Diagnostic Impasse and Wandering in Patients With Rare Neuromuscular Diseases: Insights Into Patient Characteristics From the French National Network for Rare Neuromuscular Diseases (FILNEMUS) and the French National Rare Disease Database (BNDMR)

ABSTRACT

Background

Diagnostic wandering and impasse are major challenges for rare disease management. This study describes the characteristics of patients with rare neuromuscular diseases (RNMDs) without a diagnosis being managed by the French national network for RNMDs (FILNEMUS).

Methods

Data for RNMD patients managed by FILNEMUS centers between January 2017 and November 2022 were extracted from the French National Rare Disease Database (BNDMR). A network‐wide, standardized, and quality‐controlled process was established to collect additional data for patients without a diagnosis. The demographic and socioeconomic characteristics of these patients were then compared with patients with a confirmed diagnosis.

Results

13.5% of patients evaluated (n = 5696/42,256) had no confirmed diagnosis. Comparison with 25,682 managed in the same centers and during the same periods with a confirmed diagnosis revealed that socioeconomic characteristics and region of residence did not influence diagnostic status. However, lack of a confirmed diagnosis was more common in patients aged > 50 years, and older patients had longer periods between first symptom onset and first interaction with an expert center. Evaluation of medical records identified eight RNMDs associated with increased risk of diagnostic wandering and impasse.

Conclusions

The FILNEMUS national network of expert centers has enabled equality of care for RNMD patients across France, but further measures are needed to promote more rapid referral to these centers, reduce times to first consultation, and maintain patient engagement in the diagnostic process, particularly for later‐onset RNMDs.

Between 2017 and 2022, 13.5% of the 42,256 FILNEMUS patients (n = 5696) still lacked a confirmed diagnosis. Socio‐economic status and postcode are off the hook, but crossing the 50‐year mark sharply lengthens the gap between first symptoms and expert evaluation. Eight neuromuscular diseases top the “whodunnit” list, highlighting the need for nimbler diagnostic pathways especially for the silver‐haired sleuths among us.

1. Introduction

In Europe, a disease is defined as rare if it affects less than one in 2000 people in the general population. Around 7000 rare diseases have been identified, affecting some 30 million people in Europe and more than 3 million people in France [1, 2, 3]. Since 2004, three successive French National Plans for Rare Diseases (Plans Nationaux Maladies Rares, PNMRs) have been implemented, positioning France as a leading country in this field within Europe. The PNMRs aim to improve patient care by coordinating all stakeholders and establishing a nationwide network of accredited expert and reference centers. These centers follow shared clinical guidelines and benefit from access to two national genotyping platforms, one serving the northern regions and the other the southern, both operating under harmonized procedures and clinical indications. The expert centers also collect a standardized minimal data set (MDS) for all patients via a national information system developed for the French National Rare Disease Registry (Banque Nationale de Données Maladies Rares, BNDMR), thereby generating a unified dataset of all individuals living with a rare disease in France [4]. Despite these efforts and improvements in patient care, diagnostic wandering, defined as the period between symptom onset and the time at which a precise diagnosis is made, and diagnostic impasse, resulting from the inability to define the precise cause of a disease after carrying out all available investigations, continue to constitute a significant challenge for patients and healthcare systems [5, 6, 7, 8].

In 2018, the third version of the PNMR (PNMR‐3: 2018–2022) set priorities to reduce diagnostic wandering and impasse [9]. The 23 existing accredited national health networks for rare diseases were therefore tasked, using the BNDMR, to create a dynamic national registry of people subject to diagnostic wandering and impasse. As part of this task, the network dedicated to rare neuromuscular diseases (RNMDs), called FILNEMUS, began in September 2020 to identify patients managed by the network who had no confirmed diagnosis, and to collect additional data about their disease to complement the shared BNDMR dataset [10].

