Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy

Vandana Ayyar Gupta; Jacqueline M Pitchforth; Joana Domingos; Deborah Ridout; Mario Iodice; Catherine Rye; Mary Chesshyre; Amy Wolfe; Victoria Selby; Anna Mayhew; Elena S Mazzone; Valeria Ricotti; Jean-Yves Hogrel; Erik H Niks; Imelda de Groot; Laurent Servais; Volker Straub; Eugenio Mercuri; Adnan Y Manzur; Francesco Muntoni; on behalf of the iMDEX Consortium and the U.K. NorthStar Clinical Network

doi:10.1371/journal.pone.0283669

. 2023 Apr 26;18(4):e0283669. doi: 10.1371/journal.pone.0283669

Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy

Vandana Ayyar Gupta ^1,^#, Jacqueline M Pitchforth ^1,^#, Joana Domingos ¹, Deborah Ridout ^2,³, Mario Iodice ¹, Catherine Rye ¹, Mary Chesshyre ¹, Amy Wolfe ¹, Victoria Selby ¹, Anna Mayhew ⁴, Elena S Mazzone ⁵, Valeria Ricotti ^1,³, Jean-Yves Hogrel ⁶, Erik H Niks ^7,⁸, Imelda de Groot ⁹, Laurent Servais ^6,^10,¹¹, Volker Straub ⁴, Eugenio Mercuri ^5,¹², Adnan Y Manzur ¹, Francesco Muntoni ^1,^3,^*; on behalf of the iMDEX Consortium and the U.K. NorthStar Clinical Network^¶

Editor: Stephen E Alway¹³

¹UCL Great Ormond Street Institute of Child Health, Dubowitz Neuromuscular Centre, Great Ormond Street Hospital for Children, London, United Kingdom

²Population, Policy & Practice Research and Teaching Department, UCL Great Ormond Street (GOS) Institute of Child Health, London, United Kingdom

³NIHR Great Ormond Street Hospital Biomedical Research Centre, London, United Kingdom

⁴The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom

⁵Child Neurology Unite Centro Nemo, IRCCS Fondazione Policlinico Gemelli, Universita Cattolica del Sacro Cuore, Rome, Italy

⁶Institute of Myology, Paris, France

⁷Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands

⁸European Reference Network for Rare Neuromuscular Diseases – ERN EURO NMD

⁹Department of Rehabilitation, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands

¹⁰Division of Child Neurology, Reference Center for Neuromuscular Disease, Centre Hospitalier Régional de Références des Maladies Neuromusculaires, Department of Paediatrics, University Hospital Liège & University of La Citadelle, Liège, Belgium

¹¹Department of Paediatrics, MDUK Neuromuscular Center, University of Oxford, Oxford, United Kingdom

¹²Child Neurology Unit, Universita Cattolica del Sacro Cuore, Rome, Italy

¹³University of Tennessee Health Science Center College of Graduate Health Sciences, UNITED STATES

Competing Interests: E.H.Niks report grants from Spieren voor Spieren, Duchenne Parent Project, ZonMW, AFM and PPMD. He has been site principal investigator for clinical trials conducted by BioMarin, GSK, Eli Lilly, Santhera Pharmaceuticals, Italfarmaco SpA, Roche Pharma, Reveragen, NS Pharma, Fibrogen, Sarepta, Alexion, Janssen and Argnx outside the submitted work. He also reports ad hoc consultancies for BioMarin, Summit, PTC therapeutics, WAVE Life Sciences, Edgewise, Epirium Bio, Janssen, Sarepta and Regenxbio. All reimbursements were received by the LUMC. No personal financial benefits were received. I.de Groot has received consulting and education fees from PTC Therapeutics, Santhera, Biomarin/Prosensa. J-Y.Hogrel has received consulting fees from Biogen, Sarepta, Minoryx and Roche. L.Servais has received consulting fees from Roche, Biogen, Avexis, Cytokinetics, Sarepta, Biomarin, Santhera, Servier, Biophytis and Dynacure. He is coordinating natural history studies funded by Valerion, Dynacure and Roche. A.Mayhew has received consulting fees from Roche, Novartis (Avexis), Biogen, Rehenxbio, PTC, BMS/Roche, Sarepta, Italfarmaco, Pfizer, Summit, Catabasis, Santhera, Vision, Mallinckrodt, Lysogen, Modis and Wave. V.Straub received speaker honoraria from Sanofi Genzyme and has participated in advisory boards for Audentes Therapeutics, Biogen, AveXis, Pharmaceuticals, Pfizer, Roche, Sanofi Genzyme, Sarepta Therapeutics, Summit Therapeutics and Wave Therapeutics. V.Ricotti is co-founder, EVP, CMO of DiNAQOR, and served as a consultant for Solid Biosciences and Antisense Therapeutics. F.Muntoni reports grants from Sarepta, grants from Wave, grants from PTC Therapeutics, personal fees from Avexis, Roche, Pfizer, Dyne Therapeutics, Sarepta, outside the submitted work. M.Chesshyre has had the costs associated with attending a conference (including travel, accommodation, conference fee, food and drink) funded by PTC Therapeutics. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

¶ Membership of the iMDEX Consortium and the U.K. NorthStar Clinical Network is provided in the Acknowledgments.

^✉

* E-mail: f.muntoni@ucl.ac.uk

Contributed equally.

Roles

Vandana Ayyar Gupta: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Visualization, Writing – original draft

Jacqueline M Pitchforth: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft

Joana Domingos: Conceptualization, Methodology

Deborah Ridout: Data curation, Formal analysis, Methodology, Visualization, Writing – review & editing

Mario Iodice: Investigation, Project administration, Writing – review & editing

Catherine Rye: Investigation, Project administration, Writing – review & editing

Mary Chesshyre: Methodology, Project administration, Writing – review & editing

Amy Wolfe: Investigation, Project administration, Writing – review & editing

Victoria Selby: Methodology, Writing – review & editing

Anna Mayhew: Conceptualization, Methodology, Supervision, Writing – review & editing

