Community-Based Physician Attitudes Related to the Diagnosis and Treatment of Early Alzheimer’s Disease in the United States

Abstract

The increasing incidence of Alzheimer’s disease (AD) coupled with emerging diagnostics and treatments underscores the need for early detection of AD, yet identifying these individuals remains challenging. This US study sought to examine community-based physician attitudes regarding diagnosis and treatment of early AD (mild cognitive impairment [MCI] due to AD and mild AD). A total of 177 primary care physicians (PCPs) and 147 neurologists recruited through a national physician panel were surveyed about early AD diagnostic and treatment processes, and self-confidence in identifying and managing the condition. Physicians identified patient and family/caregiver involvement as critical in triggering the diagnostic process. Patterns of use of neurocognitive assessments, structural imaging tests, and AD-specific biomarkers varied between PCPs and neurologists. Confidence diagnosing and managing early AD was a concern across specialties, although was greater among PCPs. Programs promoting awareness of early AD symptoms, and emerging technologies and treatments are critical to timely management.

Keywords

Alzheimer’s disease mild cognitive impairment mild Alzheimer’s disease early Alzheimer’s disease MCI detection neurocognitive assessment

Introduction

Alzheimer’s disease (AD) is a progressive and debilitating neurological disorder that is expected to affect 14 million patients in the United States (US) by 2060.¹ Mild cognitive impairment (MCI) due to AD and mild AD represent the early stages of AD, and have been highlighted as points for intervention,² especially with the introduction of novel therapeutic agents intended to treat AD early in the disease cascade. The diagnosis of AD, particularly during these early stages, is challenging due in part to the non-specificity of symptoms, which may mirror the effects of the normal aging process.³ Receipt of a diagnosis is further limited by the lack of a uniform diagnostic process. In the absence of clearly defined objective criteria, the current diagnostic process for AD considers a combination of clinical assessment and the use of diagnostic tools such as neurocognitive and imaging assessments, biomarker and laboratory tests, or other tools.⁴ However, the use of such tests may vary widely across physicians and may be influenced by various factors, such as physician training, physician preferences, patient characteristics, and patient access to care.⁵

MCI and mild AD are complex conditions that may require collaborative care and specialized management. While referrals to clinical specialists such as geriatricians, neurologists, psychologists, or psychiatrists may provide comprehensive and individualized care to patients with AD, the importance of primary care physicians (PCPs) should not be underestimated, as these providers often serve as the frontline during the initial diagnostic process and may also manage patients throughout AD progression.⁵ PCPs may have longitudinal familiarity with their patients, which could offer a unique lens for assessing cognitive changes. Yet, some studies suggest that while PCPs may recognize cognitive decline, many do not provide timely evaluation or referral to a specialist.⁶ Shortages of specialists coupled with rising demand for early identification and treatment mean that PCPs will likely play an increasingly important role in MCI and mild AD care, including diagnosing, referring, and prescribing treatments.^5,7

The introduction of novel treatment agents for AD that may improve outcomes when started during the earliest symptomatic stages of disease makes a timely diagnosis critical.^8,9 Receipt of care could be further expedited through appropriate triaging of patients based on cognition tools and blood-based biomarkers in the primary care setting.^7,10 In addition, understanding physician’s perspectives about current practices may yield insights to optimize care.¹¹ Therefore, it is important to understand the attitudes and experiences among community-based physicians regarding how early AD is diagnosed and managed and to identify gaps in early AD care across physician specialties. This study sought to describe physician attitudes and experiences in diagnosis and treatment of MCI due to AD and mild AD among community-based PCPs and neurologists in the US.

Methods

Participants and Study Procedures

This cross-sectional study recruited community-based PCPs and neurologists to complete a web-based survey regarding diagnostic and treatment practices of patients with MCI due to AD and mild AD (i.e., early AD) from their perspective. Physicians were recruited from a verified physician panel with broad geographic representation throughout the US. To participate in the study, physicians were required to practice primarily in community-based settings, have at least 3 years of experience diagnosing and managing AD (inclusive of residency), and have seen at least 15 patients with early AD in the previous 12 months. The survey, which was administered in August and September 2023, took approximately 20 minutes to complete.

Data collected included physician demographics, and their use of and familiarity with components of the early AD diagnostic process, including the use of neurocognitive assessments, AD-specific biomarker tests, structural imaging tests, genetic testing for apolipoprotein E4 (APOEε4), referrals, pharmacological treatments, perceived benefits of treatments, and perceived confidence in diagnosing and treating MCI due to AD and mild AD. AD-specific biomarker tests included: amyloid positron emission tomography (PET) scan, cerebrospinal fluid (CSF) tests, blood test for AD pathology, and tau PET scan. Structural imaging tests included: fluorodeoxyglucose PET scan, magnetic resonance imaging (MRI), functional MRI, computerized tomography (CT) scan, and diffusor tension imaging.

This study did not involve interactions with or interventions in human subjects and all data were de-identified per US federal regulations (45 CFR 46, 102(f))20. Thus, it was exempt from institutional review board review, consent requirements, and registration.

Statistical Analyses

Descriptive statistics were used to summarize physician responses to survey questions. Continuous variables were reported using means and standard deviations, and categorical variables were reported using frequencies and percentages. Descriptive statistics were summarized for the overall physician sample and stratified by physician specialty (i.e., PCPs vs neurologists). Comparisons of variables between physician specialties were conducted using Student’s t-tests for continuous variables, and chi-square tests or Fisher’s exact tests (if at least one category had sample size ≤5) for categorical variables. All analyses were performed using SAS Enterprise Guide (version 7.1) and R statistical software (version 4.2.1).