Neuromuscular diseases are a very diverse group of mostly genetic or autoimmune disorders. Almost 700 different disease‐associated genes have been identified so far, and around 90% of these disorders are classed as rare diseases [11, 12]. RNMDs, which include myopathies, neuromuscular transmission diseases, peripheral nerve diseases, spinal muscular atrophy, and mitochondrial neuromuscular diseases, affect between 40,000 and 50,000 children and adults in France [13, 14].

In the current study, we retrospectively analyzed the MDS collected by the BNDMR from RNMD patients managed at centers belonging to the FILNEMUS network and compared the demographic, socioeconomic, and diagnostic pathway characteristics of patients identified as being in a state of diagnostic wandering or impasse with a population of patients with a confirmed diagnosis, with the aim of identifying common factors associated with the absence of a diagnosis.

2. Methods

2.1. Study Design

This retrospective, multicenter, cohort study, based on BNDMR MDS collected before November 15, 2022, included patients residing in France and treated and followed up at a FILNEMUS network center after January 2017.

2.2. Data Sources and Management

The data collected consisted of the MDS routinely collected using the BaMaRa database (date of birth, sex, residential address, diagnosis, type of consultation, etc.) and extracted from the BNDMR for each patient with a rare disease presenting at a FILNEMUS expert center [4, 15], together with additional data (disease phenotype, symptom severity, diagnostic workup history, etc.) collected for patients without a diagnosis.

Patients in the BNDMR are identified by a unique, permanent, and irreversible identifier (Identifier Maladie Rare; IdMR) [16], which makes it possible to identify individual patients followed in different centers and aggregate their multihospital records while preserving their privacy. Discrepancies in data collected for patients being managed at multiple centers were resolved by retaining the earliest date, the lowest age, and the residential address closest to the hospital most visited by the patient.

The diagnostic status of patients recorded in the BNDMR was reviewed, and additional data were collected and entered for those identified as being in a state of diagnostic wandering or impasse. This process began in January 2021 and was carried out by clinical research associates (CRAs) recruited by centers within the FILNEMUS network, under the supervision of a dedicated project manager. The CRAs received training (via videoconferences and online tutorials), were provided with instruction manuals and guidelines on how to use the BaMaRa database, examine patient status and collect and enter additional data, and took part in regular follow‐up meetings with the project manager to monitor progress and resolve any issues, all of which ensured the standardization and quality of the data collected across participating centers. A dedicated field allows clinicians to indicate the diagnostic status, with options including “in progress,” “probable,” “undetermined,” or “confirmed.” Patients whose diagnosis was marked as “probable” or “undetermined” were re‐evaluated, and their status was updated accordingly. Patients for whom no further diagnostic procedures were planned were classified into the “no confirmed diagnosis” group. Additional data were collected from medical records or, when necessary, through direct contact with the patient. These supplementary data were not used in the present study; they served solely to identify patients classified as being in a state of diagnostic wandering or impasse.

2.3. Ethical Considerations

This study was approved by the BNDMR Scientific Committee (OHRP number: IRB00013741), complied with EU general data protection regulations, and was conducted in accordance with French MR‐004 reference methodology. Patients were informed about the re‐use of their data for research purposes, and a detailed information sheet was published on the BNDMR website (www.bndmr.fr). Only patients not objecting to the re‐use of their data for research purposes were enrolled in the study, and only anonymous statistical results were returned.

2.4. Participants

RNMD patients treated in one of the 39 centers of the FILNEMUS network participating in the collection of additional data for patients with no diagnosis and who were alive in January 2021 were eligible. The cohort consisted of two groups: the “no confirmed diagnosis group,” that is, patients identified as being in a state of diagnostic wandering or impasse, and the “control group,” that is, those with a diagnosis confirmed by genetic or biological testing, managed at the same network center and at around the same time (within 4 months) as patients in the no confirmed diagnosis group. Vital status and median income were determined using information from the BNDMR linked with data from the French National Institute of Statistics and Economic Studies (INSEE).