Elena S Mazzone: Conceptualization, Methodology, Writing – review & editing

Valeria Ricotti: Conceptualization, Writing – review & editing

Jean-Yves Hogrel: Methodology, Writing – review & editing

Erik H Niks: Writing – review & editing

Imelda de Groot: Writing – review & editing

Laurent Servais: Supervision, Writing – review & editing

Volker Straub: Writing – review & editing

Eugenio Mercuri: Conceptualization, Writing – review & editing

Adnan Y Manzur: Conceptualization, Writing – review & editing

Francesco Muntoni: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing

Stephen E Alway: Editor

PMCID: PMC10132589 PMID: 37099511

Abstract

The North Star ambulatory assessment (NSAA) is a functional motor outcome measure in Duchenne muscular dystrophy (DMD), widely used in clinical trials and natural history studies, as well as in clinical practice. However, little has been reported on the minimal clinically important difference (MCID) of the NSAA. The lack of established MCID estimates for NSAA presents challenges in interpreting the significance of the results of this outcome measure in clinical trials, natural history studies and clinical practice. Combining statistical approaches and patient perspectives, this study estimated MCID for NSAA using distribution-based estimates of 1/3 standard deviation (SD) and standard error of measurement (SEM), an anchor-based approach, with six-minute walk distance (6MWD) as the anchor, and evaluation of patient and parent perception using participant-tailored questionnaires. The MCID for NSAA in boys with DMD aged 7 to 10 years based on 1/3 SD ranged from 2.3–2.9 points, and that on SEM ranged from 2.9–3.5 points. Anchored on the 6MWD, the MCID for NSAA was estimated as 3.5 points. When the impact on functional abilities was considered using participant response questionnaires, patients and parent perceived a complete loss of function in a single item or deterioration of function in one to two items of the assessment as an important change. Our study examines MCID estimates for total NSAA scores using multiple approaches, including the impact of patient and parent perspective on within scale changes in items based on complete loss of function and deterioration of function, and provides new insight on evaluation of differences in these widely used outcome measure in DMD.

Introduction

Duchenne Muscular Dystrophy (DMD) is an X-linked recessive neuromuscular disorder caused by mutations in the DMD gene leading to loss of the dystrophin protein. This leads to progressive loss of motor function with eventual loss of the ability to walk, progressing to respiratory insufficiency, cardiomyopathy and premature death [1]. DMD affects 19.5 cases per 100,000 live births in the UK and is one of the most common forms of neuromuscular disease in childhood [2].

Currently, the mainstay of pharmacological treatment for DMD outside of clinical trials and managed access agreements is glucocorticoids. However, there has been significant progress in the development of novel therapeutic agents for DMD. In recent years, mutation specific therapies such as Ataluren and the antisense oligonucleotides Eteplirsen, Golodirsen and Viltolarsen and Casimersen have been successful in receiving regulatory approvals in the EU (Ataluren) and in the USA (the oligonucleotides) [3–5]. Furthermore, several other therapies targeting the primary defect in DMD such as gene replacement viral therapies, small molecules to induce exon skipping of out-of-frame deletions, or to induce read-through non-sense mutations as well as addressing the secondary consequences of the disease are in various stages of clinical testing or have received conditional approval in various countries. The rapid advance in the field of DMD therapeutics has highlighted the importance of validated outcome measures that can capture treatment efficacy in ambulant and non-ambulant DMD patients.

The North Star Ambulatory Assessment (NSAA) [6] is a widely used and validated tools for the measurement of motor function in children with DMD. In addition to its use in clinical practice in many countries, this measure is widely used to assess functional motor outcomes in clinical trials and natural history studies. Several ongoing clinical trials use the NSAA as a primary outcome measure [7–9].

The NSAA is a DMD-specific, physiotherapist administered assessment scale measuring lower limb function in ambulant children with DMD. It consists of 17 items scored on a scale of 0–2; a score of 2 indicating the activity is performed without difficulty, 1 indicating the activity is performed with some compensation and a score of 0 indicating that the child cannot perform the activity independently (S2 Appendix). In the natural course of the disease, the scores in this assessment scale demonstrate an upward trajectory with improvements up to the age of six years, followed by an average decline of approximately 3.7 units/year after seven years of age [10]. Studies have also shown a wide range of scores reflecting heterogeneity in disease progression such that important factors when interpreting an individual NSAA scores are not only age, but also scores at previous assessments, enabling better interpretation of functional trajectory [11].

The increasing use of NSAA in clinical practice, clinical trials and natural history studies highlight the need to ascertain clinically relevant threshold values for these outcomes that relate to patient and parent perception of a meaningful change. Limitations of interpreting measures of statistical significance in isolation are widely known and there is a substantial body of work on methods to estimate thresholds such as minimum clinically important difference (MCID) of clinical outcome measures. However, there is very limited work on the evaluation of meaningful changes for these outcomes in the context of DMD research for both clinical trials evaluating novel therapies and exploratory studies using observational data to predict natural disease trajectories. This poses challenges in the interpretation of clinical trial results and developing adequately powered clinical trials, with implications for patients, clinicians, policy makers and commercial stakeholders. This necessitates the careful evaluation of a meaningful change in the outcome measures used that truly captures the aspects of disease progression of marked significance to patients and their families. An additional complexity when considering meaningful changes for DMD relates to the fact that many current clinical trials in this rapidly progressing disease are aimed at slowing disease progression rather than an improvement of motor function, thus magnifying the need for interpreting a meaningful change in maintenance or loss of motor function from a patient and parent perspective.

The concept of minimum clinically important difference (MCID) evolved to address the inference of a ‘statistically significant difference’ in relation to a clinically meaningful change. Originally described by Jaeschke et al. [12], MCID refers to the smallest difference in scores that patients perceive as beneficial to mandate a change in management, in absence of troublesome side effects and excessive cost.

Several statistical approaches to estimating the MCID for outcome measures have been recommended over the years and are broadly grouped into ‘distribution based’ and ‘anchor based’ methods. While each approach aims at measuring a quantifiable change in outcome, the type of change and perspective of change varies with each approach used [13]. For example, in anchor-based methods, the change in outcomes is compared to a change in another measure used as an external criterion or ‘anchor’ and estimations would depend on the type of anchor used and the association between the anchor and the outcome of interest. In distribution-based methods, change in outcome is compared to measures such as standard error of measurement (SEM), standard deviation (SD) or effect size and depends on the measure of variability that is chosen. Limitations of using a single approach to determining MCID are widely known, an important limitation being the lack of patient perspective itself in the estimation of MCID. Recommendations have therefore been made to combine statistically derived metrics, clinical data and patient insight to derive estimates which are empirically sound and clinically relevant [13–15].

In DMD, using a distribution-based approach with SD and effect size, previous research has suggested a minimally important difference for the NSAA as 10 units on a linearised scale [16]. Evaluation of meaningful change in NSAA, using a combined statistical and patient/parent-based approach to include patient and parent perspective on different functional implications of decline has not been previously evaluated.

The current study aims to evaluate important and meaningful changes in NSAA scores using statistical techniques and participant tailored questionnaires to capture patient and parent perspective of a meaningful change in NSAA. In addition, the study explores patients’ and parents’ perspective on their minimum requirements for change in motor function that would influence their participation in a clinical trial.

