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DETERMINANTS OF MEDICAL DIRECT COSTS OF CARE AMONG PATIENTS OF A MEMORY CENTER

 

V. Dauphinot1, A. Garnier-Crussard1, C. Moutet1, F. Delphin-Combe1, H.-M. Späth2, P. Krolak-Salmon1,3,4

 

1. Clinical and Research Memory Center of Lyon, Lyon Institute For Elderly, University hospital of Lyon, Lyon, France; 2. EA 4129 “Parcours Santé Systémique”, University Lyon 1, Lyon, France; 3. Clinical Research Centre CRC – VCF (Vieillissement – Cerveau – Fragilité), Hospital of Charpennes, University Hospital of Lyon, Lyon, France; 4. Neuroscience Research Centre of Lyon, Inserm 1048, CNRS 5292, Lyon, France

Corresponding Author: Dr Virginie Dauphinot, Hôpital des Charpennes, 27 rue Gabriel Péri, 69100 Villeurbanne, France, Tel: +33 (0) 472433114. Fax: +33 (0) 472432054, E-mail address: virginie.dauphinot@chu-lyon.fr
J Prev Alz Dis 2021;
Published online April 10, 2021, http://dx.doi.org/10.14283/jpad.2021.16

 


Abstract

Background: Alzheimer’s disease and related diseases (ADRD) are a major cause of health-related cost increase.
Objectives: This study aimed to estimate the real medical direct costs of care of patients followed at a memory center, and to investigate potential associations between patients’ characteristics and costs.
Design: Cross-sectional analyses conducted on matched data between clinical data of a cohort of patients and the claims database of the French Primary Health Insurance Fund.
Setting: Memory center in France
Participants: Patients attending a memory center with subjective cognitive complaint
Measurements: Medical or nonmedical direct costs (transportation) reimbursed by the French health insurance during the one year after the first memory visit, and socio-demographic, clinical, cognitive, functional, and behavioral characteristics were analyzed.
Results: Among 2,746 patients (mean ± SD age 79.9 ± 8 years, 42.4% of patients with dementia), the total direct cost was on average € 9,885 per patient during the year after the first memory visit: € 7,897 for patients with subjective cognitive complaint, € 9,600 for patients with MCI, and € 11,505 for patients with dementia. A higher functional and cognitive impairment, greater behavioral disorders, and a higher caregiver burden were independently associated with a higher total direct cost. A one-point decrease in the Instrumental Activities of Daily Living score was associated with a € 1,211 cost increase. The cost was higher in patients with Parkinson’s disease, and Lewy body disease compared to patients with AD. Diabetes mellitus, anxiety disorders and number of drugs were also significantly associated with greater costs.
Conclusions: Higher real medical direct costs were independently associated with cognitive, functional, and behavioral impairment, diabetes mellitus, anxiety disorders, number of drugs, etiologies as well as caregiver burden in patients attending a memory center. The identification of factors associated to higher direct costs of care offers additional direct targets to evaluate how interventions conducted in patients with NCD impact direct costs of care.

Key words: Costs of care, dependence, cognitive status, economics, Alzheimer’s disease.


 

Introduction

Alzheimer’s disease and related diseases (ADRD) are considered as the main cause of health-related cost increase in developed countries (1, 2). Dementia represented a total cost of € 105.2 billion in Europe in 2010 (3). In France, the prevalence of dementia has been estimated to 7.9% among people aged 65 and over, and it is expected to reach 9.6% by 2050 (4). To anticipate and optimize interventions targeting patients developing neurocognitive disorders (NCD)(5), it is of crucial importance to evaluate the cost of resources associated with the main characteristics of NCD. Cost-of-illness studies for ADRD appear essential to anticipate future resource needs, nevertheless they remain difficult to conduct as aging is related to various health conditions and comorbidities, and it is unclear whether comorbidities should be directly linked to ADRD (6, 7). In cost-of-illness studies, costs of care have been mainly estimated from self-reported resource utilization by patients and/or their informal caregivers (8-10). The use of real costs associated to patients’ care (estimated from claims data) offers an objective evaluation of costs related to patient care, independently of the possible recall bias that self-report might induce (11). Most previous studies have estimated the average cost per patient selected with a specific diagnosis (12-14), and costs of care in patients with ADRD were generally related to symptoms severity such as cognitive, functional and behavioral impairment (6, 12-23). These costs were presented with different amplitudes depending on the study population characteristics, the perspective of the study (payer, societal), the components of the costs (direct, indirect, informal), and the time of evaluation, which makes difficult any comparisons (12, 24, 25). Analyses of economic data of patients suffering from neurocognitive disorders with real-world data are scare in France while they are needed to evaluate the economic impact of interventions and for policy makers (26). The present study aimed at estimating the real medical direct costs of care of patients of a memory center at all stages of cognitive impairment during the one year after their first memory visit, and at investigating the potential associations between patient socio demographic and clinical characteristics and the average real medical and non-medical direct costs. Furthermore, these associations were assessed in the sub-group of patients with Alzheimer’s disease (AD).

 

Methods

Study design and setting

The present study was a cross-sectional analysis conducted on matched data between the MEMORA cohort including patient clinical data and the claims database of the French Primary Health Insurance Fund (PHIF). The protocol of the MEMORA cohort has been published previously (27). The match between the two databases was performed using the date of the 1st visit at a memory center. The claims database includes real medical and nonmedical direct costs of care for patients. Claims data were analyzed for one year after the first visit at a memory center. The present study was conducted at the University Clinical and Research Memory Centre of Lyon (University Hospital of Lyon, France), in collaboration with the regional PHIF of Rhône (Lyon, France). Around 90% of the French population is covered by the PHIF (28).

Study population

The study population included consecutive patients who underwent a medical examination in a memory center with a neurologist, geriatrician, or psychiatrist between 2014 and 2017. The inclusion criteria of patients were: to attend a memory visit, to have an evaluation of the functional autonomy level, not to live in a nursing home, and to be covered by the PHIF. Patients under legal protection were excluded from the study. The ethics Committee for the Protection of Persons Lyon Sud-Est IV was consulted on the 21st June 2013, and as the study was not classified as an interventional study, no written consent was required for participation. Written information regarding collection of individual data was provided to the patients and their informal caregivers and they were given the possibility to decline participation. Authorization for handling these data has been granted by the French Data Protection Authority (CNIL: Commission Nationale de l’Informatique et Libertés).

Real medical and nonmedical direct costs of cares

Source of cost data

This study was carried out from the perspective of the main payer of cares in France: the PHIF. The PHIF collects for each patient the real costs in Euros (€) of each care, act, and treatment that are reimbursed to patients. The costs included all the medical direct costs supported by the PHIF and one nonmedical direct cost (medical transportation). The others nonmedical direct costs such as home support and the indirect costs were not included since they are not covered by the PHIF.

Collected items of costs

The collected items of costs were grouped as medical direct costs ((1) outpatient cares, i.e. consultations and cares provided by general practitioners or specialists, surgical procedures in private practice, ophthalmological and hearing devices, dental cares, laboratory analyses, radiology examinations (radiology, scanners, MRI, PET, echography, bone densitometry), immunization, home dialysis, at-home hospitalizations, and health cures, (2) paramedical cares, i.e. nursing, physiotherapist, speech therapist, orthoptist, (3) pharmaceutical treatment in retail pharmacies, (4) public hospital stays, and (5) private hospital stays) and nonmedical direct costs (the medical transportations).

