By Northern Peptides Staff | October 27, 2026
What has Alzheimer’s research established, and what remains uncertain? Scientists can now measure several disease-associated biological changes, including amyloid and tau abnormalities, and randomized trials have demonstrated modest slowing of clinical decline in selected people with early symptomatic disease. In the 2023 New England Journal of Medicine CLARITY AD trial, Christopher van Dyck and colleagues studied 1,795 participants and reported an 18-month change of 1.21 versus 1.66 points on a clinical dementia scale for the investigated antibody versus placebo. These results mark progress, not a cure or a prediction for every individual. That distinction guides responsible Alzheimers disease research.
This educational review examines molecular mechanisms, biomarker science, clinical trial outcomes, and emerging questions. It is written for scientific literacy, not to provide diagnosis, treatment selection, medical advice, or dosing instructions. The focus is on what peer-reviewed evidence supports and how readers can interpret research claims accurately.
Table of contents
- Nine important findings
- Understanding pathology
- Blood and imaging biomarkers
- Landmark randomized trials
- Clinical endpoints and safety
- Prevention and population studies
- What remains unknown
- Reading studies critically
- Frequently asked questions
- References
Nine findings from Alzheimers disease research
Alzheimer’s disease is investigated through neuropathology, molecular biology, cognitive testing, imaging, and prospective trials. Each method answers a different question. A biomarker may show a biological state without fully determining the trajectory of everyday function, while a clinical scale may measure changes without revealing every underlying mechanism.
| Finding | Evidence type | Interpretation |
|---|---|---|
| 1. Amyloid accumulates in disease-associated patterns | Pathology and molecular imaging | A biological marker is not a complete clinical history. |
| 2. Tau changes track other aspects of pathology | Pathology, fluids, imaging | Different tau measures answer different questions. |
| 3. Biology may precede symptoms | Longitudinal and biomarker work | A positive marker does not specify when symptoms occur. |
| 4. Blood biomarkers are improving | Validation studies and expert criteria | Performance and intended population matter. |
| 5. Early symptomatic disease can be studied in trials | CLARITY AD | Modest group-level differences do not equal reversal. |
| 6. Another major trial supports a clinical signal | TRAILBLAZER-ALZ 2 | Effect varies by outcome and analysed population. |
| 7. Safety outcomes are essential | Randomized trials | Benefits must be interpreted with adverse events. |
| 8. Dementia risk is multifactorial | Epidemiological research | Association is not guaranteed prevention. |
| 9. The science remains incomplete | Multiple study programmes | Replication and broader representation are needed. |
Alzheimers disease research has become more precise as biological measurements improve. That progress also creates a responsibility to avoid describing laboratory markers as interchangeable with cognition, personal independence, or clinical benefit.
That separation of evidence types is foundational to Alzheimers disease research.
1. Amyloid is a major research target
Amyloid-beta is a peptide produced through processing of amyloid precursor protein. Its aggregation into several forms, including plaques observed in brain tissue, is one characteristic of Alzheimer’s pathology. Researchers distinguish soluble species, aggregates, deposited plaques, and the techniques used to measure them.
The amyloid hypothesis has guided decades of work, but a hypothesis is not a complete explanation of every observed symptom. Investigators continue to examine how amyloid interacts with tau pathology, inflammation, cellular vulnerability, and other biological pathways.
An important lesson for Alzheimers disease research is that reducing an amyloid measure and improving a person’s clinical outcome are separate findings. A trial must measure and report both if it intends to claim a relationship between them.
Mechanistic and clinical endpoints should remain clearly distinguished in Alzheimers disease research.
2. Tau provides additional information
Tau is a protein associated with microtubule function in neurons. In Alzheimer-associated pathology, abnormal tau-related processes and neurofibrillary changes are important research features. Different tau species and measurement methods should not be treated as identical biomarkers.
Some studies assess tau through positron emission tomography, while others measure phosphorylated tau species in cerebrospinal fluid or blood. These tests can capture different aspects of biology and may have distinct roles in classification or disease staging.
Alzheimers disease research increasingly examines amyloid and tau together, along with downstream neurodegeneration and clinical function. No single tau measurement can replace careful consideration of the study population and measurement method.
Multimodal assessment is an expanding theme in Alzheimers disease research.
3. Biological changes may appear before dementia
Researchers distinguish underlying pathology from symptoms and functional consequences. Disease-associated molecular changes can emerge before a person meets clinical criteria for dementia. This has encouraged longitudinal studies of people at different biological and symptomatic stages.