Methods

The following approaches were used to estimate MCID in this study:

Distribution based approach
Anchor based approach
Single visit participant tailored questionnaire to understand and capture patient and parent perspective of a meaningful change

1. Distribution based approach

Data from the iMDEX natural history study (ClinicalTrials.gov Identifier: NCT02780492), funded by the Association Francaise contre les Myopathies (AFM) and data from the U.K. NorthStar Clinical Network, a U.K. wide network for the collection of clinical data for DMD (NND, National Neuromuscular Database) was used to estimate MCID for the NSAA.

Based on previous reports of MCID for motor outcomes in DMD [16, 17] and evidence of an average decline in NSAA from the age of seven years [10], MCID was evaluated using two distribution measures [18–20]: 1) one-third standard deviation (SD) of baseline scores for ambulant boys with DMD from the age of seven years within a paediatric cohort and 2) 1 SEM calculated as SD as baseline x (square root of 1 –internal consistency of the scale). Evaluation of test-retest reliability for NSAA using a standardised training protocol in a younger cohort of boys between 4 to 7 years of age, to assess the variability of pre-treatment assessments and effect of learning and age dependence, reported an Intraclass correlation coefficient (ICC) of 0.84 [21]. We used this observed ICC for the calculation of SEM in this study.

The NSAA linearised scale (interval level data, scoring from 0 to 100) is a transformation of the original NSAA raw scale (ordinal level data, scoring from 0–34), which allows for equivalent clinical interpretation per unit change, across the full range of the scale [16]. While use of the linearised scale is limited currently, we present the MCID estimated for both raw and linearised NSAA scale.

Previous evaluation of six minute walk distance (6MWD) in ambulant boys with DMD between the ages of 5 and 20 years reports an MCID based on 1/3 of baseline SD as 30m [17]. In the present study, we present MCID based on 1/3 SD on first available 6MWD assessment after the age of 7 years. The 6MWD data in this study was only available from the iMDEX natural history study. The patient characteristics of the cohort for whom the 6MWD data was available for this study was representative of patient characteristics in the wider iMDEX natural history cohort.

2. Anchor based approach

Using an annual decline of 6MWD of 30m as an anchor, the annual decline in NSAA was evaluated using an anchor-based approach from the data available from the iMDEX natural history study.

Statistical analysis for the distribution and anchor approaches were performed using Stata v15.

3. Participant tailored questionnaire

A descriptive study was conducted to capture patient and parent perspectives on change in NSAA scores, which they deem as meaningful. We also asked parents and patients regarding their minimum requirements for change in motor function for participation in a clinical trial.

Potential participants were identified from the cohort of DMD patients at the Great Ormond Street Hospital for Children. Interested participants were given the study information sheet and informed written consent was taken prior to the interviews and administering the questionnaires.

These responses were captured during a face-to-face interview with participating parents and patients using a participant-tailored questionnaire (S1 Appendix) at a single visit. The questionnaire was tailored to each patient, with the patient’s current NSAA functional assessment score prepopulated prior to administration. If a recent score (within one month of this visit) was unavailable, the NSAA assessment was undertaken prior to administering the participant questionnaire. Participating parents and patients of the same family were interviewed separately to minimise bias in responses.

Recruitment for the participant questionnaire for NSAA included patients with DMD from the age of 10 years and parents of boys with DMD from the age of 7 years with an NSAA assessment completed within the previous month.

NHS Health Research Authority (NHS South West-Exeter Research Ethics Committee, ref: 17/SW/0213) granted ethical approval for this study.

Construction of participant questionnaires

The Delphi technique was used to derive the participant tailored questionnaires of patient and parent perspective of meaningful changes in the NSAA. Three research centres with neuromuscular expertise (University College London, Newcastle University and Università Cattolica del Sacro Cuore, Rome) contributed to the Delphi process. The questionnaires were drafted over several rounds of the Delphi technique, and included input from families of boys with DMD, leading to construction of the final versions of the questionnaire (S1 Appendix) administered in this study.

Each participant questionnaire consisted of the following key sections:

Current mobility status and expectation of change in mobility status over the next two years.
Perception of meaningful change based on the scores of the recent NSAA assessment.
Minimum requirements of motor function changes to want participation in a clinical trial for a period of two years.

a) Current mobility status and expectations over next 2 years:

Patients and parents were asked to indicate the current mobility status of the patient and how they expected mobility to change in the next 2 years.

b) Perception of meaningful change in scores:

The NSAA assessment monitors the course of the disease as a change in the item scores in subsequent assessments, such that:

Change from 2 to 1 in an item score indicates ‘deterioration’ of a function.
Change from 1 to 0 in an item score indicates ‘loss’ of a function.

The most recent NSAA assessment of the patient was prepopulated in the questionnaire prior to administration, to indicate total scores, and list items for which the patient scored 2 or scored 1. Thus, each administered questionnaire was tailored for responses based on the patient most recent performance on the scale. Based on this recent assessment and perception of a significant or meaningful change in their/their child’s daily life, participants were asked:

The minimum number of items for which the score should not change from 2 to 1, i.e., ‘deterioration’ of function is prevented and,
The minimum number of items for which the score should not change from 1 to 0, i.e., ‘loss’ of function is prevented.

The responses for these questions were then collected as ‘at least 1 item’, ‘at least 2 items’ or ‘more than 2 items’.

c) Participation in a clinical trial:

Participants were also asked regarding their minimum requirement for enrolling into a clinical trial lasting two years on the following three criteria:

Slowing of decline in motor function–minimum number of items to have a slowing of decline that would be considered as sufficient for participating in a clinical trial
Improve motor function—minimum number of items having an improvement of function that would be considered as sufficient for participating in a clinical trial
Stop any decline in motor function.

Responses were collected as slow decline, stop decline or improve motor function. If the minimum requirement was for slowing decline of a function or of improving motor function, participants were asked the minimum number of items in their current assessment having a slowing of decline or improvement in motor function that they would consider as sufficient for participation in a clinical trial.

Evaluation of responses

Summary of collated responses from the participant questionnaires are presented as frequencies for perception of minimal change in scores that are significant and minimum requirement for participation in a clinical trial. The overall minimum change in scores that are significant or meaningful as perceived by patients and parents was estimated by majority response.

Results

The study cohort includes boys born between 1996 and 2014, with physiotherapy assessments (including NSAA assessments) between 2005 and 2020. Patient characteristics for the study cohort are show in Table 1.

Table 1. Patient characteristics at first NSAA assessment.