Data from healthy carriers, patients treated at centers before they were accredited, patients without an indication of their enrollment date with a network center, fetuses, and patients whose gender was not specified were excluded.

2.5. Variables

The demographic and follow‐up variables analyzed included the proportion of patients from each French region, age at initial treatment by a FILNEMUS network center, age at first symptoms, sex, time between the first and latest interaction with a FILNEMUS network center, time between initial symptoms and first interaction with a FILNEMUS network center, and number of interactions with a FILNEMUS network center. Estimates of patients' socioeconomic status were based on the median income of the general population in each patient's city of residence. This variable was then binarized according to whether the assigned income was below or above the national median income in France. Data on the distance between the patient's residence and the network center, as well as on the diagnosis, were also collected. Distance was similarly binarized according to whether it was shorter or longer than the first quartile distance of patients attending the same center. For patients in the “no confirmed diagnosis group”, suspected/probable diagnoses were examined based on analysis of ORPHAcodes, a rare disease‐specific codification system used to record diagnoses [17].

2.6. Statistical Analysis

Categorical variables (sex and distribution of patients in the French regions) were described as the number and percentage (n%) of patients in the study population and analyzed using a chi‐squared test. Quantitative variables (age, delay, number of interactions) were described as the median and interquartile range and analyzed using a Wilcoxon test. Statistical tests were performed using a 5% significance level.

For demographic and follow‐up characteristics, data were analyzed according to three age categories: 0–15 years (pediatric patients), 15–50 years (young adult and adult patients), and over 50 years (older adult patients). Given the substantial differences in care management between children, adults, and older adults, we hypothesized that the differences between undiagnosed patients and controls would vary significantly across age groups. Consequently, a stratified analysis was conducted based on these three predefined age categories.

We then performed an analysis on the entire population to assess the impact of socioeconomic factors (attributed median income) and access to specialized care (distance to expert center). Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for each variable—median income and distance to the expert center—using the Mantel–Haenszel method, with or without adjustment for the location of the treating hospital, in order to account for potential regional socioeconomic bias. Associations between diagnoses (ORPHAcodes) affecting more than 100 patients in the cohort and the likelihood of diagnostic wandering or impasse were analyzed by calculating odds ratios (ORs) and 95% confidence intervals (95% CIs). This analysis aimed to identify diseases positively associated with an increased probability of diagnostic wandering or impasse (i.e., OR > 1 with 95% confidence). All statistical analyses were performed using the R software package (version 4.2.2, 2022).

3. Results

3.1. Study Population

By November 2022, 47,432 patients with a RNMD were identified as eligible for the study (Figure 1). Of these, 5696 patients (13.5% of the 42,256 patients managed at the same centers over the same period) were identified as being in a state of diagnostic wandering or impasse (no confirmed diagnosis group) and 25,682 managed in the same centers and during the same periods were identified with a confirmed diagnosis (control group).

FIGURE 1.

Study flow chart. BNDMR, French National Rare Diseases Database; FILNEMUS, French National Network for rare neuromuscular diseases.

3.2. Demographic and Follow‐Up Characteristics

Included patients came from all regions of France, including French Overseas Departments and Territories (Table S1).

The proportion of the population without a diagnosis in the 0–15, 15–50, and > 50‐year age groups was 17.8%, 15.3%, and 20.7%, respectively (Table 1). The median age at first referral to a FILNEMUS center differed between the no confirmed diagnosis group and the control group in the 15–50‐year age category (p = 0.036), but was similar across the other age groups.

TABLE 1.

Demographic and follow‐up characteristics of the study population by diagnostic status and age group.