Results

Physician Demographics

A total of 324 physicians completed the survey, including 177 PCPs and 147 neurologists. Physician demographic and practice characteristics are described in Table 1. Physicians were, on average, 51 years old, and predominantly male (73.8%) and White (58.0%). PCPs and neurologists had an average of 19.7 and 17.9 years of experience providing care for patients with MCI due to AD or mild AD, respectively (p=0.06). On average, PCPs reported seeing 100 patients with MCI due to AD, and 95 patients with mild AD in the past year, while neurologists reported seeing 115 patients with MCI due to AD and 123 patients with mild AD (p=0.17 and p<0.05, respectively). Most physicians practiced in urban or suburban locations (89.2%), though PCPs had more rural representation than neurologists (14.1% vs 6.8%; p=0.05). The vast majority of neurologists reported having received training or continuing education on cognitive impairment than PCPs (89.1% vs 80.8%; p=0.06). The most common form of training or education was continuing medical education (CME) credits for both neurologists and PCPs (69.4% overall). Compared to PCPs, neurologists were also more likely to receive training or education through community groups (44.9% vs 26.6%; p<0.001) and fellowships (34.0% vs 13.6%; p<0.001).

Table 1.

Community-Based Physician Demographics Stratified by Provider Type

	Overall	Neurologist	PCP	P-value¹
	N = 324	N = 147	N = 177	P-value¹
Physician inclusion criteria
Number of years providing care for patients with MCI or mild AD				0.06
Mean ± SD	18.9 ± 8.7	17.9 ± 8.9	19.7 ± 8.4
Number of patients seen with MCI in the past year				0.17
Mean ± SD	106.4 ± 99.8	114.7 ± 105.2	99.5 ± 94.8
Number of patients seen with mild AD in the past year				< 0.05*
Mean ± SD	107.5 ± 100.1	122.7 ± 104.8	94.9 ± 94.5
Physician demographics
Physician age² (years)				0.74
Mean ± SD	51.2 ± 10.6	51.0 ± 10.9	51.4 ± 10.3
Physician sex
Male	239 (73.8%)	112 (76.2%)	127 (71.8%)	0.44
Female	68 (21.0%)	25 (17.0%)	43 (24.3%)	0.14
Declined to answer	17 (5.2%)	10 (6.8%)	7 (4.0%)	0.37
Practice location
Urban/suburban	289 (89.2%)	137 (93.2%)	152 (85.9%)	0.05
Rural	35 (10.8%)	10 (6.8%)	25 (14.1%)	0.05
Geographic region
West	92 (28.4%)	49 (33.3%)	43 (24.3%)	0.09
South	90 (27.8%)	35 (23.8%)	55 (31.1%)	0.18
Northeast	73 (22.5%)	35 (23.8%)	38 (21.5%)	0.71
Midwest	62 (19.1%)	21 (14.3%)	41 (23.2%)	0.06
Unknown	7 (2.2%)	7 (4.8%)	0 (0.0%)	< 0.05*
Practice setting
Group	221 (68.2%)	96 (65.3%)	125 (70.6%)	0.37
Solo	57 (17.6%)	23 (15.6%)	34 (19.2%)	0.49
Hospital based	46 (14.2%)	28 (19.0%)	18 (10.2%)	< 0.05*
Race³
White	188 (58.0%)	79 (53.7%)	109 (61.6%)	0.19
Asian	90 (27.8%)	44 (29.9%)	46 (26.0%)	0.51
Black or African American	9 (2.8%)	5 (3.4%)	4 (2.3%)	0.74
American Indian or Alaska Native	1 (0.3%)	0 (0.0%)	1 (0.6%)	1.00
Native Hawaiian or Other Pacific Islander	1 (0.3%)	0 (0.0%)	1 (0.6%)	1.00
Other	7 (2.2%)	3 (2.0%)	4 (2.3%)	1.00
Declined to answer	32 (9.9%)	18 (12.2%)	14 (7.9%)	0.26
Physician ethnicity
Not Hispanic/Latino	278 (85.8%)	118 (80.3%)	160 (90.4%)	< 0.05*
Hispanic/Latino	16 (4.9%)	10 (6.8%)	6 (3.4%)	0.25
Declined to answer	30 (9.3%)	19 (12.9%)	11 (6.2%)	0.06
Continuing education
CME credits	225 (69.4%)	102 (69.4%)	123 (69.5%)	1.00
Professional education through community groups	113 (34.9%)	66 (44.9%)	47 (26.6%)	< 0.001*
Fellowship	74 (22.8%)	50 (34.0%)	24 (13.6%)	< 0.001*
No continuing education	50 (15.4%)	16 (10.9%)	34 (19.2%)	0.06
Other	11 (3.4%)	5 (3.4%)	6 (3.4%)	1.00

Abbreviations: AD: Alzheimer’s Disease; CME: Continuing Medical Education; MCI: Mild Cognitive Impairment; PCP: Primary Care Physician; SD: Standard Deviation.

Notes. [1] T-tests were used to compare means for continuous variables and chi-square or Fisher’s exact tests were used to compare categorical variables. Significance was defined as a p-value of <0.05, denoted with an asterisk (*). [2] Age was calculated for 130 neurologists and 170 PCPs. 17 neurologists and 7 PCPs did not respond to this question. [3] Race categories were not mutually exclusive.

Initial Presentation and Use of Neurocognitive Assessments

Patient-reported memory concerns (45.7%) were cited as the most common reason for triggering a diagnostic evaluation for MCI due to AD, followed by memory complaint raised by a family member or caregiver (21.6%). For mild AD, memory complaint from a family member or caregiver (30.9%) was the most commonly reported reason for triggering a diagnostic evaluation, followed by observed cognitive impairment (19.8%) (Figure 1). The reasons for triggering a diagnostic evaluation of MCI due to AD and mild AD were largely consistent between PCPs and neurologists.

Figure 1.

Top events or symptoms on initial presentation that trigger a diagnostic evaluation for MCI due to AD and mild AD.

Figure 2 shows physicians’ usage of neurocognitive assessments during the diagnostic process. The most commonly used neurocognitive assessments among both PCPs and neurologists in diagnosing MCI due to AD or mild AD were the Mini-Mental State Examination (MMSE) (74.0% vs 66.0%; p=0.15) and the Clock Drawing test (43.5% vs 36.1%; p=0.21). While twice as many neurologists as PCPs reported using the Montreal Cognitive Assessment (MoCA) (46.3% vs 20.9%; p<0.001), more PCPs reported using the Mini-Cog test than neurologists (32.2% vs 14.3%; p<0.001). Approximately 3.4% of all physicians, including 5.1% of PCPs and 1.4% of neurologists, reported that they did not routinely use neurocognitive assessments (p=0.12). The most common reasons for use of neurocognitive assessments were to assess MCI or dementia-specific characteristics (64.8%), and to make a final diagnosis of MCI due to AD or mild AD (50.3%). All physicians were also asked to identify reasons why they may not use a neurocognitive assessment, with 29.6% noting limited time during appointments.

