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Assessing the effectiveness of measurement scales in evaluating the health-related quality of life in rare disease patients after treatment: a systematic review

Health and Quality of Life Outcomes volume 22, Article number: 108 (2024) Cite this article

Abstract

Background

Rare diseases often entail significant challenges in clinical management and health-related quality of life (HRQoL) assessment. HRQoL assessment tools for rare diseases show substantial variability in outcomes, influenced by disease heterogeneity, intervention types, and scale characteristics. The variability in reported quality of life (QoL) improvements following interventions reflects a need to evaluate the effectiveness of HRQoL assessment tools and understand their suitability across diverse contexts.

Objective

This systematic review aims to analyse the effectiveness of various assessment scales in evaluating QoL and explores the general trends observed in the studies using the same and different assessment scales on rare diseases.

Methods

A comprehensive literature search was conducted across various databases to identify studies that reported QoL outcomes related to interventions for rare diseases. Search terms included various synonyms, and both the generic and specific terms related to rare diseases and QoL. Key variables, including intervention types, patient demographics, study design, and geographical factors, were analysed to determine their role in influencing the reported HRQoL outcomes. The findings were then compared with existing literature to identify consistent patterns and discrepancies.

Results

A total of 39 studies were included, comprising randomised controlled trials, observational studies, and cohort studies, with 4737 participants. Significant variations were observed in QoL improvements across studies, even when using the same assessment scales. These differences were primarily attributed to the heterogeneity in disease severity, intervention types, and patient characteristics. Studies employing disease-specific scales reported more nuanced outcomes than generic ones. Additionally, methodological differences, including study design and intervention type, contributed to variations in results and geographical factors influencing patients’ perceptions of health and well-being.

Conclusion

The reported differences in QoL outcomes across studies can be explained by a combination of factors, including disease heterogeneity, treatment modalities, patient demographics, and assessment scale characteristics. These findings underscore the importance of selecting appropriate HRQoL assessment tools based on the research context and patient population. For more accurate comparisons across studies, it is crucial to consider these factors alongside consistent methodology and cultural adaptability of scales. Future research should focus on developing standardised guidelines for QoL assessments that accommodate the diverse needs of patients with rare diseases.

Background

Assessing quality of life (QoL) or health-related quality of life (HLQoL) is vital for evaluating health outcomes in patients with rare diseases, which often pose unique challenges in healthcare delivery. Rare diseases are defined as those affecting fewer than 200,000 individuals in the U.S. or less than 1 in 2,000 in the EU [1, 2]. These conditions can lead to considerable physical, emotional, and financial burdens for patients and their families, underscoring the necessity for reliable and comprehensive tools to measure HRQoL. Practical HRQoL assessments are critical for understanding both the impact of the disease and the efficacy of treatments [3, 4].

Existing literature reveals that the variability in reported QoL improvements following interventions complicates clinical decision-making and treatment evaluation, depending on the type of intervention and the patient population involved [1, 5]. This variability can partially be attributed to the lack of consensus regarding appropriate HRQoL measurement tools. Although various HRQoL assessment scales have been developed, the choice between generic and disease-specific tools to accurately measure QoL in rare diseases remains controversial [2, 6, 7]. Generic scales provide standardised measures that facilitate broad comparisons. In contrast, disease-specific scales can offer more relevant insights into patient experiences, allowing for a better understanding of the quality of life-related to particular conditions [8,9,10].

Generic tools, such as Europe quality of life-5 dimension (EQ-5D), short-form health survey 36 items (SF-36), and SF-12, offer broad applicability and facilitate comparisons across populations and conditions, making them valuable for policy-making and economic evaluations. However, they often fail to capture the unique challenges faced by patients with rare diseases, such as symptoms specific to the condition or psychological impacts, leading to incomplete or misleading assessments of a patient’s quality of life [11]. On the other hand, disease-specific scales, like individualised neuromuscular quality of life (INQoL) or myasthenia gravis quality of life 15 items revised (MG-QoL15r), offer a more detailed understanding of the specific challenges faced by patients with a particular condition but may lack the generalisability required for broader healthcare policy decisions [12, 13].

Recent studies have demonstrated significant variability in reported QoL improvements depending on the assessment scales used; the study designs employed, and the specific characteristics of the patient populations. For instance, studies using the EQ-5D scale frequently report improvements across multiple domains after intervention, particularly in physical health and general well-being [12, 14]. However, other studies using the same scale have noted only modest or no significant changes, especially in cases where the disease’s impact is primarily psychological or where long-term chronic management is involved [9, 15]. Similarly, disease-specific scales have shown varied results, with some studies indicating substantial QoL improvements post-intervention, while others reveal minimal changes, reflecting the diverse experiences of patients even within the same disease category [16, 17].

These inconsistencies highlight the need for a more nuanced understanding of how QoL outcomes are assessed in rare disease populations. Factors such as patient heterogeneity, differences in disease severity, and variations in the type and duration of interventions all play crucial roles in determining the effectiveness of these assessment tools [18, 19]. Additionally, cultural differences, healthcare access, and the psychological burden of living with a rare condition can further influence QoL outcomes. This underscores the importance of selecting the appropriate scale based on the specific research or clinical context [20, 21].