However, identifying pathology does not tell researchers with certainty whether, when, or how quickly a particular person will experience symptoms. Biological stage, cognitive performance, and daily functioning are related dimensions, not synonyms.
The distinction underlies modern Alzheimers disease research frameworks. It encourages accurate descriptions such as “biomarker-positive” within a defined research context instead of assuming that one laboratory result captures a person’s current abilities or future.
Longitudinal evidence remains essential for Alzheimers disease research on progression.
4. Blood tests are advancing, with important limits
Research into blood-based amyloid and phosphorylated-tau markers has accelerated. Some assays now show strong diagnostic accuracy in studied clinical settings, but that does not make every commercial test equivalent. Test performance depends on assay design, thresholds, reference standards, and population selection.
In 2025, a specialist-care clinical practice guideline evaluated blood-based biomarkers using explicit accuracy thresholds. It described at least 90% sensitivity and 75% specificity for certain triage roles, and at least 90% sensitivity and specificity for certain confirmatory-use roles in specialized diagnostic settings.
These are guideline performance criteria, not a claim that every marketed assay meets them. Alzheimers disease research must distinguish a recommended accuracy threshold from the measured performance of an individual product.
Transparent assay validation strengthens Alzheimers disease research interpretation.
5. Clinical decline can be measured in randomized trials
CLARITY AD was a randomized, double-blind phase 3 investigation in early symptomatic Alzheimer’s disease with evidence of amyloid pathology. Its principal cognitive and functional outcome was the Clinical Dementia Rating–Sum of Boxes, often abbreviated CDR-SB.
At 18 months, the adjusted mean score change was 1.21 in the lecanemab group and 1.66 in the placebo group, a between-group difference of −0.45 points (95% CI −0.67 to −0.23). Both groups worsened on average, but the investigated group worsened less by that measure.
That distinction is fundamental to Alzheimers disease research. A slowing in average decline is not improvement back to an earlier baseline, a cure, or evidence of benefit for people outside the trial’s eligibility criteria.
Absolute scale changes should accompany relative percentages in Alzheimers disease research.
6. A second large trial adds evidence and complexity
The 2023 TRAILBLAZER-ALZ 2 randomized trial, reported by John Sims and colleagues in JAMA, enrolled 1,736 participants with early symptomatic disease and specified amyloid and tau pathology. It assessed the investigational antibody donanemab using the integrated Alzheimer’s Disease Rating Scale (iADRS).
Among participants with low or medium tau pathology, the adjusted mean iADRS change at 76 weeks was −6.02 with donanemab versus −9.27 with placebo, a difference of 3.25 points (95% CI 1.88–4.62). Decline continued in both groups.
For Alzheimers disease research, the trial provides a distinct clinical endpoint and population. Its results should not be compared numerically with CLARITY AD’s CDR-SB points as though the scales measured exactly the same units.
Cross-trial comparisons require special care in Alzheimers disease research.
7. Adverse events belong beside efficacy
Treatments targeting amyloid have been associated with amyloid-related imaging abnormalities, often referred to as ARIA, which can include brain swelling and bleeding-related imaging findings. Published clinical trials and follow-up analyses report such events, including serious cases.
A scientific summary that quotes a percentage slowing in decline while omitting adverse events is incomplete. Safety findings depend on participant characteristics, monitoring, definitions, and the investigated intervention. They are not peripheral to the benefit–risk question.
Balanced Alzheimers disease research presents clinical effects and harms without turning either into consumer-level treatment guidance. Clinical decisions require specialist evaluation and relevant regulatory context, which are outside this article’s purpose.
8. Dementia risk has many contributors
Population studies examine age, genetics, vascular exposures, social conditions, education, hearing and vision problems, and other factors associated with dementia risk. These relationships can inform public-health hypotheses and priorities, although Alzheimer’s disease is not identical to every cause of dementia.
An observed association cannot prove that a single change will prevent a person’s illness. Modelling studies make assumptions about causality, prevalence, overlap, and feasibility that require careful interpretation. The path from observational evidence to demonstrated prevention is not automatic.
Alzheimers disease research must distinguish risk-factor epidemiology from randomized prevention trials. That boundary guards against both exaggerated promises and premature dismissal of worthwhile scientific questions.
9. Replication and representation are ongoing needs
Trials and biomarker studies have eligibility criteria. Participants may differ from broader populations by age, disease stage, background health conditions, ancestry, access to specialized assessment, and other characteristics. A result in a selected cohort may not generalize perfectly.
