In the Journals

New approach may determine dementia risk in patients with MCI

Recent findings showed accuracy of biomarker-based prognostic models for determining Alzheimer’s disease dementia and any type of dementia among patients with mild cognitive impairment.

“Identification of abnormal biomarkers in patients with [mild cognitive impairment (MCI)] helps to identify individuals at high risk of progression to [Alzheimer’s disease] dementia. Atrophy on brain MRI and cerebrospinal fluid (CSF) concentrations of amyloid-1-42 and tau protein are among the most widely used [Alzheimer’s disease] biomarkers and are associated with an increased risk of [Alzheimer’s disease] dementia at follow-up. ... However, these criteria do not specify how to deal with conflicting or borderline biomarker results and how to take patient characteristics into account,” Ingrid S. van Maurik, MSc, of VU University Medical Center, Amsterdam, and colleagues wrote.

To develop biomarker-based prognostic models that determine future Alzheimer’s disease dementia in patients with MCI, researchers evaluated 525 patients with MCI from the Amsterdam Dementia Cohort. Participants’ baseline visits to a memory clinic occurred from September 1997 through August 2014. Mean age was 67.3 years.

Clinical endpoints included AD dementia and any type of dementia after 1 and 3 years.

According to results, 3-year progression risk for Alzheimer’s disease dementia ranged from 26% (95% CI, 19-34) in younger men with Mini-Mental State Examination (MMSE) scores of 29 to 76% (95% CI, 65-84) in older women with MMSE scores of 24. One-year risk ranged from 6% to 24%.

When MRI results were abnormal, 3-year progression risk was 86% (95% CI, 71-95) and 1-year progression risk was 27% (95% CI, 17-41).

When CSF test results were abnormal, 3-year progression risk was 82% (95% CI, 73-89) and 1-year progression risk was 26% (95% CI, 20-33).

When both MRI and CSF test results were abnormal, 3-year progression risk was 89% (95% CI, 79-95) and 1-year progression risk was 26% (95% CI, 18-36).

Conversely, 3-year progression risk was 18% (95% CI, 13-27) and 1-year progression risk was 3% (95% CI, 2-5) after normal MRI results.

After normal CSF test results, 3-year progression risk was 6% (95% CI, 3-9) and 1-year progression risk was 1% (95% CI, 0.5-2).

After combined normal MRI and CSF test results, 3-year progression risk was 4% (95% CI, 2-7) and 1-year progression risk was 0.5% (95% CI, 0.2-1).

Prognostic value of determination models for any type of dementia followed the same order of magnitude, but were somewhat lower, according to researchers.

External validation in Alzheimer’s Disease Neuroimaging Initiative 2 showed the models were highly robust.

“The prognostic models described in our study could be easily implemented in daily practice, contributing to personalized diagnostic care and harmonization of clinical practice. In this article, we present a framework for a precision medicine approach. Worldwide translation of these models remains challenging and requires particular attention to generalizability across samples and measurement methods,” the researchers wrote. “Furthermore, models will further improve when longer-term follow-up becomes available. Nonetheless, our models show how biomarker research can be translated into clinical practice in a tractable manner.” – by Amanda Oldt

Disclosures: van Maurik reports no relevant financial disclosures. Please see the study for all other authors’ relevant financial disclosures.

Recent findings showed accuracy of biomarker-based prognostic models for determining Alzheimer’s disease dementia and any type of dementia among patients with mild cognitive impairment.

“Identification of abnormal biomarkers in patients with [mild cognitive impairment (MCI)] helps to identify individuals at high risk of progression to [Alzheimer’s disease] dementia. Atrophy on brain MRI and cerebrospinal fluid (CSF) concentrations of amyloid-1-42 and tau protein are among the most widely used [Alzheimer’s disease] biomarkers and are associated with an increased risk of [Alzheimer’s disease] dementia at follow-up. ... However, these criteria do not specify how to deal with conflicting or borderline biomarker results and how to take patient characteristics into account,” Ingrid S. van Maurik, MSc, of VU University Medical Center, Amsterdam, and colleagues wrote.

To develop biomarker-based prognostic models that determine future Alzheimer’s disease dementia in patients with MCI, researchers evaluated 525 patients with MCI from the Amsterdam Dementia Cohort. Participants’ baseline visits to a memory clinic occurred from September 1997 through August 2014. Mean age was 67.3 years.

Clinical endpoints included AD dementia and any type of dementia after 1 and 3 years.

According to results, 3-year progression risk for Alzheimer’s disease dementia ranged from 26% (95% CI, 19-34) in younger men with Mini-Mental State Examination (MMSE) scores of 29 to 76% (95% CI, 65-84) in older women with MMSE scores of 24. One-year risk ranged from 6% to 24%.

When MRI results were abnormal, 3-year progression risk was 86% (95% CI, 71-95) and 1-year progression risk was 27% (95% CI, 17-41).

When CSF test results were abnormal, 3-year progression risk was 82% (95% CI, 73-89) and 1-year progression risk was 26% (95% CI, 20-33).

When both MRI and CSF test results were abnormal, 3-year progression risk was 89% (95% CI, 79-95) and 1-year progression risk was 26% (95% CI, 18-36).

Conversely, 3-year progression risk was 18% (95% CI, 13-27) and 1-year progression risk was 3% (95% CI, 2-5) after normal MRI results.

After normal CSF test results, 3-year progression risk was 6% (95% CI, 3-9) and 1-year progression risk was 1% (95% CI, 0.5-2).

After combined normal MRI and CSF test results, 3-year progression risk was 4% (95% CI, 2-7) and 1-year progression risk was 0.5% (95% CI, 0.2-1).

Prognostic value of determination models for any type of dementia followed the same order of magnitude, but were somewhat lower, according to researchers.

External validation in Alzheimer’s Disease Neuroimaging Initiative 2 showed the models were highly robust.

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“The prognostic models described in our study could be easily implemented in daily practice, contributing to personalized diagnostic care and harmonization of clinical practice. In this article, we present a framework for a precision medicine approach. Worldwide translation of these models remains challenging and requires particular attention to generalizability across samples and measurement methods,” the researchers wrote. “Furthermore, models will further improve when longer-term follow-up becomes available. Nonetheless, our models show how biomarker research can be translated into clinical practice in a tractable manner.” – by Amanda Oldt

Disclosures: van Maurik reports no relevant financial disclosures. Please see the study for all other authors’ relevant financial disclosures.