Figure 2.

Use of neurocognitive assessments stratified by provider type.

Use of AD-Specific Biomarker, Structural Imaging, and Genetic Tests

Figure 3 and Table 2 describe physicians’ usage of AD-specific biomarker and structural imaging tests during their diagnostic process. MRI was the most frequently used structural imaging test for both provider types (77.2% overall), though it was used more often by neurologists than PCPs (86.4% vs 69.5%; p<0.001). CT scan was used more often by PCPs than neurologists (33.9% vs 21.1%; p<0.05). Approximately 15.1% of physicians reported they do not routinely use any structural imaging tests. Lower use of structural imaging was reported by PCPs compared to neurologists, with nearly 1 in 5 PCPs reporting they do not routinely use structural imaging tests (19.2% vs 10.2%; p<0.05).

Figure 3.

Use of AD-specific biomarker and structural imaging tests stratified by provider type.

Table 2.

Use of Biomarker, Imaging, and Genetic Tests Stratified by Provider Type

	Overall	Neurologist	PCP	P-value¹
	N = 324	N = 147	N = 177	P-value¹
Top reasons for not using biomarker or imaging tests
Cost or insurance concerns	199 (61.4%)	91 (61.9%)	108 (61.0%)	0.96
Does not provide clinical insight specific to MCI due to AD or mild AD	105 (32.4%)	39 (26.5%)	66 (37.3%)	0.05
Availability of biomarker/imaging appointments	66 (20.4%)	37 (25.2%)	29 (16.4%)	0.07
Amyloid PET scan
Percentage of patients who received an amyloid PET scan				0.34
Mean ± SD	21.5 ± 22.9	23.0 ± 22.5	19.5 ± 23.5
Physician has never had a patient receive an amyloid PET scan	163 (50.3%)	56 (38.1%)	107 (60.5%)	< 0.001*
Top reasons for not using amyloid PET scan
Cost or insurance concerns	223 (68.8%)	116 (78.9%)	107 (60.5%)	< 0.001*
Unsure of clinical utility or will not alter treatment options	101 (31.2%)	41 (27.9%)	60 (33.9%)	0.30
Test accuracy or reliability concerns	57 (17.6%)	25 (17.0%)	32 (18.1%)	0.92
APOEε4 testing
Routine testing for the APOEε4
Never	105 (32.4%)	42 (28.6%)	63 (35.6%)	0.22
Seldom	85 (26.2%)	43 (29.3%)	42 (23.7%)	0.32
Sometimes	57 (17.6%)	33 (22.4%)	24 (13.6%)	0.05
I am not familiar with APOEε4 testing	35 (10.8%)	3 (2.0%)	32 (18.1%)	< 0.001*
Often	31 (9.6%)	19 (12.9%)	12 (6.8%)	0.09
Almost always	11 (3.4%)	7 (4.8%)	4 (2.3%)	0.24
Percentage of patients suspected of MCI or mild AD who were tested for APOEε4 within the past 2 years				< 0.001*
Mean ± SD	14.3 ± 23.8	20.3 ± 27.0	9.6 ± 19.9

Abbreviations: AD: Alzheimer’s Disease; APOEε4: Apolipoprotein E4; MCI: Mild Cognitive Impairment; PCP: Primary Care Physician; PET: Positron Emission Tomography; SD: Standard Deviation.

AD-specific biomarker imaging tests were used less frequently than structural imaging tests, and they were used more commonly by neurologists than PCPs (32.0% vs 11.9%; p<0.001). Among these tests, amyloid PET scans were the most frequently utilized, and were used more often by neurologists than PCPs (22.4% vs 7.3%; p<0.001). Approximately 60.5% of PCPs reported never having a patient receive an amyloid PET scan, compared to 38.1% of neurologists (p<0.001; Table 2). Likewise, neurologists were more likely to use CSF tests (10.9% vs 2.3%; p<0.01). Blood tests for AD pathology and/or neurodegeneration were used by only 5.6% of physicians, including 5.6% of PCPs and 5.4% of neurologists (p=1.00). Approximately 13.9% of all physicians, including 19.2% of PCPs and 7.5% of neurologists, reported that they do not routinely use any AD-specific biomarker or structural imaging tests (p<0.01; Figure 3).

Physicians most commonly cited cost or insurance concerns (61.4%) as reasons for not using biomarker or imaging tests. Over a third of PCPs also felt that these tests do not provide clinical insights specific to MCI due to AD or mild AD, compared to approximately a quarter of neurologists (37.3% vs 26.5%; p=0.05). Similarly, cost and insurance concerns were the topmost reason specific to not using amyloid PET scans, with more neurologists raising this concern than PCPs (78.9% vs 60.5%; p<0.001). In addition, PCPs and neurologists noted uncertainty in the clinical utility of amyloid PET scans or felt that the test does not alter treatment options (33.9% vs 27.9%; p=0.30) (Table 2).

Table 2 also provides information about APOEε4 testing. At the time of the survey, most physicians did not routinely test for APOEε4. Nevertheless, neurologists reported testing for APOEε4 status more frequently, with an average of 20.3% of patients tested in the past 2 years compared to 9.6% of patients tested by PCPs (p<0.001).

Referral and Treatment Patterns

Table 3 and Figure 4 describe physician-reported referral and treatment patterns for early AD. On average, compared to neurologists, PCPs referred a greater percentage of patients with suspected MCI due to AD for cognitive/behavioral concerns (32.4% vs 17.3%; p<0.001). Similarly, a greater percentage of patients with suspected mild AD was referred to specialists for cognitive/behavioral concerns by PCPs than by neurologists (35.9% vs 17.9%; p<0.001) (Table 3). While PCPs most frequently referred patients to neurologists (78.0%), neurologists most frequently referred patients to memory clinics or other multi-discipline specialist centers (32.0%) (Figure 4). When making a referral, PCPs and neurologists often considered neurocognitive testing results (49.7% vs 40.1%; p=0.11) and behavioral concerns (45.8% vs 37.4%; p=0.16) as factors influencing their referral decisions. In addition, more than twice as many PCPs as neurologists considered memory decline (54.8% vs 25.2%; p<0.001) when making a referral decision (Table 3).

