIENTS WITH MILD COGNITIVE IMPAIRMENT
Sheng-Min Wang, Seoul St Mary Hospital, Seoul, The Republic of Korea. Contact e-mail: [email protected]
P903
Background: Although depression is a common co-morbid disorder in patients with mild cognitive impairment (MCI), not all patients with MCI exhibit depressive symptoms. This study aimed to investigate the effect of depression on cognitive and functional decline in MCI. Methods: 300 patients with amnestic MCI (aMCI) defined by 0.5 score on Clinical Dementia Rating were included in the study. Patients were divided in to three groups based on their Geriatric Depression Scale (GDS) scores: aMCI without depression (GDS<10, n¼55), aMCI with mild depression (GDS10w19, n¼127), and aMCI with severe depression (GDS>20, n¼118). Cognitive function tests (verbal fluency, trail making test-A, and verbal learning test) and Blessed Dementia Scale-Activities of Daily Living (BDS-ADL) were measured. Group differences were analyzed using an analysis of variance (ANOVA). Correlation between GDS scores and BDS-ADL were analyzed. Results: An ANOVA test showed that activities of daily living differed significantly across groups (F(2, 297) ¼ 13.58, p<0.001). Post-hoc analysis showed aMCI with severe depression had a significantly higher mean BDS-ADL score compared with both aMCI without depression and aMCI with mild depression (both, p<0.001). Correlation analysis showed significant positive correlation between GDS and BDS-ADL (r¼0.321, p<0.001). However, mean scores of various cognitive function tests (verbal fluency, verbal learning and TMT-A) were not different among three groups. Conclusions: The present study suggests that co-morbid depressive symptoms may have negative effect on functional impairments rather than cognitive impairments in patients with MCI. This may further suggest the importance of evaluation and treatment of depressive symptoms in patients with MCI. P3-207
EFFECTS ON FAMILIES OF OLDER ADULTS EXPERIENCING COGNITIVE TESTING (EFECT): A PILOT STUDY
Nicole R. Fowler1, Amanda M. Harrawood2, Malaz A. Boustani3, 1Indiana University, Indianapolis, IN, USA; 2Regenstrief Institute, Indianapolis, IN, USA; 3Indiana University Center for Aging Research, Indianapolis, IN, USA. Contact e-mail: [email protected] Background: More than 2 million adults with Alzheimer’s disease and related dementias in the United States never receive a formal diagnosis. More than 70% of people with Alzheimer’s disease live in the community and receive care from their family. There is a tremendous psychological, physical, and financial burden of the syndrome borne by patients and family caregivers. This burden may be exacerbated by a delayed diagnosis. The potential risks and benefits screening for Alzheimer’s disease for family members are unknown. Methods: In preparation for a randomized controlled trial to assess the potential benefits and harms of dementia screening on family members of older adults, we: (1) tested the feasibility of recruiting family members of older adults who are part of a dementia screening trial, and (2) measured family members concerns about cognition and screening. Results: 65% of eligible family members agreed to be in the study (n¼96). 33% were a spouse, 51% an adult child, and 16% another relative. The mean age of the family member was 56.8 years. 94.7% live within 50 miles of the patient and endorsed seeing them in-person at least weekly 90% of the time. There was no difference in enrollment rate between family members of patients who were screened for Alzheimer’s disease vs. not screened. When asked about concerns regarding screening for Alzheimer’s disease, 84% endorsed being moderately or extremely concerned if their family member does not have any problems with memory or thinking, but tests positive. 61% endorsed being
