Specific Neuropsychiatric Symptoms Are Associated with Faster Progression in Alzheimer’s Disease: Results of the Prospective Dementia Registry (PRODEM-Austria)

Abstract

Background:

Neuropsychiatric symptoms (NPS) occur frequently in the course of Alzheimer’s disease (AD) and are suspected to be associated with a faster dementia progression. Numerous reports have defined specific subsyndromes, summarized in clusters of items of the Neuropsychiatric Inventory (NPI).

Objective:

This study investigated the influence of specific NPI subsyndromes and clinical patient characteristics on dementia progression.

Methods:

Data of the prospective registry on dementia in Austria (PRODEM) were retrospectively analyzed. Cognitive functioning was determined at baseline and 2 yearly follow-up visits using the Mini-Mental State Examination (MMSE) and the Consortium to Establish a Registry for Alzheimer’s dementia neuropsychological test battery (CERAD). To assess NPS, the NPI was used: NPI items were classified in three subsyndromes (psychotic cluster, behavioral cluster, emotional cluster).

Results:

Out of the 662 included patients (mean age 76.4±8.4 years), 43% completed follow-up visits for two years. Significant correlation between higher scores in all three subsyndromes and worse cognitive performance were found for MMSE score, naming, and verbal fluency. Results of linear mixed model analysis revealed lower age and higher scores in the psychotic cluster as significant predictors of changes in MMSE with time.

Conclusion:

In this study, we report the influence of psychotic subsyndromes and lower age on faster MMSE decline in early AD. These results emphasize the importance of not only assessing but also differentiating neuropsychiatric symptoms in subsyndromes in the early stages of AD as a possible predictor of disease progression.

Keywords

Alzheimer’s disease disease progression Neuropsychiatric Inventory neuropsychiatric symptoms

INTRODUCTION

Multiple factors, such as young age, severe cognitive deficits, behavioral status, psychosis, and other neuropsychiatric symptoms (NPS) can result in faster cognitive decline in patients with Alzheimer’s disease (AD) [1, 2]. NPS occur frequently in patients with AD. Up to 91.2% of patients show at least one or more different NPS in the course of disease [3]. Prevalence rates of specific NPS range from 49% for apathy to 7% for euphoria [4]. The presence of NPS can increase caregiver burden, lower perceived quality of life, and lead to earlier institutionalization of patients [5 –7]. Persistent neuropsychiatric symptoms seem to accelerate cognitive decline [8]. Additionally, symptoms like aggression, agitation, and psychosis often lead to physical restraints and the use of psychotropic drugs such as antipsychotics and sedatives. In particular, the use of antipsychotics in AD patients can cause numerous severe side effects and therefore requires a careful case-by-case assessment, together with an accurate proof of possible drug-drug and/or drug-disease interactions [9]. Importantly, besides increasing cognitive decline, NPS such as depression, apathy, and anxiety are also suspected as risk factors or prodromal symptoms of dementia [10].

The severity of cognitive impairment over the course of AD is commonly measured by the Mini-Mental State Examination (MMSE) [11]. A loss of 3 or more MMSE points during six months has been defined as rapid cognitive decline, whereas a stable course or a decrease of up to 2 points of MMSE score per year is considered as slow cognitive decline [12]. Different NPS might varyingly influence disease progression. The clinical and pathological correlates of different NPS and their impact on the course of AD still remains uncertain. Prior studies suggested that the early involvement of certain neuroanatomical structures underlies distinct NPS, even though they occur more likely at later stages of progressive dementia. Nevertheless, NPS are often extremely dynamic conditions over the course of AD [13, 14]. Their severity does not progress linearly, but their frequency and severity commonly go hand in hand with severity and duration of AD [13]. The clinical phenomenology and severity of NPS themselves may be influenced by several different factors such as age, gender, concomitant pharmacological treatments, onset of dementia, and psychiatric or somatic co-morbidities. So far, little is known about distinct effects of specific NPS on cognitive decline in AD patients. Particularly, longitudinal studies assessing the association between NPS and decline of cognitive functioning are scarce and controversial. Analysis of a large cohort study [15] found no influence of Neuropsychiatric Inventory (NPI) subsyndromes on the cognitive course of AD. In contrast, others reported that specific NPS such as psychosis and apathy negatively affect cognitive decline in AD [16, 17].

