Rapidly Versus Slowly Progressing Patients With Alzheimer’s Disease

Abstract

Rate of progression of cognitive deficits is variable among patients with Alzheimer’s disease (AD). The purpose of the current study was to compare demographic characteristics and performance on neuropsychological measures at baseline evaluation between rapidly and slowly progressing patients. Participants were divided into 2 groups based on change in Alzheimer’s Disease Assessment Scale-Cognitive subscale score from baseline to 2-year follow-up, and baseline performance was compared between the groups. Participants were 55 rapidly progressing and 55 slowly progressing patients with probable AD who had a follow-up evaluation 21 to 27 months after the baseline evaluation. The groups differed in age and initial Clinical Dementia Rating. Performance differed significantly between the groups on Verbal Series Attention Test time, Logical Memory I, Visual Reproduction I, Block Design, and Controlled Oral Word Association Test. Differences were found between rapidly and slowly progressing patients on baseline neuropsychological testing.

Introduction

Rate of progression of cognitive and functional deficits is variable among patients with Alzheimer’s disease (AD). Identifying variables related to the rate of progression could help patients, families, and health care providers to prepare for cognitive and functional declines. The ability to predict whether a particular patient will have a rapid or slow rate of decline could provide very valuable information when planning for future care. Methods for estimating rate of decline in AD have been developed. A patient’s estimated decline prior to the diagnosis can be used to predict subsequent rate of observed decline. ¹ Using the estimated decline on the Mini Mental State Examination (MMSE) prior to the patient’s first visit to the physician, the authors were able to identify slow, intermediate, and rapid progressors. Another model incorporating cognitive, behavioral, and functional data has been developed by Stallard and colleagues as a multiattribute model of AD progression. ² The authors concluded that the rate of progression in AD was influenced by complex physiological processes. However, research continues into identifying factors related to the rate of progression in AD. It could be particularly important to have the ability to predict which patients will progress slowly and which will progress more rapidly.

Studies Comparing Rapidly and Slowly Declining Groups

Buccione et al ³ examined differences in a group of 22 rapidly declining patients and a group of 21 slowly declining patients over a period of 2 years and found no differences in baseline dementia severity or demographics between the 2 groups. However, the group declining cognitively at a faster rate was found to have poorer performance on neuropsychological testing, especially on tests of memory, constructional abilities, reasoning, and executive functioning. Those who were functionally declining more rapidly had poorer performance on tests of construction. In a study comparing a group of 18 rapidly declining and a group of 27 slowly declining patients over a period of 1 year, it was reported that those patients in the rapidly declining group had poorer performance on tests of verbal memory, mental control, and tests demanding attention at baseline. ⁴ Patients were divided into rapidly and slowly declining groups on the basis of the rate of change in the MMSE over the 1-year period. Bhargava et al ⁵ studied 124 rapidly progressing and 123 slowly progressing patients in the early stages of AD over a period of 3 years. Those patients who progressed to the moderate stage of AD in this time frame were considered to be progressing rapidly, and those who did not were progressing slowly. The authors found that the only differences between rapid and slow progressing groups at an initial visit were lower MMSE score and greater global impairment in the rapid progressing group. A recent study comparing faster and slower progressors found that performance on measures of executive function, processing speed, and memory distinguished between the groups; however, the measure of processing speed best distinguished between the two groups. ⁶

Studies Using Rate of Progression as a Continuous Variable

Demographic variables

Certain demographic risk factors have been identified as related to the rate of decline. Older age at onset has been associated with a slower rate of cognitive decline and cerebral atrophy over an 18-month period. ⁷ Mungas and colleagues ⁸ found that the rate of progression decreased as patients aged but increased with age in those patients with a history of stroke. Likewise, Lucca et al ⁹ found that earlier age of onset was related to rapider rate of decline. However, older age of onset has also been found to be related to a faster rate of decline. ¹⁰ Haupt and colleagues ¹¹ did not find evidence that age of onset was related to variability in symptom progression over a period of 12 months in a small sample of early onset patients with a family history of AD. Other studies have also found no differences in the rate of decline based on age of onset. ^{12 –14}

Gender may also be related to the rate of cognitive decline in AD. Generally, studies suggest that women experience a faster rate of decline than men. ^9,15 In developing a mathematical model to predict rate of decline in AD, Ito and colleagues ¹⁶ also reported that men had a slower rate of decline; however, gender was not a strong predictor of the rate of decline.