P904
Poster Presentations: Tuesday, July 26, 2016
moderately or extremely concerned if a family member had problems with memory and thinking, but tests negative. 95% endorsed being moderately or extremely concerned if a family member had problems with memory and thinking and tests positive, and 25% endorsed being moderately or extremely concerned if a family member does not have any problems with memory and thinking and tests negative. Conclusions: Family members of older adults endorse high levels of concern regarding their family members risk of have Alzheimer’s disease and express willingness to participate in trials measuring the potential benefits and harms of dementia screening on family members of older adults. P3-208
EQUIVALENCE OF IPAD AND PAPER VERSION OF THE BEHAVIOURAL NEUROLOGY ASSESSMENTREVISED
David F. Tang-Wai1,2,3, Larry Leach4, Robert Partridge1, Robyn Spring5, Nima Nourhaghighi3,6, Tom Gee3,7, Stephen C. Strother7,8,9, Barry D. Greenberg1,3, Ellie Aghdassi1,3, Yael Goldberg7, Kathryn A. Stokes7, Mohammad Alhaj10, Alita Fernandez7, Michelle Gyenes7, Josh Kirstein7, Jordana L. Waserman7, Sandra E. Black3,6,11, Morris Freedman2,3,12, 1University Health Network, Toronto, ON, Canada; 2University of Toronto, Toronto, ON, Canada; 3 Toronto Dementia Research Alliance, Toronto, ON, Canada; 4York University, Toronto, ON, Canada; 5Baycrest Health Sciences Centre, Toronto, ON, Canada; 6Sunnybrook Health Sciences Centre, Toronto, ON, Canada; 7Baycrest Health Sciences, Toronto, ON, Canada; 8Rotman Research Institute, Baycrest, Toronto, ON, Canada; 9Toronto Dementia Research Alliance, Toronto, ON, Canada; 10Canada International Scientific Exchange Program, Toronto, ON, Canada; 11Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 12Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada. Contact e-mail: David.Tang-Wai@ uhn.ca Background: The Behavioural Neurology Assessment (BNA)-
Revised (BNA-R) is a revision of the original BNA to enhance its detection of mild cognitive impairment. It serves as an in-depth cognitive assessment that is intermediate between short screening tests and lengthy neuropsychological assessments, and can be administered by any health professional. It is comprised of subtests within 7 cognitive domains: orientation, immediate verbal recall, delayed verbal and visual recall, delayed verbal and visual recognition, visuospatial function, working memory/attention/executive control, and language. Using a paper version, a normative database was developed testing 303 people between the ages of 50-89 years, with 75 participants per decade. We developed an iPad version of the BNA-R (iBNA-R) and compared participant performance on the iPad to the paper version. Methods: Thirty-two participants, who did not receive the paper version of the BNA-R, were administered the iBNA-R (original n¼36, 4 were excluded - 2 due to inability to complete the serial 7’s subtest and 2 due to scores deemed abnormally low compared to compiled norms) and were compared to 5 independent random samples of approximate sample size of 40, drawn from the normative database (age: M¼69.8; SD¼10.9). Using SPSS Version 23, analysis of the results obtained from the iPad and paper versions of the BNA-R included one-way ANOVA of the age, education, and the raw total score (SUM) of the BNA-R. Results: There was no significant group effect for age, F(5, 186)¼.16, p¼.98 or for education, F(5,186)¼.33, p¼.89. A univariate ANOVA revealed a marginally significant group effect on the mean SUM scores (F(5, 186)¼2.23, p¼.053) likely due to random differences in sample selection than a systematic bias of the medium by which subject responses are scored. No between group comparisons with Bonferonni corrections were significant.