Table 3.

Referral and Treatment Patterns Stratified by Provider Type

	Overall	Neurologist	PCP	P-value¹
	N = 324	N = 147	N = 177	P-value¹
Referral patterns
Referral to another provider
Percentage of patients suspected of MCI due to AD referred by the physician for cognitive/behavioral concerns				< 0.001*
Mean ± SD	25.5 ± 30.3	17.3 ± 24.0	32.4 ± 33.2
Percentage of patients suspected of mild AD referred by the physician for cognitive/behavioral concerns				< 0.001*
Mean ± SD	27.7 ± 31.0	17.9 ± 24.0	35.9 ± 33.8
Specific patient factors or symptoms that influence the decision to make a referral
Neurocognitive testing	147 (45.4%)	59 (40.1%)	88 (49.7%)	0.11
Behavioral concerns	136 (42.0%)	55 (37.4%)	81 (45.8%)	0.16
Memory decline	134 (41.1%)	37 (25.2%)	97 (54.8%)	< 0.001*
Treatment patterns
Prescribing frequency
Medications for MCI due to AD
Almost always	103 (31.8%)	57 (38.8%)	46 (26.0%)	< 0.05*
Often	107 (33.0%)	49 (33.3%)	58 (32.8%)	1.00
Sometimes	76 (23.5%)	31 (21.1%)	45 (25.4%)	0.43
Seldom	32 (9.9%)	8 (5.4%)	24 (13.6%)	< 0.05*
Never	6 (1.9%)	2 (1.4%)	4 (2.3%)	0.69
Medications for mild AD
Almost always	152 (46.9%)	84 (57.1%)	68 (38.4%)	< 0.01*
Often	102 (31.5%)	36 (24.5%)	66 (37.3%)	< 0.05*
Sometimes	54 (16.7%)	24 (16.3%)	30 (16.9%)	1.00
Seldom	12 (3.7%)	3 (2.0%)	9 (5.1%)	0.24
Never	4 (1.2%)	0 (0.0%)	4 (2.3%)	0.13
Prescription of oral medications for MCI due to AD
Physician routinely prescribes oral medications for MCI due to AD	297 (91.7%)	137 (93.2%)	160 (90.4%)	0.48
Donepezil	273 (84.3%)	123 (83.7%)	150 (84.7%)	0.91
Memantine	150 (46.3%)	68 (46.3%)	82 (46.3%)	1.00
Prescription of oral medications for mild AD
Physician routinely prescribes oral medications for mild AD	312 (96.3%)	143 (97.3%)	169 (95.5%)	0.56
Donepezil	279 (86.1%)	128 (87.1%)	151 (85.3%)	0.77
Memantine	192 (59.3%)	85 (57.8%)	107 (60.5%)	0.71
Prescription of anti-amyloid monoclonal antibody therapies²
Physician routinely prescribes anti-amyloid medications for MCI due to AD	68 (21.0%)	44 (29.9%)	24 (13.6%)	< 0.001*
Physician routinely prescribes anti-amyloid medications for mild AD	81 (25.0%)	51 (34.7%)	30 (16.9%)	< 0.001*

Abbreviations: AD: Alzheimer’s Disease; MCI: Mild Cognitive Impairment; PCP: Primary Care Physician; SD: Standard Deviation.

Notes. [1] T-tests were used to compare means for continuous variables and chi-square or Fisher’s exact tests were used to compare categorical variables. Significance was defined as a p-value of <0.05, denoted with an asterisk (*). [2] Anti-amyloid monoclonal antibody therapies included aducanumab and lecanemab.

Figure 4.

Target of referral for cognitive/behavioral concerns stratified by provider type.

For patients with MCI due to AD, 64.8% of all physicians reported frequently (almost always or often) prescribing AD medications, with the percentage being higher for neurologists compared to PCPs (72.1% vs 58.8%; p<0.05). For patients with mild AD, 78.4% of all physicians frequently prescribed AD medications, with this percentage being slightly higher among neurologists than PCPs (81.6% vs 75.7%; p<0.01) (Table 3).

Most physicians reported prescribing oral medications for MCI due to AD (91.7%) and mild AD (96.3%). Among oral medications, donepezil was the most frequently prescribed medication by PCPs and neurologists for both MCI due to AD (84.7% vs 83.7%; p=0.91) and mild AD (85.3% vs 87.1%; p=0.77). Memantine was also commonly prescribed for both MCI due to AD (46.3% for both PCPs and neurologists) and mild AD (60.5% vs 57.8%; p=0.71). Approximately 21.0% and 25.0% of physicians prescribed anti-amyloid monoclonal antibody therapies for MCI due to AD and mild AD, respectively. Neurologists were more likely than PCPs to prescribe these therapies for MCI due to AD (29.9% vs 13.6%; p<0.001) and mild AD (34.7% vs 16.9%; p<0.001), (Table 3).

Physician Confidence in Managing MCI Due to AD and Mild AD

Table 4 describes the self-rated ability of physicians in diagnosing and treating early AD. Overall, PCPs were less confident of their ability to diagnose MCI due to AD and mild AD compared to neurologists; 50.9% of PCPs rated their ability to correctly identify MCI due to AD as confident or extremely confident, compared to 74.8% of neurologists (p<0.001), and 57.1% of PCPs rated their ability to correctly identify mild AD as confident or extremely confident, compared to 76.2% of neurologists (p<0.001). Neurologists were also more likely to rate their ability to manage medications for MCI due to AD or mild AD as confident or extremely confident as compared to PCPs (83.7% vs 60.5%; p<0.001).

Table 4.