Higher levels of education may be associated with a faster rate of decline. ¹⁰ However, Bowler and colleagues ¹⁷ found no association between rate of progression and any demographic variables, including education. A study by Pavlik et al ¹⁸ found that baseline American National Adult Reading Test (AMNART) score is a better predictor of rate of cognitive decline than was education, with higher estimated premorbid verbal intellectual ability associated with a slower rate of decline.

Genetic variables

A disease progression model developed using data from the Alzheimer’s Disease Neuroimaging Initiative Database found that the presence of the APOE ∊4 allele was associated with a more rapid cognitive decline. ¹⁶ However, Tschanz and colleagues ¹⁵ did not find an association between APOE ∊4 allele status and rate of progression.

Cognitive variables

Mortimer and colleagues ¹⁹ found a faster rate of decline in cognition among patients with lower scores on tests of verbal ability, while faster functional decline was predicted by lower scores on tests of nonverbal ability. A study by Coen et al ²⁰ compared patients who were more impaired on category fluency than letter fluency and those who were more impaired on letter fluency than category fluency. Category fluency was found to be equally impaired in both groups, although those in the letter fluency groups were especially impaired on letter fluency. Although not statistically significant, those who were more impaired on letter fluency than category fluency had a faster rate of decline in AD. The authors hypothesized that this result was consistent with the finding that rapid progression is associated with greater dysfunction of the frontal lobe. ²⁰ Musicco et al ²¹ also found that more severe executive functioning impairments were associated with a faster rate of decline over a 2-year period. Chan and colleagues ²² constructed a measure of deterioration of semantic knowledge by calculating the difference between an individual’s semantic network and the standard normal control network. This measure, the similarity index, was found to better predict the rate of progression than initial Dementia Rating Scale (DRS) score or other measures of language and semantic memory. The authors also found that performances on tests of naming and fluency were not associated with the rate of cognitive decline. Storandt et al ²³ found that the rate of decline was not associated with demographic predictors or APOE allele status, but those patients with difficulties on tests of naming and visuospatial tasks tended to progress more quickly.

Purpose of the Current Study

Patients with AD decline cognitively at different rates, with some experiencing rather rapid loss of cognition and others progressing more slowly. There is not currently a method for practically predicting the rate of cognitive decline among patients in a clinical setting, and although there is evidence for the contribution of demographic variables, cognitive functioning at baseline, and health and genetic risk factors to the rate of progression of the disease, the evidence has been somewhat mixed. Identifying those patients who are likely to progress very rapidly or very slowly could provide particularly important information for health care providers and caregivers that would allow them to plan for the patient’s future. The purpose of the current study is to examine both demographic variables and cognitive performance at baseline neuropsychological testing to determine whether there are differences at baseline in those who progress most rapidly from those who progress most slowly. Advantages of the current study are a large and carefully diagnosed sample of patients with AD, use of a well-defined, clinically relevant, sufficiently long-time window (progression from baseline to a follow-up evaluation 21-27 months later), utilization of the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) to categorize patients as rapid or slow progressors, and use of a comprehensive neuropsychological battery to compare baseline cognitive profiles of rapid versus slow progressors.

Hypotheses

It is expected that those patients in the rapidly progressing group will demonstrate poorer performance at baseline evaluation on tests of neuropsychological functioning, particularly tests of memory, constructional abilities, attention, and executive functioning, as well as test of global functioning such as the MMSE and ADAS-Cog. It is also expected that patients in the rapidly progressing group will be younger, have less education, and have a higher initial Clinical Dementia Rating (CDR) score than patients in the slowly progressing group.

