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@ARTICLE{vanMaurik:141557,
      author       = {van Maurik, Ingrid S and Vos, Stephanie J and Bos, Isabelle
                      and Bouwman, Femke H and Teunissen, Charlotte E and
                      Scheltens, Philip and Barkhof, Frederik and Frolich, Lutz
                      and Kornhuber, Johannes and Wiltfang, Jens and Maier,
                      Wolfgang and Peters, Oliver and Rüther, Eckart and Nobili,
                      Flavio and Frisoni, Giovanni B and Spiru, Luiza and
                      Freund-Levi, Yvonne and Wallin, Asa K and Hampel, Harald and
                      Soininen, Hilkka and Tsolaki, Magda and Verhey, Frans and
                      Kłoszewska, Iwona and Mecocci, Patrizia and Vellas, Bruno
                      and Lovestone, Simon and Galluzzi, Samantha and Herukka,
                      Sanna-Kaisa and Santana, Isabel and Baldeiras, Ines and de
                      Mendonça, Alexandre and Silva, Dina and Chetelat, Gael and
                      Egret, Stephanie and Palmqvist, Sebastian and Hansson, Oskar
                      and Visser, Pieter Jelle and Berkhof, Johannes and van der
                      Flier, Wiesje M and Initiative, Alzheimer's Disease
                      Neuroimaging},
      title        = {{B}iomarker-based prognosis for people with mild cognitive
                      impairment ({ABIDE}): a modelling study.},
      journal      = {The lancet / Neurology},
      volume       = {18},
      number       = {11},
      issn         = {1474-4422},
      address      = {London},
      publisher    = {Lancet Publ. Group},
      reportid     = {DZNE-2020-07881},
      pages        = {1034-1044},
      year         = {2019},
      abstract     = {Biomarker-based risk predictions of dementia in people with
                      mild cognitive impairment are highly relevant for care
                      planning and to select patients for treatment when
                      disease-modifying drugs become available. We aimed to
                      establish robust prediction models of disease progression in
                      people at risk of dementia.In this modelling study, we
                      included people with mild cognitive impairment (MCI) from
                      single-centre and multicentre cohorts in Europe and North
                      America: the European Medical Information Framework for
                      Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease
                      Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia
                      Cohort (ADC; n=666), and the Swedish BioFINDER study
                      (n=233). Inclusion criteria were a baseline diagnosis of
                      MCI, at least 6 months of follow-up, and availability of a
                      baseline Mini-Mental State Examination (MMSE) and MRI or CSF
                      biomarker assessment. The primary endpoint was clinical
                      progression to any type of dementia. We evaluated
                      performance of previously developed risk prediction models-a
                      demographics model, a hippocampal volume model, and a CSF
                      biomarkers model-by evaluating them across cohorts,
                      incorporating different biomarker measurement methods, and
                      determining prognostic performance with Harrell's C
                      statistic. We then updated the models by re-estimating
                      parameters with and without centre-specific effects and
                      evaluated model calibration by comparing observed and
                      expected survival. Finally, we constructed a model combining
                      markers for amyloid deposition, tauopathy, and
                      neurodegeneration (ATN), in accordance with the National
                      Institute on Aging and Alzheimer's Association research
                      framework.We included all 2611 individuals with MCI in the
                      four cohorts, 1007 $(39\%)$ of whom progressed to dementia.
                      The validated demographics model (Harrell's C 0·62, $95\%$
                      CI 0·59-0·65), validated hippocampal volume model (0·67,
                      0·62-0·72), and updated CSF biomarkers model (0·72,
                      0·68-0·74) had adequate prognostic performance across
                      cohorts and were well calibrated. The newly constructed ATN
                      model had the highest performance (0·74, 0·71-0·76).We
                      generated risk models that are robust across cohorts, which
                      adds to their potential clinical applicability. The models
                      could aid clinicians in the interpretation of CSF biomarker
                      and hippocampal volume results in individuals with MCI, and
                      help research and clinical settings to prepare for a future
                      of precision medicine in Alzheimer's disease. Future
                      research should focus on the clinical utility of the models,
                      particularly if their use affects participants'
                      understanding, emotional wellbeing, and
                      behaviour.ZonMW-Memorabel.},
      keywords     = {Aged / Aged, 80 and over / Alzheimer Disease: cerebrospinal
                      fluid / Alzheimer Disease: epidemiology / Alzheimer Disease:
                      pathology / Amyloid beta-Peptides: cerebrospinal fluid /
                      Biomarkers: cerebrospinal fluid / Cognitive Dysfunction:
                      cerebrospinal fluid / Cognitive Dysfunction: pathology /
                      Disease Progression / Europe: epidemiology / Female /
                      Follow-Up Studies / Hippocampus: pathology / Humans /
                      Kaplan-Meier Estimate / Magnetic Resonance Imaging / Male /
                      Middle Aged / Multicenter Studies as Topic: statistics $\&$
                      numerical data / Nerve Degeneration / Neuroimaging / North
                      America: epidemiology / Organ Size / Peptide Fragments:
                      cerebrospinal fluid / Phosphorylation / Prognosis /
                      Proportional Hazards Models / Protein Processing,
                      Post-Translational / tau Proteins: cerebrospinal fluid / tau
                      Proteins: chemistry},
      cin          = {AG Wiltfang / U Clinical Researchers - Bonn / AG Priller},
      ddc          = {610},
      cid          = {I:(DE-2719)1410006 / I:(DE-2719)7000001 /
                      I:(DE-2719)5000007},
      pnm          = {342 - Disease Mechanisms and Model Systems (POF3-342) / 344
                      - Clinical and Health Care Research (POF3-344)},
      pid          = {G:(DE-HGF)POF3-342 / G:(DE-HGF)POF3-344},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31526625},
      doi          = {10.1016/S1474-4422(19)30283-2},
      url          = {https://pub.dzne.de/record/141557},
}