Valorization of the costs

The total cost per patient was estimated by adding all the costs of care, act, and treatment that occurred during the first year after the first memory center visit. The costs were presented as constant costs after adjustment using the value of Euro in 2017 as a reference, this value was available from the French national institute for statistical and economic studies (INSEE: Institut National de la Statistique et des Etudes Economiques) (https://www.insee.fr/fr/information/2417794). For each care, act, and treatment, the PHIF applies a specific reimbursement level, which is similar nationally.

Socio-demographic and clinical data at the memory center

Socio-demographic and clinical data were collected from the MEMORA cohort database, upon the first visit to the memory center (27). Socio-demographic data were: gender, age, marital status, and educational level.
Diagnosis etiologies and stages were determined by the specialist physician (neurologist, geriatrician, or psychiatrist) in charge of the patient (29-33). Patients with a cognitive complaint and normal neuropsychological performances were considered as having subjective cognitive complaint. A time to death variable was considered and calculated as the number of months between the first visit to the memory center and either the occurrence of the death or the last time the patient was known to be alive (corresponding to the end of the study period).
The following comorbidities information was collected: hypertension, hypercholesterolemia, diabetes mellitus, anxiety disorders and depressive disorders using medical report, as well as the number of drugs. The functional autonomy level was assessed during the interview with the primary caregiver with the Instrumental Activities of Daily Living (IADL) scale, including 8 activities (34). The IADL score ranges from 0 (dependent) to 8 (independent). Overall cognitive performances were assessed using the Mini Mental State Examination (MMSE), which ranges from 0 to 30 (35). The behavioral and psychological symptoms of dementia were assessed using the Neuropsychiatric Inventory (NPI) (36). A higher overall NPI score (maximum 144) is indicative of more severe behavioral disorders. The caregiver burden was assessed using the mini-Zarit scale, ranging from 0 to 7 (37). MMSE, IADL, NPI, and mini-Zarit scores were considered as continuous scores and as tertiles. MMSE scores were also considered using categories i.e. <10 (severe), 10-20 (moderate), >20 (mild).

Statistical analysis

The study population characteristics were described using the mean value ± standard deviation (SD) or the percentage, as appropriate. The costs per patient were expressed in euros and decomposed according to the origin of the costs, using means and their 95% confidence intervals (CI), medians, the 25th and 75th percentiles, and the minimum and maximum values. As the nonmedical direct costs of medical transport did not represent a large amount of the total cost, they were added, after description, to the medical direct costs to obtain a global cost per patient for further analyses.
As the distribution of the global cost was skewed, the relationship between each patient’s characteristics and the global cost was studied using generalized linear model (GLM) with log link and gamma distribution (38, 39). All significant variables associated with the total cost were then modeled together in multivariate GLM. Due to missing values for NPI and mini-Zarit scores, two different multivariate models were performed: the model 1 did not take into account the NPI and mini-Zarit scores, the model 2 did. The same multivariate models were performed within the sub-group of patients with AD. Results were summarized and presented as unadjusted and adjusted mean total cost, 95% CI, and p value. Additionally, the adjusted cost per 1 unit of IADL decrease was estimated and represented graphically.
A sensitivity analysis was conducted to examine the effect of potential “outliers” on the results. The “outliers” were identified as individual total cost greater than 3SD from the mean. The characteristics of the patients with outlier costs were compared to the characteristics of other patients, using Student t test or Pearson’s chi-square test. A new model was then performed after excluding the costs from the patients with outliers to verify whether the associations remained similar. P values below 0.05 were considered as statistically significant. Analyses were performed using STATA version 13 for Windows (StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP), and SPSS (Statistical Package for the Social Sciences) version 19.0 for Windows (SPSS Inc., Chicago, Illinois, USA).

 

Results

Study population characteristics

The study population included 2,746 patients (Table 1). Overall, 62.8% of patients were female; the mean age was 79.9 ± 8 years. The mean MMSE score was 19.7 ± 7, the mean IADL score was 4.2 ± 2, and the mean NPI score was 19.8 ± 17. In terms of etiology, 27.6% of patients had probable AD with or without cerebrovascular component, 6.4% had vascular encephalopathy (with no AD), 1.5% had Lewy body disease, and 0.4% had fronto temporal dementia. For 53.5% of the patients, the diagnosis etiology could not be established at the 1st visit at the memory center.

Table 1. Characteristics of the study population

* Time to death was the number of months from the first visit to the memory center until either the occurrence of the death or the last time the patient was known to be alive; IADL: Instrumental Activities of Daily Living; MMSE: Mini-Mental State Examination; NPI: Neuropsychiatric Inventory

 

Real direct costs of care

The total direct cost of cares was on average € 9,885 [9,175; 10,594] per patient during the year after the first memory center visit (including € 9,647 [8,946; 10,350] for medical direct costs and € 238 [213; 263] for the medical transport considered as nonmedical cost (Table 2). Most of the direct medical cost was attributable to the hospital care in public hospital (€ 6,158 [5,492; 6,824]), representing 62% of the total direct cost, followed by the cost of paramedical care (€ 1,933 [1,816; 2,050]), to the pharmaceutical treatment in retail pharmacies (€ 725 [671; 779]), to the ambulatory medicine (€ 595 [553; 637]), and finally to the care in private hospital (€ 238 [177; 299]).

Table 2. Direct costs of cares according to the origin of the cost (in Euros)

* It includes consultations and cares provided by general practitioners or specialists, surgical procedures in private practice, ophthalmological and hearing devices, dental cares, biological analyses, radiology examinations (radiology, scanners, MRI, PET, echography, bone densitometry), vaccinations, home dialysis, at-home hospitalizations, and SPA treatments; † It includes nursing, physiotherapy, speech therapy, orthoptist.

 

Unadjusted associations between patient characteristics and the mean total cost of cares

The mean total cost was significantly higher with increasing age (p<0.0001), whereas no difference was found between genders (p=0.53; Table 3). The mean total cost was significantly higher when the educational level was lower (p<0.0001) e.g. € 10,782 [9,850; 11,714] for patients with primary educational level vs. € 6,938 [5,909; 7,967] for patients with tertiary educational level. The mean total cost was also significantly associated with the marital status (p<0.0001) and it was higher for patients with diabetes mellitus (€ 12,042 [10,580; 13,505], p<0.0001) or anxiety disorders (€ 12,557 [11,388; 13,725], p<0.0001) compared to those without (€ 9,491 [8,963; 10,018] and € 8,844 [8,314; 9,375] respectively). The mean total cost was higher when the number of drugs increased (p<0.0001). The mean total cost varied depending on the diagnosis etiology (p<0.0001): € 10,444 [9,444; 11,444] for patients with AD, while it was the highest for patients with Parkinson’s disease (€ 21,155 [11,443; 30,866]) and Lewy body disease (€ 20,433 [11,913; 28,951]). The mean total cost increased with the diagnosis severity (p<0.0001): the mean total cost was € 7,897 [7,142; 8,651] for patients with subjective cognitive complaint, € 9,600 for patients with MCI [8,714; 10,487], and € 11,505 [10,614; 12,396] for patients with dementia. The mean total cost was higher when the cognitive performance was lower (based on the MMSE score, p<0.0001); a one-point decrease of the MMSE score was associated with an increase cost of € 288 [170; 408]. The mean total cost was higher when the functional autonomy level was lower (based on the IADL score, p<0.0001), and a one-point decrease of the IADL score was associated with an increase cost of € 1,359 [1,069; 1,648]. The mean total was higher when the behavioral disturbances were higher (based on the NPI score, p=0.0001).