Methods

Participants

The sample consisted of 110 participants (55 slow progressing and 55 rapid progressing) selected from the database of the Baylor College of Medicine’s Alzheimer’s Disease and Memory Disorders Center (ADMDC) in Houston, Texas. Participants met the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) ²⁴ criteria for a diagnosis of probable AD. Diagnoses were made in a consensus conference composed of neurologists, neuropsychologists, and nurses. Consent forms permitting storage and use of data were signed by all participants or legally designated representatives. For inclusion in this study, participants needed to have baseline ADAS-Cog scores, follow-up ADAS-Cog scores 21 to 27 months after their baseline examination, and a diagnosis of probable AD at both time points. Patients were excluded if they had a history of significant head injury, stroke, or other neurological disorders. The average length of time between baseline appointment and follow-up appointment was 2.06 years (standard deviation [SD] = 0.11). The mean length of time between appointments for the slowly progressing group was 2.05 years (SD = 0.01) and for the rapidly progressing group was 2.07 (SD = 0.02). The groups did not significantly differ in length of follow-up time. A total of 247 participants met these initial criteria. The distribution of change in ADAS-Cog scores was inspected to determine the cutoff scores for inclusion in the rapid progressing or slow progressing groups. Upper and lower ends of the distribution could be defined by a clinically meaningful change of 0 points or an improvement in score for the slowly progressing group (n = 55; 22% of the original sample) and a decrease of 6 points or more for the rapidly progressing group (n = 55; 22% of the original sample). Any participants with a change of 0 points or an improvement in score were considered to be slowly progressing, and those participants with a decrease of 6 points or more from baseline evaluation to follow-up evaluation were considered to be rapidly progressing. Although the authors are not aware of any previous studies using ADAS-Cog change scores to compare rapidly and slowly progressing groups, change in ADAS-Cog score has been used in previous studies as a measure of change in cognition. ²⁵ The ADAS-Cog was chosen as the grouping measure because it is the most widely used cognitive instrument in clinical trials.

Measures

• Alzheimer’s Disease Assessment Scale-Cognitive subscale ²⁶ : The ADAS contains 11 subtests/ratings which assess orientation, attention, memory, language, ideational praxis, and visuoconstructional ability.

• Mini Mental State Examination ²⁷ : The MMSE is a brief measure that screens for cognitive impairment. A total of 30 points can be earned over the areas of orientation, attention and calculations, immediate and delayed recall, repetition, naming, following commands, reading, visual construction, and writing. A score for preprogression MMSE can be calculated by the formula: (MMSE score [expected] − MMSE score [initial])/physician’s estimate of duration (in years) obtained from review of medical records and interview with the patient and caregiver. ¹

• Clinical Dementia Rating scale ²⁸ : The CDR is a scale of severity of dementia. Possible scores are 0 to indicate no symptoms of dementia, 0.5 to indicate very mild symptoms of dementia or mild cognitive impairment, 1 to indicate mild dementia, 2 to indicate moderate dementia, and 3 to indicate severe dementia. Scores are assigned based on the participant’s performance in the areas of memory, orientation, judgment and problem solving, community affairs, home and hobbies, and personal care. These scores were used a dependent variable in the analyses.

• Western Aphasia Battery (WAB) sequential commands ²⁹ : Sequential commands require the participant to follow spoken commands that increase in complexity. Raw scores were used as a dependent variable in the analyses.

• Multilingual Aphasia Examination’s Controlled Oral Word Association Test (COWAT) ³⁰ : The COWAT is a test of phonemic fluency in which the participant names as many words as he or she can think of that begin with the letters F, A, and S (in 1-minute time periods). Raw scores were used as a dependent variable in the analyses.

• Boston Naming Test ³¹ : The Boston Naming Test is a test of naming to confrontation. Drawings are viewed and must be named by the participant. Raw scores were used as dependent variables in the analyses.

• American National Adult Reading Test ³² : The AMNART is a test of single-word reading ability that is often used to estimate premorbid intelligence levels. Raw scores were used as a dependent variable in the analyses.

• Verbal Series Attention Test (VSAT time) ³³ : The VSAT allows participants 60 seconds to complete various tasks of attention and mental control as quickly and accurately as possible, including counting forward and backward, serial subtraction of 3’s, days of the weeks and months of the year forward and backward, and saying numbers and letters in ascending, alternating order (ie, 1-A-2-B, etc.). The time taken to complete each task is recorded. Raw scores were used as a dependent variable in the analyses.

• Rey-Osterrieth Complex Figure Test (ROCFT) ³⁴ : The ROCFT is a test of visual construction requiring the participant to copy a 2-dimensional line drawing. Raw scores were used as a dependent variable in the analyses.

• Wechsler Adult Intelligence Scale-R and III (WAIS-R and WAIS-III): Vocabulary and Block Design (BD) subtests ^35,36 : Scaled scores were used for WAIS subtests. The Vocabulary subtest assesses a participant’s verbal knowledge of orally and visually presented words. The BD subtest is a test of visual construction requiring participants to put together blocks to form various patterns. As data were used from a long-running longitudinal database, a transition was made from using the WAIS-R to the WAIS-III. For Vocabulary, 73 participants had WAIS-R scores and 33 participants had WAIS-III scores. For BD, 67 participants had WAIS-R scores, and 32 participants had WAIS-III. The scores for WAIS-R and WAIS-III were not significantly different for the Vocabulary subtest (WAIS-R: mean [M] = 9.46; WAIS-III: M = 9.79) and were not significantly different for the BD subtest (WAIS-R: M = 7.29; WAIS-III: M = 7.42). Scaled scores were used as dependent variables in the analyses.