Patient characteristics	n = 663
Age in years
Mean (SD)	7.8 (1.1)
Range	6.5–10.5
Age at diagnosis, n = 280
Mean (SD)	3.6 (2.1)
Corticosteroid-treated, n = 661
n (%)	627 (94.9)
Corticosteroid regime, n = 627
Daily, n (%)	333 (53.1)
Intermittent, n (%)	264 (42.1)
Regime unknown, n (%)	30 (4.8)
DMD genotype, n = 624,
Deletion, n (%)	414 (66.3)
Duplication, n (%)	66 (10.6)
Point mutation, n (%)	110 (17.6)
Other or unknown mutation, n (%)	34 (5.4)
First available total NSAA score
Mean (SD)	22.5 (7.8)
Range	2–34
First available Linear total NSAA score
Mean (SD)	62.1 (17.9)
Range	0–100
Baseline 6MWD, n = 31
Mean (SD)	380.1 (79)

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In the first column, n indicates the total number for which data is available for a characteristic, where different from the total cohort of 663. Percentage reflect percentage within the data available for a characteristic.

Distribution based approach

The MCID was estimated from the NSAA scores of 663 ambulant boys, between the ages of 7 to 10 years. Table 2 presents MCID for NSAA for each age range. Based on a calculation of 1/3 SD of observed baseline values, the estimated MCIDs for NSAA ranged from 2.3 to 2.9 points representing 9.6% to 15.2% of the mean NSAA. On a linearised scale, the MCID ranged from 5.6 to 6.8 points corresponding to 8.3%–12.6% of the mean (Table 3).

Table 2. Estimates of MCID for NSAA (raw score) and 6MWD based on distribution methods.

NSAA
Age (years)	N	Mean (SD)	Method	MCID	MCID/Mean^a
7	338	23.9 (6.9)	1/3 SD	2.3	9.6%
7	338	23.9 (6.9)	SEM	2.9	11.6%
8	350	22.6 (7.7)	1/3 SD	2.6	11.4%
8	350	22.6 (7.7)	SEM	3.1	13.7%
9	306	20.8 (8.8)	1/3 SD	2.9	14.1%
9	306	20.8 (8.8)	SEM	3.5	16.9%
10	249	19.4 (8.8)	1/3 SD	2.9	15.2%
10	249	19.4 (8.8)	SEM	3.5	18.2%
6MWD
Mean Age (SD)	N	Mean (SD)	Method	MCID	MCID/Mean
7.6 (1.1)	31	380.1 (79)	1/3 SD	26.3	6.9%

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The MCID corresponding to 1/3 SD is the MCID estimated from one-third of standard deviation; MCID corresponding to SEM is the MCID estimated from standard error of measurement.

The MCID for the NSAA total scores is presented for 4 different age bands (7 years, 8 years, 9 years, and 10 years). Each age band correspond to age +/- 6 months with assessment closest to the mid-point used.

^aMCID/Mean refers to the MCID when expressed as a % of the mean of this outcome for the population.

Table 3. Estimates of MCID for NSAA (linearized scale) based on distribution methods.

NSAA
Age (years)	N	Mean (SD)	Method	MCID	MCID/Mean^a
7	338	64.8 (16.2)	1/3 SD	5.6	8.3
7	338	64.8 (16.2)	SEM	6.5	10.0
8	350	61.9 (18.0)	1/3 SD	6.0	9.7
8	350	61.9 (18.0)	SEM	7.2	11.6
9	306	57.7 (20.1)	1/3 SD	6.7	11.6
9	306	57.7 (20.1)	SEM	8.1	14.0
10	249	54.1 (20.4)	1/3 SD	6.8	12.6
10	249	54.1 (20.4)	SEM	8.2	15.1

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The MCID corresponding to 1/3 SD is the MCID estimated from one-third of standard deviation; MCID corresponding to SEM is the MCID estimated from standard error of measurement.

^aMCID/Mean refers to the MCID when expressed as a % of the mean of this outcome for the population

Based on a calculation of standard error of measurement (SEM) of the observed values, the MCID ranges from 2.9 to 3.5 points representing 11.6% to 18.2% of the mean NSAA. On a linearised scale, the MCID ranged from 6.5 to 8.2 points representing 10% to 15.1% of the mean.

Based on the observed 6MWD values for first visit after age 7 years in 31 patients, the estimated MCID using 1/3 of SD was 26.3m.

Anchor based approach, NSAA

Based on 36 non-overlapping observed annual changes in 24 boys above the ages of 7 years, a positive correlation of 0.50 (p = 0.002) was observed between change in NSAA and change in 6MWD (Fig 1). Using mixed methods regression analysis to account for multiple changes per patient and the previously reported MCID for 6MWD as a decline of 30m [17], the equivalent decline in NSAA was observed as -3.5 points (95% CI = -1.9, -5.0).

Participant questionnaires, NSAA

Forty participant questionnaires were completed for 33 boys in this study. These included responses from 7 boys and 33 parents. The 33 parent responses included those from 7 parents of the participating boys. Patient characteristics and perceived mobility status for this group is shown in Table 4.

Table 4. Patient (boys with DMD) characteristics and perceived mobility status.

Total number of questionnaires completed	40
Number of questionnaires completed by a boy with DMD	7
Number of questionnaires completed by a parent (including 7 parents of the 7 participating boys)	33
Mean age (SD) of boys with DMD in years	10.2 (2.1)
Mean NSAA (SD) for NSAA total raw score	19.6 (9.5)
Participant perception of mobility status	Boys N = 7	Parents N = 33
Current mobility status
Walk >1 km	3	11
Walk ≤ 1 km	3^a	9
Walk short distances only	1	10
Walk indoors only	0	3
Perception of current mobility compared to last year
Deteriorated	3	17
Remained stable	3^b	12
Improved	1^c	4
Expectation of change in mobility over the next two years
Deterioration	4	27
Stability	3^d	5
Improvement	0	1

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^a. 1 boy noted current ability to walk ≤ 1 km, and their parent noted short distances only

^b. 1 boy noted remaining stable, and their parent noted deteriorated

^c. 1 boy noted improved, and their parent noted remained stable

^d. 2 boys noted stability and their parents’ noted deterioration

Prior to questions regarding meaningful change in NSAA scores, participants were asked questions regarding their perception of current mobility status compared to the previous year, expectations over the next two years and the three key activities that they felt were most important to maintain in their lives. Compared to their or their child’s mobility in the previous year, most patients and parents felt that they either had deteriorated (50% of participants) or had remained stable (37.5% of participants), but their expectation was largely of deterioration in mobility and function over the next two years (77.5% of participants) (Table 4). General mobility (walking and stair climbing), sporting activities (running, swimming and playing with siblings) and self-care (independently dressing and eating) were the three key areas that were important for the participants to maintain.