The current data from the prospective dementia registry (PRODEM) Austria followed a large cohort of patients with mild to moderate AD attending memory clinics for a period of two years. The aim of the study was to work out the association between different NPS summarized in three predefined subsyndromes with cognitive decline of patients with AD over time. Since this was a naturalistic study, analysis of clinical, demographic, and neuropsychiatric measures of drop-out patients provided additional information not only about disease progression but also on adherence to memory clinics over the course of AD.

MATERIAL AND METHODS

Ethics statement

The study was approved by the ethics committees of the following participating centers:

Medical University of Graz, the Medical University of Innsbruck, the Medical University of Vienna, the Konventhospital Barmherzige Brüder Linz, the Province of Upper Austria, the Province of Lower Austria and the Province of Carinthia. Written informed consent was obtained from all patients and their caregivers.

Study population

All patients were participants in the multi-centric cohort study “Prospective Dementia Registry Austria (PRODEM-Austria)” of the Austrian Alzheimer Society. The study population consisted of 662 patients diagnosed with possible or probable AD according to NINCDS-ADRDA criteria [18, 19]. Inclusion criteria comprised no need for 24-h care, and availability of a caregiver who was able to provide information on neuropsychiatric symptoms of the patient and to provide information on the patients’ condition. Patients were excluded from the study if they were unable to sign an informed consent or if co-morbidities were likely to preclude termination of the study. The thirteen study sites were situated in six of nine provinces of the State of Austria with investigators representing the specialties of neurology and/or psychiatry.

Patients were clinically examined and demographics such as a family history of dementia, years of education, occupational and social status were assessed. Further, current somatic and psychotropic medication including antidepressants, benzodiazepines, and antipsychotics were obtained from medical records of patients and/or caregivers.

Neuropsychological measures

All patients completed a neuropsychological assessment at baseline. Except for drop-outs, patients had follow-up visits within the regular clinical routine after one year (FU 1) and two years (FU 2). They were tested utilizing the “Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuropsychological test battery (Plus version) [20]. This battery includes subtests for verbal memory and recognition (word list learning, word list delayed recall, and word list recognition), constructional praxis (figure drawing), figural memory (delayed recall), confrontational object naming (Boston Naming Test [BNT] – short version), verbal fluency (animals/min, s-words/min), cognitive flexibility (Trail Making Test A and B), as well as the MMSE [11]. The MMSE served as measure for the severity of cognitive impairment. Out of these measures (age and education corrected z-scores) the CERAD total score was calculated.

Depressive symptoms were assessed using the 15-items Geriatric Depression Scale (GDS) [21].

The Neuropsychiatric Inventory (NPI) [22], as used to assess frequency (range: 0–4 points), severity (1–3 points), and emerging caregiver burden (0–5 points) of 12 neuropsychiatric and behavioral symptoms. Subsyndromes were calculated based on the aggregate scores of frequency and severity of each symptom, reflecting the overall impact on the patient (NPI-total score). Definitions of different subsyndromes according to NPI items were based on Garre-Olmo et al. [23], resulting in (a) a ‘psychotic” cluster (including “delusions” and “hallucinations”), (b) an “emotional” cluster (including “agitation/aggression”, “depression/dysphoria”, “anxiety”, and “irritability”), and (c) a “behavioral” cluster (including “elation/euphoria”, “apathy”, “disinhibition”, and “aberrant motor behavior”).

Statistical methods

Before analysis, all variables were checked for deviations from normality. Variables with skewness values >1 or < –1 were regarded as an indication of marked departures from a symmetric distribution requiring non-parametric testing. Changes of cognitive functioning over time were analyzed by means of the Wilcoxon signed-rank test, as most of the variables of the CERAD test battery exhibited departures from normality. Spearman rank correlation coefficients were used to analyze associations between changes in MMSE score over time and both socio-demographics and baseline values of NPI clusters as the latter variables displayed high levels of skewness. Linear mixed models were applied to analyze the combined effects of socio-demographic variables, neuropsychiatric subsyndromes (scores of NPI clusters), and psychotropic medication on MMSE scores, using “time” as the repeated factor (baseline, FU1, FU2). A first-order autoregressive covariance structure (AR(1)) was used to model intra-subject dependencies. Both main effects and interactions with time were considered in the analysis, where the former indicates effects of independent variables on mean MMSE level, whereas the latter reflects effects of the independent variables on changes in MMSE. No transformation of the dependent variable was required as the corresponding skewness value was small.