Physician Level of Confidence Towards Diagnosis and Management of Early AD

	Overall	Neurologist	PCP	P-value¹
	N = 324	N = 147	N = 177	P-value¹
Rated ability to correctly identify MCI due to AD
Confident or extremely confident	200 (61.7%)	110 (74.8%)	90 (50.8%)	< 0.001*
Rated ability to correctly identify mild AD
Confident or extremely confident	213 (65.7%)	112 (76.2%)	101 (57.1%)	< 0.001*
Rated ability to manage medications for MCI due to AD or mild AD
Confident or extremely confident	230 (71.0%)	123 (83.7%)	107 (60.5%)	< 0.001*

Abbreviations: AD: Alzheimer’s Disease; MCI: Mild Cognitive Impairment; PCP: Primary Care Physician.

Notes. [1] Chi-square test or Fisher’s exact tests were used to compare categorical variables. Significance was defined as a p-value of <0.05, denoted with an asterisk (*).

Discussion

With the evolving landscape of medical therapies for early AD, it is increasingly important to optimize the diagnostic and management process and ensure timely detection and intervention, which can improve patient outcomes and reduce the long-term healthcare burden for both patients and healthcare systems.^7,12 Likewise, diagnostic improvements, including increased diagnostic specificity, improved operational processes, training, and access to resources, can similarly improve outcomes for patients with other AD-related dementias (ADRD), potentially allowing for earlier interventions. While there are no currently approved disease-modifying treatments for ADRD, the earlier stages of such conditions are an active area of research and are prone to similar gaps in care.¹³ This study provides a summary of current physician attitudes and experiences in the diagnosis and treatment of MCI due to AD and mild AD in real-world settings, based on a survey of community-based physicians in the US. The study findings also offer insights on differences in diagnostic and management patterns by physician specialty (PCPs vs neurologists) and according to early AD conditions (MCI due to AD vs mild AD), highlighting potential areas for quality-of-care improvement efforts.

At initial presentation, this study found that patient-reported memory complaints were the most common reason triggering an evaluation for MCI due to AD, while memory concerns from family members or caregivers were the most common reason triggering an evaluation for mild AD. This pattern was consistent with the general view of MCI due to AD as a transitional stage between normal aging and dementia,¹⁴ as well as previous studies that observed fewer self-reported cognitive complaints in patients with poorer cognitive ability.^15,16 Short-term memory loss has been reported as an outstanding clinical feature on presentation in most patients with early AD, characterized by repetition of questions or statements, frequently misplacing items, and difficulty remembering the names of familiar people.¹⁷ These symptoms are expected to be increasingly noticeable to family members or caregivers, and less so to the patients themselves, as the patients’ cognitive function declines over time, as evidenced in this study. Therefore, these data point to the importance of educating the public to recognize early signs and symptoms of AD.

Most clinical guidelines recommend the use of brief neurocognitive assessments to aid in the diagnosis of patients with suspected AD.¹⁸ In this study, both PCPs and neurologists reported the MMSE as the most commonly used neurocognitive assessment. While the MoCA was more often used by neurologists, the Mini-Cog test was more often used by PCPs. Current guidelines lack consensus on which neurocognitive tests to use in the diagnosis and monitoring of AD.¹⁹ Although most widely used as an overall measure of cognitive impairment in clinical and community settings, the diagnostic properties of the MMSE for identifying patients with MCI are not well understood, with studies suggesting limitations as a stand-alone tool.²⁰ By contrast, the MoCA was designed to enable earlier detection of MCI compared to the MMSE and showed a better performance in detecting MCI than MMSE in a meta-analysis.^21,22 The Mini-Cog has been noted as most suitable for routine use in primary care due to its quick administration time and good psychometric properties.²³ The more frequent use of MoCA by neurologists in this study may suggest their familiarity with comprehensive and well-performing neurocognitive tests to identify MCI cases, while the more frequent use of Mini-Cog by PCPs is consistent with the test’s suitability in primary care settings. Notably, 5.1% of PCPs in this study reported that they did not routinely use neurocognitive tests despite the critical role of these assessments in the initial evaluation for early AD.²³ This finding suggests continuing needs for physician education, which can potentially focus on educating physicians about options that are feasible given practice constraints, and more sensitive to earlier stages of AD.

Biomarker and imaging assessments, such as AD-specific biomarkers and structural imaging tests play an increasingly important role in both research and clinical settings, shifting the diagnosis of AD from the later dementia stages towards earlier stages, yet 13.9% of physicians reported they do routinely use either in their practice.²⁴ Among AD-specific biomarker and structural imaging assessments, MRI was the most frequently used tool for both provider types in this study. Structural MRI reveals brain atrophy and other tissue abnormalities distinctive of patients with MCI and AD,²⁵ and consideration of abnormalities on MRI has been recommended as part of the diagnostic criteria for MCI due to AD and dementia due to AD by the National Institute on Aging and the Alzheimer’s Association.^26,27 Moreover, previous studies have established the clinical utility of MRI in differentiating AD from other neurodegenerative diseases.²⁸ Still, 30.5% of PCPs and 13.6% of neurologists in this study reported that they did not routinely use MRI during the diagnostic process, suggesting the need for further education among physicians on the role of neuroimaging in AD diagnosis.

Amyloid PET scans, one of the newer biomarker tools, allow for accurate noninvasive detection of amyloid plaques, a core neuropathologic feature associated with AD.²⁹ In the current study, only 22.4% of neurologists and 7.3% of PCPs reported routine use of amyloid PET scans, citing cost or insurance concerns as the most common reason for not using these tests. This finding was consistent with existing literature that reported concerns with the use amyloid PET scans and other PET imaging techniques, including high cost, limited access, and reliance on expensive equipment and specially trained personnel, all of which may hamper the broader clinical use.^30,31 Notably, expanded Medicare coverage for amyloid PET scans was not approved in the US until October 2023,³² which was after the data collection period of this study (August and September 2023). With the emergence of anti-amyloid monoclonal antibody therapies, along with the approval of expanded Medicare coverage for amyloid PET scans in the US, increased clinical use of amyloid PET scans is expected over time, though efforts to expand access and use are still needed. Likewise, blood-based biomarkers developed in recent years are poised to emerge as a more scalable and cost-effective tool to detect AD pathology.³³ Blood-based tests have been validated against amyloid PET scan results³⁴ and were shown to be clinically equivalent or superior to CSF tests,³⁵ which are more invasive. In the current study, 5.6% of PCPs and 5.4% of neurologists reported that they use blood tests for AD pathology and/or neurodegeneration in their diagnostic process. Due to the relatively recent introduction of these blood-based biomarkers into the diagnostic landscape and the lack of clinical recommendations for their use as standalone diagnostic tests,³⁶ physicians may have limited knowledge or experience with these tests, and reimbursement policies of such tests are still evolving.³⁷ Considering these limitations, the observed percentage of blood-based biomarker test use among physicians in this study, although numerically low, could still be perceived as encouraging. Given the overlap in early symptomology of ADRD conditions, blood-based biomarkers represent a potential area where improvements in the diagnostic process across conditions can be readily implemented.