Research teams continue to investigate the reproducibility of biomarkers across laboratories, diversity in clinical trials, long-term outcomes, and mechanisms beyond amyloid. Negative findings and unsuccessful hypotheses are informative when transparently reported.
Progress in Alzheimers disease research requires both better tools and more careful explanations. An expanding evidence base should increase precision, not turn promising findings into unsupported certainty.
Broader representation can make Alzheimers disease research findings more informative.
What researchers mean by Alzheimer’s pathology
Alzheimer-associated pathology is classically characterized by amyloid plaques and tau-related neurofibrillary changes. Researchers examine these features through tissue studies, molecular imaging, and fluid biomarkers, although each modality has different strengths and limitations.
The 2024 revised criteria led by Clifford Jack and colleagues define Alzheimer’s disease biologically and discuss how particular biomarker categories can inform classification and staging. That framework reflects advances in research measurement, but it is not proof that symptoms, disease severity, and biomarker level move in lockstep.
Alzheimers disease research often uses several layers of evidence. Amyloid-related tests help address one aspect of pathology; tau-related tests add information about another; clinical and functional assessments address how a person is doing.
Amyloid production, clearance, and aggregation
Amyloid precursor protein can be processed through different enzymatic pathways. One sequence of processing generates amyloid-beta peptides that may aggregate under certain conditions. Scientists investigate why deposition develops, how it relates to synapses and neurons, and why pathological changes vary between individuals.
The presence of a proposed molecular mechanism does not establish the clinical effect of manipulating it. A cell experiment may show altered peptide aggregation while leaving the central human question unanswered: does a tested intervention improve a meaningful outcome?
This is why Alzheimers disease research integrates mechanism studies with longitudinal observations and randomized trials. Each component tests a different part of the explanation.
Tau changes and neuronal dysfunction
Tau-related pathology provides a second important biological axis. Researchers study abnormal phosphorylation, aggregation, regional distribution, and the relationship between tau findings and clinical symptoms. Measurement methods include tissue-based assays, imaging, and fluid biomarkers.
Not every measured tau species has equivalent clinical meaning. Assays must be characterized for their intended use, and interpretation depends on what biological process they capture. The same abbreviation in two papers may not mean the same analytical method or threshold.
For Alzheimers disease research, accurate method descriptions are necessary for comparing cohorts and evaluating whether a biomarker result can be reproduced elsewhere.
Blood biomarkers and brain imaging
Historically, many research settings relied on cerebrospinal fluid analysis or positron emission tomography to characterize pathology. Blood-based biomarker technologies have made some kinds of assessment more accessible in principle, though measurement precision and appropriate use remain important.
The 2024 criteria and 2025 specialist-setting guidance reflect this rapid development. Importantly, an official document recommending performance thresholds does not certify every assay sold to consumers. Independent validation, pretest probability, and intended clinical setting influence a test’s useful interpretation.
Alzheimers disease research benefits from assays with clear reference methods, reported sensitivity and specificity, and transparent handling of borderline results. A single attractive accuracy percentage can obscure differences in the population tested.
Sensitivity and specificity are not the same as predictive value
Sensitivity describes how often a test gives a positive result among people meeting the reference definition of the condition. Specificity describes how often it gives a negative result among those not meeting that definition. Neither alone gives the probability that a positive test accurately represents pathology in an unselected population.
Positive predictive value also depends on the prevalence of the target condition in the tested setting. Therefore, accuracy established in specialized memory clinics may not transfer unchanged to people without symptoms or to unrelated screening populations.
Responsible Alzheimers disease research reports the reference standard, thresholds, uncertainty, and characteristics of the tested group. It avoids interpreting a research test as a universal answer about an individual’s cognitive future.
Imaging and fluid tests answer related questions
Amyloid PET imaging characterizes a specific pattern of tracer binding. Tau PET imaging examines a different molecular target. Cerebrospinal fluid and blood assays quantify selected molecules or ratios under laboratory conditions. These measurements are not interchangeable even when they relate to overlapping pathophysiology.
Longitudinal studies examine how markers change relative to each other and to clinical outcomes. Such work can improve disease models while also exposing disagreements between biomarker categories. Those differences are scientific information rather than evidence that one universal marker must explain everything.
Alzheimers disease research should report each modality by name, the biological construct measured, and the limits of comparison between tests.
Clear biomarker nomenclature is essential to reproducible Alzheimers disease research.