RESULTS

Demographic data

Six hundred and sixty two patients (58% female) diagnosed with AD according to criteria of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA criteria) [19] were included in the study at baseline. Of these, 418 (63%) completed FU 1 and 282 (43%) FU2. The decreasing numbers of participants with duration of the study were due to the naturalistic design of the study, withdrawal of consent. Further, some drop-outs may have been caused by death—unfortunately we have no information about this. Detailed subject characteristics are presented in Table 1 taking drop-outs into account.

Table 1

Demographic characteristics (mean value/standard deviation SD) of the study population at baseline (BL), comparison of patients who completed the study until 2-year follow-up (FU 2) and patients who dropped out after BL (no follow-up visit)

BL data		Mann-Whitney Test
Demographic data	All N = 662 Mean±SD or N (%)	BL+FU 2 visit N = 282 Mean±SD or N (%)	drop-out N = 380 Mean±SD or N (%)	p Two-tailed
Age (y)	76.4±8.4	75.6±7.9	76.9±8.3	0.026
Sex (% female)	381 (57.6%)	169 (59.9%)	212 (56.1%)	0.626
Family history of dementia (positive)	225 (34%)	162 (57.4%)	124 (32.8%)
GDS^† – 15 score	2.8±2.6	2.3±2.1	3.1±2.9	0.003
MMSE^‡	22.1±4.3	22.2±4.0	21.9±4.4	0.252
CERAD^§ total z-score	–10.3±6.9	–10.1±8.9	–10.5±5.0	0.106
Antidepressants	316 (47.4%)	146 (51.8%)	170 (45%)	0.084
Sedatives	96 (14.5%)	44 (15.6%)	51 (13.5%)	0.445
Antipsychotics	119 (18%)	64 (22.7%)	55 (13.5%)	0.007
NPI subyndromes
Psychotic cluster (0–14)	0.8±2.1	0.7±1.9	0.8±2.3	0.503
Emotional cluster (0–42)	5.9±5.9	5.4±5.6	6.3±6.2	0.113
Behavioral cluster (0–32)	3.1±4.3	2.9±4.3	3.2±4.4	0.474

^†Geriatric Depression Scale, ^‡Mini-Mental State Examination, ^§Consortium to Establish a Registry for Alzheimer’s Disease, Neuropsychiatric Inventory, ^*Correlation is significant at the 0.05 level (2-tailed). ^**Correlation is significant at the 0.01 level (2-tailed).

Drop-out analysis

At baseline, 662 patients were included in the study. At 1-year follow-up data of 430 patients and at 2-year follow-up data of remaining 282 patients could be analyzed. Analysis of patient characteristics at baseline showed higher age (76.6±8.3 versus 75.6±7.9 years, p = 0.037) in the drop-outs compared to the patients completing the 2-year follow-up. At baseline, 119 (18%) of patients took antipsychotics. Significantly less patients in the drop-out group compared to the remaining patients (14.5% versus 22.7%, p = 0.006) took antipsychotics at baseline. For all other patient characteristics (NPI subyndromes, MMSE, CERAD-score, demographics, medication), drop-outs showed no significant differences compared to patients remaining in the study.

Correlation analyzes of MMSE-change with demographics and NPI clusters

Correlation analyzes revealed that higher age at baseline correlates with a less pronounced decrease in MMSE score within 2 years. A higher rate of all NPI subsyndromes was associated with a more pronounced decline in MMSE score within one year. At two-year follow-up, solely a higher baseline score in the psychotic cluster was associated with a faster decline of the MMSE score. Detailed results are presented in Table 2.