Table 3. Unadjusted relationships between patient’s characteristics and costs of care (in Euros) (n=2,746)

* Generalized linear model with log-normal link and gamma distribution; † Time to death was the number of months from the first visit to the memory center until either the occurrence of the death or the last time the patient was known to be alive; IADL: Instrumental Activities of Daily Living; MMSE: Mini-Mental State Examination; NPI: Neuropsychiatric Inventory

 

Adjusted associations between patient characteristics and the mean total cost of care

When all the variables that were significantly associated with the mean total cost in the unadjusted models were modeled together, all the variables still contributed significantly to the model, and the adjusted mean total cost was 13,057 [10,957; 15,168] per patient (Table 4). More precisely, the IADL score was negatively correlated to the mean cost, and a one-point decrease in the IADL score corresponded to an increase of the cost of € 1,211 [890; 1,532], after adjustment for age, educational level, diabetes mellitus, anxiety disorders, number of drugs, marital status, diagnosis etiology, time to death variable and MMSE score (Figure 1).

Figure 1. Adjusted means* of medical costs according to the IADL score

*Adjusted for age, educational level, diabetes mellitus, anxiety disorders, number of drugs, marital status, diagnosis etiology, MMSE score and time to death; IADL: Instrumental Activities of Daily Living

Table 4. Adjusted relationships between patient’s characteristics and costs of care (in Euros)

* Model 1: Generalized linear model (GLM) with log-normal link and gamma distribution including age, educational level, marital status, diabetes mellitus, anxiety disorders, number of drugs, etiology, time to death, IADL score and MMSE score tertiles; † Model 2: GLM with log-normal link and gamma distribution including the variables of the model 1, and NPI score and mini-Zarit score tertiles; IADL: Instrumental Activities of Daily Living; MMSE: Mini-Mental State Examination; NPI: Neuropsychiatric Inventory

 

In the sub-group of patients with AD (n=758), the adjusted mean total cost was 11,421 [9,982; 12,859]; a higher age (p=0.002), the presence of hypercholesterolemia (p=0.045), the presence of anxiety disorders (p<0.0001), a higher number of drugs (p<0.0001), and a lower IADL score (p<0.0001) were independently associated with higher costs of care (Supplement Table 1). The multivariate model found higher costs for patients with a MMSE score between 13 and 18 (€ 11,918 [9,687; 14,149]) compared to patients with lower and higher MMSE score: € 7,913 [6,425; 9,401] (MMSE≤13), and € 8,400 [7,165; 9,636] (MMSE>18). When including the NPI score and the mini-Zarit score tertiles in the model (Model 2), higher behavioral disorders (p=0.003) and higher caregiver burden (p<0.0001) were significantly associated with higher cost of cares. For patients with AD, the IADL score was negatively correlated to the mean cost, and a one-point decrease in the IADL score corresponded to a cost increase of € 1,096 [372; 1,820], after adjustment for age, number of drugs, time to death variable, anxiety, hypercholesterolemia, and MMSE score (Supplement Figure 1).

Sensitivity analysis

Among the 2,746 patients included in the present study, 88 were identified as having outlier costs (Supplementary Table 2). These patients were characterized by a slightly older age (81.9 ± 7.5 years vs. 79.9 ± 7.9 years, p=0.02), a higher number of drugs (13.4 ± 5.8 vs. 11 ± 5.5, p<0.0001), a worse functional impairment (IADL≤3 in 69.4% vs. 40.8% patients, p<0.0001), a lower MMSE score (MMSE≤17 in 52.3 vs. 33.1% patients, p<0.0001) compared to the group of patients without outlier costs. Among these patients, the proportion of dementia was higher (56.8% vs. 41.9% patients, p=0.02). Caregiver burden was higher in the group with outliers compared to the group without (Mini-Zarit>4: 43.1% vs. 29.4%). The multivariate model without outliers found similar associations between characteristics and total costs (Supplementary Table 3) as obtained with the complete set of patient data, excepted for the educational level and the diabetes mellitus for which the statistical significance was not reached anymore.

 

Discussion

The present study provides an estimation of real medical and non-medical (transportation) direct costs of cares occurring during one year after the first memory center visit, for a large sample of outpatients at all stages of cognitive impairment, from the perspective of the main health insurance: annual medical direct cost of € 9,885 per patient varying from € 7,897 in patients cognitively normal but with subjective cognitive complaint, to € 9,600 in patients with MCI and € 11,505 in patients with dementia. The main part of direct costs of cares in our study was related to cares provided in public hospitals. Also, higher direct costs were independently associated with functional, cognitive and behavioral impairments, diabetes mellitus, anxiety disorders, higher number of drugs as well as with higher caregiver burden. The costs also varied across NCD etiologies, in particular they were higher in patients with Parkinson’s disease, and Lewy body disease compared to patients with AD. The associations between higher direct costs and functional, cognitive and behavioral impairments, anxiety disorders, number of drugs as well as with higher caregiver burden remained significant in the sub-group of patients with AD and in the sensitivity analyses restricted to individuals for whom the cost was not considered as outlier.
These results are consistent with the study of Leibson et al. conducted in a US population-based sample, showing that 70% of the direct costs of care was related to public hospitals cares, and which found an annual medical direct cost at $ 11,678 for patients with prevalent dementia, $ 9,431 for patients with newly discovered dementia, $ 6,784 for patients with MCI, and $ 6,042 for patients considered as cognitively normal (11). Besides, one can note that these results are surprisingly close in terms of level of costs, given than healthcare systems differ between countries.
The present study also confirmed and extended findings of others studies conducted in different contexts and from different economic perspectives, showing that the functional abilities was a main cost driver (2, 9, 20, 25, 40-42). In Zhu et al., a decrease of one-point in functional capacities measured with the Blessed Dementia Rating Scale (score out of 22) was associated with an increase of $ 1,406 in medical direct costs among community-dwelling patients with probable AD (15), whereas a decrease of one-point in functional capacities measured with the IADL scale (score out of 8) was associated with an increase of € 1,096 for one-point decrease of IADL in the sub-group of AD patients in the present study.
In the present study, direct medical costs were higher in patients with Lewy body disease or Parkinson’s disease compared to others NCD etiologies such as AD. While sample sizes in these sub-groups were limited, this observation is sustained by previous studies showing that Lewy body dementia was the costliest compared to others dementia’s etiologies (43), explained in part by cost of cares related to falls, urinary incontinence or infection, depression, anxiety, dehydration, and delirium. Another study also showed that Parkinson’s disease was associated with higher direct health care cost per patient compared to dementia without providing possible explanations (3).
Additional evidences of the association between costs and the MMSE were provided herein, in accordance with others studies (12, 25). However, in the study of Lindholm et al., the MMSE was not associated with the costs after adjustment for functional abilities (40). In the latter study, the characteristics of the population (community-dwelling population-based with a mean MMSE score of 26.6 ± 6) differed from the characteristics of the population studied here (patients of a memory center with a mean MMSE score of 19.7 ± 7), and the sample size was smaller, which may partially explain this discrepancy. Interestingly, in adjusted models, higher direct costs were found in patients with a MMSE score in the second tertile in the whole population study as well as in the AD sub-group (i.e. 13-18), whereas costs were lower in patients with lower or higher MMSE. In particular, patients with a MMSE score at 13-18 were found to have higher costs related to hospital stays for surgery and geriatric cares, higher costs for ambulatory cares in linked with visits to physicians, hearing device, radiology, and laboratory evaluations, and higher costs linked with medical transportation compared to patients with lower or higher MMSE score (detailed results not shown). A possible explanation for this finding is that patients at a more advanced stage of NCD may undergo less elective surgery due to higher risks of complications and higher mortality rates following surgical procedures in patients with dementia (44), and they might have lower health care consumption since the diagnosis has been previously made and less exploratory examinations are needed.
Similarly, higher direct costs were significantly associated with behavioral disorders in accordance with some studies (20, 21), but not all (23, 45). The use of reimbursement data from claims database in the present study instead of self-report use of care reinforces the objectivity of the analysis and strengthens the conclusion that behavioral disorders are associated with a significant increase of cost independently of other patient characteristics.
Also, higher costs were associated with higher caregiver burden, as observed in a previous study conducted from a societal point of view (23). Since the association remained significant after adjustment for others characteristics, we hypothesize that higher costs could directly contribute to the higher burden carried by the informal caregiver, independently of the patients’ impairments. This hypothesis is supported by a previous study showing an association between the financial stress and the higher caregiver burden (46). Even though the costs were estimated from the perspective of the national health insurance in the present study, the insurance may not cover the entire cost borne by patients and their caregivers. Nevertheless, further evidences are needed to confirm this hypothesis.
An original result of the present study was that among the comorbidities considered in the present study, diabetes mellitus and anxiety disorders were independently related to higher costs, while hypertension and hypercholesterolemia were not in the whole sample. In patients with AD, diabetes mellitus was not associated with costs, whereas a slight association was observed with hypercholesterolemia. The results are controversial in the literature concerning the link between comorbidities and costs in patients with NCD, e.g. Jutkowitz et al did not find significant link between comorbidities and costs (42), whereas Hill et al did (47).