Characteristic	Patients aged 0–15 years			Patients aged 15–50 years			Patients aged > 50 years
	No confirmed diagnosis (N = 922)	Control group (N = 4244)	p	No confirmed diagnosis (N = 1834)	Control group (N = 10,181)	p	No confirmed diagnosis (N = 2930)	Control group (N = 11,234)	p
Age when first managed a FILNEMUS network center, years	m = 0	m = 0		m = 0	m = 0		m = 0	m = 0
Median [Q1‐Q3]	5.9 [2.1–10.6]	6.3 [2.5–10.6]	0.32 ‡	35.8 [26.3–43.7]	34.9 [25.7–43.0]	0.036 ‡	65.0 [57.5–72.0]	64.6 [57.3–71.8]	0.32 ‡
Age at first signs of disease, years	m = 188	m = 913		m = 520	m = 3428		m = 836	m = 3582
Median [Q1‐Q3]	1.0 [0.0–3.0]	1.0 [0.0–4.0]	0.03 ‡	20.0 [8.0–34.0]	18.0 [7.0–31.0]	< 0.001 ‡	55.0 [47.0–65.0]	57.0 [45.0–66.0]	0.06 ‡
Sex, n (%)	m = 0	m = 0		m = 0	m = 0		m = 0	m = 0
Female	393 (43%)	1689 (40%)	0.11 †	857 (47%)	5219 (51%)	< 0.001 †	1315 (45%)	5263 (47%)	0.057 †
Male	529 (57%)	2555 (60%)	0.11 †	977 (53%)	4962 (49%)	< 0.001 †	1615 (55%)	5971 (53%)	0.057 †
Time between first signs of disease and first interaction with a FILNEMUS network center, years	m = 188	m = 913		m = 520	m = 3428		m = 836	m = 3582
Median [Q1‐Q3]	2.5 [0.7–6.1]	2.5 [0.7–6.3]	0.6 ‡	9.2 [2.5–21.1]	12.2 [3.6–22.3]	< 0.001 ‡	6.3 [2.6–15.5]	5.3 [1.6–16.4]	< 0.001 ‡
Time between the first and the most recent interaction with a FILNEMUS network center, years	m = 0	m = 0		m = 0	m = 0		m = 0	m = 0
Median [Q1‐Q3]	4.3 [1.8–8.2]	5.9 [3.0–9.6]	< 0.001 ‡	2.7 [0.7–6.2]	4.5 [1.6–8.5]	< 0.001 ‡	2.3 [0.6–4.8]	3.1 [1.0–6.1]	< 0.001 ‡
Number of interactions with a FILNEMUS network center	m = 0	m = 0		m = 0	m = 0		m = 0	m = 0
Total, median [Q1‐Q3]	7.0 [4.0–12.0]	9.0 [5.0–16.0]	< 0.001 ‡	4.0 [2.0–7.0]	5.0 [2.0–9.0]	< 0.001 ‡	4.0 [2.0–7.0]	5.0 [2.0–9.0]	< 0.001 ‡
Before the period when additional diagnostic data were collected for patients without a diagnosis, median [Q1‐Q3]	6.0 [3.0–10.0]	7.0 [3.0–13.0]	< 0.001 ‡	3.0 [1.0–5.0]	3.0 [2.0–7.0]	< 0.001 ‡	3.0 [1.0–5.0]	3.0 [2.0–7.0]	< 0.001 ‡
After the period when additional diagnostic data were collected for patients without a diagnosis, median [Q1‐Q3]	1.0 [0.0–2.0]	1.0 [0.0–3.0]	< 0.001 ‡	1.0 [0.0–2.0]	1.0 [0.0–2.0]	< 0.001 ‡	0.0 [0.0–2.0]	1.0 [0.0–2.0]	< 0.001 ‡

^† p Values for differences between groups obtained using the chi‐squared test.

^‡ p Values for differences between groups obtained using the Wilcoxon signed rank test.

In addition, no difference was found between the no confirmed diagnosis and control groups for age at onset of the initial disease signs, except in the 15–50‐year age category, where the age of patients without a diagnosis was higher (p < 0.001). For the 15–50‐year age category, the time between initial disease signs and first interaction with a FILNEMUS network center was significantly shorter for the no confirmed diagnosis group (p < 0.001). Conversely, the time to first interaction with a center was significantly longer in the > 50‐year age group for the no confirmed diagnosis group (p < 0.001). Finally, although the time from the first to the most recent interaction with a FILNEMUS network center tended to be significantly shorter for patients in the no confirmed diagnosis group, regardless of age category (p < 0.001), these patients had fewer interactions with the centers than those with a diagnosis.