This systematic review addresses a significant gap in the literature by evaluating the effectiveness and limitations of these tools in the context of rare diseases. Furthermore, it delves into general trends in the reported QoL outcomes across various studies. The review aims to thoroughly understand the factors that influence reported QoL outcomes, such as methodological design, patient characteristics, and the cultural adaptability of measurement scales. These insights are designed to aid researchers and clinicians in selecting appropriate HRQoL tools, thereby enhancing the precision of rare disease management and informing policymaking.

Methods

Materials and methods

In this systematic review, the PRISMA® (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) instructional guidelines [22] was followed to evaluate the effectiveness of measurement scales in assessing patients with rare diseases. The PROSPERO (Prospective Register of Systematic Reviews) registered the study protocol with confirmation number CRD42024583835.

Data sources and search strategy

A comprehensive search of electronic databases, including PubMed, EMBASE and SCOPUS, was used as a source from inception to June 2024. Search terms included keywords related to rare diseases and quality of life, rating scales, and outcomes. The search strategy incorporated variations in spelling and grammar (e.g., “Quality of Life,” “HRQoL”) and terms for specific rare disease categories. Medical Subject Heading (MeSH) terms were also used to capture synonyms and related terms. The search was also manually supplemented with reference lists of included studies and review articles in the field. The complete search terms can be found in Supplementary File 1.

Study selection

Study selection was performed by two independent reviewers (JSD and JL) who screened the title and abstract of the identified articles for eligibility based on the following inclusion criteria: [1] Studies assessing quality of life using any rating scale in patients with rare diseases [2], studies reporting the psychometric properties of the rating scales used [3], studies with participants of all ages, from children to adults, to ensure a comprehensive understanding of quality of life assessment in patients with rare diseases [4], studies with any study design and [5] studies published in English. In contrast, studies were excluded if: [1] they did not assess the quality of life using rating scales or did not report psychometric properties of the rating scales [2], studies published in languages other than English [3], studies that did not consider patients with rare diseases or focused on comorbidities with no relevance to rare diseases [4], studies that evaluated the effectiveness of interventions without detailed evaluation of available HRQoL outcome data, and [5] studies that did not meet the inclusion criteria mentioned. Disagreements between reviewers were resolved through discussion until a consensus was reached.

Text screening

The lead author (JSD) carried out an initial evaluation of all titles and abstracts to determine their suitability. Two additional researchers (JL and BA) contributed by independently reviewing the titles and abstracts for relevance. Any uncertainties regarding eligibility were discussed among the reviewers to ensure comprehensive coverage and to minimise the risk of including studies that did not meet the established criteria. Following the initial screening, the same reviewers assessed the full texts of the selected studies to finalise which ones would be included in the systematic review.

Data extraction and analysis

JSD performed data extraction and analysis. The following data points were extracted from the included studies: authors, year of publication, country, study design, sample size, rare diseases included, the rating scale used, psychometric properties of the rating scale, intervention type, and key outcomes. The extracted data were further reviewed and analysed independently by two reviewers (JL and BA). Discrepancies were resolved through discussion to ensure the completeness of extracted information.

Data synthesis

A narrative synthesis was performed based on the extracted data. The synthesis assessed the reliability, validity and applicability of HRQoL rating scales used to assess patients with rare diseases. Because no effect measures were used, quantitative analysis was not applicable. No meta-analysis was performed as most of the articles extracted were single-arm interventions and post hoc analyses of previous RCT data. High heterogeneity was expected due to the broad inclusion criteria and the inclusion of multiple measurement scales in each study. Therefore, the heterogeneity of the studies was not assessed. Likewise, no sensitivity analyses were carried out.

Risk of bias assessment

The study protocol reported a risk of bias assessment using the JBI critical appraisal tools for systematic reviews and research syntheses. These provided a more comprehensive range of checklists [23]. It contains 11 questions that, in rare cases, should be answered with “Yes,” “No,” “Unclear,” and “Not applicable.” No meta-bias was analysed as the results of the studies were not of interest due to the heterogeneity of the outcome variables. Additionally, we employed the COSMIN (Consensus-based Standards for the Selection of Health Measurement Instruments) framework to evaluate psychometric properties [24]. For simplicity, we focused our ratings on the reliability, validity and responsiveness of the HRQoL instruments utilised since our focus was on effectiveness and general trends in reported patients’ QoL outcomes.

Results

General characteristics of data

Figure 1 illustrates the study selection process for the systematic review, encompassing 39 studies, including two sets of interconnected reports. Karaa et al. published two papers on the treatment of primary mitochondrial myopathy (PMM) with elamipretide in 2020 and 2023, respectively. Table 1 provides an overview of the study characteristics, encompassing 4737 participants across the 39 included studies. Among these, 21 studies were randomised controlled trials (RCTs), 6 were observational cohort studies, 3 were cross-sectional studies, 4 were posthoc analyses, 2 were prospective studies, 1 was a pilot study, and 2 had other study designs (Supplementary file 2). Within the 21 RCTs, 14 utilised double-blind randomisation [11, 13, 14, 19, 25,26,27,28,29,30,31,32,33,34]; four employed open-label randomisation [12, 18, 35, 36]; one had a prospective design [37]; and two did not specify the type of randomisation [3, 4].