Strengths and limits of the study

The present study included a large sample of outpatients attending a memory center with matched patient clinical data and costs. Real costs of care were estimated from claims database from the PHIF that is the main insurance in France and covers 90% of the French population (28), this limited the introduction of selection biases in the population other than the ones considered for the study. The study included patients at all stages of cognitive impairment, which allowed to conduct study between stage groups and to have a global overview of the medical direct costs (plus the medical transport) of patients visiting a memory center. According to a previous study based on the French National Alzheimer Database (48), 118,776 patients with AD attended a memory center in 2010, based on the results of the present study, the total direct cost covered by the PHIF for patients with AD one year after the first visit would be estimated to €370,337,356.
Limitations should nevertheless be considered when interpreting the results herein. This study had a cross-sectional design which does not allow causal relationships between the associations to be determined. The study did not include the societal perspective: this cost analysis did not include the indirect costs (e.g. indirect consequences of the disease such as lost work productivity or earning and informal costs), and the others nonmedical direct costs (e.g expenditures linked with the disease but not associated with medical services such as home services, nonmedical transport), except medical transportation, which led to an underestimation of the costs related to NCD, nevertheless it was specified that this study is not a cost-of-illness study. Previous studies have shown that a major part of the cost related to patients with cognitive impairment was supported by informal caregivers (informal care costs), especially when the patients were living at home, and costs estimation required specific surveys, often based on self-reported caregiving time allowed to patient and an extrapolation of the caregiver’s loss of earnings (21). In addition, the interpretation of these results should take into account the fact that a part of the direct medical costs can also be covered by private insurance that the patients can contract, the present study is from the point of view of the main French public health insurance. This study should also be interpreted in regards of the setting since all patients with cognitive impairment are not managed in memory centers and a part are followed by community practitioners, the care and then the costs may differ. Finally, mean costs should be interpreted with caution as the distribution of costs was skewed, nevertheless the statistical models took into account this data distribution.

 

Conclusion

This large study showed that functional and cognitive impairment, behavioral disorders, caregiver burden, diabetes mellitus, anxiety disorders, and the number of drugs were independently associated with higher direct cost of care for patients attending a memory center, from the payer perspective (French health insurance). The identification of these factors associated to higher direct costs of care offers additional direct targets to evaluate how interventions conducted in patients with NCD impact direct costs of care. Further researches are needed to broaden the economic perspective to the societal one and verify whether societal costs remain driven by the same factors.

 

Funding: The MEMORA study has received funding supports from MSD Avenir Fund, and Biogen Inc. These sponsors enabled the funding of nurses to carry out the research and questionnaires; they had no role in the design, conduct, collection, analysis and interpretation of the data, as well as in the preparation of the manuscript, its review and approval.

Acknowledgements: We thank Mrs. Pascale Gauthier-Robino and Mr. Laurent Colas from the Primary Health Insurance Fund of the Rhône (CPAM Rhône, France) for their collaboration during this research, Dr Michele Potasham for her advice, Mrs. Hélène Boyer (Direction de la Recherche Clinique et Innovation, Hospices Civils de Lyon, Lyon, France) for her help in the manuscript preparation and Mrs. Sarah Achi for her help in data management. We are grateful to the participants and the hospital staff.

Conflict of interest: The authors declare that they have no competing interests.

Study registration: ClinicalTrials.gov Identifier: NCT02302482. Registered: 27th November 2014, https://clinicaltrials.gov/ct2/show/NCT02302482.

Ethical standards: Written information regarding collection of individual data was provided to the patients and their informal caregivers and they were given the possibility to decline participation. This research conducted in routine care was considered as non-interventional by the local ethics committee CPP Lyon Sud-Est IV (Comité de Protection des Personnes / committee for the protection of people). Authorization for handling these data has been granted by the French Data Protection Authority (CNIL: Commission Nationale de l’Informatique et Libertés).

 
Supplementary Material
 

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DEPENDENCE LEVELS AS INTERIM CLINICAL MILESTONES ALONG THE CONTINUUM OF ALZHEIMER’S DISEASE: 18-MONTH RESULTS FROM THE GERAS OBSERVATIONAL STUDY

 

K. Kahle-Wrobleski1, J.S. Andrews1, M. Belger2, W. Ye1, S. Gauthier3, D.M. Rentz4, D. Galasko5

 

1. Eli Lilly and Company, Indianapolis, IN, USA; 2. Lilly Research Centre, Windlesham, UK; 3. McGill Center for Studies in Aging, Douglas Mental Health Research Institute, Montreal, QC, Canada; 4. Harvard Medical School, Boston, MA, USA; 5. University of California San Diego, San Diego, CA, USA

Corresponding Author: Kristin Kahle-Wrobleski, PhD, Global Patient Outcomes and Real World Evidence, Eli Lilly and Company, Lilly Corporate Center, Indianapolis IN 46285, USA, Phone: 317-651-9881, Fax: 317-276-5791, Email: wrobleski_kristin_kahle@lilly.com

J Prev Alz Dis 2017;4(2):72-80
Published online January 24, 2017, http://dx.doi.org/10.14283/jpad.2017.2


 

