In one paragraphArticle in Clinical nuclear medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0citing papers in PubMed
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What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
27 authors.
Sohyun YimDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0002-9357-768 Yuna GuDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0009-0007-3200-3977 Heekyung KangDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0003-0287-6818 Daeun ShinDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0003-4834-1026 Hyemin JangDepartment of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Jongno-gu, Seoul, Republic of Korea.
Heejin YooDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0003-4341-6906 Henrik ZetterbergDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.ORCID 0000-0003-3930-4354 Kaj BlennowDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
Fernando Gonzalez-OrtizDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.ORCID 0000-0001-7897-9456 Nicholas J AshtonDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.ORCID 0000-0002-3579-8804 Michael W WeinerDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA.ORCID 0000-0002-0144-1954 Theresa A DayLilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN.
Eun Hye LeeDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0002-4206-6214 Duk L NaDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0002-0098-7592 Hee Jin KimDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0002-3186-9441 Sung Hoon KangDepartment of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0002-2481-0302 Ko Woon KimDepartment of Neurology, Jeonbuk National University Medical School and Hospital, Jeonju, Republic of Korea.ORCID 0000-0002-4564-9714 Yeo Jin KimDepartment of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0002-6564-3774 Yeshin KimDepartment of Neurology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Republic of Korea.
Jaeho KimDepartment of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea.ORCID 0000-0003-3770-2359 Min Young ChunDepartment of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0003-3731-6132 Na Yeon JungDepartment of Neurology, Pusan National University Yangsan Hospital, Research Institute for Convergence of Biomedical Science and Technology, Yangsan, Republic of Korea.ORCID 0000-0002-8265-9508 Soo Hyun ChoDepartment of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea.
Jun Pyo KimDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.ORCID 0000-0003-4376-3107 Jihwan YunDepartment of Neurology, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea.ORCID 0000-0002-2436-4947 Sang Won SeoDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.
K-ROAD study groups
Funding
Alzheimer Drug Discovery Foundation 201809-2016862Alzheimer's Association 2021 Zenith Award ZEN-21-848495Alzheimer's Association 2022-2025 Grant SG-23-1038904 QCBluefield Project, Cure Alzheimer's Fund, Olav Thon Foundation, Erling-Persson Family Foundation, Familjen Rönströms Stiftelse, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden FO2022-0270European Union Joint Program for Neurodegenerative Disorders JPND2019-466-236European Union Joint Programme - Neurodegenerative Disease Research JPND2021-00694European Union's Horizon Europe research and innovation 101053962Future Medicine 20*30 Project of the Samsung Medical Center SMX1250081Hjärnfonden, Sweden FO2017-0243Institute of Information & Communications Technology Planning & Evaluation (IITP) No.RS-2021-II212068Korea Dementia Research Project through the Korea Dementia Research Center (KDRC) RS-2020-KH106434Korea Dementia Research Project through the Korea Dementia Research Center (KDRC) RS-2020-KH107436Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) RS-2022-KH125667Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) RS-2025-02223212Korea National Institute of Health research project 2024-ER1003-01National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, and the UK Dementia Research Institute at UCL UKDRI-1003National Research Foundation of Korea (NRF) RS-2019-NR040057Swedish Alzheimer Foundation AF-930351Swedish Research Council 2017-00915Swedish Research Council 2023-00356Swedish State Support for Clinical Research ALFGBG-71320Swedish state under the agreement between the Swedish government and the County Councils, ALF-agreement ALFGBG-715986
6 · The paper itselfAbstract
backgroundAlzheimer disease (AD) is characterized by amyloid-β plaques (A), tau tangles (T), and neurodegeneration (N), collectively defining the ATN framework. While imaging biomarkers are well-established, the prognostic value of plasma biomarkers in predicting cognitive decline remains underexplored. This study compares plasma and imaging A/T/N biomarkers in predicting cognitive decline and evaluate the impact of combining biomarkers across modalities. PATIENTS AND
methodsWe conducted a longitudinal study using K-ROAD cohort participants who underwent at least 2 cognitive assessments. All participants had plasma biomarker testing (Aβ ratio, p-tau181, p-tau231, p-tau217, NfL), and a subset with imaging biomarker assessments (Aβ PET, tau PET, structural MRI) formed an imaging subcohort. Multiple linear regression models identified the most predictive markers within each modality and evaluated the effect of combining A/T/N biomarkers.
resultsAmong 1,614 plasma cohort and 130 imaging subcohort participants, tau markers demonstrated the strongest predictive value. p-tau217 MSD outperforming other plasma biomarkers, and the neo-temporal ROI showing the highest predictive power among imaging biomarkers. In plasma-based model, adding neurodegeneration markers to combination of amyloid and tau biomarkers improved the performance. In imaging-based models, same strategy decreased the performance, suggesting that combinations of amyloid and tau PET captures the most relevant prognostic information.
conclusionsImaging biomarkers, particularly tau PET, show superior prognostic accuracy compared with plasma biomarkers, whereas plasma biomarkers offer advantages in combination models through neurodegeneration markers. These findings underscore the complementary roles of plasma and imaging biomarkers and emphasize the need for tailored strategies for prognostic modeling in AD.
Indexed as
Alzheimer DiseaseAgedAmyloid beta-PeptidesBiomarkersFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMalePositron-Emission TomographyPrognosistau ProteinsAmyloid beta-PeptidesBiomarkerstau Proteinsalzheimer diseaseATN frameworkimaging biomarkersplasma biomarkersprediction of cognitive declineprognostic modeling
Identifiers
PMID40910876
PMCPMC12617315
What Socratic holds
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