Most physicians in this study routinely prescribed oral medications for early AD, with donepezil, an acetylcholinesterase (AChE) inhibitor for symptomatic treatment, being most frequently prescribed for both MCI due to AD and mild AD. While donepezil was approved by the US Food and Drug Administration (FDA) for the treatment of mild AD,³⁸ it has not been approved for the treatment of MCI due to AD and showed limited benefits in improving cognitive functions among patients with MCI based on clinical trials.³⁹ However, both PCPs and neurologists reported high usage of donepezil among patients with MCI due to AD in this study (84.7% vs 83.7%). Similarly, a previous systematic literature review observed common usage of AChE inhibitors among patients with MCI due to AD despite lack of approval and guideline recommendations.⁴⁰ This divergence in clinical practice from drug labels suggests unmet needs in treatment options for MCI due to AD and may reflect physicians’ efforts to offer hope of symptomatic relief for patients with MCI despite limited proven benefit. Aside from symptomatic treatments, anti-amyloid monoclonal antibody therapies were routinely prescribed by 21.0% and 25.0% of physicians for MCI due to AD and mild AD, respectively, in this study. While aducanumab, which received accelerated approval by the FDA in 2021, demonstrated limited use in clinical practice before its discontinuation in 2024,⁴¹ lecanemab received traditional approval from the FDA in July 2023,⁴² followed by the approval of donanemab in July 2024,⁴³ ushering in new treatment options. Other anti-amyloid monoclonal antibody therapies may also be on the horizon. Given the data collection timing for this study, these percentages still reflect the early clinical adoption of anti-amyloid monoclonal antibody therapies, and are expected to increase over time as the usage of these therapies grows in real-world settings.

Throughout the survey, neurologists were more likely than PCPs to report using diagnostic tests, prescribing medications for AD, and were more confident in their ability to recognize MCI due to AD and mild AD and manage AD medications. While many practice guidelines advocate a major role for PCPs in the diagnosis and management of AD,⁴⁴ evidence from both this study and existing literature suggests that there remain gaps and challenges in managing early AD among PCPs.⁴⁵ Consistent with this study, previous literature found that many PCPs noted low confidence in making an AD diagnosis, especially in the early disease stages, and that PCPs often felt their training insufficient to prepare them for accurate and confident screening or diagnoses.^45-47 To support PCPs in fulfilling their central role in AD and ADRD care, future strategies may not only include further physician education or training specific to AD, but also promote collaborative models of care enabling PCPs to work within a wider interdisciplinary team, which is associated with improvement in quality of care, more appropriate medication use, and improved caregiver outcomes.^44,48 On the other hand, while more confident than PCPs, 15% to 25% of neurologists still showed limited confidence in the diagnosis and treatment of early AD despite their specialized training, suggesting that further training and education on AD care would be beneficial for specialists as well.

This study presents valuable insights into community-based physicians’ diagnostic and treatment practices for early AD. However, this study should be interpreted considering its limitations. This survey was intended to capture the general attitudes of community-based physicians toward diagnosis and treatment of early AD, which might not accurately reflect their actual diagnostic and treatment patterns for individual patients in their practice. While survey questions were carefully worded to avoid leading language and was reviewed by experts in AD, there is a risk of recall bias. As previously noted, the timing of data collection should also be considered, as data collection occurred immediately after lecanemab approval, and immediately before Medicare’s expansion of PET coverage, thus results may change as beta-amyloid scans are used more widely, and as treatments become more widely use. The recruitment of physicians from a national physician panel may introduce selection bias, as those included may be more knowledgeable or engaged in AD care than the general population of community-based providers. This could result in an overrepresentation of physicians who are more familiar with diagnostic and treatment advancements in AD. To address this bias in future research, a more diverse recruitment strategy should be employed, ensuring inclusion of physicians from a broader range of practice settings (e.g., solo practitioners, rural-based providers) and varying levels of experience managing patients with AD. Finally, as this study was a cross-sectional descriptive study, future studies could incorporate longitudinal designs or multivariate analyses to adjust for confounding factors, such as geographic region, practice setting, and the availability of diagnostic tools. Such adjustments would enable a clearer understanding of how these variables influence diagnostic practices and treatment decisions in early AD care.

The findings from this study highlight heterogeneity in early AD care and establish an important real-world baseline during a period of significant therapeutic transition. As disease-modifying therapies and biomarker-based diagnostic approaches become increasingly available, understanding current practice patterns provides context to guide implementation of new diagnostic approaches, educational initiatives, and treatment strategies. Future research should evaluate the real-world use and value of emerging modalities, such as expanded amyloid PET access and blood-based biomarkers, and assess their impact on treatment access and management. Studies should seek to broaden understanding of how these tools influence time to diagnosis, referral pathways, and care coordination. Results from such studies will provide valuable evidence for identifying disparities, knowledge gaps, and workflow limitations that can be addressed to improve patient outcomes and strengthen clinical practice.

Conclusions

Patient and family/caregiver involvement play a critical role in triggering the diagnostic process for early AD. Differences in utilization patterns of neurocognitive assessments between PCPs and neurologists were consistent with the distinct training, which may suggest a need for further training particularly for PCPs. This was further supported by higher levels of perceived confidence among neurologists compared to PCPs. Physician and population-based education programs, such as initiatives that promote timely awareness of AD symptoms, are key to triggering the evaluation and diagnostic process, which is increasingly important given the need for timing the initiation of new therapies while still in earlier disease stages. Efforts to improve access to care, especially through the expansion of access to new and emerging diagnostic technologies, including blood-based biomarkers, and therapeutics are also needed. Physician education initiatives across specialties may help to bridge these gaps.