Table 2

Pearson correlation analysis of changes in MMSE with demographic data and NPI scores at baseline

MMSE^§ change from baseline to 1-year follow-up		MMSE^§ change from baseline to 2-year follow-up
Measures	Correlation coefficient	p	Correlation coefficient	p
Age	0.092	0.059	0.131	0.028^*
Education	–0.021	0.664	–0.041	0.496
GDS^† – 15	0.018^*	0.712	0.089	0.135
Psychotic cluster	–0.113	0.021^*	–0.232	<0.001^**
Emotional cluster	–0.138	0.005^**	–0.061	0.310
Behavioral cluster	–0.212	<0.001^**	–0.103	0.087

^†Geriatric Depression Scale, Neuropsychiatric Inventory, ^§Mini-Mental State Examination, ^*Correlation is significant at the 0.05 level (2-tailed). ^**Correlation is significant at the 0.01 level (2-tailed).

Correlation analyzes revealed that higher rates of all NPI subsyndromes were associated with a lower MMSE score and lower z-scores in the speech associates neuropsychological measures (verbal fluency s-words, BNT). Furthermore, higher scores in the emotional and the behavioral cluster were additionally associates with more pronounced cognitive deficits in constructing praxis. Results are presented in Table 3.

Table 3

Pearson correlation analysis of NPI subsyndromes with neuropsychological measures at baseline (BL)

	Psychotic cluster		Emotional cluster		Behavioral cluster
Neuropsychological measures at BL	Correlation coefficient	p	Correlation coefficient	p	Correlation coefficient	p
MMSE^† total score	–0.127	0.002	–0.150	<0.001^**	–0.112	0.007
CERAD total score^‡	–0.055	0.194	–0.095	0.024	–0.093	0.027
Word list learning^‡	–0.029	0.490	–0.044	0.286	–0.025	0.555
Word list savings^‡	–0.013	0.761	–0.069	0.107	–0.061	0.153
Constructive praxis^‡	–0.025	0.543	–0.109	0.009	–0.111	0.008
BNT^‡§	–0.087	0.034	–0.092	0.026	–0.095	0.021
Verbal fluency animals^‡	–0.128	0.002	–0.083	0.043	–0.129	0.002
Verbal fluency s-words^‡	0.000	0.999	0.021	0.061	0.008	0.840
Trail A^‡	–0.056	0.208	–0.071	0.109	–0.030	0.506
Trail B^‡	0.008	0.887	0.014	0.081	0.012	0.0831

^†Mini-Mental State Examination, ^‡,z-score at baseline, ^§Boston Naming Test, ^*Correlation is significant at the 0.05 level (2-tailed).^**Correlation is significant at the 0.01 level (2-tailed).

Results of neuropsychological measures

Comparison of neuropsychological measures between baseline and FU 2 showed a significant worsening for all neuropsychological measures except for Trail B and constructing praxis using the Wilcoxon test. Within the first year, solely the MMSE score, the CERAD total score, the BNT score, and verbal fluency (s-words, animals) significantly decrease.

Results of linear mixed model analysis

Findings of the linear mixed model analysis are presented in Table 5. Significant predictors of mean MMSE score were age, psychotic symptoms, and behavioral symptoms at baseline, and use of antipsychotics at baseline. Higher age predicted more favorable MMSE scores; more psychotic or behavioral symptoms went along with lower MMSE scores, and the same was true for patients taking antipsychotics at baseline.

Only two variables emerged as significant predictors of changes in MMSE with time, namely age and psychotic symptoms. Patients of higher age showed significantly less deterioration in MMSE, whereas patients with more psychotic symptoms at baseline displayed a sharper MMSE decline than those with less symptoms.

DISCUSSION

In this study, we investigated whether different NPI subsyndromes and type of psychopharmacological treatment are associated with cognitive decline in patients with mild to moderate AD. Our results showed that higher scores in the psychotic cluster at baseline and lower age in early disease stages of AD are associated with a pronounced MMSE decline over time. In accordance to these results, antipsychotic medication, which is frequently used to treat behavioral and psychotic symptoms, was predictive for a more rapid disease progression. Focusing on cognitive functions we found a close association with deficits in language dependent neuropsychological measures and the presents of all NPI subsyndromes as well as a more rapid decline of MMSE score over two years.

