New method predicts when Alzheimer's patients will need full-time care and how long they'll live
Researchers from Columbia University Medical Center have developed a clinically proven method for predicting the length of time from the onset of Alzheimer’s disease to the need for full-time care and eventual death.
The researchers validated the new method after developing a prediction algorithm using data from a single visit with an Alzheimer’s patient to estimate how much time they had before needing full-time care or nursing home residence and then death. Their findings were published online recently in the Journal of Alzheimer's Disease.
The ability to predict a reasonably accurate timeline for Alzheimer’s patients has been a long time in the making, starting 25 years ago when researchers first began working on a way to estimate certain disease endpoints, including death. One reason it has taken so long is because of the complexity of the disease and how it varies greatly from one person to the next.
As senior author Yaakov Stern, PhD, professor of neuropsychology at CUMC, explained it, you could have two different Alzheimer's patients who appear to have the same symptoms in the early stages of the disease, but one patient might suddenly deteriorate and continue to do so at a much faster rate, while the progression of the disease for the other occurs much more slowly.
This new method, which Stern says allows medical professionals to predict the path of the disease “with great specificity”, is based on a multifaceted model of the progression of Alzheimer’s disease that Dr. Stern, along with the other members of the research team, developed by following two groups of Alzheimer's patients for a full decade.
Having the ability to predict this timeline for the disease has strong implications for patients and their caregivers, as well as those involved in health policy, economics and interventional studies related to Alzheimer’s disease.
It also has the potential to become a valuable tool for both the doctors and the families of the Alzheimer’s patient by providing a reasonably accurate prediction of how long it will before the patient transitions from being self-reliant to needing full-time care and/or possible nursing home residence, and then death.
Another benefit of this new prediction method is that it can be used by researchers in future studies on Alzheimer’s disease, safeguarding the right balance between patients who progress quickly with the disease and those who progress much more slowly. It can also help health economists make more accurate predictions regarding the future impact of Alzheimer's disease on our nation’s economy.
One advantage of the model, which the new method is based on, is that it accounts for a variety of complex factors related to Alzheimer's disease because there is no “one size fits all” category for diagnosing the severity of the disease, such as saying it’s mild, moderate or severe. According to Dr. Stern, this is because some patients may have symptoms considered to be severe – like hallucinations or violent outbursts – yet they are still self-reliant and able to live independently for many, many years.
In contrast, other patients may present themselves with hardly any visible symptoms of Alzheimer’s, only to suddenly deteriorate to the point where they need to be institutionalized. With the new method, however, Dr. Stern says that such factors are taken into consideration; thus, the method is reliable and flexible enough to make timeline predictions – even when there are missing variables.
An example confirming the accuracy of the new method’s results involved two Alzheimer’s patients, both of whom were 68-year-old and were similar in mental status at the time of their initial visit, although one patient was experiencing delusions and was more dependent on his caregiver.
There were other subtle differences between the two patients, and they showed up in different predictions from the time of their initial visit until their predicted death, with the new method correctly predicting that the first patient would die within three years, and the other would live for over 10 years.
Other Alzheimer’s disease endpoints that the new method can predict, in addition to onset of disease to nursing home residence or death, is the time it takes before assisted living and/or other types of care are needed, including help getting dressed, help eating, and help going to the bathroom or to bathe.
Meanwhile, Dr. Stern and the research team are also working on a study of aging and dementia that involves elderly residents living in urban areas. The elderly participants are currently free of any symptoms of dementia, which will enable the researchers to follow them and track symptoms that develop over time in order to capture the age of those with an onset of dementia when it happens.
There is also recent research that may eventually lead to an effective preventive treatment for Alzheimer's disease.
To learn about a "sniff test" for predicting Alzheimer's disease that's quick and inexpensive, check out this fascinating EmaxHealth report from Kathleen Blanchard.
SOURCE: Journal of Alzheimer's Disease, “A New Algorithm for Predicting Time to Disease Endpoints in Alzheimer’s Disease Patients”; Published September 24, 2013. DOI 10.3233/JAD-131142