What landmark randomized trials found
Randomization is a powerful way to compare assigned interventions, but it does not remove all uncertainty. Eligibility restrictions, missing outcomes, adverse events, duration, clinical scoring, and differences in follow-up matter. Large trials can provide compelling evidence while still leaving important long-term questions unresolved.
| Trial | Publication | Participants and period | Primary reported clinical result |
|---|---|---|---|
| CLARITY AD, van Dyck et al. | NEJM, 2023 | 1,795 early symptomatic participants; 18 months | CDR-SB change 1.21 vs 1.66; difference −0.45 (95% CI −0.67 to −0.23) |
| TRAILBLAZER-ALZ 2, Sims et al. | JAMA, 2023 | 1,736 early symptomatic participants; outcome at 76 weeks | Low/medium-tau iADRS change −6.02 vs −9.27; difference 3.25 (95% CI 1.88–4.62) |
These trials are foundational to recent Alzheimers disease research because they measured cognitive or functional clinical endpoints in randomized comparisons. They do not establish cure, applicability to every disease stage, or identical effects across populations.
Reading CLARITY AD without exaggeration
The CDR-SB measures dementia-related clinical domains. The published difference of −0.45 points at 18 months indicates slower average worsening in the investigated arm, not a return to normal cognition. The group-level result is statistically significant under the trial’s model, while the practical meaning of a given point difference requires appropriate context.
The trial also reported biomarker outcomes and adverse events, including ARIA. Scientific interpretation should examine them together rather than choosing the most favourable number. Long-term outcomes beyond the primary observation window cannot be invented from an 18-month finding.
For Alzheimers disease research, the methodological lesson is to identify the prespecified endpoint, follow-up, effect measure, and uncertainty rather than substituting a simplified percentage for the original findings.
Reading TRAILBLAZER-ALZ 2 accurately
TRAILBLAZER-ALZ 2 used the iADRS, which integrates cognitive and functional components. Lower scores indicate greater impairment, so the negative changes in both groups represent decline. The smaller negative change in the investigated group indicates a lesser average deterioration under the analysed comparison.
The study reported different analyses for low/medium-tau and combined populations. The often-quoted 35.1% slowing concerns the reported low/medium-tau population under that trial’s metric and should not be generalized to every participant in every setting.
Accurate Alzheimers disease research communication keeps subgroup definitions attached to percentages. It also includes the observed absolute scale-point difference and the trial’s safety data rather than repeating only a relative headline.
The trials cannot simply be ranked against each other
Differences in enrolled participants, pathology thresholds, outcome scales, follow-up time, and analysis plans prevent a simple numerical ranking of these separate trials. A result of 0.45 points on CDR-SB is not commensurate with 3.25 points on iADRS.
Comparative effectiveness requires appropriate head-to-head research or carefully justified methods with transparent limitations. Informal comparisons across isolated press headlines are vulnerable to confounding and incompatible measurements.
Alzheimers disease research advances through these independently informative trials, not by treating their percentage changes as a universal league table.
Meaningful comparisons are an open methodological challenge for Alzheimers disease research.
Clinical endpoints, safety, and trade-offs
Researchers use standardized cognitive and functional scales to make clinical outcomes comparable between randomized groups. Each scale measures a specific combination of tasks, observations, or domains, and results require interpretation within that instrument’s structure.
An improvement in a biomarker is not necessarily an improvement in quality of life or independence. Similarly, a slowing of decline over one period does not establish reversal of pathology or continued benefit indefinitely. Clinical significance and statistical significance are related but different concepts.
Alzheimers disease research should communicate absolute scale changes, confidence intervals, safety findings, and how outcomes were measured. This is especially important when a trial’s groups both deteriorated, but at different average rates.
Amyloid-related imaging abnormalities
ARIA includes imaging findings such as edema or hemorrhage-related abnormalities associated with certain amyloid-targeting interventions. Reported events vary in severity, and trials have described serious adverse events. This complicates efforts to summarize benefit with a single percentage.
An ethical research summary does not provide instructions about monitoring or treatment decisions for individual consumers. It does acknowledge that efficacy cannot be separated from safety in evaluating the clinical evidence.
For Alzheimers disease research, adverse-event data are part of the central result. A report omitting them cannot reasonably be called a complete appraisal.
Why trial selection matters
Participants in recent antibody trials generally had early symptomatic disease and biomarker-confirmed pathology under specific study criteria. They were not a random sample of every person with dementia or every person with an abnormal biomarker. Comorbidities and other criteria affected eligibility.
