Improving CSF biomarker accuracy in predicting prevalent and incident Alzheimer disease

OBJECTIVE

To investigate factors, including cognitive and brain reserve, which may independently predict prevalent and incident dementia of the Alzheimer type (DAT) and to determine whether inclusion of identified factors increases the predictive accuracy of the CSF biomarkers Aβ(42), tau, ptau(181), tau/Aβ(42), and ptau(181)/Aβ(42).

METHODS

Logistic regression identified variables that predicted prevalent DAT when considered together with each CSF biomarker in a cross-sectional sample of 201 participants with normal cognition and 46 with DAT. The area under the receiver operating characteristic curve (AUC) from the resulting model was compared with the AUC generated using the biomarker alone. In a second sample with normal cognition at baseline and longitudinal data available (n = 213), Cox proportional hazards models identified variables that predicted incident DAT together with each biomarker, and the models' concordance probability estimate (CPE), which was compared to the CPE generated using the biomarker alone.

RESULTS

APOE genotype including an ε4 allele, male gender, and smaller normalized whole brain volumes (nWBV) were cross-sectionally associated with DAT when considered together with every biomarker. In the longitudinal sample (mean follow-up = 3.2 years), 14 participants (6.6%) developed DAT. Older age predicted a faster time to DAT in every model, and greater education predicted a slower time in 4 of 5 models. Inclusion of ancillary variables resulted in better cross-sectional prediction of DAT for all biomarkers (p < 0.0021), and better longitudinal prediction for 4 of 5 biomarkers (p < 0.0022).

CONCLUSIONS

The predictive accuracy of CSF biomarkers is improved by including age, education, and nWBV in analyses.

Independent practice associations: risk contracting, financial controls and processes

The decision to enter into risk contracting with a health plan should be carefully considered. With today's pressure to control health care costs, an IPA's financial position can change rapidly. Even small numbers of enrollees can precipitate losses of hundreds of thousands of dollars over a few months if utilization and costs are not carefully projected and monitored. Prudent contracting to limit the IPA's downside risk in a new contract's early years is the most effective tool for preserving financial stability. However, the IPA must also develop sophisticated claims processing and financial reporting systems to ensure consistent payment practices and enable management to identify problem areas rapidly. Contracts with physician providers must allow the IPA flexibility in implementing administrative withholds and in renegotiating rates with short lead times.