Fig. 1
figure 1

PRISMA flow chart showing the identification and screening of included studies

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Table 1 Characteristics of included studies
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Geographically, most studies were conducted in multiple countries (Fig. 2). Specifically, there were six studies in Germany [3, 4, 15, 26, 27, 41]; four in the USA [31, 36, 43, 47]; three in China [18, 48, 49]; three in the Netherlands [35, 44, 50]; two in Italy [42, 46]; and one each in the UK [16], Belgium [37], Czech Republic [17], Canada [33], Brazil [28], and South Korea [40]. Seventeen studies were performed in a single-centre setting, two in a tertiary setting, five were multicenter, and 15 were multinational (Fig. 2).

Fig. 2
figure 2

The number of included studies according to country, settings, system/organ and publication year

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As depicted in Fig. 2, seven studies exclusively addressed genetic-related diseases, six focused on haematological diseases, five on neuromuscular diseases, five on respiratory diseases, and three on endocrine/metabolic, musculoskeletal, and autoimmune diseases. Additionally, one study each focused on cardiovascular, liver, tumour, and neurodegenerative diseases, and three studies involved multiple rare diseases. Regarding interventions, three studies were related to physical therapy, three to surgical interventions, one to a rehabilitation programme, one on self-help books and telephone counselling, and the rest were medication treatment interventions (Fig. 2). Furthermore, 21 studies focused on adult patients, seven on children, and eleven on adult and child patients (Fig. 3).

Fig. 3
figure 3

Percentage of included studies for category, scale type, level of improvement and intervention type

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Assessment of measurement scales

In total, 13 studies used generic scales to assess the quality of life following an intervention, while eight used disease-specific scales, and 18 employed both generic and disease-specific scales (Fig. 3). Studies that utilised both types of scales demonstrated similar overall health improvement in patients with rare diseases [14, 25]. Whereas other studies identified in this review reported minor differences in overall health improvement after the intervention [18, 28]. The most frequently used generic scales included EQ-5D, SF-36, visual analogue scale (VAS), paediatric quality of life inventory (PedsQL), patient health questionnaire-9 (PHQ-9), and SF-12; the characteristics of most of these measurement scales are detailed in Table 2. EQ-5D was the most used generic scale for assessing the quality of life in patients with rare diseases. Regarding interventions (including medications, physical therapy, rehabilitation, surgery, etc.), most of the included studies reported a significant improvement in quality of life after treatment, while others indicated no substantial improvement or no change from baseline parameters. This highlights the likelihood that generic scales for quality-of-life assessment vary across diseases and may not adequately capture or evaluate the main features specific to each disease type.

Table 2 Characteristics of some measurement scales
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Analysis of overall health improvement in various RD patients

Analyses of overall health improvement in multiple patients with rare diseases (RDs) have yielded varied results. Most of the included studies have reported an improvement in the QoL after intervention [3, 4, 11,12,13,14, 25, 29, 31, 32, 36, 37]. However, one study indicated no discernible change in patients' QoL following treatment compared to baseline parameters [27], and seven studies reported no significant improvement [18, 19, 26, 28, 30, 33, 35].

The disparity in QoL improvement is partly attributed to the use of different scales to measure QoL after intervention, as well as the specific disease being studied, the extent of the research, and the use of generic versus disease-specific scales (Supplementary File 3). For example, in patients with systemic sclerosis (SSc), two studies used the health assessment questionnaire-disability index (HAQ-DI) to evaluate QoL after intervention [20, 28], while Heřmánková et al. utilised the health assessment questionnaire (HAQ), SF-36, and Beck’s depression inventory-2 (BDI-2) to assess HRQoL [17]. Similarly, in patients with myasthenia gravis (MG), one study used both generic scales (EQ-5D, VAS, Work Productivity and Activity Impairment [WPAI]) and a disease-specific scale (MG-QoL-15r) to evaluate patients' QoL [14], while one study solely used the disease-specific scale to evaluate patients' QoL [13].

Those reporting improvement after treatment also exhibited variability in the degree of improvement based on the scale used to assess HRQoL (Fig. 3). This variability was influenced by several factors, including the specific HRQoL instruments utilised, the nature of the rare disease, and the demographics of the patient populations studied. For instance, research employing disease-specific scales often yielded more nuanced and contextually relevant outcomes than those relying on generic scales [11, 25].

Disease-specific tools, such as the MG-QoL15r for myasthenia gravis and the Behcet disease quality of life (BDQoL) scale for patients with Behcet disease, effectively address the unique challenges faced by individuals with these specific conditions [13, 42]. These scales can accurately capture changes in patient experiences that generic instruments might overlook, thus providing a more comprehensive clinical picture. In contrast, while useful for broad comparisons, generic scales such as EQ-5D and PedsQoL often reveal only moderate improvements or fail to identify significant changes in QoL [18, 39]. This limitation is particularly evident in patients experiencing complex and multifaceted symptoms. The heterogeneity in disease characteristics significantly influenced the variability in QoL reporting. For example, conditions with a predominant psychological component, such as systemic sclerosis, often exhibited minimal changes in QoL when assessed using generic instruments [17, 20]. In contrast, research focusing on diseases that primarily affect physical health showed more pronounced improvements in QoL following treatment [11, 13].