This limits direct generalization. A trial showing one average effect in early symptomatic disease does not necessarily answer questions about asymptomatic individuals, advanced disease, or people excluded by the protocol.
Sound Alzheimers disease research identifies the enrolled population before discussing the result. That protects readers from mistaking a valid narrow finding for an all-purpose conclusion.
Population risk and prevention research
Population studies explore links between dementia risk and cardiovascular, metabolic, social, sensory, and lifestyle exposures. Their value lies partly in identifying associations that merit causal investigation. Yet not all dementia is Alzheimer’s disease, and observed correlations do not guarantee that changing one factor prevents an individual diagnosis.
The 2024 Lancet Commission on dementia prevention examined multiple potentially modifiable factors in a life-course framework. Such population-attributable models can guide public-health questions, but they rely on assumptions about causality, overlaps, prevalence, and the achievable scale of change.
Alzheimers disease research must therefore distinguish prevention hypotheses, observational associations, and interventions that have demonstrated a reduction in diagnosed disease through rigorous trials. Overstating observational findings risks misleading the public.
Genetics and susceptibility
Researchers study genetic variants associated with disease risk, as well as rare inherited forms with strong links to specific pathogenic variants. These situations differ substantially in prevalence and interpretation. A common risk allele does not determine with certainty that a person will develop dementia.
Family-based studies, population cohorts, and molecular experiments help establish which variants affect biological pathways. Risk prediction depends on multiple variables, and genetic observations require care in communicating uncertainty and privacy.
This is one reason Alzheimers disease research cannot be reduced to a single gene or a single peptide. Multiple biological and social influences contribute to the patterns seen in populations.
What a prevention claim would need
A strong clinical prevention claim requires clearly defined participants, an intervention and comparator, adequate follow-up, meaningful disease outcomes, and appropriate statistical analysis. Surrogate biomarker changes or associations alone are insufficient to demonstrate prevention of clinical disease.
Even when a mechanistic pathway is compelling, an experimental intervention may not succeed in human outcome trials. That possibility is a normal part of science and should be communicated openly rather than concealed.
In Alzheimers disease research, precise evidence categories protect readers from treating promising laboratory work as established medical benefit.
Unanswered biological questions
The relationship among amyloid, tau, neuroinflammation, synaptic dysfunction, vascular contributions, and neuronal loss remains an active area of research. These processes may interact in complex ways, and the chronology can vary across individuals and disease stages.
Researchers also investigate sleep-related physiology, immune-cell activity, metabolic signalling, and genetic influences. Observations in cell or animal models can identify pathways worth exploring but cannot directly establish safety or effectiveness of experimental substances in people.
The future of Alzheimers disease research depends on tests of well-specified hypotheses and meaningful human outcomes. Reproducibility and transparent publication of negative results are as important as striking mechanistic discoveries.
Better biomarkers and diverse cohorts
Biomarker work faces questions about assay harmonization, diagnostic thresholds, population differences, and the effect of coexisting health conditions. A test validated in a specialist memory-clinic cohort may not retain identical predictive performance in broader settings.
More diverse enrollment can help determine whether findings generalize across populations. Longer follow-up can clarify how biomarkers relate to actual cognitive trajectories and everyday function. Both require substantial resources and careful participant protections.
Alzheimers disease research becomes more reliable when scientists report uncertain and borderline findings rather than forcing every observation into an overly confident category.
Molecular targets beyond amyloid
Scientists examine tau-related mechanisms, neuroimmune pathways, vascular factors, mitochondrial function, and other targets. Some experimental candidates are antibodies, some are small molecules, and some are investigational biological approaches. A proposed target is not a proven intervention.
Even when a preclinical experiment produces a favourable molecular change, it does not establish improvement in human cognition, long-term function, or survival. The evidence must cross several independent steps before those claims are supportable.
Responsible Alzheimers disease research distinguishes target engagement from clinical effectiveness. This distinction is especially important when discussing experimental peptides or unapproved compounds.