Abstract

Background: While functional loss forms part of the current diagnostic criteria used to identify dementia due to Alzheimer’s disease, the gradual and progressive nature of the disease makes it difficult to recognize clinically relevant signposts that could be helpful in making treatment and management decisions. Having previously observed a significant relationship between stages of functional dependence (the level of assistance patients require consequent to Alzheimer’s disease deficits, derived from the Alzheimer’s Disease Cooperative Study – Activities of Daily Living Scale) and cognitive severity, we investigated whether measures of functional dependence could be utilized to identify clinical milestones of Alzheimer’s disease progression.
OBJECTIVES: To describe the patterns of change in dependence over the course of 18 months in groups stratified according to cognitive Alzheimer’s disease dementia severity (determined using the Mini-Mental State Examination score) and to identify characteristics associated with patients showing worsening dependence (progressors) versus those showing no change or improvement (non-progressors).
DESIGN: Analysis of longitudinal data from the GERAS study.
SETTING: GERAS is an 18-month prospective, multicenter, naturalistic, observational cohort study reflecting the routine care of patients with Alzheimer’s disease in France, Germany, and the United Kingdom.
PARTICIPANTS: 1495 community-living patients, aged ≥55 years, diagnosed with probable Alzheimer’s disease dementia, and their caregivers.
MEASUREMENTS: Dependence levels, cognitive function, behavioral symptoms, caregiver burden, and cost were assessed at baseline and at 18 months.
RESULTS: Of 971 patients having both baseline and 18-month data, 42% (408) were progressors and 563 (58%) were non-progressors. This general pattern held for all three levels of baseline Alzheimer’s disease dementia severity – mild (Mini-Mental State Examination score 21–26), moderate (15–20) or moderately severe/severe (<15) – with 40–45% of each group identified as progressors and 55–60% as non-progressors. No baseline differences were seen between progressors and non-progressors in cognitive scores or behavioral symptoms, although progressors had significantly shorter times since diagnosis and showed milder functional impairment. Baseline factors predictive of increasing dependence over 18 months included more severe cognitive impairment, living with others, and having multiple caregivers. A higher level of initial dependence was associated with less risk of dependence progression. Total societal costs of care also increased with greater dependence.
CONCLUSIONS: In this large cohort, 42% of Alzheimer’s disease dementia patients at all levels of cognitive severity became more dependent within 18 months of observation while 58% did not progress. Dependence levels may be considered as meaningful interim clinical milestones that reflect Alzheimer’s disease-related functional deficits, although a time frame that extends beyond 18 months may be necessary to observe changes if used in clinical trials or other longitudinal studies. Recognition of predictors of greater dependence offers opportunities for intervention.

Key words: Alzheimer disease, dependence, observational study, ADCS-ADL, GERAS.


 

Introduction

The core clinical criteria for making a diagnosis of dementia due to Alzheimer’s disease (AD) include declines in memory and other cognitive abilities, impairments in activities of daily living (ADL) and global functioning, as well as uncharacteristic changes in behavior or personality (1). As AD is a progressive and chronic illness, it is challenging to characterize clinically significant and discrete milestones of disease progression (2, 3). Nevertheless, defining some clinically relevant AD milestones may be useful to physicians, caregivers, and healthcare systems, as well as patients themselves, in making appropriate and timely treatment and management decisions.
Functional loss forms part of the current diagnostic criteria used to identify dementia due to AD (1); however, it is defined with less granularity than cognition, which includes standard domains such as memory and language (4). Yet, accurate measurement of functional loss can help determine the type, level, and costs associated with current and future care of a patient with AD dementia. Measures of meaningful clinical change in clinical trials of AD dementia have not been well established (5); hence, both the European Medicines Agency and the US Food and Drug Administration recommend that changes in cognition as well as function are needed for approval of a treatment for cognitive symptoms in AD dementia.
A variety of scales, developed to assess function in patients with AD dementia, have been incorporated into clinical trials and observational studies seeking to evaluate the impact of treatments or interventions. They include the Functional Activities Questionnaire; Disability Assessment for Dementia scale; Lawton scale; Global Deterioration Scale/Functional Assessment Staging system; Clinical Dementia Rating scale; Blessed Dementia Rating Scale; Amsterdam IADL (Instrumental Activities of Daily Living) Questionnaire; and the Alzheimer’s Disease Cooperative Study – Activities of Daily Living Scale (ADCS-ADL).
Assessing dependence, which refers to the level of assistance a patient requires due to AD dementia-related deficits, is an alternative, pragmatic approach to monitoring AD progression. As patients become more dependent, they face increased need for home assistance or possible institutionalization (or equivalent institutional care), along with higher healthcare, informal-care, and total-care costs (6–9). Increased dependence is accompanied by changes in family dynamics, and raises ethical and legal issues regarding financial and healthcare decision-making and guardianship (10). Dependence is thought to be influenced by – but different from – cognition, functioning, or behavior (6, 11, 12). It has been described as a distinct measurable component of dementia and an important determinant of AD-related disability (13). In the DADE Study, Jones et al. (8) observed significant associations between dependence, assessed by the Dependence Scale (DS) (13), and service use cost, patient quality of life (QoL), and caregiver perceived burden. They also suggested that, as a construct, dependence could be used to reflect the combined effects of cognitive functional, and behavioral changes seen in AD dementia into a more easily interpretable form.
Our previous work, a cross-sectional analysis of baseline data from the GERAS study (14), showed that dependence levels can be adapted from functional scales (15). Our results showed a significant relationship between assigned levels of dependence, derived from the ADCS-ADL score, and cognitive severity category in a large cohort of AD dementia patients receiving routine care. Importantly, with a greater assigned level of dependence, clinical and economic indicators showed a pattern of greater disease severity and higher costs. This work provided initial support for the use of dependence levels as appropriate interim clinical milestones that characterize the functional deficits associated with AD dementia. Our goal is to develop a system that can be used to stage disease progression in patients with AD dementia that is informative to both care providers and stakeholders, and that can also be used as a common metric in clinical trials or other research studies.
This report from the current longitudinal phase of the GERAS study expands the above-mentioned analysis with data from 18 months of evaluation. The objectives were to describe patterns of change in dependence within an 18-month period in groups stratified according to baseline cognitive AD dementia severity, to examine the correlation between dependence level and other outcome measures, and to identify characteristics that differentiated patients with AD dementia who showed worsening dependence (progressors) from those who showed no change or improved (non-progressors).

 

Methods

GERAS Study Design and Participants

The GERAS study was an 18-month, prospective, multicenter, naturalistic, observational, cohort study, which reflected the routine care of patients with AD dementia in France, Germany, and the United Kingdom (UK). The study was extended by a further 18-month follow-up period in France and Germany. The study design, methods, and baseline patient characteristics were previously described (14, 15). Patients were enrolled from October 2010 until September 2011. Patients and their caregivers were evaluated at baseline and during three care visits at 6-month intervals as part of their routine care. The study centers involved were mostly specialist secondary care clinics (“memory clinics”).
Briefly, patients were community-dwellers aged ≥55 years with probable AD dementia (National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer’s Disease and Related Disorders Association [NINCDS-ADRDA] criteria) (16), a Mini-Mental State Examination (MMSE) score of ≤26 (17), and who presented within the normal course of care. Those with other potential causes of dementia were excluded from the study.
Each patient was also required to have a primary caregiver who agreed to participate in the study and to undertake responsibility for the patient for at least 6 months of the year. All patients (or their legal representatives) and caregivers gave written informed consent before entering the study, which was approved by ethical review boards in each country according to country-specific regulations.

Patient and Caregiver Data

Patients were stratified according to AD dementia severity, based in part on National Institute for Health and Care Excellence (NICE) guidance 217 (18), as having mild (MMSE score 21–26), moderate (15–20) or moderately severe/severe (<15) AD dementia. The study aimed to achieve approximately equal numbers of patients in the three AD dementia severity groups within each country. Functional ability was assessed using the caregiver-rated ADCS-ADL (19), with basic (BADL) and instrumental (complex) (IADL) sub-scales. Cognitive function was evaluated using the MMSE (17) in patients with mild or moderate AD dementia. The proxy version of the EuroQol-5 Dimension (EQ-5D) was used to obtain information from caregivers regarding patients’ health status (20). Behavioral symptoms were evaluated using the 12-item Neuropsychiatric Inventory (NPI-12) (21). Direct and indirect patient and caregiver resource use was measured using the Research Utilization in Dementia Scale (RUD) (22). To evaluate the impact on caregivers, total caregiver time and caregiver supervision time from the RUD were measured, as well as caregiver burden using the Zarit Burden Interview (ZBI) (23). Data were generally collected at baseline, 6, 12 and 18 months, although ADCS-ADL and EQ-5D data were measured only at baseline and 18 months.