The EQ-5D scale is widely used to evaluate the quality of life in patients with rare diseases. One study noted a substantial enhancement in QoL following treatment, reflected in increased scores across all EQ-5D domains and improvements in depression, anxiety, and work productivity loss. Notably, patients receiving higher medication doses experienced the most significant improvements in their QoL [12]. Another study reported a discernible improvement in participants' quality of life across all EQ-5D domains, which aligned with the disease-specific scale [14]. High health utility scores post-treatment were indicative of pronounced improvement [44, 49]. Some studies included in this review illustrated moderate improvements in quality of life using the EQ-5D scale in conjunction with other measurement scales [29, 39]. However, different outcomes were reported when evaluating the impact of interventions on patients' quality of life. Cleary et al. reported a decrease in self-care and mobility subdomain scores after treatment follow-up, while utility scores remained stable, suggesting mild improvement[16]. Additionally, several studies indicated significant improvements in the EQ-5D VAS scale after intervention [8, 14, 42, 49], moderate improvement [20, 37], and mild improvement following treatment [29], as well as no change or minimal improvement after treatment [15].

The SF-36 scale is utilised to assess the impact of rare diseases on patients' QoL. Most of the included studies have indicated the effectiveness of this scale in quantifying the impact of rare diseases on patients' QoL, with many demonstrating significant enhancements across all SF-36 domains [37, 41, 45]. Some studies have shown improvements in specific domains, such as physical function, role function, bodily pain, social function, and the Physical Component Summary (PCS) following interventions [25]. Another study reported significant improvement in the PCS subdomain and other measurement scales [17]. Nonetheless, some studies have reported a decline in HRQoL following treatment [39]. Furthermore, there were differing outcomes when comparing surgical and nonsurgical interventions [40]. Similar to the SF-36 scale, the simplified SF-12 scale is also utilised to assess the impact on the quality of life in patients with rare diseases. All SF-12 domains demonstrated improvement after intervention [43]. Following treatment, there was moderate improvement in the PCS subdomain [29] and higher Mental Component Summary (MCS) scores, while no significant difference in PCS scores was observed, indicating mild improvement in patients’ quality of life [3].

PedsQL is a scale that assesses the impact on the QoL of paediatric patients with rare diseases. Several of the included studies have reported significant improvements in all PedsQL domains following intervention for both the children's and family versions of the PedsQL subtypes [38]. Significant enhancements in PedsQL physical functioning, emotional functioning, and school functioning were noted after treatment, with parents also demonstrating similar overall improvement [46]. Another study reported an improvement in QoL for family members caring for pantothenate kinase-associated neurodegeneration (PKAN) patients, while the patients themselves did not experience any change following treatment [18]. However, some studies indicated no improvement after treatment, with no statistically significant differences observed between the placebo and treatment groups, and other assessment scales showed no enhancements in patients’ QoL [19]. In contrast, the disease-specific CF scale (PedsQl-GI) demonstrated significant improvement in overall health for children as well as in the parental CFAbd-scores [8].

Moreover, other assessment scales identified in this review showed moderate improvement in patients with various RDs when used alongside the aforementioned scales. For instance, the generalised anxiety disorder-7 (GAD-7) scale revealed mild anxiety following the intervention, while the patient health questionnaire-9 (PHQ-9) scale indicated mild depression [4]. On the other hand, factors such as depression, anxiety, somatic symptom severity, and perceived disease benefit did not show significant improvement, with no notable group differences observed as assessed by the PHQ-9/15 and GAD-7 scales [3]. Anxiety and depression significantly improved as assessed by the hospital anxiety and depression scale (HADS) scale, along with a reduction in work productivity loss (apart from absenteeism) as evaluated by WPAI. Disease-specific scales angioedema quality of (AE-QoL) and hereditary angioedema quality of life (HAE-QoL) also showed similar enhancements in patients' quality of life [12]. In a separate study, the HADS scale assessment showed that 34% of the treatment group experienced depression compared to 44% in the control group, indicating a moderate improvement in patients' overall quality of life [34]. Significant improvement was observed in the MG-QoL15r assessment scale, which exhibited a substantial correlation with other generic scales [14].

There was a meaningful enhancement in patients' QoL based on the health assessment questionnaire (HAQ) scale, as well as on other measurement scales [17]. Additionally, an improvement in QoL assessed by the MPS-HAQ scale and an increase in distance walked after treatment, as evaluated by the 6-min walk test (6MWT), were noted [16]. On the other hand, Karaa et al. reported conflicting results in the improvement of QoL assessed by 6MWT [30, 31]. Furthermore, there was an overall improvement in QoL except for body image, based on the individualized neuromuscular quality of life (INQOL) scale [25]. However, no QoL improvement (increased mean score) was observed following treatment when assessed by the HAQ scale [28]. Nonetheless, disease-specific assessment scales indicated an overall improved QoL.

The study conducted by Cella et al. revealed significant improvements in global health status, diarrhoea, nausea and vomiting, pain, and GI symptoms for patients with neuroendocrine tumours (NETs) following treatment, as evaluated by the EORTC QLQ-C30 and GINET21 scales [11]. On the contrary, de Hosson et al. found that patients with similar NETs disease did not experience reduced stress or enhanced satisfaction with the information received, as measured by the EORTC QLQ-INFO25 scale [35]. Additionally, Vissing et al. reported a notable improvement in QoL for MG patients [13], whereas Schramm et al. observed some QoL enhancement for patients with PBC following treatment [32]. In contrast, Griese et al. did not find any improvement in QoL for patients with children with interstitial lung disease (chILD) using disease-specific measurement scales [26]. Furthermore, Dittrich et al. observed no significant difference in QoL post-intervention for Duchenne muscular dystrophy (DMD) patients using the kiddo-KINDL scale [27], and Thompson et al. found no meaningful change in QoL for hereditary haemorrhagic telangiectasia (HHT) patients as evaluated by the epistaxis severity score (ESS) scale [33].

