Scientists establish universal standard for Alzheimer's blood test readings
Researchers have identified consistent thresholds for interpreting amyloid PET scans using a standardized measurement called Centiloid, resolving years of confusion in how doctors diagnose Alzheimer's disease. The finding could streamline patient eligibility for new dementia drugs and reduce costly diagnostic delays across clinics and hospitals.
Originaltitel: Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease: An Individual Participant Data Meta-Analysis.
Amyloid-PET blir ett allt viktigare diagnostiskt verktyg för att skilja Alzheimers sjukdom från andra kognitiva nedsättningar och för att välja kandidater till nya läkemedel. En ny samanalys från 49 227 patienter i 53 studier etablerar enhetliga, datadrivna gränsvärden för hur bilderna ska tolkas — ett problem som hittills varierat mellan kliniker och forskargrupper. Forskarna testade två metoder: en enkel gränsvärdesmodell för klassificering som positiv eller negativ, samt en tvåstegsmodell som identifierar en osäkerhetszon där resultatet är mindre säkert. Analyserna baserades på så kallad Centiloid-skala, en standardiserad måttenhet för amyloidmängd som möjliggör jämförbara läsningar oavsett vilket radioaktivt spårämne som används. Resultatet ger kliniker och läkemedelsutvecklare ett gemensamt språk för amyloid-PET-diagnostik. Det förkortar tiden från undersökning till terapibeslut och minskar risken för feldiagnoser — kritiskt när nya alzheimermediciner kräver biologisk bekräftelse av amyloidpatolgi.
IMPORTANCE: Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. OBJECTIVE: To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. DATA SOURCES: PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). STUDY SELECTION: Studies were included if they provided Centiloids, radiotracer, age, and sex. DATA EXTRACTION AND SYNTHESIS: Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. MAIN OUTCOMES AND MEASURES: Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. RESULTS: This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I2 = 80%). CONCLUSIONS AND RELEVANCE: In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.