Footnotes

Acknowledgements

We would like to thank Richard Batrla for his insights throughout this study.

ORCID iDs

Timothy R. Juday

Ashley Holub

Soeren Mattke

Keith A. Betts

Hongjiao Liu

Feride H. Frech

Ara S. Khachaturian

Ethical Considerations

This study did not involve interactions with or interventions among human subjects and all data were de-identified per US federal regulations (45 CFR 46, 102(f))20. Thus, it was exempt from institutional review board review, consent requirements, and registration, as determined by the Western Copernicus Group Institutional Review Board.

Consent to Participate

This study was determined exempt by the Western Copernicus Group Institutional Review Board. All physicians were presented with an information sheet describing the study, and asked to click continue before starting the survey as confirmation of their consent.

Author Contributions

Timothy R. Juday (Conceptualization; Methodology; Project administration; Supervision; Writing – review & editing); Ashley Holub (Conceptualization; Formal analysis; Investigation; Methodology; Writing – original draft; Writing – review & editing); Soeren Mattke (Conceptualization; Writing – review & editing); Keith A. Betts (Conceptualization; Formal analysis; Investigation; Methodology; Writing – original draft; Writing – review & editing); Sophie A. Kitchen (Conceptualization; Formal analysis; Investigation; Methodology; Writing – original draft; Writing – review & editing); Hongjiao Liu (Formal Analysis; Methodology; Writing – review & editing); Feride H. Frech (Conceptualization; Methodology; Project administration; Supervision; Writing – review & editing); Ara S. Khachaturian (Conceptualization; Writing – review & editing).

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research funding was provided by Eisai Inc.

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: TRJ and FHF are employees of Eisai Inc. AH, KAB, SAK, and HL are employees of Analysis Group, a company that received funding for this research from Eisai Inc. SM has received consulting and speaker fees from Biogen, C2N, Eisai, Novartis, Novo Nordisk and Roche/Genentech. ASK is an officer and director of the Campaign to Prevent Alzheimer’s Disease/Brain Watch Coalition (PAD 20/20) and has received consulting and speaker fees from Alzheimer’s Association, Acadia Pharmaceuticals, Alzheon, Biogen, Eisai, Eli Lilly & Company, High Lantern Group, RELX Plc, and Serdi Publishing.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, upon reasonable request.*

References

Alzheimer’s Association . 2024 Alzheimer’s disease facts and figures. Alzheimers Dement. 2024;20:3708-3821.

Skolariki

Terrera

Danso

. Predictive models for mild cognitive impairment to Alzheimer’s disease conversion. Neural Regeneration Research. 2021;16:1766-1767.

Alzheimer’s Association . More than Normal aging: understanding mild cognitive impairment. Alzheimer’s Disease Facts and Figures. 2022; https://adrag.org/wp-content/uploads/2024/02/alzheimers-facts-and-figures-1.pdf.

Porsteinsson

Isaacson

Knox

Sabbagh

Rubino

. Diagnosis of early Alzheimer’s disease: clinical practice in 2021. The journal of prevention of Alzheimer's disease. 2021;8:371-386.

Alzheimer's Association . Special Report. On the Front Lines: Primary Care Physicians and Alzheimer’s Care in America. 2020. https://www.alz.org/getmedia/a3df5a45-a254-4e49-b7c0-20b412715069/alzheimers-facts-and-figures-special-report-2020.pdf

Bernstein

Rogers

Possin

, et al. Primary care provider attitudes and practices evaluating and managing patients with neurocognitive disorders. Journal of General Internal Medicine. 2019;34:1691-1692.

Liss

Seleri Assunção

Cummings

, et al. Practical recommendations for timely, accurate diagnosis of symptomatic Alzheimer’s disease (MCI and dementia) in primary care: a review and synthesis. Journal of internal medicine. 2021;290:310-334.

Alzheimer’s Association . Special report. American Perspectives on Early Detection of Alzheimer’s Disease in the Era of Treatment. 2025. https://www.alz.org/getmedia/3d226bf2-0690-48d0-98ac-d790384f4ec2/alzheimers-facts-and-figures-special-report.pdf

Frederiksen

Arus

Zetterberg

, et al. Focusing on earlier diagnosis of Alzheimer’s disease. Future Neurology. 2024;19:2337452.

10.

Galvin

Aisen

Langbaum

, et al. Early stages of Alzheimer’s disease: evolving the care team for optimal patient management. Frontiers in Neurology. 2021;11:592302.

11.

Sideman

De Jesus

, et al. Primary care practitioner perspectives on the role of primary care in dementia diagnosis and care. JAMA Network Open. 2023;6:e2336030.

12.

Barnett

Lewis

Blackwell

Taylor

. Early intervention in Alzheimer’s disease: a health economic study of the effects of diagnostic timing. BMC neurology. 2014;14:1-9.

13.

Dickerson

Atri

Clevenger

, et al. The Alzheimer’s Association clinical practice guideline for the Diagnostic Evaluation, Testing, Counseling, and Disclosure of Suspected Alzheimer's Disease and Related Disorders (DETeCD‐ADRD): Executive summary of recommendations for specialty care. Alzheimer’s & Dementia. 2025;21:e14337.

14.

Petersen

Smith

Waring

Ivnik

Tangalos

Kokmen

. Mild cognitive impairment: clinical characterization and outcome. Archives of neurology. 1999;56:303-308.

15.

Bruce

Bhalla

Westervelt

Davis

Williams

Tremont

. Neuropsychological correlates of self-reported depression and self-reported cognition among patients with mild cognitive impairment. Journal of geriatric psychiatry and neurology. 2008;21:34-40.

16.

Silva

Moser

Pflüger

, et al. Self-reported and informant-reported memory functioning and awareness in patients with mild cognitive impairment and Alzheimer s disease. Neuropsychiatrie. 2016;30:103-112.

17.

Tarawneh

Holtzman

. The clinical problem of symptomatic Alzheimer disease and mild cognitive impairment. Cold Spring Harbor perspectives in medicine. 2012;2:a006148.

18.