3.3. Socioeconomic Characteristics

A total of 5441 patients without a diagnosis and 24,429 patients in the control group had data entered for place of residence.

The distance between a participant's city of residence and the reference center had no impact on diagnostic status, with comparable percentages of patients living at a distance greater than the first quartile from their treatment center in both groups (86% vs. 85% in the no confirmed diagnosis and control groups, respectively; OR [95% CI]: 0.95 [0.88, 1.04]).

Over half of the patients in the cohort had an attributed median income below the French median, with a similar rate in both groups (56% vs. 55% in the no confirmed diagnosis and control groups, respectively; OR [95% CI]: 0.96 [0.91, 1.02]).

3.4. Analysis of Diagnoses

Isolated asymptomatic elevation of creatine phosphokinase and mitochondrial myopathy was the RNMDs most positively associated with an increased likelihood of diagnostic wandering or impasse (Table 2).

TABLE 2.

Conditions affecting more than 100 patients in the cohort and associated with an increased likelihood of diagnostic wandering or impasse.

Disease name	Whole cohort, n	No confirmed diagnosis group, n	No confirmed diagnosis, %	OR [95% CI]
Isolated asymptomatic elevation of creatine phosphokinase	139	63	45%	5.13 [3.67, 7.18]
Mitochondrial myopathy	169	76	45%	5.08 [3.74, 6.88]
Chronic idiopathic axonal polyneuropathy a	142	44	31%	2.77 [1.93, 3.95]
Cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome	135	40	30%	2.59 [1.79, 3.76]
Hereditary sodium channelopathy‐related small fiber neuropathy	164	39	24%	1.92 [1.34, 2.75]
Bethlem muscular dystrophy	102	23	23%	1.79 [1.12, 2.84]
Polymyositis	164	33	20%	1.55 [1.05, 2.27]
Central core disease	162	32	20%	1.51 [1.02, 2.23]

Abbreviations: CI, confidence interval; OR, odds ratio.

^a Due to the lack of specific ORPHAcode for this disease, patients with a suspected diagnosis of chronic idiopathic axonal polyneuropathy were assigned the ORPHAcode for acute motor and sensory axonal neuropathy. Chronic idiopathic axonal polyneuropathy was then identified by a partial review of the patient's medical records.

4. Discussion

This retrospective study of a large cohort of RNMD patients managed by expert centers belonging to the FILNEMUS network provided the most accurate estimate to date of the proportion of French RNMD patients in a state of diagnostic wandering or impasse and allowed for detailed analysis of their demographic, socioeconomic, and diagnostic pathway characteristics. In this study, 13.5% of the RNMD patients were in a state of diagnostic wandering or impasse. Differences in region of residence and socioeconomic status were not found to influence the likelihood of obtaining a diagnosis. However, the absence of a confirmed diagnosis appeared to be more common in older patients (> 50 years of age) and the time to expert center referral was also significantly longer for this age group. Regardless of age, patients lacking a confirmed diagnosis also had fewer interactions with their expert center. Finally, eight RNMDs were positively associated with an increased likelihood of diagnostic wandering or impasse: isolated asymptomatic elevation of creatine phosphokinase, mitochondrial myopathy, chronic idiopathic axonal polyneuropathy (CIAP), cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS), hereditary sodium channelopathy‐related small fiber neuropathy, Bethlem muscular dystrophy, polymyositis, and central core disease.