How to read an Alzheimer’s study
Research claims become easier to evaluate when the reader looks beyond headlines. The most important questions are the study design, participants, biological measures, clinical endpoints, duration, numerical results, and limits of generalization.
| Question | What to look for |
|---|---|
| Who was enrolled? | Disease stage, biomarker criteria, age, key exclusions |
| What was compared? | Random assignment, placebo or comparator, masking |
| What was primary? | Prespecified clinical versus biomarker endpoint |
| How large was the effect? | Actual scale changes, confidence intervals, event counts |
| What harms occurred? | Adverse events, discontinuations, serious safety findings |
| How long was follow-up? | Whether claims go beyond observed data |
| What remains uncertain? | Missing data, subgroup limits, generalizability |
This checklist helps readers distinguish robust Alzheimers disease research from selective reporting. Even a statistically significant result can be exaggerated if the outcome is mislabelled or its safety context is omitted.
Recognizing misleading percentage claims
A statement that progression slowed by a certain percentage needs the scale, population, period, and analysis from which that number came. Relative percentages can obscure an absolute difference of less than a point on one measure or a few points on another.
Different studies may use scales that are not directly convertible. Choosing the largest published percentage from each trial and comparing them side by side does not produce a valid comparative-effectiveness result.
The most useful Alzheimers disease research reporting quotes absolute and relative findings in context, states what the placebo group experienced, and resists sensational language.
Progress without false promises
The existence of measurable biological changes and clinically significant trial results represents meaningful progress. At the same time, current evidence leaves many questions about long-term outcomes, side effects, variation in response, and broader eligibility.
Being clear about those limits is compatible with scientific optimism. Careful communication makes discovery more trustworthy and helps the public understand why rigorous trials and biomarker validation matter.
Alzheimers disease research is moving rapidly, but dependable conclusions remain tied to transparent methods and reproducible human evidence.
Frequently asked questions
What is the biggest advance in Alzheimers disease research?
Major advances include better amyloid and tau biomarker measurement and randomized trials demonstrating slower average clinical decline in selected early symptomatic populations. The 1,795-person CLARITY AD trial reported an 18-month CDR-SB difference of −0.45 points versus placebo. This is not a cure.
Does a positive Alzheimer’s biomarker mean someone has dementia?
Not necessarily. Biological pathology and clinical symptoms are distinct dimensions. Interpretation depends on the specific test, study or clinical context, accuracy, and disease stage. A biomarker result alone is not a full account of cognitive function.
Can blood tests replace all other Alzheimer’s assessments?
No. Some validated blood-based biomarkers may have defined roles in specialized settings under accuracy criteria, but not every assay qualifies and results require appropriate context. The 2025 specialist guideline distinguishes triage and confirmatory performance thresholds.
Did the major antibody trials reverse Alzheimer’s disease?
No. In CLARITY AD and TRAILBLAZER-ALZ 2, both trial groups declined on average, with less decline in the investigated groups under specified endpoints. Efficacy findings must be interpreted alongside adverse events and the enrolled populations.
Do animal or laboratory findings prove an experimental peptide treats Alzheimer’s disease?
No. Mechanistic data can support hypotheses but cannot establish clinical efficacy, safety, or authorization for human use. Relevant human studies measuring meaningful outcomes are needed before such claims can be supported.
References
- van Dyck CH, Swanson CJ, Aisen P, et al. “Lecanemab in Early Alzheimer’s Disease.” New England Journal of Medicine. 2023;388:9–21. 1,795 participants; 18-month CDR-SB change 1.21 versus 1.66; difference −0.45 (95% CI −0.67 to −0.23). DOI: 10.1056/NEJMoa2212948. Published trial.
- Sims JR, Zimmer JA, Evans CD, et al. “Donanemab in Early Symptomatic Alzheimer Disease: The TRAILBLAZER-ALZ 2 Randomized Clinical Trial.” JAMA. 2023;330(6):512–527. 1,736 participants; low/medium-tau iADRS difference at 76 weeks 3.25 (95% CI 1.88–4.62). DOI: 10.1001/jama.2023.13239. Published trial.
- Jack CR Jr, Andrews JS, Beach TG, et al. “Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association Workgroup.” Alzheimer’s & Dementia. 2024;20:5143–5169. DOI: 10.1002/alz.13859. Full text.
- Palmqvist S, et al. “Alzheimer’s Association Clinical Practice Guideline on the use of blood-based biomarkers in the diagnostic workup of suspected Alzheimer’s disease within specialized care settings.” Alzheimer’s & Dementia. 2025. Specified ≥90% sensitivity and ≥75% specificity for triage and ≥90% for both in confirmatory roles. PubMed PMID 40729527.
- Jack CR Jr, et al. “Revised criteria for the diagnosis and staging of Alzheimer’s disease.” Nature Medicine. 2024;30:2121–2124. Publication.
For laboratory research use only. Not for human consumption.
