The ADAS-Cog revisited: novel composite scales based on ADAS-Cog to improve efficiency in MCI and early AD trials

BACKGROUND

The Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) has been used widely as a cognitive end point in Alzheimer's Disease (AD) clinical trials. Efforts to treat AD pathology at earlier stages have also used ADAS-Cog, but failure in these trials can be difficult to interpret because the scale has well-known ceiling effects that limit its use in mild cognitive impairment (MCI) and early AD. A wealth of data exists in ADAS-Cog from both historical trials and contemporary longitudinal natural history studies that can provide insights about parts of the scale that may be better suited for MCI and early AD trials.

METHODS

Using Alzheimer's Disease Neuroimaging Initiative study data, we identified the most informative cognitive measures from the ADAS-Cog and other available scales. We used cross-sectional analyses to characterize trajectories of ADAS-Cog and its individual subscales, as well as other cognitive, functional, or global measures across disease stages. Informative measures were identified based on standardized mean of 2-year change from baseline and were combined into novel composite endpoints. We assessed performance of the novel endpoints based on sample size requirements for a 2-year clinical trial. A bootstrap validation procedure was also undertaken to assess the reproducibility of the standardized mean changes of the selected measures and the corresponding composites.

RESULTS

All proposed novel endpoints have improved standardized mean changes and thus improved statistical power compared with the ADAS-Cog 11. Further improvements were achieved by using cognitive-functional composites. Combining the novel composites with an enrichment strategy based on cerebral spinal fluid beta-amyloid (Aβ(1-42)) in a 2-year trial yielded gains in power of 20% to 40% over ADAS-Cog 11, regardless of the novel measure considered.

CONCLUSION

An empirical, data-driven approach with existing instruments was used to derive novel composite scales based on ADAS-Cog 11 with improved performance characteristics for MCI and early AD clinical trials. Together with patient enrichment based on Aβ(1-42) pathology, these modified endpoints may allow more efficient clinical trials in these populations and can be assessed without modifying current test administration procedures in ongoing trials.

Rivastigmine in Alzheimer's disease and Parkinson's disease dementia: an ADAS-cog factor analysis

Rivastigmine treatment is associated with significant improvements on the cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog) in patients with mild-to-moderate Alzheimer's disease (AD) and Parkinson's disease dementia (PDD). Both AD and PDD are purported to have different profiles of cognitive impairment, which may respond differentially to rivastigmine treatment. This was a retrospective analysis of 3 randomized, double-blind, rivastigmine trial databases (Investigation of transDermal Exelon in ALzheimer's disease [IDEAL; AD], EXelon in PaRkinson's disEaSe dementia Study [EXPRESS; PDD], and Alzheimer's Disease with ENA 713 [ADENA; AD]). Factor analyses of the 11 baseline ADAS-cog items derived the same factors in the 2 diseases, that is, "memory" and "language". Rivastigmine-treated AD and PDD patients showed significant improvements (P < .0001 versus placebo) on both factors. For both AD and PDD, rivastigmine had a numerically greater effect on memory than language. Treatment effect sizes were numerically greater in PDD compared with AD. Rivastigmine treatment is associated with improvement in memory and language in AD and PDD. The numerically greater response in PDD is consistent with greater cholinergic deficits in this disease state.

Quantitative pharmacology approach in Alzheimer's disease: efficacy modeling of early clinical data to predict clinical outcome of tesofensine

Effective therapeutic options for Alzheimer's disease (AD) are limited and much research is currently ongoing. The high attrition rate in drug development is a critical issue. Here, the quantitative pharmacology approach (QP-A) and model-based drug development (MBDD) provide a valuable opportunity to support early selection of the most promising compound and facilitate a fast, efficient, and rational drug development process. The aim of this analysis was to exemplify the QP-A by eventually predicting the clinical outcome of a proof-of-concept (PoC) trial of tesofensine in AD patients from two small phase IIa trials. Retrospective population pharmacokinetic/pharmacodynamic (PK/PD) modeling of tesofensine, its metabolite M1, and assessment scale-cognitive subscale data from two 4-week placebo-controlled studies in 62 mild AD patients was performed using non-linear mixed effects modeling. The final PK/PD model was used to predict data of a negative 14-week phase IIb PoC trial (430 AD patients). For the PK, one-compartment models for tesofensine and M1 with first-order absorption and elimination were sufficient. An extended Emax model including disease progression best described the PK/PD relationship using effect compartments. The placebo effect was also implemented in the final PK/PD model based on a published placebo model developed in a large AD cohort. Various internal evaluation techniques confirmed the reliability and predictive performance of the PK/PD model, which also successfully predicted the 14-week PoC data. For tesofensine, the dose concentration-effect relationship has successfully been described in mild AD patients demonstrating the supportive value of PK/PD models in QP-A/MBDD in early phases of clinical development for decision-making.

Item analysis of ADAS-Cog: effect of baseline cognitive impairment in a clinical AD trial

We explored the association of Alzheimer's disease (AD) Assessment Scale (ADAS-Cog) item scores with AD severity using cross-sectional and longitudinal data from the same study. Post hoc analyses were performed using placebo data from a 12-month trial of patients with mild-to-moderate AD (N =281 randomized, N =209 completed). Baseline distributions of ADAS-Cog item scores by Mini-Mental State Examination (MMSE) score and Clinical Dementia Rating (CDR) sum of boxes score (measures of dementia severity) were estimated using local and nonparametric regressions. Mixed-effect models were used to characterize ADAS-Cog item score changes over time by dementia severity (MMSE: mild =21-26, moderate =14-20; global CDR: mild =0.5-1, moderate =2). In the cross-sectional analysis of baseline ADAS-Cog item scores, orientation was the most sensitive item to differentiate patients across levels of cognitive impairment. Several items showed a ceiling effect, particularly in milder AD. In the longitudinal analysis of change scores over 12 months, orientation was the only item with noticeable decline (8%-10%) in mild AD. Most items showed modest declines (5%-20%) in moderate AD.