The most recent global analysis of BNDMR records indicated that around 200,000 French rare disease patients were in a state of diagnostic impasse or wandering, representing almost 30% of patients registered in the database between 2007 and 2022 [5]. Despite the challenges posed by the complexity and diversity of RNMDs, the percentage of patients in a state of diagnostic wandering or impasse in our study was estimated at 13.5%. This lower value compared to the global BNDMR estimate was likely associated with the standardized analysis of individual patient data by trained personnel in each network center, allowing for the most accurate evaluation of diagnostic status conducted in the RNMD field to date. This study therefore demonstrates the feasibility of the methodology for creating a detailed registry of patients in a state of diagnostic wandering and impasse across a national rare disease network, as laid out in PNMR‐3 as part of the strategy for improving patient care.

Our finding that patients received equal care regardless of where they lived in France or their socioeconomic status is consistent with the precepts of the French healthcare system, which aims to provide equal treatment for all patients [18]. By contrast, studies in other countries, notably the UK, have highlighted disparities in healthcare provision based on socioeconomic status and the region of residence. As highlighted by the COVID‐19 pandemic, people from black and minority ethnic groups, lower socioeconomic backgrounds, urban areas, and deprived rural areas are more likely to be adversely affected by health inequalities [19].

In contrast to the regional and socioeconomic equality of care in France, our findings showed patient age had an influence on diagnostic status, with the > 50 years age group having the largest percentage of patients with no confirmed diagnosis (20.7%). This may be linked to difficulties in diagnosing late‐onset diseases related to an increased number of co‐morbidities in this age group, underreporting of symptoms due to older patients attributing them to normal aging, or long preclinical phases of disease, as described for more prevalent conditions [20]. In addition, compared to young patients (0–15 years), patients aged 15–50 years and those aged over > 50 years in our study had longer intervals between the first signs of disease and first interaction with an expert center. This finding highlights the need for better training for general practitioners (GPs) and local hospital neurologists to allow for more rapid referral of adults and older patients to expert centers. Indeed, as the results of a recent European survey of people living with rare diseases demonstrated, referral to an expert center is a key strategy for reducing diagnostic delay [21].

Evaluation of the characteristics of the eight RNMDs that were positively associated with an increased likelihood of diagnostic wandering or impasse provided additional insights into factors that may influence diagnostic status. First, the eight diseases identified tended to be of unknown prevalence or ultra‐rare (e.g., only 100 cases of CANVAS and 8 cases of hereditary sodium channelopathy‐related small fiber neuropathy have been reported in the literature). As little is known about these diseases, even physicians practicing in expert centers may have limited experience of these conditions and will thus implement a step‐by‐step diagnostic strategy, first ruling out the most common rare diseases and leaving only the ultra‐rare conditions.

Second, rare non‐familial diseases may be harder to diagnose, potentially explaining why diseases such as isolated asymptomatic elevation of creatine phosphokinase [22], CIAP [23, 24], and polymyositis [25] were positively associated with the absence of a confirmed diagnosis.

Third, RNMDs that belong to a group of diseases, such as central core disease, polymyositis, and mitochondrial myopathy, often require expert differential diagnosis. For example, polymyositis belongs to a larger class of idiopathic inflammatory myopathies, of which it is considered the least frequent. It is a diagnosis of exclusion, and a broad range of differential diagnoses has to be considered before a diagnosis of pure polymyositis can be proposed [25, 26]. Similarly, mitochondrial myopathy is one of many mitochondrial diseases caused by mitochondrial electron transport chain impairment, which can present with very polymorphous phenotypes [27]. The diagnostic approach for these diseases is time‐consuming and complex, requiring measurement of serum lactate levels, exercise testing, electromyography, magnetic resonance spectroscopy, muscle histology, and enzymology, and genetic analysis [28].

Fourth, a lack of disease‐specific confirmatory diagnostic tests (genetic or antibody testing) is also a likely cause of diagnostic wandering and impasse for several of the diseases identified in our study. However, in the case of CANVAS, Cortese et al. recently identified biallelic AAGGG expansions in the replication factor complex subunit 1 (RFC1) gene as a major cause of this disease [29]. The diagnosis of this disease should therefore be facilitated by genetic testing, thus reducing the future number of misdiagnoses.

