Computer-assisted prediction of clinical progression in the earliest stages of AD

Abstract

Introduction: Individuals with subjective cognitive decline (SCD) are at increased risk for clinical progression. We studied how combining different diagnostic tests can help to identify individuals who are likely to show clinical progression.

Methods: We included 674 patients with SCD (46% female, 64 ± 9 years, Mini-Mental State Examination 28 ± 2) from three memory clinic cohorts. A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time. We developed and internally validated the model in one cohort and externally validated it in the other cohorts.

Results: After 2.9 ± 2.0 years, 151(22%) patients showed clinical progression. Overall performance of the classifier when combining cognitive tests, magnetic resonance imagining, and cerebrospinal fluid showed a balanced accuracy of 74.0 ± 5.5, with high negative predictive value (93.3 ± 2.8).

Discussion: We found that a combination of diagnostic tests helps to identify individuals at risk of progression. The classifier had particularly good accuracy in identifying patients who remained stable.

Keywords: Alzheimer's disease; Clinical decision support system; Diagnostic test assessment; Prognosis; Subjective cognitive decline.

Fig. 1

The visualization of group-wise volume differences between stable subjective cognitive decline (SCD) and progressive SCD groups. The map visualizes the relative volume difference: $\frac{V_p-V_s}{0.5\times \left(V_p+V_s\right)}$, where V_p and V_s are the mean volumes for progressive and stable groups, respectively. Blue indicates the structures on MRI that were larger in the progressive group, and red indicates the structures that were smaller.

Fig. 2

Examples of DSI fingerprints: patient A and patient C remained stable, and patient B progressed to MCI. The DSI fingerprint combines all data available from one patient and displays it in a visually attractive format to the clinician. The DSI value is presented both numerically and visually with color. The color changes from blue to red when DSI increases from zero (high similarity to the stable group) to one (high similarity to the progressive group). The relevance is visualized by the size of the box. The larger the box, the better the specific marker discriminates the stable and progressive SCD patients. Abbreviations: MMSE, Mini–Mental State Examination; TMT, Trail Making Test; cGCA: computed cortical atrophy score, estimated using gray matter concentration; cMTA, computed medial temporal lobe atrophy score, (left + right)/2, derived from volumes of hippocampus and lateral ventricles; Amyloid β, amyloid-β 1–42; Phosphorylated tau, tau phosphorylated at threonine 181; DSI, Disease State Index.