With regards to the prevention of loss of function, 57.5% (23/40) of participants required a minimum of 1 item to be prevented from changing from a score of 1 to a score of 0 to deem a meaningful change (Fig 2). In addition, with regards to the maintenance of function, 38% (14/37) of participants required a minimum of maintaining a score of 2 in at least one sub-item to deem a meaningful change and 38% (14/37) of participants required maintaining a score of 2 in at least two sub-items to deem a meaningful change (Fig 3). Three parents did not respond to the question on minimum number of items for maintaining a score of 2 as their child had a maximum score of 1 for any item on the NSAA.

Fig 2 — Distribution of participant responses for significant change as minimum number of items on NSAA for preventing loss of activity (i.e., preventing a change in score from 1 to 0). The x-axis represents minimum number of sub items for which prevention of loss of function was meaningful for a parent (red) and for a patient with DMD (blue).

Fig 3 — Distribution of participant responses for significant change as minimum number of items on NSAA for maintenance of function (i.e., preventing a change in score from 2 to 1). The x-axis represents minimum number of sub items for which maintaining the activity was meaningful for a parent (red) and for a patient with DMD (blue).

We observed similar responses from boys and their parent within the 14 responses from the 7 pairs of participating boys and their parent. We did observe small differences in 3 pairs. One boy required preventing loss of function (change of 1 to 0) in 2 activities while the parent required that in 3 activities. One boy required maintenance of function (change of 2 to 1) in at least 2 activities while the parent required that for 3 activities. One boy required maintenance of function (change of 2 to 1) in at least 2 activities while the parent required that for 1 activity.

For the majority of participants, the prevention of the loss of function in at least one item was deemed important for a meaningful change. With regards to maintaining a particular function, one third of participants stated the importance of maintaining good function in at least 1 item as being clinically important, another third stated the importance of maintaining good function in at least 2 items and for the remain third maintaining good function in at least 3 items was important.

Trial participation

Most parents (26/33) required a ‘slowing decline’ in function for at least of 1 item on the NSAA scale as a minimum outcome that they would consider as sufficient for participating in a clinical trial lasting two years. Fig 4 represents the frequency of response for minimum requirement for a trial participation for NSAA.

Discussion

The North Star Ambulatory assessment is a functional outcome measure that is widely used in clinical trial and clinical monitoring of patients with Duchenne Muscular Dystrophy. In this study, we aimed to evaluate and understand minimal clinically important changes using multiple approaches for NSAA scores in ambulant boys with DMD from the age of 7 years.

Our statistical approach included two distribution estimates of MCID: 1) 1/3 standard deviation, which estimated MCID ranging from 2.3 to 2.9 points on the raw NSAA scale and 5.6–6.8 points on the linearised NSAA scale for age ranges 7–10 years, and 2) One standard error of measurement which estimated MCID ranging from 2.9–3.5 points on the raw NSAA scale and 6.5–8.2 points on the linearised NSAA scale for age ranges 7–10 years. Using the six-minute walk distance as an anchor, a previously reported MCID of 30m for this anchor corresponded to a change of 3.5 points on the raw NSAA scale for boys with DMD above the age of 7 years.

Separate to the above methods to evaluate minimal changes in total NSAA scores, our participant questionnaire approach sought to evaluate changes within the scale on individual item scores. This study’s participant responses from boys with DMD and parents of boys between 7–13 years indicated the change in an item score to zero (complete loss of item) and change in an item score to 1 (reduced ability to perform the item activity) for a minimum of 1 or 2 items as having a meaningful or significant impact on their quality of life for age range 7–13 years. The items in question would depend on a boy’s level of ability.

In addition, we also asked families and patients what they would consider as the minimal significant change in NSAA for participating in a clinical trial lasting two years. Our study finds that boys with DMD and parents required slowing of decline in 1 item of the NSAA as a minimum requirement to warrant their participation in a clinical trial in which no serious adverse event would occur, lasting two years. The study responses showed overall concordance between responses from affected boys and their parents; differences in 3 patient-parent responses suggests that at least in these families affected boys have a lower threshold for assigning a meaningful change compared to their parents.

Our study uses different approaches on two aspects of the NSAA, for total score and the perception of changes as loss of activity and deterioration of activity within the scale. Being conceptually different, the estimates of a minimal change on total score by one method cannot be taken in isolation. Distribution measures while established as proxy for MCID, are patient/parent agnostic. In this study we use a clinical measure, 6MWD, as an anchor and thus limited in being patient agnostic.

For this study, we wanted to capture differences between complete loss of function (i.e., a score of 0 in the NSAA) and partially compromised function (i.e., a score of 1 in the NSAA), an aspect which was incorporated during the development of the participant questionnaires administered in this study. Indeed, an identical numerical change in the total NSAA score could reflect different patterns of disease progression. For example, a patient losing 4 points in the NSAA total score, could have completely lost function for two items (score changing from 2 to 0 for two items) or alternatively partially lost function in 4 items (score changing from 2 to 1 for four items). The idea that the difference between complete and partial loss of function could be clinically meaningful for patients was originally hypothesised by McDonald et al. [4], but the implication of this hypothesis and subsequent implications for study assessments, has not been examined. Our participant questionnaires indicated that patients and parent perceived a differential impact of a complete loss of function and partial loss in function such that preventing complete loss of one activity (item on the scale) and preventing partial loss (deterioration) in two activities would have a significant impact. Like the distribution and anchor-based methods for minimal changes in total score, implication of perceived difference in partial and complete loss of function items on minimal significant change should be interpreted with caution, carefully considering the scale reliability, burden of intervention and safety of the therapy.

Comparison with other studies

Using a sample of 198 males with DMD between the ages of 4–18 years, Mayhew et al. [16] calculated the minimal important difference after transforming the raw NSAA score (ordinal scale, 0–34) into a linearised version of the NSAA (interval scale, 0–100) to allow for a better interpretation of change in scores than from an ordinal scale. Based on a calculation from 0.5 SD, a 10 unit (ranging between 7 and 14) on the linearised NSAA scale was estimated to be a minimally important difference for males with DMD at different levels of ability. This study presents the MCID for linearised NSAA estimated in this study is based on a calculation of 1/3SD and ranges from 5.5 to 7.3 for ages between 7 and 10 years. Based on a calculation of 0.5 SD similar to Mayhew et al. [16] in our cohort, estimated MCID for linearised NSAA ranged from 7.8 to 12.1 for ages between 7 and 10 years.