Cost Estimations

For each country, monthly cost values were estimated by applying unit costs of services and products (2010 values) to the health and social care resource use data collected over the 18-month follow-up period. For resource use items, full details of the unit costs applied and their sources for each country have already been reported (14). All UK costs in pounds sterling (£) were converted to Euros (€) using the conversion rate £1=€1.1661, calculated as the average monthly exchange rate for 2010.
In this analysis, we looked at direct medical costs and total societal costs. Total societal costs were calculated by adding patient healthcare costs (including medications, hospitalizations, and outpatient visits), patient social care costs (including community care services, structural adaptations to the home, and extra financial support), and caregiver informal care costs (excluding caregiver direct healthcare costs).
Caregiver time, calculated as the number of hours for BADL and IADL, was capped at 24 hours/day; supervision time was excluded from cost calculations. The unit costs of caregiver time for working caregivers was the value of lost production time based on the national average wage per country population; for non-working caregivers, it was the value of lost leisure time based on 35% of the national average wage per country population.
The following imputation rules were applied for missing data: for institutionalized patients, mean monthly costs from the last visit were used for the period until institutionalization, then monthly costs of institutionalization were used from institutionalization up to 18 months; for patients who died, last observation carried forward (LOCF) was used such that costs from the last known visit were extrapolated up to the date of death (no costs after death were computed); for patients lost to follow-up, multiple imputation stratified by MMSE group and country was performed on missing costs. The factors used in the multiple imputation procedure were selected from those recently identified by Dodel et al. (24).

Categorizing Dependence Levels

Exploratory factor analysis of ADCS-ADL data was conducted in order to create subscales to aid the construction of dependence levels (4), details of which were described in our earlier analysis (15). In brief, baseline data suggested a 4-factor solution that included subdomains for specific competencies, including BADLs (eating, walking, toileting, bathing, grooming and dressing), domestic/household activities (choosing clothes, using the telephone, clearing the dishes, finding belongings, cooking, putting out the rubbish, using appliances), communication/engagement with the environment (watching television, paying attention to conversation, keeping appointments, talking about current events, reading, writing, performing hobbies), and outdoor activities (going out, shopping, paying, being left alone) (15).
The DS includes a scheme to derive levels of dependence based on the ability to perform ADLs (13), such as those represented within the ADCS-ADL (19). In an earlier study, we described six theory-driven assigned levels of dependence beginning with Level 0 (no care needed and completely independent), with dependence increasing incrementally over levels 1 through 5, which represents complete dependence, such as the needs of someone living in a nursing home (15). In the present analysis, the level of functional dependence, calculated from the ADCS-ADL, was determined for each patient at baseline and at 18 months.
A functional progressor was defined as someone whose change in functional dependence from baseline to the 18-month follow-up increased by 1 or more levels, while a non-progressor showed either no change or a decrease in 1 or more dependence levels.

Statistical Analysis

All patients and associated caregivers who provided informed consent and fulfilled the study entry criteria were included in the present analysis. All calculations were based on non-missing observations. Since dependence levels were derived from the ADCS-ADL, this analysis was limited to patients with ADCS-ADL data collected at baseline and at 18 months. Descriptive statistics (mean and standard deviation [SD] or frequency) for two groups (those for whom dependence level improved or did not change [non-progressors] and those for whom dependence level worsened [progressors]) were used to summarize baseline continuous variables (time since diagnosis, age, patient education, MMSE, ADL [total, basic, and instrumental] scores, and NPI total score and subscores) and categorical variables (gender, country, marital status, patient lives alone, any AD treatment, patient has falls, dependence level, and AD severity).
The distribution of patients at each level of dependence at baseline and 18 months for the overall patient sample and also according to cognitive severity at baseline were described. The percentage of patients with worsening dependence levels was also calculated.
Correlations between dependence levels and certain key outcome variables at baseline and at 18 months were examined using Pearson correlation coefficients. Generalized Linear Models (GLMs) with normal distribution and identity link function were used to examine whether changes in dependence level could predict changes in outcomes measures. The outcome measures were selected to reflect a range of outcomes that we expected would be related to level of dependence, including cognition (MMSE), caregiver burden (ZBI), overall caregiver time, NPI-12 total scores, patient-reported QoL (EQ-5D), patient direct medical costs, and total societal costs. GLMs were controlled for the core list of patient baseline characteristics (outcome measures, country, age, gender, cognitive severity, number of comorbidities, and total ADCS-ADL scores) and caregiver baseline characteristics (age, caregiver spouse [yes/no], and caregiver works for pay [yes/no]). In these models, changes in dependence levels and other outcome measures were considered as continuous variables to facilitate interpretation of the findings.
A stepwise logistic regression analysis was applied to the data to identify factors associated with patient progression versus non-progression. Baseline factors considered included: patient and caregiver age, gender, and country; patient cognitive MMSE severity (mild, moderate, moderately severe/severe), level of dependence, time since AD diagnosis, and NPI-12 scores (total and subdomains); indicator variables related to the patient (marital status, education, lives alone, comorbidities, receipt of AD medication, history of falling) and caregiver (lives with patient, is patient’s spouse, works for pay); number of caregivers other than the primary caregiver; NPI-12 caregiver distress score; and ZBI scores. ADCS-ADL scores were not included as the baseline dependence levels included in the model were calculated using these scores.
All data were analyzed using SAS software, version 9.2 (SAS Institute, Cary, North Carolina, USA).

 

Results

Overall, 1532 patients and their primary caregivers were enrolled by 94 investigators. After excluding 35 patients who did not fulfill the study entry criteria and 2 patients following the baseline database lock, 1497 patients with probable AD dementia and caregivers (14) were included in the baseline analyses. Of these, 971 had both baseline and 18-month ADCS-ADL data. In the current analysis, 563/971 (57.98%) patients showed no change (479/971, 49.33%) or improvement (84/971, 8.65%) in dependence levels over 18 months (non-progressors) while 408/971 (42.02%) exhibited worsening of dependence levels (progressors).

Descriptive Statistics

A summary of baseline characteristics of patients and caregivers for progressors versus non-progressors is shown in Table 1. Full baseline statistics were previously reported (14, 15).
Non-progressors and progressors were similar in age, gender, years of education and marital status as well as caregiver characteristics. Most patients were married or lived with another person. Progressors had significantly shorter times since diagnosis than non-progressors (p=0.0096) and showed milder functional impairment at baseline, as indicated by total ADL (p=0.0002), BADL (p<0.0001), and IADL (p=0.0046) scores.
No differences were seen between progressors and non-progressors in cognitive (MMSE) scores or behavioral symptoms, as assessed by NPI-12 total scores or subscores. When patients were categorized according to AD dementia severity, the progressor and non-progressor groups contained approximately the same proportions of those with mild, moderate, and moderately severe/severe disease. Most patients in both groups had received treatment for AD dementia. No difference was observed between groups in the tendency to fall.
Some significant differences in dependence levels between groups were apparent at baseline (all p<0.0001). Progressors included more patients at lower dependence levels than non-progressors (e.g., 51.72% vs. 27.10% at dependence levels 0–2) and fewer at higher dependence levels (18.63% vs. 49.20% at levels 4–5, respectively).

Table 1. Mean baseline demographics (SD) for dependence non-progressors and progressors

Table 1. Mean baseline demographics (SD) for dependence non-progressors and progressors

Abbreviations: AD, Alzheimer’s Disease; ADL, activities of daily living; BADL, basic ADL; IADL, instrumental ADL; MMSE, Mini-Mental State Examination; NPI, Neuropsychiatric Inventory; SD, standard deviation. *Alzheimer’s Disease dementia severity based on MMSE scores: mild (21-26), moderate (15–20) and moderately severe/severe (<15).