• Wechsler Memory Scale-Revised: Logical Memory (LM) I and II and Visual Reproduction (VR) I and II subtests ³⁷ : LM is a measure of verbal memory. Logical Memory I measures the ability to recall a story immediately after it is read. Logical Memory II measures the ability to recall those stories after a 30-minute delay. Visual Reproduction is a measure of visual construction and memory. During VR I, participants are presented with cards with line drawings for 10 seconds each. After the card is removed, the line drawings must be reproduced. Visual Reproduction II requires the participant to reproduce all 4 drawings after a delay of 30 minutes. Scales scores were used as dependent variables in the analyses.

• Physical Self-Maintenance Scale (PSMS-basic activities of daily living [ADLs]) ³⁸ : The PSMS-basic ADLs assess functional abilities in 6 basic ADLs: continence, ambulation, feeding, bathing, grooming, and dressing. Scores range from 5 to 30. A higher score indicates greater dependence on others. Raw scores were used as a dependent variable in the analyses.

• Instrumental Activities of Daily Living (IADLs) ³⁸ : The IADL scale assesses independence in 8 daily living tasks: using the telephone, shopping, housekeeping, cleaning, laundry, driving, and management of medications and finances. Scores range from 0 to 31. Higher scores indicate a greater level of dependence. Since some items are nonapplicable for a given patient, a potential highest score is calculated, and the obtained score is divided by the highest possible score to yield a ratio between 0 and 1. Higher ratios indicate more impaired performance. Ratio scores were used as a dependent variable in the analyses.

• Geriatric Depression Scale (GDS) ³⁹ : The GDS is a 30-question self-report measure that assesses symptoms of depression among older adults. Raw scores were used as a dependent variable in the analyses.

• Cumulative Drug Exposure: This measure is the cumulative exposure to both cholinesterase inhibitors and memantine for the participant measured in days at the follow-up evaluation.

• Drug Persistency Index: This measure is the ratio of cumulative drug exposure and duration of symptoms in years. It is generally not greater than 1 but can be in rare cases.

Procedure

Participants received baseline neuropsychological testing as part of their participation in ongoing research at the Baylor College of Medicine ADMDC. Neuropsychological testing was administered according to standard protocol, and participants were contacted to return for follow-up testing approximately 2 years following baseline evaluation. Only those participants with follow-up testing data available 21 to 27 months after baseline evaluation were included in the current study. Participants were divided into rapidly and slowly progressing groups based on the procedure described in the Participants section. Independent sample t tests and χ² analyses were conducted to determine differences between the groups in baseline performances.

Results

Demographic and Other Patient Characteristics

All results presented are the product of analyses comparing baseline characteristics between the rapidly and slowly progressing groups. Results of independent samples t tests revealed that age was significantly different between slow and rapid progressors, with slow progressors being significantly older than rapid progressors, t(108) = 2.26, P = .03 (see Table 1). Since the rapidly progressing group was found to be younger, on average, than the slowly progressing group, adjustment for age was not considered to be necessary, as such adjustment would likely result in a magnification of the results found rather than resulting in a change in results. Results of χ² analyses revealed that the proportion of women and men did not differ between the groups. There were not enough non-Caucasian and Hispanic participants to meaningfully examine differences in race and ethnicity between the groups. Education also did not differ between rapid and slow progressors nor did estimated premorbid verbal intellectual ability as measured by the AMNART. The groups significantly differed in initial CDR, χ²(2, N = 108) = 7.80, P = .02. Those with a CDR score of 0.5 were more likely to be classified as slowly progressing than those with a CDR score 1 or greater. Neither baseline ADAS-Cog nor baseline MMSE scores differed significantly between the groups, and MMSE preprogression scores also did not differ between rapid and slow progressors. There was no significant difference between the 2 groups in duration of symptoms. The 2 groups did not differ in APOE ∊4 status. Cumulative Drug Exposure and Drug Persistency Index values did not differ between rapidly and slowly progressing patients (P > .80 for both t tests).

Table 1.

Demographics and Other Patient Characteristics.