Psychopharmacologic treatment, neuropsychiatric symptoms, and disease progression

We found that both the presence of antipsychotic medication and the presence of neuropsychiatric symptoms in the behavioral and psychotic cluster were predictive for a faster MMSE decline in patients with mild AD within two years of evaluation. Since the mean MMSE score at baseline was clearly above twenty points we suggest, an especially negative influence of these two factors in early stages of AD. However, we assume that the impact of behavioral and psychotic neuropsychiatric symptoms has to be distinguished from those of antipsychotic treatment. Antipsychotic treatment has previously been reported to boost cognitive functions and disease progression [24], but a recent meta-analysis [25] found very heterogeneous results and limited evidence for such an effect. This inconsistency may be due to the numerous and heterogeneous indications of antipsychotics in patients with AD. Symptoms of the psychotic and behavioral cluster, primarily such as delusions, hallucinations, and disinhibition are typical indications for antipsychotic treatment. However, in clinical routine sleep disturbances are frequently treated with antidepressants and sedatives but also sporadic with antipsychotics such as, e.g., quetiapine or protyphendyl. In our study, detailed indication of antipsychotic medication has not been assessed. For this reason, the causal relationship of NPS and antipsychotic treatment remain partial open. This missing information has to be mentioned as a possible limitation of our study. Furthermore, the presence of psychotic symptoms may be related to a dysfunction in the dopaminergic system as widely reported in other forms of dementia such as Lewy body dementia or frontotemporal dementia. Since our study population solely included patients with AD, we could not address this issue in more detail.

Results from patients under antidepressant treatment showed not only higher depression scores and higher scores in the emotional cluster but also lower scores in verbal memory (recall, savings). These findings are in line with the widely reported increased risk of elderly patients with depression to develop AD [26, 27].

In our study, deficits in verbal memory showed no correlation with NPI clusters while constructing praxis impairment was associated with the emotional and the behavioral cluster. In addition, deficits mainly in language associated cognitive test (verbal fluency, BNT) were positively associated with all three NPI subsyndromes at baseline. Vice versa, a follow-up study by Tsai et al. [28] in patients with AD assessed the impact of impaired verbal fluency on progression of neuropsychiatric symptoms within 2 years. The authors reported a negative effect of verbal fluency solely on change of behavior symptoms in the psychosis domain. These results support our findings on the close association of distinct and varying cognitive and neuropsychiatric symptoms in patients with AD. On the other hand, it raises the question of time-dependent effects of neuropsychiatric symptoms and cognitive changes in the course of AD. Further, besides MMSE score, results of language dependent tests showed a significant decrease between baseline and both follow-up visits. Solely at two-year follow-up, we found additionally a clear decrease in verbal memory and psychomotor speed. These results underpin the importance of deficits in verbal communication in early AD.

We found a frequently use of antidepressants of 47.4% in our study population at baseline. These results are somehow inconsistent because detailed analysis showed in 116 patients (17.5%) mild depressive symptoms and only in 18 patients (2.7%) moderate to severe symptoms with a GDS score >10. A reason for this discrepancy could be that antidepressants have a number of other implications besides depression in patients with AD. These are anxiety, agitation, sleep disturbances, or even loss of appetite [29]. Further, prior studies reported that behavioral disturbances of any reason were associated with increased use of psychotropic medication in patients with AD [30]. The prescription of antipsychotics in 18% of patients at baseline was in comparison to the literature, reporting prescription rates up to 60%, very low [31].

Results of the linear mixed model analysis are presented in Table 4. Significant predictors of MMSE score over time were age, psychotic and behavioral NPI subsyndromes, and use of antipsychotics at baseline. Higher age predicted a less progressive decline of MMSE scores; more psychotic or behavioral symptoms went along with lower MMSE scores, and the same was true for patients taking antipsychotics at baseline. These findings support those reported by Wilkosz et al. [17] who found a more rapid cognitive decline in AD patients with higher psychotic symptoms as well as younger age of disease onset.