 

Dependence Levels

Dependence level distributions for the entire cohort at baseline and 18 months are shown in Figure 1. Compared with baseline, at 18 months fewer patients in the overall patient sample were categorized as level 2 (requiring the equivalent of limited or informal home care services) and, correspondingly, more patients were found to require care equivalent to that provided by assisted living plus nursing support or placement into a nursing home (levels 4 and 5). A small proportion of patients at both time points showed either no impairments (level 0) or little impairment (level 1).

Figure 1. Dependence levels distribution at baseline and 18 months (entire cohort)

Figure 1. Dependence levels distribution at baseline and 18 months (entire cohort)

Patients with AD dementia (as determined by baseline MMSE cognitive scale) were assigned to one of six derived dependence levels, based on functional ability using the Alzheimer’s Disease Cooperative Study Activities of Daily Living Inventory (ADCS-ADL), at baseline and 18 months. The dependence levels were: level 0, no care needs; level 1, independent living with check-ins; level 2, care equivalent to limited or informal home care services; level 3, care equivalent to extensive home care with supervision or assisted living; level 4, care equivalent to that provided by assisted living plus nursing support; and level 5, care equivalent to a nursing home. Lower levels of dependence indicate better function.

Figure 2 illustrates the distribution of dependence levels according to AD dementia severity at baseline and at 18 months. The results demonstrate that both at baseline and after 18 months, patients with AD dementia at all levels of cognitive impairment had a range of dependence levels, although the distribution of patients at each dependence level differed according to severity group.

 

Figure 2. Dependence level distributions according to AD dementia severity at baseline and 18 months

Figure 2. Dependence level distributions according to AD dementia severity at baseline and 18 months

Patients were stratified according to disease severity by baseline cognitive function using the Mini-Mental State Examination (MMSE) as having mild (26–21), moderate (20–15) or moderately severe/severe (≤14) AD dementia. Patients with AD dementia were then assigned to one of six derived dependence levels, based on functional ability assessed using the Alzheimer’s Disease Cooperative Study Activities of Daily Living Inventory (ADCS-ADL) at baseline and again at 18 months. The dependence levels were: level 0, no care needs; level 1, independent living with check-ins; level 2, care equivalent to limited or informal home care services; level 3, care equivalent to extensive home care with supervision or assisted living; level 4, care equivalent to that provided by assisted living plus nursing support; and level 5, care equivalent to a nursing home. Note that no patients were determined to be at dependence level 0 or level 1 in the moderate AD group at 18 months or the moderately severe/severe group at baseline and at 18 months.

 

At baseline, 49.64% of those diagnosed with mild AD dementia required the equivalent of limited or informal home care services (dependence level 2), whereas 42.69% required at least the equivalent of extensive home care services with supervision or assisted living plus nursing support (levels 3–4). Less than 7% (6.72%) of patients with mild AD required no or little assistance (level 0 or 1) and 0.96% required the equivalent of nursing home care (level 5).
After 18 months, fewer patients (31.18%) with mild AD dementia showed the equivalent of level 2 dependence compared with baseline, while 58.75% required higher levels of assistance (levels 3–4). Almost 6% (5.76%) required the equivalent of nursing home care.
In those with moderate AD dementia, the proportion of patients requiring the equivalent of assisted living plus nursing support or placement in a nursing home (levels 4 and 5) rose from 34.50% at baseline to 57.51% after 18 months. The majority of those with severe disease needed high levels of assistance at baseline (69.71%), with a greater proportion requiring high levels of assistance at 18 months (86.72%).
The pattern of relative progression versus non-progression in dependence level observed in the overall cohort (42.02% progression/57.98% non-progression) was similar in all groups of AD dementia severity. For those with mild AD dementia (n=417), 39.57% progressed compared with baseline whereas 60.43% did not; corresponding values in the moderate AD dementia (n=313) group were 44.73% and 55.27%. Patients with severe AD dementia (n=241) manifested high levels of dependence at baseline and this pattern became more prominent at 18 months, with 42.74% of patients becoming more functionally dependent and 57.26% not progressing during the 18-month follow-up. Of the 408 progressors, 294 (72.06%) worsened by one level, 98 (24.02%) worsened by two levels and 16 (3.92%) worsened by more than two levels.

Relationship Between Dependence Levels and Other Outcome Measures

In unadjusted correlations using Pearson correlation coefficients, a number of patient clinical outcome measures correlated significantly (all p-values <0.05) with levels of dependence at baseline and at 18 months. These included negative correlations for cognition (MMSE total score) (r=−0.50 at baseline, r=−0.57 at 18 months) and patient QoL (r=−0.37, −0.46, respectively) and a positive correlation for patient neuropsychiatric disturbance (r=0.33, 0.34, respectively). From the caregiver’s perspective, increased dependence correlated with greater caregiver time (r=0.49, 0.44, respectively) and greater overall ZBI burden (r=0.36, 0.30, respectively). Although there was no statistically significant correlation with patient direct medical costs at baseline (r=0.05), dependence was positively correlated with these costs at 18 months (r=0.13), and total societal costs increased with greater dependence (r=0.35, 0.43, respectively).
Table 2 shows the degree to which a change in one dependence level is strongly associated with changes in other clinical and outcome variables. Results of the GLM regression analyses controlling for a core list of covariates for each outcome suggest that positive linear relationships between change in dependence level and change in ZBI, caregiver time, NPI-12 total score, medical costs, and total societal costs, and negative linear relationships between change in dependence level and change in MMSE and EQ-5D are statistically significant.

Table 2. Relationship between change in each outcome measure versus change in dependence levels from GLMs

Table 2. Relationship between change in each outcome measure versus change in dependence levels from GLMs

Abbreviations: AD, Alzheimer’s Disease; ADL, activities of daily living; EQ-5D, EuroQol-5 Dimension; GLM, generalized linear model; MMSE, Mini-Mental State Examination; NPI, Neuropsychiatric Inventory; ZBI, Zarit Burden Interview. Note: Δ = change from baseline to 18 months. The changes in outcomes measures from baseline to 18 months were fitted using GLM models with normal distribution with identity link function. All models were adjusted for the core list of covariates. The model is listed as follows: change in outcome measure = baseline outcome measure + change in dependence level + the core list of covariates. The core list of covariates includes AD dementia severity, country, patient age, patient gender, number of comorbidities, baseline ADL total score, caregiver age, caregiver is spouse (yes/no), and caregiver works for pay (yes/no).

Factors Associated with Progressors versus Non-progressors

Results of the logistic regression analysis shown in Figure 3 suggest that several patient baseline factors were significantly predictive of increasing dependence. They included greater cognitive impairment, such that patients with mild or moderate cognitive impairment were less likely than more severely impaired patients to have progressed a minimum of one dependency level over 18 months. However, having higher initial levels of dependence (e.g., level 2 vs. level 1) was associated with less risk of dependence progression over 18 months, as indicated by an odds ratio of 0.27 (95% CI 0.22, 0.33). Other potential predictors of increasing dependency included the patient living with someone else compared to living alone, and having multiple caregivers. Age, education, gender, other comorbidities, neuropsychiatric symptoms, and elevated caregiver burden were not found to be predictive of dependence progression.

Figure 3. Association between baseline factors and dependence progression in patients with AD dementia

Figure 3. Association between baseline factors and dependence progression in patients with AD dementia

*Note that factors with OR<1 indicate less likelihood of dependence progression, those with OR=1 have no association with dependence progression, and those with OR>1 are predictive of dependence progression.