Arevalo-Rodriguez

Pedraza

Rodríguez

, et al. Alzheimer’s disease dementia guidelines for diagnostic testing: a systematic review. American Journal of Alzheimer’s Disease & Other Dementias®. 2013;28:111-119.

19.

Tahami Monfared

Phan

Pearson

, et al. A systematic review of clinical practice guidelines for Alzheimer’s disease and strategies for future advancements. Neurology and Therapy. 2023;12:1257-1284.

20.

Arevalo‐Rodriguez

Smailagic

i Figuls

, et al. Mini‐Mental State Examination (MMSE) for the detection of Alzheimer's disease and other dementias in people with mild cognitive impairment (MCI). Cochrane database of systematic reviews. 2015;3:CD010783.

21.

Trzepacz

Hochstetler

Wang

Walker

Saykin

. Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults. BMC geriatrics. 2015;15:1-9.

22.

Ciesielska

Sokołowski

Mazur

Podhorecka

Polak-Szabela

Kędziora-Kornatowska

. Is the Montreal Cognitive Assessment (MoCA) test better suited than the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) detection among people aged over 60? Meta-analysis. Psychiatr Pol. 2016;50:1039-1052.

23.

Cordell

Borson

Boustani

, et al. Alzheimer’s Association recommendations for operationalizing the detection of cognitive impairment during the Medicare Annual Wellness Visit in a primary care setting. Alzheimer’s & Dementia. 2013;9:141-150.

24.

Dubois

von Arnim

Burnie

Bozeat

Cummings

. Biomarkers in Alzheimer’s disease: role in early and differential diagnosis and recognition of atypical variants. Alzheimer's Research & Therapy. 2023;15:175.

25.

Chandra

Dervenoulas

Politis

Alzheimer’s Disease Neuroimaging Initiative . Magnetic resonance imaging in Alzheimer’s disease and mild cognitive impairment. Journal of neurology. 2019;266:1293-1302.

26.

Albert

DeKosky

Dickson

, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Focus. 2013;11:96-106.

27.

McKhann

Knopman

Chertkow

, et al. The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia. 2011;7:263-269.

28.

Frisoni

Fox

Jack

Jr Scheltens

Thompson

. The clinical use of structural MRI in Alzheimer disease. Nature Reviews Neurology. 2010;6:67-77.

29.

Chapleau

Iaccarino

Soleimani-Meigooni

Rabinovici

. The role of amyloid PET in imaging neurodegenerative disorders: a review. Journal of Nuclear Medicine. 2022;63:13S-19S.

30.

Witte

Foster

Fleisher

, et al. Clinical use of amyloid-positron emission tomography neuroimaging: practical and bioethical considerations. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring. 2015;1:358-367.

31.

Schindler

Atri

. The role of cerebrospinal fluid and other biomarker modalities in the Alzheimer’s disease diagnostic revolution. Nature Aging. 2023;3:460-462.

32.

Beta Amyloid Positron Emission Tomography in Dementia and Neurodegenerative Disease. https://www.cms.gov/medicare-coverage-database/view/ncacal-decision-memo.aspx?proposed=N&ncaid=308

33.

Canestaro

Bateman

Holtzman

Monane

Braunstein

. Use of a Blood Biomarker Test Improves Economic Utility in the Evaluation of Older Patients Presenting with Cognitive Impairment. Population Health Management. 2024;27:174-184. doi:10.1089/pop.2023.0309.

34.

Kirmess

Meyer

, et al. Assessment of a plasma amyloid probability score to estimate amyloid positron emission tomography findings among adults with cognitive impairment. JAMA network open. 2022;5:e228392.

35.

Barthélemy

Salvadó

Schindler

, et al. Highly accurate blood test for Alzheimer’s disease is similar or superior to clinical cerebrospinal fluid tests. Nature medicine. 2024;30:1085-1095.

36.

Hansson

Edelmayer

Boxer

, et al. The Alzheimer’s Association appropriate use recommendations for blood biomarkers in Alzheimer’s disease. Alzheimer's & Dementia. 2022;18:2669-2686.

37.

Mattke

Cho

Bittner

Hlávka

Hanson

. Blood-based biomarkers for Alzheimer’s pathology and the diagnostic process for a disease-modifying treatment: Projecting the impact on the cost and wait times. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring. 2020;12:e12081. doi:10.1002/dad2.12081.

38.

Birks

Harvey

. Donepezil for dementia due to Alzheimer’s disease. Cochrane Database of systematic reviews. 2018;6:CD001190.

39.

Stiles

Martin

. Does treatment with donepezil improve memory for patients with mild cognitive impairment? 2006;55:435.

40.

Garcia

Leadley

Lang

, et al. Real-world use of symptomatic treatments in early Alzheimer’s disease. Journal of Alzheimer’s Disease. 2023;91:151-167.

41.

Heidebrink

Paulson

. Lessons Learned from Approval of Aducanumab for Alzheimer's Disease. Annual Review of Medicine. 2024;75:99-111.

42.

U.S. Food and Drug Administration . FDA Converts Novel Alzheimer’s Disease Treatment to Traditional Approval. https://www.fda.gov/news-events/press-announcements/fda-converts-novel-alzheimers-disease-treatment-traditional-approval

43.

U.S. Food and Drug Administration . FDA approves treatment for adults with Alzheimer’s disease. 2024.

44.

Geldmacher

Kerwin

. Practical diagnosis and management of dementia due to Alzheimer’s disease in the primary care setting: an evidence-based approach. The primary care companion for CNS disorders. 2013;15:27455.

45.

de Levante

. The knowledge and attitudes of primary care and the barriers to early detection and diagnosis of Alzheimer’s disease. Medicina. 2022;58:906.

46.

Bradford

Kunik

Schulz

Williams

Singh

. Missed and delayed diagnosis of dementia in primary care: prevalence and contributing factors. Alzheimer Disease & Associated Disorders. 2009;23:306-314.

47.

Brodaty

Howarth

Kurrle

. General practice and dementia: a national survey of Australian GPs. Medical Journal of Australia. 1994;160:10-14.

48.

Heintz

Monette

Epstein-Lubow

Smith

Rowlett

Forester

. Emerging collaborative care models for dementia care in the primary care setting: a narrative review. The American Journal of Geriatric Psychiatry. 2020;28:320-330.