Table 4

Combined effects of socio-demographics, neuropsychiatric subsyndromes, and psychotropic medication on MMSE scores - findings of linear mixed model analysis

Parameter	Estimate	s.e.^†	d.f.^‡	t	p
Intercept	20.5251	1.956	834.8	10.522	<0.001
Main effects
Time since baseline (y)	–4.9994	1.2892	1629.5	–3.878	<0.001
Age	0.0589	0.0221	630.9	2.665	0.008
Sex (female versus male)	0.0043	0.3523	636.3	0.012	0.990
Psychotic cluster	–0.2812	0.0988	668.9	–2.845	0.005
Emotional cluster	–0.0024	0.0383	638.1	–0.063	0.950
Behavioral cluster	–0.1071	0.0513	630.7	–2.090	0.037
Sedatives (yes versus no)	0.3461	0.5134	620.2	0.674	0.500
Antidepressants yes versus no)	–0.3754	0.3666	628.3	–1.024	0.306
Antipsychotics (yes versus no)	–1.2575	0.4987	616.2	–2.521	0.012
Interactions with time (y)
Time ^*Age	0.0424	0.0157	1623.5	2.700	0.007
Time ^* Sex	0.0421	0.2549	1620.1	0.165	0.869
Time ^*Psychotic cluster	–0.2198	0.0763	1625.4	–2.881	0.004
Time ^*Behavioral cluster	–0.0581	0.0365	1615.6	–1.591	0.112
Time ^*Emotional cluster	0.0253	0.0274	1631.6	0.926	0.355
Time ^*Sedatives	0.0196	0.3534	1615.1	0.055	0.956
Time ^*Antidepressants	0.0626	0.2556	1625.1	0.245	0.807
Time ^*Antipsychotics	–0.6149	0.3389	1606.9	–1.814	0.070

s.e., standard error^†, d.f., degrees of freedom.^‡ ^*Correlation is significant at the 0.05 level (2-tailed).^**Correlation is significant at the 0.01 level (2-tailed).

In contrast to Canevelli et al. [15], we found a distinct influence of specific NPI subsyndromes on the cognitive course of patients with early AD. More precisely, more severe psychotic symptoms at baseline were associated with a sharper decline in MMSE scores. However, the study of Canavelli reported an association of the behavioral subsyndrome with faster cognitive decline in only severe stages of AD [15]. However, our results are in line with those of Starkstein et al. [16] who found a negative influence of apathy as part of the behavioral cluster on faster general disease progression. Our results showed a negative correlation of all three NPI clusters (emotional, behavioral, psychotic) with a faster decline in MMSE at least within the first year. Our study additionally assessed the influence of NPI subsyndromes on decline of different cognitive functions. Therefore, our data gives more detailed and sophisticated information on the variable impact of NPS on disease progression in AD.

Analysis of study drop-outs

Interestingly, higher scores in NPI clusters were not associated with higher rates of withdrawal of the study and, thus, lower adherence to regular visits at a memory clinic. However, depressive symptoms were more frequent in patients who did not come to their regular visits at the study centers over 2 years. These results may be due to the depressive syndrome per se, including lack of motivation, daytime sleepiness, or higher rate of comorbid anxiety in these patients, which interfere with the willingness to undergo regular cognitive testing. Even though depressive symptoms were not associated with a more rapid cognitive decline, they could prevent patients from a continuous care at a memory clinic. The prescription of antipsychotics at baseline was higher in patients who came to their regular clinical controls to memory clinics until follow-up 2 compared to drop-outs. We assume that adherence to specialized medical facilities is higher in patients with prescribed antipsychotic since side effects of these drugs are frequent or low treatment response can necessitate regular controls. Further, a positive family history of dementia was seen less frequent in drop-outs. We hypothesize that the personal experience of AD in close relatives rather than genetics encourage caregivers and patients to consider the regular support of memory clinics as more important.

Conclusion

In conclusion, our results emphasize the critical negative influence of neuropsychiatric symptoms on cognitive decline especially in mild to moderate stages of AD. Further, our results confirm the widely reported finding that multiple behavioral symptoms can co-occur in the course of dementia [32]. The present study confirms partially previous findings and contributes additional evidence for the important influence of language dependent cognitive functions together with behavioral and psychotic symptoms on disease progression in mild stages of AD.

Footnotes

ACKNOWLEDGMENTS

We thank the Austrian Alzheimer's society for supporting this study.

Authors’ disclosures available online ().

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