Analysis of overall health improvement in various RD patients

Analyses of overall health improvement in multiple patients with rare diseases (RDs) have yielded varied results. Most of the included studies have reported an improvement in the QoL after intervention [3, 4, 11,12,13,14, 25, 29, 31, 32, 36, 37]. However, one study indicated no discernible change in patients’ QoL following treatment compared to baseline parameters [27], and seven studies reported no significant improvement [18, 19, 26, 28, 30, 33, 35].

The disparity in QoL improvement is partly attributed to the use of different scales to measure QoL after intervention, as well as the specific disease being studied, the extent of the research, and the use of generic versus disease-specific scales (Supplementary File 3). For example, in patients with systemic sclerosis (SSc), two studies used the health assessment questionnaire-disability index (HAQ-DI) to evaluate QoL after intervention [20, 28], while Heřmánková et al. utilised the health assessment questionnaire (HAQ), SF-36, and Beck’s depression inventory-2 (BDI-2) to assess HRQoL [17]. Similarly, in patients with myasthenia gravis (MG), one study used both generic scales (EQ-5D, VAS, Work Productivity and Activity Impairment [WPAI]) and a disease-specific scale (MG-QoL-15r) to evaluate patients’ QoL [14], while one study solely used the disease-specific scale to evaluate patients’ QoL [13].

Those reporting improvement after treatment also exhibited variability in the degree of improvement based on the scale used to assess HRQoL (Fig. 3). This variability was influenced by several factors, including the specific HRQoL instruments utilised, the nature of the rare disease, and the demographics of the patient populations studied. For instance, research employing disease-specific scales often yielded more nuanced and contextually relevant outcomes than those relying on generic scales [11, 25].

Disease-specific tools, such as the MG-QoL15r for myasthenia gravis and the Behcet disease quality of life (BDQoL) scale for patients with Behcet disease, effectively address the unique challenges faced by individuals with these specific conditions [13, 42]. These scales can accurately capture changes in patient experiences that generic instruments might overlook, thus providing a more comprehensive clinical picture. In contrast, while useful for broad comparisons, generic scales such as EQ-5D and PedsQoL often reveal only moderate improvements or fail to identify significant changes in QoL [18, 39]. This limitation is particularly evident in patients experiencing complex and multifaceted symptoms. The heterogeneity in disease characteristics significantly influenced the variability in QoL reporting. For example, conditions with a predominant psychological component, such as systemic sclerosis, often exhibited minimal changes in QoL when assessed using generic instruments [17, 20]. In contrast, research focusing on diseases that primarily affect physical health showed more pronounced improvements in QoL following treatment [11, 13].

The EQ-5D scale is widely used to evaluate the quality of life in patients with rare diseases. One study noted a substantial enhancement in QoL following treatment, reflected in increased scores across all EQ-5D domains and improvements in depression, anxiety, and work productivity loss. Notably, patients receiving higher medication doses experienced the most significant improvements in their QoL [12]. Another study reported a discernible improvement in participants’ quality of life across all EQ-5D domains, which aligned with the disease-specific scale [14]. High health utility scores post-treatment were indicative of pronounced improvement [44, 49]. Some studies included in this review illustrated moderate improvements in quality of life using the EQ-5D scale in conjunction with other measurement scales [29, 39]. However, different outcomes were reported when evaluating the impact of interventions on patients’ quality of life. Cleary et al. reported a decrease in self-care and mobility subdomain scores after treatment follow-up, while utility scores remained stable, suggesting mild improvement [16]. Additionally, several studies indicated significant improvements in the EQ-5D VAS scale after intervention [8, 14, 42, 49], moderate improvement [20, 37], and mild improvement following treatment [29], as well as no change or minimal improvement after treatment [15].

The SF-36 scale is utilised to assess the impact of rare diseases on patients’ QoL. Most of the included studies have indicated the effectiveness of this scale in quantifying the impact of rare diseases on patients’ QoL, with many demonstrating significant enhancements across all SF-36 domains [37, 41, 45]. Some studies have shown improvements in specific domains, such as physical function, role function, bodily pain, social function, and the Physical Component Summary (PCS) following interventions [25]. Another study reported significant improvement in the PCS subdomain and other measurement scales [17]. Nonetheless, some studies have reported a decline in HRQoL following treatment [39]. Furthermore, there were differing outcomes when comparing surgical and nonsurgical interventions [40]. Similar to the SF-36 scale, the simplified SF-12 scale is also utilised to assess the impact on the quality of life in patients with rare diseases. All SF-12 domains demonstrated improvement after intervention [43]. Following treatment, there was moderate improvement in the PCS subdomain [29] and higher Mental Component Summary (MCS) scores, while no significant difference in PCS scores was observed, indicating mild improvement in patients’ quality of life [3].

PedsQL is a scale that assesses the impact on the QoL of paediatric patients with rare diseases. Several of the included studies have reported significant improvements in all PedsQL domains following intervention for both the children’s and family versions of the PedsQL subtypes [38]. Significant enhancements in PedsQL physical functioning, emotional functioning, and school functioning were noted after treatment, with parents also demonstrating similar overall improvement [46]. Another study reported an improvement in QoL for family members caring for pantothenate kinase-associated neurodegeneration (PKAN) patients, while the patients themselves did not experience any change following treatment [18]. However, some studies indicated no improvement after treatment, with no statistically significant differences observed between the placebo and treatment groups, and other assessment scales showed no enhancements in patients’ QoL [19]. In contrast, the disease-specific CF scale (PedsQl-GI) demonstrated significant improvement in overall health for children as well as in the parental CFAbd-scores [8].