Conclusions: Administration of the BNA-R by a trained examiner using either standard paper records or iPad to record subject responses were equivalent. The iBNA-R can be used reliably in the clinical setting to assess cognition. P3-209
IMPACT OF BIOMARKERS ON DIAGNOSTIC CONFIDENCE IN CLINICAL ASSESSMENT OF PATIENTS WITH SUSPECTED ALZHEIMER’S DISEASE AND HIGH DIAGNOSTIC UNCERTAINTY: AN EADC STUDY
Paolo Bosco1, Alberto Redolfi1, Martina Bocchetta2,3, Clarissa Ferrari1, Anna Mega1, Samantha Galluzzi2, Frederic Assal4, Mircea Balasa5, Christine Bastin6, Anastasia Bougea7, Derya Durusu Emek-Savas8, Sebastiaan Engelborghs9,10, Panteleimon Giannakopoulos11, Gabriel Gold12, Timo Grimmer13, Galina Grosu14, Milica G. Kramberger15, Brian Lawlor16, Gorana Mandic Stojmenovic17, Mihaela Marinescu14, Patrizia Mecocci18, Jose Luis Molinuevo19, Ricardo Morais20, Ellis Niemantsverdriet9, Flavio Nobili21, Konstantinos Ntovas22, Sarah O’Dwyer16, George Paraskevas23, Luca Pelini24, Agnese Picco25, Eric Salmon26, Isabel Santana27, Oscar Sotolongo-Grau28, Luiza Spiru29,30, Elka Stefanova31, Katarina Surlan Popovic32, Magda Tsolaki22, G€orsev Yener8, Dina Zekry4, Giovanni B. Frisoni2,33, 1IRCCS Fatebenefratelli, Brescia, Italy; 2IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; 3University College London, London, United Kingdom; 4University Hospitals and University of Geneva, Geneva, Switzerland; 5Hospital Clinic i Universitari, Barcelona, Spain; 6Cyclotron Research Centre, University of Liege, Liege, Belgium; 7Eginition Hospital Kapodistrian University, Medical School of Athens, Athens, Greece; 8Dokuz Eyl€ul University, Izmir, Turkey; 9Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium; 10 Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium; 11University Hospital of Geneva, Geneva, Switzerland; 12Division of Geriatrics, University Hospital of Geneva, Geneva, Switzerland; 13Klinikum Rechts der Isar, Technische Universitaet Muenchen, Munich, Germany; 14Elias University Clinical Hospital, Bucharest, Romania; 15University Medical Centre Ljubljana, Ljubljana, Slovenia; 16Mercer’s Institute for Successful Ageing, St. James’s Hospital, Dublin, Ireland; 17Institute of Neurology, CCS, Belgrade, Serbia; 18University of Perugia, Perugia, Italy; 19ICN Hospital Clinic Universitari and Pasqual Maragall Foundation, Barcelona, Spain; 20Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal; 21 University of Genoa, Italy, Genoa, Italy; 22Aristotle University of Thessaloniki, Thessaloniki, Greece; 23Eginition Hospital Kapodistrian University, Medical School of Athens, Athens, Greece; 24Istituto di Gerontologia e Geriatria, Universita degli Studi di Perugia, Perugia, Italy; 25 Neurology Unit, IRCCS AOU San Martino, University of Genoa, Genoa, Italy; 26GIGA-CRC, University of Liege, Liege, Belgium; 27University of Coimbra, Coimbra, Portugal; 28Fundacio ACE. Barcelona Alzheimer Treatment & Research Center, Barcelona, Spain; 29Carol Davila University of Medicine, Bucharest, Romania; 30Ana Aslan Intl Foundation-Memory Clinic, Bucharest, Romania; 31Neurology Clinic, Clinical Centre Serbia, Belgrade, Serbia; 32Clinical Institute of Radiology University Medical Center Ljubljana, Ljubljana, Slovenia; 33Memory Clinic and LANVIE Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland. Contact e-mail: pbosco@fatebenefratelli. eu Background: NIA-AA and IWG diagnostic criteria for Alzheimer’s Disease (AD) include core structural, functional, and CSF biomarkers. The impact of core biomarkers in clinical settings is still unclear. This study aimed at measuring the impact of core biomarkers on the diagnostic confidence of uncertain AD cases in a routine memory clinic setting. Methods: 356 patients with mild dementia (MMSE ¼ 20) or Mild Cognitive Impairment possibly due to AD were recruited in 17 European Alzheimer’s Disease