Measure	Total, N	Slow Progressors (n = 55)		Rapid Progressors (n = 55)
		Mean	SD	Mean	SD
Age	110	75.79a	6.10	73.02	6.75
Sex (% women)	110	64%		60%
Education	110	13.93	3.42	14.07	2.95
AMNART	105	108.76	11.31	109.56	7.57
CDR (% 0.5)	108	48%a		24%
Baseline ADAS-Cog	110	20.43	8.81	21.35	8.12
Baseline MMSE	110	22.69	4.23	21.22	4.71
MMSE preprogression	110	3.12	2.19	3.37	2.72
APOE ∊4 (% ≥1 ∊4 allele)	109	57%		65%
Duration of symptoms, years	110	3.02	1.83	3.19	1.41
Cumulative drug exposure	104	894.71	495.89	880.81	539.05
Drug persistency	104	0.49	0.24	0.48	0.26

Abbreviations: AMNART, American National Adult Reading Test; ADAS-Cog, Alzheimer’s Disease Assessment Scale-Cognitive subscale; CDR, Clinical Dementia Rating; MMSE, Mini Mental State Examination; SD, standard deviation.

^a Differed significantly from the rapid progressor subgroup at P < .05.

Neuropsychological Measures

All results presented are the product of analyses comparing neuropsychological performance between the rapidly and slowly progressing groups at the baseline visit. Results of independent samples t tests revealed a number of significant differences in the subgroups’ neuropsychological test performances (see Table 2). The rapidly progressing group had significantly poorer scores on LM I (t[108] = 3.34, P = .001), VR I (t[107] = 2.68, P < .01), VSAT time (t[108] = −3.64, P < .001), COWAT Verbal Fluency (t[104] = 2.40, P = .02), and BD (t[100] = 2.55, P = .01). Additional analyses were conducted and revealed that these differences between the rapidly and the slowly progressing groups remained at the follow-up evaluation. Repeated-measures analysis of covariance indicated significant time by group interactions for the Boston Naming Test, LM I, VR I and II, VSAT, Rey-Osterrieth Complex Figure, COWAT, WAB Commands, BD, and ADLs.

Table 2.

Neuropsychological Measures: Differences at Baseline Visit.^a

Measure	Total, N	Slow Progressors (n = 55)		Rapid Progressors (n = 55)
		Mean	SD	Mean	SD
ADAS delayed recall	110	8.96	2.02	9.05	1.67
PSMS	105	6.98	1.46	7.75	3.02
IADL ratio	108	0.84	0.23	0.88	0.19
LM I	110	9.76b	5.13	6.53	5.03
LM II	110	2.36	3.41	1.93	3.29
VR I	109	17.65b	7.05	14.00	7.15
VR II	109	2.87	4.90	1.80	3.02
VSAT Time	110	178.02b	84.12	234.15	77.54
ROCFT copy	74	26.65	8.17	23.24	11.09
BNT uncued	108	43.41	11.74	41.41	11.33
COWAT	106	26.70c	11.70	21.46	10.73
WAB commands	109	76.89	7.99	76.35	7.34
Vocabulary	103	10.10	3.21	9.02	2.89
Block Design	102	8.04c	2.95	6.60	2.74
GDS	108	6.24	4.57	5.91	4.59

Abbreviations: ADAS, Alzheimer’s Disease Assessment Scale; BNT, Boston Naming Test; COWAT, Controlled Oral Word Association Test; GDS, Geriatric Depression Scale; IADL, Instrumental Activities of Daily Living; LM, Logical Memory; PSMS, Physical Self-Maintenance Scale; ROCFT, Rey-Osterrieth Complex Figure Test; SD, standard deviation; VR, Visual Reproduction; VSAT, Verbal Series Attention Test; WAB, Western Aphasia Battery.

^a LM I, LM II, VR I, VR II, Vocabulary, and Block Design scores all represent scaled scores; all other scores presented are raw scores.

^b Differed significantly from the rapid progressor subgroup at P < .01.

^c Differed significantly from the rapid progressor subgroup at P < .05.

To determine whether group membership could be predicted by a model containing the neuropsychological measures that differed significantly between groups, a discriminant function analysis was performed. Results revealed that the variables predicted group memberships (71.7% correctly predicted in the slowly progressing group and 71.2% correctly predicted in the rapidly progressing group, Wilks’ λ = 0.84, χ²[5, N = 105] = 17.11, P < .01). See Table 3 for discriminant function coefficients for the neuropsychological variables. A second discriminant function analysis was performed including CDR, but this did not enhance the accuracy of the classification rates.

Table 3.

Standardized Canonical Discriminant Function Coefficients for Neuropsychological Measures.