Moreover, other assessment scales identified in this review showed moderate improvement in patients with various RDs when used alongside the aforementioned scales. For instance, the generalised anxiety disorder-7 (GAD-7) scale revealed mild anxiety following the intervention, while the patient health questionnaire-9 (PHQ-9) scale indicated mild depression [4]. On the other hand, factors such as depression, anxiety, somatic symptom severity, and perceived disease benefit did not show significant improvement, with no notable group differences observed as assessed by the PHQ-9/15 and GAD-7 scales [3]. Anxiety and depression significantly improved as assessed by the hospital anxiety and depression scale (HADS) scale, along with a reduction in work productivity loss (apart from absenteeism) as evaluated by WPAI. Disease-specific scales angioedema quality of (AE-QoL) and hereditary angioedema quality of life (HAE-QoL) also showed similar enhancements in patients’ quality of life [12]. In a separate study, the HADS scale assessment showed that 34% of the treatment group experienced depression compared to 44% in the control group, indicating a moderate improvement in patients’ overall quality of life [34]. Significant improvement was observed in the MG-QoL15r assessment scale, which exhibited a substantial correlation with other generic scales [14].

There was a meaningful enhancement in patients’ QoL based on the health assessment questionnaire (HAQ) scale, as well as on other measurement scales [17]. Additionally, an improvement in QoL assessed by the MPS-HAQ scale and an increase in distance walked after treatment, as evaluated by the 6-minute walk test (6MWT), were noted [16]. On the other hand, Karaa et al. reported conflicting results in the improvement of QoL assessed by 6MWT [30, 31]. Furthermore, there was an overall improvement in QoL except for body image, based on the individualized neuromuscular quality of life (INQOL) scale [25]. However, no QoL improvement (increased mean score) was observed following treatment when assessed by the HAQ scale [28]. Nonetheless, disease-specific assessment scales indicated an overall improved QoL.

The study conducted by Cella et al. revealed significant improvements in global health status, diarrhoea, nausea and vomiting, pain, and GI symptoms for patients with neuroendocrine tumours (NETs) following treatment, as evaluated by the EORTC QLQ-C30 and GINET21 scales [11]. On the contrary, de Hosson et al. found that patients with similar NETs disease did not experience reduced stress or enhanced satisfaction with the information received, as measured by the EORTC QLQ-INFO25 scale [35]. Additionally, Vissing et al. reported a notable improvement in QoL for MG patients [13], whereas Schramm et al. observed some QoL enhancement for patients with PBC following treatment [32]. In contrast, Griese et al. did not find any improvement in QoL for patients with children with interstitial lung disease (chILD) using disease-specific measurement scales [26]. Furthermore, Dittrich et al. observed no significant difference in QoL post-intervention for Duchenne muscular dystrophy (DMD) patients using the kiddo-KINDL scale [27], and Thompson et al. found no meaningful change in QoL for hereditary haemorrhagic telangiectasia (HHT) patients as evaluated by the epistaxis severity score (ESS) scale [33].

Psychometric properties of QoL scales

The studies analysed revealed variability in patients’ QoL improvements based on various psychometric properties. Table 3 provides an overview of the COSMIN checklist for some of the identified scales. The EQ-5D and SF-36 scales demonstrated high reliability across most studies [14, 45]. However, test-retest reliability occasionally fell short in the context of chronic rare diseases, notably when patients’ conditions remained relatively stable over time. In contrast, the MG-QoL15r and INQoL scales exhibited excellent reliability, with strong internal consistency and test-retest reliability, making them well-suited for monitoring disease-specific changes [13, 25].

Table 3 COSMIN checklist for psychometric properties of quality of life scales
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The SF-36 and pedsQL scales showed moderate to strong construct validity, correlating well with other health status measures [18, 41]. Nonetheless, their content validity in rare diseases was somewhat limited, as they did not sufficiently capture disease-specific symptoms. Conversely, disease-specific scales such as the MG-QoL15r and QLQ-C30 demonstrated high content and construct validity, effectively reflecting the unique impacts of conditions like myasthenia gravis and neuroendocrine tumours [11, 13]. While the SF-36 and EQ-5D scales were moderately responsive to changes in general health, they were less sensitive to minor disease-specific changes in chronic rare diseases [14, 45]. In comparison, the MG-QoL15r and QLQ-C30 scales proved highly responsive to treatment changes and disease progression, successfully capturing clinically significant changes in disease-specific outcomes (Table 3).

Discussion

The systematic review highlights significant variability in the methodologies, interventions, and outcome measures used in evaluating quality of life (QoL) for rare disease patients. A comprehensive analysis of 39 studies involving 4737 participants underscores the complexities and challenges of assessing QoL across diverse rare disease conditions. This research explores the general trends in QoL outcomes across various instruments observed in the studies, which is essential for understanding how different measurement tools can yield varying results in this heterogeneous patient population. Our analysis uncovered notable variability in reported QoL improvements among the studies, primarily due to differences in the specific HRQoL instruments used, the characteristics of the rare diseases being examined, and the demographics of the patient populations. These findings underscore the complexity of QoL assessments in rare diseases and reinforce our objective to elucidate the performance of different instruments across diverse contexts.