In the case of Bethlem muscular dystrophy, the association with diagnostic impasse and wandering is likely due to variabilities in the clinical presentation of laxity and contractures and the complexity of the diagnostic pathway [30, 31]. Although Bethlem muscular dystrophy is classified as a collagen VI‐related disease and immunohistology and molecular testing are available, biopsy reveals nonspecific myopathic changes and immunohistology does not allow detection of collagen VI abnormalities. Muscle MRI, of the patient and their close relatives, is often required for diagnosis [32]. In addition, to identify a causal mutation, all 107 exons of the three collagen VI α chain genes (COL6A1, COL6A2, and COL6A3) have to be screened, which is costly and can be time‐consuming due to the presence of extensive polymorphism [33].

Several of the factors discussed above are likely to have influenced the rate of diagnostic impasse and wandering in patients with a suspected diagnosis of CIAP. CIAP is a slowly progressive sensorimotor axonal polyneuropathy of unknown etiology with onset typically occurring in the sixth decade of life [34]. Only around 20% of cases of chronic polyneuropathy are idiopathic, and thus diagnosis requires exclusion of a range of known and potentially treatable causes of axonal polyneuropathy, including diabetes, renal or liver failure, thiamine and vitamin deficiencies, exposure to toxins or some prescribed medications [34], autoimmune diseases (chronic inflammatory demyelinating polyneuropathy [35]) and hereditary diseases (e.g., hereditary transthyretin amyloid polyneuropathy and Charcot–Marie–Tooth disease type 1B [36, 37]). In addition, the diagnostic wandering and impasse associated with CIAP may also have been compounded by the current lack of a specific entry for the condition in the rare disease ORPHAcode system [17], perhaps hampering recognition of the disease and resulting in patients, including those evaluated in this study, being incorrectly assigned as having other forms of axonal neuropathy (e.g., acute motor and sensory axonal neuropathy; AMSAN).

Finally, loss of engagement on the part of patients may be a contributing factor in diagnostic wandering and impasse. The period between appearance of the first symptoms and identification of the correct diagnosis is often long for patients with rare diseases, with an average duration of around 5 years before an accurate diagnosis is achieved [8, 21]. Furthermore, approved treatments are only available for about 5% of the rare diseases identified so far [38]. Many patients therefore repeatedly undergo diagnostic tests that yield no results or do not lead to the prescription of a specific treatment and are thus likely to become discouraged and stop seeking care. In a recent analysis, some 50% of patients in a state of diagnostic wandering ceased consulting because they became discouraged and disengaged from the diagnostic process (personal communication, Prof. Attarian). More rapid referral to expert centers through better training of GPs and local hospital neurologists, advances in screening and sequencing methods, improvements to diagnostic services to enable faster delivery of test results and genetic counseling, and continued research and development into disease‐modifying treatments will hopefully reduce diagnostic delays in the future [39], promote patient engagement, and allow more patients to benefit from earlier diagnosis and better disease management.

The main strength of this study was the use of the standardized and quality‐controlled approach implemented by the FILNEMUS network to analyze BNDMR data and collect additional data for patients without a recorded diagnosis. However, limitations in BNDMR coding at the time of the study meant that patients in a state of diagnostic wandering could not be distinguished from those in a state of diagnostic impasse. This situation will improve in future studies due to the creation of a specific code for diagnostic impasse in the internationally recognized specific coding system for rare diseases based on ORPHAcodes [40]. This will enable patients with undiagnosed rare diseases to be coded in health information systems and thus be counted in epidemiological data [17, 40].