Strengths and limitations of the study

By incorporating patient and parent perspectives, in addition to statistical approaches to estimate MCID, this study finds that patient and parent perception of minimal change in scores gives valuable additional insight into the patterns of change in motor function that are considered clinically meaningful compared to the use of statistical approaches alone, which has not been previously reported.

The age group of focus for our participant questionnaire evaluation was from 7 years for NSAA, age ranges in which natural history studies have demonstrated it can be expected that there will be a plateau or decline in function as measured by these outcome measures. The higher MCID values for higher ages reported for the distribution-based method also reflect increasing heterogeneity in disease affection from age 7 thus a mathematically higher MCID. Our findings from the questionnaires reflect perceptions during this stage of the disease with the possibility that changes smaller in numerical value than those evaluated by statistical methods are felt more keenly. The minimal requirement for trial participation for a period of two years in this study also adds to the possibility that once functional decline starts, the sensitivity to minimal changes is heightened.

The NSAA scale has been validated in children above 5 years and therefore this study does not capture changes in children between 5 and 7 years. Our study group is slightly older with a fuller understanding of their condition and who have already experienced some loss of function. We expect the changes and perception of changes in younger children who have not yet experienced deterioration or loss of function will be different. Given that recruitment into clinical trials for some therapies is at a younger age, this evaluation in younger patients would be of benefit in future studies. Similarly, future evaluation in older patients for relevant outcome measures such as Performance of Upper Limb (PUL) would be beneficial.

This study was unable to provide age based MCID estimates for 6MWD due to limited data and use of a previously published single MCID estimate for 6MWD [17] in our anchor approach. For the questionnaire study, we had limited number of responses particularly from affected boys.

The distinction between loss of function and deterioration in function has been applied to analysis of drug efficacy and has been of focus in recent trial reports in an attempt that these may be more sensitive to demonstrating a treatment effect compared to change in total score over time. Such an approach was used in the reporting of a phase 3 clinical trial assessing the efficacy of Ataluren [4]. A post-hoc analysis after 48 weeks demonstrated that patients given ataluren lost 12.2% of functions in the NSAA compared with 17.8% in the placebo group. Similarly, an exploratory analysis for a phase 2 placebo control trial of Domagrozumab in boys with DMD presented an exploratory analysis of number of NSAA skills gained on individual items (score change from 0 to 1 or 2) or lost (change from 1 or 2 to 0) between treatment groups as well as cumulative loss of function over time [22].

Conclusion

This study presents an evaluation of the MCID for NSAA in boys with DMD from 7 years of age using statistical approaches and patient/parent perspectives on minimal significant changes. Our study highlights careful interpretation of MCID after considering underlying conceptual differences and heterogeneity of the disease. We demonstrate that while the statistical methods we used to estimate the MCID provide an estimate of the MCID of the total NSAA, additional use of a patient and parent based approach allowed us to differentiate within scale changes based on loss of ability to complete an item in the assessment and the reduced ability to complete the item in the assessment. These findings provide insight on the value of assessing NSAA scores not only as total scores, but also in considering the different implications of reduced ability in function and a complete loss of function, as has been suggested previously [4, 22] for better interpretation of disease progression from these measures which includes the perspective of the family.

Supporting information

S1 Appendix. Participant tailored questionnaire.

(DOCX)

Click here for additional data file.^{(64.5KB, docx)}

S2 Appendix. NSAA questionnaire manual.

(PDF)

Click here for additional data file.^{(710.5KB, pdf)}

Acknowledgments

The data for the cohorts in this study were gratefully received from the iMDEX natural history study funded by Association Française contre les Myopathies and from the U.K. NorthStar Clinical Network funded by Muscular Dystrophy U.K. Several members of the iMDEX consortium are members of the European Reference Network for Neuromuscular Diseases (EURO-NMD)

The authors would like to pay tribute to the memory of Joana Pisco Domingos, who was suddenly deceased in early January 2018

Members of the iMDEX working group include:

Dubowitz Neuromuscular Centre, UCL Great Ormond Street Institute of Child Health, London: Lianne Abbott, Efthymia Panagiotopoulou, Mario Iodice and Maria Ash.

Radboud University Medical Centre, Nijmegen: Merel Jansen, Maaike Pelsma and Marian Bobbert.

Leiden University Medical Centre, Leiden: Menno Van Der Holst PhD (Department of Orthopaedics, Rehabilitation and Physiotherapy), Yvonne D Krom PhD (Department of Neurology) and Marjolein J van Heur-Neuman (Department of Neurology).

Institute of Myology, Paris: Dr Silvana De Lucia, Professor Thomas Voit (current affiliations^1,3), Valérie Decostre and Stéphanie Gilabert.

John Walton Muscular Dystrophy Research Centre, Newcastle: Michela Guglieri and Alexander Murphy

Participating centres in the The UK NorthStar Clinical network include:

Dubowitz Neuromuscular Centre, Great Ormond Street Hospital for Children NHS Trust, London:

Prof. F. Muntoni, Dr. A. Y. Manzur, M. Main,

McCallum Institute of Human Genetics, John Walton Muscular Dystrophy Research Centre, Newcastle: Prof. V. Straub, Dr. M. Guglieri, Dr. A. Mayhew

University Hospitals Birmingham NHS Foundation Trust: Dr. D. Parasuraman, Dr Z. Alhaswani H. McMurchie, R. M. Rabb,

Yorkshire Regional Muscle Clinic, Leeds General Infirmary: Dr. A. Childs, Dr. K. Pysden, L. Pallant,

Alder Hey Children’s NHS Foundation Trust, Liverpool: Dr. S. Spinty, Dr. R. Madhu, A. J. Shillington,

Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust: Dr. E. Wraige, Prof. H. Jungbluth, V. Gowda, J. Sheehan, F. Vann

Royal Manchester Children’s Hospital, Manchester: Dr. I. Hughes, E. Bateman, C. Cammiss,

Robert Jones and Agnes Hunt Orthopaedic Hospital NHS Foundation Trust, Oswestry: Dr. T. Willis, L. Groves, N. Emery.

Sheffield Children’s Hospital NHS Foundation Trust: Dr. P. Baxter, Dr. M. T. Ong, N. Goulborne, M. Senior.

Cardiff and Vale University Health Board: C. White, L. B. Parsons,

Bristol Royal Hospital for Children, University Hospitals Bristol NHS Foundation Trust: Dr. A. Majumdar, Dr. K. Vijaykumar, F. F. Mason, L. Jenkins, B. Toms.

University Hospitals Plymouth NHS Trust: Claire Hazel Frimpong-Ansah.

Kings Cross Hospital, Dundee: Dr. K. Naismith, J. Dalgleish, A. Keddie

Dunne Royal Hospital for Children, NHS Greater Glasgow and Clyde: Dr. I. Horrocks, M. Di Marco, J.