The included studies demonstrate a broad range of methodological designs, reflecting the diverse approaches to rare disease research. The predominance of randomised controlled trials (RCTs) (21 studies), particularly those employing double-blind randomisation (14 out of 21), suggests that rigorous methodologies are being prioritised in assessing treatment outcomes. However, the presence of open-label trials, prospective designs, and studies with unspecified randomisation methods introduce a degree of heterogeneity that complicates direct comparisons between studies [3, 12, 31]. The influence of study design on reported QoL outcomes is well-documented. For example, a review by Brundage et al. reported variability in HRQoL assessment both in data analysis and presentation patterns for RCTs [21]. Additionally, studies using RCTs show less variability than observational studies. This is consistent with our analysis, which identified methodological differences as a source of variation in QoL outcomes. Furthermore, patient-reported outcomes (PROs) have been criticised for subjectivity, which can lead to discrepancies, as highlighted by Anderson et al. [51].

Moreover, the geographical distribution of studies, spanning multiple countries and single- or multi-centre settings, indicates that research capacities and healthcare contexts vary widely across regions [26, 49]. This geographical diversity is crucial in understanding how local health systems, cultural factors, and regional practices influence QoL outcomes. In contrast, geographical and cultural differences have been shown to significantly affect QoL assessment. A cross-cultural analysis by Wille et al. demonstrated that the interpretation of HRQoL scales like EQ-5D varies across countries due to cultural differences in health perception and response styles [52]. Similarly, studies by Rabin et al. and Luo et al. found that translated scales might introduce linguistic biases, leading to variations in reported outcomes [53, 54]. This supports our analysis that cultural and regional factors are crucial when comparing QoL outcomes across different studies.

The wide range of rare diseases covered in the studies, including genetic, neuromuscular, haematological, and respiratory disorders, highlights the need for targeted and condition-specific therapeutic approaches. Most studies reported an improvement in QoL after intervention, yet the magnitude of improvement was often disease-specific and intervention-dependent [11, 14]. For instance, surgical interventions, rehabilitation programmes, and pharmacological treatments each demonstrated varying degrees of success depending on the condition being treated [18, 25]. However, some studies reported minimal or no improvement, raising concerns about the adequacy of specific interventions for particular conditions, such as systemic sclerosis (SSc) or childhood interstitial lung disease (chILD) [26, 28]. The review also underscores the importance of considering patient demographics when evaluating treatment efficacy. For instance, differences in outcomes between paediatric and adult populations were noted, with some studies indicating better responses in children while others suggested more significant improvements in adult populations [38, 46]. Recent studies have also confirmed the impact of demographics on QoL outcomes. For instance, research by Szende et al. demonstrated that age and gender play crucial roles in how patients perceive their health status, with older patients typically reporting lower QoL even with the same scale [55]. These findings are consistent with our analysis, which identified demographic differences as a critical factor. A study by Forsyth et al. also showed that children and adolescents with haemophilia experience different psychosocial impacts than adults, leading to variability in HRQoL scores when assessed using the same scales [56]. This highlights the need for age-specific interventions and tailored QoL assessment strategies.

One of the most critical findings from this review is the variability in the assessment scales used across studies. While generic scales such as EQ-5D, SF-36, VAS, and PedsQL were frequently employed, the use of disease-specific scales in combination with generic tools often provided a more comprehensive evaluation of patients’ QoL. The EQ-5D scale, the most commonly used tool, demonstrated varying degrees of improvement across studies, from significant enhancements in all domains to minimal or no change depending on the intervention and disease context [12, 14]. In line with these differences, recent studies have highlighted that generic scales like SF-36 and EQ-5D often miss disease-specific symptoms, resulting in underreporting or over-generalisation of QoL [11, 57]. Aiyegbusi et al. also reported that their patients felt that the disease-specific scale was more relevant than the generic scale in assessing HRQoL in patients with RDs [58]. This variability suggests that while generic scales offer broad applicability, they may not fully capture the nuances of specific rare diseases, leading to inconclusive or inconsistent results.

Studies utilising disease-specific scales, such as the MG-QoL15r for myasthenia gravis or the EORTC QLQ-C30 for neuroendocrine tumours (NETs), provided more detailed insights into patient outcomes and highlighted areas where generic tools fall short [11, 13]. For example, in systemic sclerosis (SSc) patients, studies using both generic and disease-specific tools revealed divergent results, indicating that QoL improvements can be scale-sensitive and disease-dependent [17, 20]. This emphasises the need to develop and validate more disease-specific assessment tools tailored to the unique challenges faced by rare disease patients. In addition, psychological and social factors are consistently reported as significant influences on QoL. Studies by Wilson et al. and Shapiro et al. emphasise that mental health conditions, social support, and coping strategies can significantly affect HRQoL scores, even within the same patient group [39, 59]. These findings align with our analysis, which points out that differences in patients’ psychological states and social environments can explain variations in reported QoL improvements.