5. Conclusions

This study provided the most accurate estimate to date of the number of patients living with an RNMD in France in a state of diagnostic wandering or impasse, and allowed better characterization of the demographic, socioeconomic, and diagnostic pathway characteristics of these patients. It also demonstrated the feasibility of applying the standardized and quality‐controlled approach across national networks of expert centers to create a dynamic registry of undiagnosed patients. Although the rate of diagnostic wandering and impasse was lower among RNMD patients than previous estimates based on global BNDMR data analysis, the complexity, diversity and slowly evolving chronic nature of some of the diseases, particularly late‐onset forms, continue to pose challenges for diagnosis and management. General improvements to the healthcare system, such as providing more training to GPs and local hospital neurologists to reduce referral times and improving diagnostic services, will help to reduce diagnostic delays and promote patient engagement.

To tackle the persistent pool of undiagnosed patients, we identify five mutually reinforcing levers that French neuromuscular centers—and, by extension, similar national networks—can activate. First, structured, competencybased training is essential: annual nationwide workshops focused on nextgeneration sequencing (NGS) interpretation and rarevariant curation, coupled with simulationbased curricula that harmonize bedside examination skills across centers. Second, inter‐center teleexpertise rounds—monthly virtual boards where clinicians, geneticists and bioinformaticians jointly review “stuck” cases—can dramatically compress the diagnostic timeline by pooling expertise in real time. Third, dynamic triage algorithms embedded in the electronic medical record—AIdriven symptom checklists and phenotypegenotype correlation engines—flag candidates for advanced testing earlier, reducing the number of patients lost in diagnostic limbo. Fourth, strategic reallocation of resources towards “greyzone” diagnostics—dedicated budgets for meta‐bolomics and longread sequencing when standard panels are negative but clinical suspicion remains high—ensures that technological depth matches clinical need. Fifth, patient‐centered pathway coordinators—specially trained nurses who shepherd each case through recommended investigations—prevent the alltoocommon “lost in transition” phenomenon. We contend that the synergistic effect of operator upskilling and streamlined organizational workflows could conservatively cut the undiagnosed rate by 10%–15% within 5 years, a projection consistent with outcomes reported by other national undiagnoseddisease programmes [41].

Recent improvements to the ORPHAcode system should improve the accuracy of epidemiological data on rare disease patients in a state of diagnostic wandering and impasse, although further adjustments are needed to ensure that diagnoses of diseases such as CIAP are correctly recorded. In addition, as demonstrated by the recent discovery of the causative genetic anomaly in CANVAS, advances in research will make diagnosis more straightforward for more patients with RNMDs in the future and hopefully lead to the development of new treatments.

Author Contributions

S.A. and A.‐S.J.: conceptualization (supporting), methodology (lead), writing – review and editing (equal). S.A. also contributed to data curation and investigation (data collection). R.D.: software (lead), formal analysis (equal), methodology (supporting), review and editing (equal), N.E.: conceptualization (supporting), methodology (supporting), writing – review and editing (equal). E.S.‐C., L.P., C.T., S.S., F.B., E.S., M.S., P.L., Y.P., A.N.‐P., A.E.‐L., A.C., L.M., L.F., F.E., C.C., C.E., I.D., C.R., P.C., T.S., and G.S. all contributed equally to data curation, investigation (data collection), and writing – review and editing. All authors read and approved the final version of the manuscript.

Conflicts of Interest

S.A. has been a speaker and board member for Alexion, argenx, Biogen, Janssen, LFB, Pfizer, Sanofi, UCB, Janssen (now Johnson & Johnson Innovative Medicine), LFB, Pfizer, Alnylam, Novartis, and Roche. The other authors have no conflicts of interest to declare in relation to this study.

Supporting information

Table S1: Region of residence of the whole study population and according to diagnostic status.

Appendix S1: Members of the FILNEMUS study group and their affiliations.

Dumas R., Jannot A.‐S., Elarouci N., et al., “Diagnostic Impasse and Wandering in Patients With Rare Neuromuscular Diseases: Insights Into Patient Characteristics From the French National Network for Rare Neuromuscular Diseases (FILNEMUS) and the French National Rare Disease Database (BNDMR),” European Journal of Neurology 32, no. 9 (2025): e70347, 10.1111/ene.70347.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.