Nottingham University Hospitals: Dr. G. C. S. Chow, A. Miah

Preston Royal Hospital, Lancashire Teaching Hospitals NHS Foundation Trust: Dr. C. de Goede, A. Selley

Southampton Children’s Hospital, University Hospital Southampton NHS Foundation Trust: Dr. N. Thomas, Dr. M. Illingworth, M. Geary, J. Palmer

Abertawe Bro Morgannwg University Health Board, Swansea: Prof. C. P. White, K. Greenfield

Royal Belfast Hospital for Sick Children, Belfast: Dr. S. Tiraputhi, S. MacAuley,

Leicester Royal Infirmary, Leicester: Dr. N. Hussain, H. Robbins, Dr. M. Iqbal

Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust: Dr. G. Ambegaonkar, Dr. D. Krishnakumar, C. Ward, J. Taylor.

Royal Aberdeen Children’s Hospital, Aberdeen: Dr. A. O’Hara, J. Tewnion.

Oxford University Hospitals NHS Foundation Trust: Dr. S. R. Chandratre, Dr. S. Ramdas, M. White, H. Ramjattan.

Royal Hospital for Sick Children, Edinburgh: Dr. A. Baxter, J. Yirrel.

Data Availability

All relevant data are within the paper and its Supporting information files. Individual patient data obtained from the U.K. NorthStar Clinical Network and iMDEX natural history study are available via data use agreements with the NorthStar Clinical Network database (https://www.northstardmd.com/) and iMDEX AFM natural history study (https://clinicaltrials.gov/ct2/show/NCT02780492).

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0283669.r001

Decision Letter 0

Katrien Janin

16 Aug 2022

PONE-D-22-17578Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy.PLOS ONE

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Dr Niks reports consultancies for BioMarin, Summit and WAVE for which reimbursements were received by the LUMC.

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Reviewer #1: Dear Dr. Gupta and colleagues.

Thank you for the opportunity to review this manuscript. I find this manuscript incredibly important, and attempts to address the very difficult topic of minimal clinically important differences in quantitative functional skills, specifically the Northstar Ambulatory Assessment (NSAA). As the field of Duchenne muscular dystrophy continues to evolve with emerging clinical trials, the importance of outcome measures remains critical for governmental approval agencies, private Biopharma corporations, and public academic research groups. I really appreciate, and acknowledge the authors attempts to include patient perceived differences in attempting to quantify a qualitative measure.

I share all of my constructive feedback with the best of intentions, not only to improve this manuscript, but to also help the field in a more broad sense. The manuscript overall is written very well, and the authors express their findings in a clear, coherent, and concise manner, which is always appreciated by reviewers. Several broader questions, which may not be able to be applied to this manuscript in a post-hoc manner are raised, for both my academic curiosity, and to plant the seeds for future investigations. I have attempted to highlight my suggestions in a methodical manner as laid out below.

General:

1. Please make sure that the figures and tables are labeled appropriately. Oftentimes I noticed that they are referred to as “Table1” instead of “Table 1”.

Introduction:

- Paragraph 2: when discussing the standards of care for treatment, it may be worthwhile two add in the multitude of clinical trials in process (different ASO targets, small molecules, biologics, AAVs, etc…) To highlight the importance of outcome measures in clinical trials.

- Paragraph 4: please consider adding these reference to the supplemental figure of the north star ambulatory assessment when discussing the NSAA.

- Paragraph 5: The importance of age is loosely referred to when interpreting the NSAA, but it may be worthwhile to include an explicit statement and what longitudinal studies of the NSAA have shown in DMD, and the impact of age dependency when interpreting NSAA results in this paragraph.

Methods:

1. Is it possible at all to combine cohort one and two? Certainly this may not be possible given differences in data collected of each of the groups, but may simplify latter analysis.

Results

1. Table 1: This table can be made much clearer, and should include information such as age, baseline NSAA scores, baseline 6 minute walk test data, clinical trial involvement, type of mutation (and location if known), age of diagnosis. If keeping two cohorts, statistical information comparing the two cohorts would be warranted To show if there are significant differences between the two groups.

2. Table 2: What does “Age band” mean? This is an interesting word choice. Table 2 is Overall hard to interpret with multiple empty boxes, repeated rows of “1/3 SD” and “SEM”, and no clear separator between “NSAA – Cohort 1” and “NSAA – Cohort 2”, and “6MWD – Cohort 2”. For the reader, I think this table can be significantly cleaned up to improve its visual appearance. Also, please remain consistent when abbreviations “SD” vs “sd” throughout the chart.

3. Table 3: Please put a space between “1/3SD” to read “1/3 SD”. try to not have words split between lines such as MCID/Mea ---- n” but rather MCID/Mean”. Similar to Table 2, this table is not very visually appearing, and though important, can be cleaned up for visual purposes for the readers, As it has multiple empty spaces, unusually spaced rows (very large “SEM” and very small “1/3 SD” rows, for instance.

4. Table 4: In the “N” column (2nd column), you say (% of sample), but only a few data points have percentages included. In NSAA, you list 34/34; I assume it means 34 of 34 patients did the NSAA?

5. Figures 2-4: these figures are very important and I am glad that the authors included them, however I think that they can be improved. First the resolution is blurry, please consider uploading higher resolution images. Imaging software such as Prism may be able to make more visually appealing figures. Consider changing the Y axis to say “Number of Responses” rather than “Count” to sound more professional.

Discussion:

1. What do you think accounts for discrepancies between participant responses between patients and parents?

2. At this point may be worthwhile to elaborate on. Would the variability amongst patient responses be an important factor to report for clinical trial outcome measure purposes? This may suggest that the objective current outcome measures (such as NSAA) it could be better than patient reported outcomes. This would also highlight the different patterns of patient perceived disease progression (such as losing complete function and two items versus partial function in four items).

3. Is it worth discussing the point that clinical trials are being targeted for younger populations and how this will impact NSAA interpretation?

Limitations

- Forgive me if I misinterpret or misunderstand the author is methodology, but the linearized scale method may weigh all contributing parts equally which may not be clinically relevant.

- Using the anchor based approach, annual decline of 30 meters for the six minute walk test may not be appropriate for all age groups, as boys naturally improve their strength until plateauing before precipitous decline. Age differences of NSAA assessment are an important limitation to consider, given age dependency of all functional tests.

- Please include a brief statement about other outcome measures that are used in clinical trials, such as biopsy, other functional tests, magnetic resonance imaging/spectroscopy, ultrasound, and electrical impedance myography.