The psychometric properties of the HRQoL scales reviewed in this study differ based on their design and intended purpose. Generic scales, such as the EQ-5D and SF-36, exhibit high reliability and broad applicability; however, they show moderate responsiveness and have limitations in content validity when applied to rare diseases. Conversely, disease-specific scales like the MG-QoL15r and INQoL demonstrate high validity and responsiveness to disease-related changes, although they may lack the cross-disease comparability that generic scales offer [14, 25]. Thus, the psychometric characteristics of the scales examined emphasise the importance of contextually appropriate selection when assessing QoL in rare disease populations. Disease-specific scales are especially suited for clinical trials and longitudinal studies, as they effectively capture subtle changes related to the disease. In contrast, generic scales remain valuable for broader comparative studies and healthcare policy evaluations, where comparisons among diverse disease populations are necessary [1, 7]. It is, therefore, evident that employing a combined approach utilising both generic and disease-specific instruments may yield the most thorough evaluation of QoL in rare diseases.

The findings of this review carry significant implications for both clinical practice and future research. First, the variability in QoL outcomes suggests that standardised approaches may not be universally practical for all rare disease populations. Clinicians should be cautious when interpreting QoL improvements based solely on generic scales and should consider incorporating disease-specific tools where appropriate [28, 39]. Additionally, the disparities in outcomes across studies highlight the need for personalised treatment plans that account for individual patient characteristics, disease severity, and the specific intervention being applied.

This review underscores the importance of selecting appropriate measurement scales that align with the targeted condition for researchers. The inconsistencies in QoL reporting across studies indicate that further research is needed to develop more sensitive and reliable tools for assessing rare disease populations. Moreover, future studies should aim to standardise assessment methodologies while maintaining flexibility to accommodate the unique aspects of different rare diseases. This balance between standardisation and customisation is crucial for improving the consistency and comparability of research findings.

Limitations

While this review provides valuable insights, several limitations should be acknowledged. The included studies varied significantly in design, sample size, and duration, which may have influenced the generalisability of the results. Moreover, the dependence on self-reported quality of life measures introduces variability influenced by individual perceptions and cultural factors, which complicates comparisons across studies. Despite adopting a thorough search strategy, some studies may have been excluded due to unrecognised abbreviations or regional terminology that was not captured in the Medical Subject Headings (MeSH) terms. Lastly, the heterogeneity in disease types and interventions limits the ability to draw definitive conclusions about the most effective approaches for improving QoL in rare disease patients.

Conclusion

In conclusion, this systematic review highlights the complexity of evaluating HRQoL in rare disease populations. The diversity in study designs, disease types, interventions, and assessment scales presents both opportunities and challenges for improving patient outcomes. While many studies report improvements in QoL, the findings underscore the importance of using a combination of generic and disease-specific scales to capture the full spectrum of patient experiences. Future efforts should focus on developing and validating standardised HRQoL assessment frameworks that can accommodate the unique characteristics of rare diseases and provide meaningful data for clinical practice and research.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

6MWD/T:

6 min walk distance/test

AE-QoL:

Angioedema quality of life

CF:

Cystic fibrosis

CF-PedsQL GI:

Cystic fibrosis paediatric quality of life inventory gastrointestinal symptom scales

chILD:

Children with interstitial lung disease

chILD-QoL:

children interstitial lung disease quality of life

DMD:

Duchenne muscular dystrophy

EQ-5D-3L/5L:

Europe quality of life-5 dimension 3 level/5 level

FACIT:

Functional assessment of chronic illness therapy-fatigue

GAD-7:

Generalised anxiety disorder-7

GADS:

Generalised anxiety disorder scale

HAE:

Hereditary angioedema

HAE-QoL:

Hereditary angioedema quality of life

HADS:

Hospital anxiety and depression scale

HAQ-DI:

Health assessment questionnaire disability index

HRQoL:

Health-related quality of life

INQoL:

Individualised neuromuscular quality of life

MG:

Myasthenia gravis

MG-ADL:

Myasthenia gravis activity of daily living

MG-QoL-15r:

Myasthenia gravis quality of life 15-items revised version

MPS-HAQ:

Mucopolysaccharidosis health assessment questionnaire

Neuro-QoL:

Quality of life in neurological disorders

PBC-40:

Primary biliary cholangitis-40 items

PedsQL:

Paediatric quality of life inventory

PHQ-9:

Patient health questionnaire-9

PKAN:

Pantothenate kinase-associated neurodegeneration

QoL:

Quality of life

RCTs:

Randomised control trials

RDs:

Rare diseases

SF-12:

Short form health survey 12 items

SF-36:

Short form health survey 36 items

SSc:

Systemic sclerosis

VAS:

Visual analogue scale

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Acknowledgements

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Funding

National Natural Science Foundation of China (82260665).

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Authors and Affiliations

  1. Department of Paediatrics, Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524002, China

    John Sieh Dumbuya, Bashir Ahmad, Cizheng Zeng & Jun Lu

  2. Haikou Affiliated Hospital of Xiangya Medical College, Central South University, Haikou, 570208, China

    Xiuling Chen

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JL, BA and JSD conceptualised and designed the manuscript; XC and JSD data retrieval and initial analysis; and JSD, JL and BA critically reviewed and revised the manuscript. All the authors approved the final manuscript.

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Dumbuya, J.S., Ahmad, B., Zeng, C. et al. Assessing the effectiveness of measurement scales in evaluating the health-related quality of life in rare disease patients after treatment: a systematic review. Health Qual Life Outcomes 22, 108 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12955-024-02324-0

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12955-024-02324-0

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Health and Quality of Life Outcomes

ISSN: 1477-7525

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