 

Discussion

Results of this large, observational cohort of patients with AD dementia at different stages of cognitive impairment reveal the heterogeneity of disease progression when it comes to functional abilities. After 18 months, even those with mild AD dementia required varied levels of support, with almost 60% needing the equivalent of extensive home care services with supervision/assisted living/nursing support and almost 6% the equivalent of nursing home care. As would be expected with AD disease progression, a general upward shift in dependence levels was observed over 18 months for all levels of AD dementia severity. However, individual variation was apparent and common. At all three levels of baseline AD dementia severity (mild, moderate and moderately severe/severe), over an 18-month period between 55% and 60% of AD dementia patients manifested no change or an improvement in dependence while 40% to 45% became more dependent.
Identifying early in their disease those AD dementia patients who will manifest functional deficits and require assistance is critical for patients, family members, and healthcare systems. Having identified progressors and non-progressors in our cohort, we then went back to baseline data to examine possible early differentiating factors. Interestingly, no differences were seen between progressors and non-progressors in cognition (MMSE scores) or behavioral symptoms, tendency to fall, whether they were receiving treatment, or caregiver characteristics. With logistic regression we identified baseline factors associated with dependence progression, including greater cognitive impairment, having multiple caregivers, and living with another person. Conversely, having higher initial levels of dependence was associated with less risk of dependence progression. These seemingly contradictory findings may be explained by disease and/or measurement issues. The association between greater cognitive impairment at baseline and higher likelihood of increased dependence is consistent with prior research showing a pattern of cognitive decline preceding functional decline (25). The present analyses are also consistent with the expectation that higher dependence levels should be associated with other indicators of functional impairment, as evidenced by the finding that progressors were more likely to have multiple caregivers or live with another person. However, the categorical nature of dependence levels means that those at higher levels of dependence at baseline may not be as likely to progress due to ceiling effects.
A change of one dependence level can have practical consequences. For example, we estimate that a patient who declines one level in dependence requires 40 more hours of caregiving time per month, and incurs €35.85 per month more in medical costs and €299.57 per month more in total societal costs. Recently, Darba and Kaskens (9) used the DS to evaluate 343 patients with AD dementia in Spain. They found that with each additional 1-point increase in DS, there was a 13.5% increase in direct medical care costs, a 25.3% increase in social care costs, and a 214.7% increase in informal care costs over 6 months. These data highlight the social and economic ramifications of deteriorating independence.
Selecting which outcome(s) to evaluate can be a challenge for an illness with as global an impact as AD dementia. Outcomes of interest reflect the needs and goals of patients, families, caregivers, clinicians, researchers, payers, and healthcare agencies. While cognition is traditionally thought to be the chief variable of interest in AD dementia, and is the hallmark impairment of the disease (26), assessment of functional abilities, behavior, caregiver burden, QoL, resource utilization, and costs also provide worthwhile information, which can be used to stage AD dementia and assess disease impact (27). Once a relevant outcome(s) of interest is chosen, it is then important to select an instrument that will provide valid and meaningful data (27, 28).
Our results support the suggestions of Zhu et al. (6, 29) that dependence is a distinct component of disability in AD dementia, and that assessment of patient function and dependence provides information not available from the MMSE or other cognitive measures. Further, increases in dependence are associated with other indicators of increasing disease severity such as more caregiver time, higher caregiver burden, and higher care costs. The additional association between cognition and dependence suggests that dependence is a useful summary measure of AD severity.
We believe that dependence levels may be considered as interim clinical milestones that reflect AD dementia-related functional deficits and can be a useful metric to monitor disease course. Measuring dependence levels may offer valuable information for tracking, managing, and treating patients with AD dementia. These assessments may be particularly informative when characterizing such patients in the mildest stage of disease, a time when discrete clinical milestones are difficult to ascertain. Whether measurable shifts in dependency can occur within 18 months with enough sensitivity to make it an appropriate 18-month endpoint for phase 3 clinical trials remains to be determined, but this metric may prove to be useful for longer-term trials, trials enriched with a population more likely to progress, or observational studies.

Strengths of the Study

The GERAS study included a large population of patients representative of the AD dementia continuum. The aim of the GERAS study was to address some of the limitations of previous cost studies by using well-established, standardized methods for assessing resource use and caregiver time over a longer follow-up period. The study also provides unique information on the societal costs of AD dementia in community-dwelling patients, both across different severity levels and between countries (14).

Study Limitations

One limitation of GERAS is that the study sample did not include the entire spectrum of functional impairment. Specifically, enrolled patients were required to be community dwelling, thus excluding those who were severely impaired. In addition, patients with cognitive impairment who did not yet show signs of dementia (prodromal AD) were also excluded. This limits the external validity of the results. The frequency of users of AD medications may be overestimated because study centers were mostly specialist clinics (14).
Another limitation is that although about 40% of the patients in the moderately severe/severe group had an MMSE score of <10 (14), the cut-offs used in the GERAS study may bias the moderately severe/severe AD dementia group toward those with less-severe symptoms. Additionally, because observed discontinuation rates tend, in general, to be higher in those with greater cognitive and functional disabilities, dependence progression may have been underestimated in our study, which focused only on completers. Also, differences in patient characteristics between AD dementia severity groups in each country may have confounding effects on resource utilization and associated costs, but these have not been taken into account. Lastly, cultural differences between countries regarding the care of patients with AD dementia, as well as differences in healthcare systems, mean that the resource utilization and cost data from the three countries in the GERAS study (France, Germany, and the UK) may limit the generalizability of the findings (14). It should also be noted that patients were enrolled in GERAS based on NINCDS-ADRDA clinical criteria; however, no biomarker information or genotype status was captured. Further research is warranted to evaluate the power of these factors to predict progression status.

 

Conclusions

Understanding the types of changes that patients with AD dementia undergo can help determine what sorts of milestones may be suitable for clinical use and/or use in clinical trials and observational studies. Our study demonstrated that dependence levels may provide unique information on clinical progression beyond what is captured with a cognitive measure. We have also shown the pragmatic consequences of increasing dependence on patients, caregivers, and costs. Identification of several baseline factors associated with functional deterioration opens up possibilities for early intervention.

 

Funding: This study was supported by Eli Lilly and Company.

Acknowledgments: The authors would like to acknowledge Amy Rothman Schonfeld, Gill Gummer and Caroline Spencer (Rx Communications, Mold, UK) for assistance with the preparation of this article, funded by Eli Lilly and Company. The authors would also like to thank Dr. Yaakov Stern for sharing his insights and expertise during the course of this research.

Disclosures: KK-W, JSA, MB and WY are all employees and minor shareholders of Eli Lilly and Company. SG has received clinical trial support from Eli Lilly and Company, Roche, TauRx and Lundbeck Pharmaceuticals, was a DSMB member for ADCS, ATRI, API and Eisai, was a scientific advisor for AbbVie, Advantage, Alzheon, Axovant, Boehringer-Ingelheim, Firalis, Heptares, IntelGen, Kalgene, Eli Lilly and Company, Lundbeck Pharmaceuticals, Novartis, Otsuka, Servier, Sanofi, Schwabe, Takeda, TauRx, TVM Capital and Roche. DMR has served as a consultant for Eli Lilly and Company, Biogen Idec, Lundbeck Pharmaceuticals, and serves as a member of the Scientific Advisory Board for Neurotrack. DG has received personal fees from Biomed Central, vTv Therapeutics, Janssen Immunotherapy, Prothena Corporation, the Michael J Fox Foundation, and has received grants from California Institute for Regenerative Medicine and the Michael J Fox Foundation.

 

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