Neuropsychological Measures	Function Coefficients
VSAT time	−0.80
LM I	0.76
BD	0.64
VR I	0.59
COWAT	0.52

Abbreviations: BD, Block Design; COWAT, Controlled Oral Word Association Test; LM, Logical Memory; VR, Visual Reproduction; VSAT, Verbal Series Attention Test.

Discussion

Patients with AD experience cognitive decline at different rates. The present study sought to identify characteristics present at baseline to distinguish those patients most at risk for experiencing rapid cognitive decline. Follow-up evaluations were conducted approximately 2 years postbaseline, and patients were identified as rapid or slow progressors based on the change in score on the ADAS-Cog between baseline and follow-up evaluation.

Demographic variables, such as sex, ethnicity, race, and education, did not differ between the rapid and slow progressing groups. This finding supports the results of Buccione et al ³ , who also found no difference in demographic variables between the rapid and slow progressing groups. Likewise, APOE ∊4 status did not differ between the groups. Evidence regarding the association of APOE ∊4 status with the rate of cognitive decline has been mixed; however, the results of the present study support the findings of Tschanz et al. ¹⁵

Age was found to significantly differ between the groups. Those in the rapidly progressing group were significantly younger than those in the slowly progressing group. This finding supports previous research suggesting that older age of onset is associated with a slower rate of decline. ^{7 –9} Baseline CDR was also found to significantly differ between groups, with those with more mild dementia (rated with 0.5) more likely to be classified as slow progressors than those with more advanced dementia. This is consistent with previous research that has found an association between more mild dementia as rated by the CDR and faster progression. ⁴⁰ However, groups did not differ on the basis of preprogression scores on either the MMSE or the ADAS. Functionally, the groups did not differ on ratings of ADLs.

There was no difference between the groups on baseline performance on the ADAS-Cog or MMSE, indicating these global measures are not as useful for predicting rate of decline as are more specific measures of neuropsychological functioning. Performance on tests of immediate verbal and visual memory (LM I and VR I), attention and mental control (VSAT), verbal fluency (COWAT), and visuospatial construction (BD) differentiated between slow and rapid progressors, with slow progressors having better performance at baseline on these tests. This finding supports previous research that patients progressing more rapidly have poorer performance on tests of memory, attention and mental control, fluency, and visuospatial construction. ^3,4,19,21,23 Additionally, performance on these neuropsychological measures was found to predict group membership for participants.

One limitation of the current study is the design. Measuring cognitive change at 2 time points to create the rapidly and slowly progressing participant groups does not provide as much information as measuring cognitive change over multiple time points would. Rapidly and slowly progressing groups could be formed with greater certainty of rate of progression had additional time points been used in the analyses. However, since the rate of change over the first 2 years after initial evaluation/diagnosis is of most immediate and practical importance to clinicians and patients/family members, we elected to adopt this focus on change over a well-defined 2-year time window. Additionally, the ADAS-Cog was used as the measure to determine classification in the groups. Although the ADAS-Cog is a commonly used measure of global cognition in AD, using other measurements of cognition or functioning, such as performance on tests of delayed memory or ADL/IADL performance, may have produced different results. Finally, the group of participants in the current study was, in general, mildly demented. It is possible that participants with more severe dementia may have exhibited differing results. Milder overall dementia severity in the slow progressing group may account for better performance on neuropsychological testing; however, it is not likely to be the only factor as performance on only some tests differed between the groups.

Certain variables were likely to significantly differ between the rapid and slow progressing groups. These variables include age, CDR, LM I, VR I, VSAT, COWAT, and BD. Patients who are younger at age of onset may be more likely to experience rapid cognitive decline. Given that those with milder overall dementia severity as measured by the CDR were more likely to be in the slowly progressing group, it may be that the rate of progression changes throughout the course of the disease such that one progresses more slowly in the early stages and more rapidly in the late stages. Tests that differed between the rapidly and slowly progressing groups tended to measure higher order cognitive skills such as executive functioning, memory, and visuospatial construction. This indicates that a full neuropsychological evaluation, rather than sole use of a global screening measure such as the MMSE or ADAS-Cog, may be useful for predicting future cognitive decline. Our evidence suggests that patients with poorer performance on neuropsychological testing in these domains are more likely to experience rapid progression of AD. Prediction of rate of decline among patients with AD may allow caregivers and physicians to make more informed decisions about future care of the patient. Future research should examine the predictive utility of performances in these domains at further time points to determine whether the differences in the rate of progression observed in the current study occur throughout the course of the disease.