Reviewer #2: This manuscript describes multiple analyses that were performed to assess the MCID for the NSAA in Duchenne muscular dystrophy. The authors first used retrospective data to calculate age-specific MCIDs based on the distribution of the data and the correlation between the NSAA and the six-minute walk distance. The authors also surveyed patients and parents to assess the minimal change in the NSAA that would be meaningful to them in the context of a clinical trial. My comments and questions are detailed below.

Introduction: “This leads to progressive loss of motor function with loss of the ability to walk typically by the age of 12 years…” This is a minor point, but the way this sentence is phrased makes it seem like all but a few patients lose ambulation by age 12. However, 12 is actually the mean age of loss of ambulation, meaning that many patients remain ambulatory beyond this age. Recent data from the TREAT-NMD cohort suggests that among steroid-treated Duchenne patients, a large percentage of patients remaing ambulatory until the age of 16.

Methods: Please include the dates during which the data for these analyses was collected.

Methods: It seems more common to have ½ the SD be the cutoff in distribution-based MCID calculations. What was the rationale for selecting ⅓ SD in the distribution based approach?

The survey questions ask what degree of change would justify participation in a two-year trial. I’m not sure how useful these survey responses are in a practical sense because the premise is not a realistic one. Trial design is predicated on the fact that the degree of efficacy is unknown, and a key element of informed consent for trials is that the participant understands that no benefit is possible (even probable) and is willing to participate anyway. We have also seen in past trials in DMD that participants/families were willing to support any amount of change that could be perceived as improvement, whether it corresponded with change in the NSAA or not. A more common approach for using patient/parent impressions to determine MCID would be to measure the NSAA at different time intervals and then ask if respondents have perceived improvement, worsening, or no change during those intervals.

Table 1: A large percentage of patients are on an intermittent steroid regimen. This is somewhat surprising, as there is evidence that intermittent dosing is not as effective as daily dosing and this schedule is rarely seen in practice now. Are there any unusual features about these cohorts that could explain this?

Was there any assessment of whether or not the data points within each age stratum were normally distributed? This would be important to know when implementing measures based on standard deviations and standard errors.

Results: The organization of Table 2 is a bit unusual. Since the data is being summarized based on age, I would expect to see age as the first column, followed by the N, mean, SD, ⅓ SD, SEM (with the row split here), MCID, and MCID/Mean.

Results: Within cohorts and 1 and 2, are there any patients who were measured multiple times at different ages? It seems that there must have been, since cohort 1 is listed as having 626 participants, but the sum total of all the participants in each age group is 1,166. If there are a significant number of non-independent data points, this could lead to underestimation of the variability between age bands.

Results: “Responses from 40 patients including 7 boys with DMD and 33 parents (7 parents of the boys that participated and 26 parents) were obtained…” This section could be clarified in a couple ways. I would avoid referring to the survey respondents as “patients” since the parents are presumably not being seen as patients and readers may interpret this to mean that 40 Duchenne patients participated when there were only 7. The phrase “7 parents of boys that participated and 26 parents” also sounds a bit incomplete. Consider changing to something like “...33 parents (7 of whom were parents of boys that participated).”

Since there are only 33 distinct DMD patients being described in the survey analysis, the descriptive statistics in Table 4 should not merge the patient and parent responses as if there were 40 distinct DMD patients. I would expect both the parent and the DMD patient to give similar answers with regards to their mobility status, but if there are discordant answers, this should be noted.

The Discussion section includes an explanation of the linearised NSAA scale. I would recommend moving this to the Methods. Otherwise, the rationale for using the linearised scale isn’t really clear at the time it is presented in the Results. It might also be useful to discuss in greater detail the reasons or scenarios in which the raw scores or the linearised scores might be preferred.

It might be useful to discuss how the MCID estimates from this analysis should be applied to clinical trial design, particularly as it relates to power and sample size calculations. The authors also point out that complete loss of function (1 to 0) may be assigned a different level of clinical importance compared to the deterioration of function (2 to 1). However, both would result in a change in the NSAA of 1 point. How would the authors suggest analyzing the NSAA data such that these distinctions can be recognized?

The section on strengths and limitations doesn’t seem to list any limitations. The sample size, particularly in the patient group, is a significant limitation in the survey study and should be noted. The analysis also doesn’t include patients younger than 7, who are the primary target population for ongoing gene therapy studies. Similarly, the MCID estimates would not apply to patients who are older.

Figure 4: The labeling of the y-axis should extend at least as high as the tallest column.

**********

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Reviewer #1: Yes: Stephen Chrzanowski

Reviewer #2: No

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PLoS One. 2023 Apr 26;18(4):e0283669. doi: 10.1371/journal.pone.0283669.r002

Author response to Decision Letter 0

29 Sep 2022

Thank you for giving us the opportunity to submit a revise draft of our manuscript “Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy.” for publication.

We are greatly appreciative of your and the reviewers’ time and efforts to provide us feedback and improve our manuscript. We have carefully considered the comments and have tried our best to address each of them. We hope the manuscript after careful revisions meet your standards for publication. We welcome further constructive comments, if any.

Please see below, a point-by-point response to the reviewer’s comments. All modifications in the manuscript are highlighted as track changes in the file labelled 'Revised Manuscript with Track Changes'. Page and line numbers in the responses refer to this file. In line with the suggested changes, any changes to the references are as highlighted in the track changes.

Responses to comments from Reviewer #1:

1. Please make sure that the figures and tables are labeled appropriately. Oftentimes I noticed that they are referred to as “Table1” instead of “Table 1”.

Author response: Thank you for pointing this out. We have corrected the labelling for Table 1 (page 13) and re-checked labelling for all tables and figures to be correct and consistent.

2. Paragraph 2: when discussing the standards of care for treatment, it may be worthwhile two add in the multitude of clinical trials in process (different ASO targets, small molecules, biologics, AAVs, etc…) To highlight the importance of outcome measures in clinical trials.

Author response: Thank you for this suggestion. We have now added the following to highlight this point as follows (page 4, lines 84 – 90):

“Furthermore, several other therapies targeting the primary defect in DMD such as gene replacement viral therapies, small molecules to induce exon skipping of out-of-frame deletions, or to induce read-through non-sense mutations as well as addressing the secondary consequences of the disease are in various stages of clinical testing or have received conditional approval in various countries. The rapid advance in the field of DMD therapeutics has highlighted the importance of validated outcome measures that can capture treatment efficacy in ambulant and non-ambulant DMD patients.”

3. Paragraph 4: please consider adding these reference to the supplemental figure of the north star ambulatory assessment when discussing the NSAA.

Author response: Thank you for this suggestion. We have now referenced Appendix 2 within this paragraph (page 5, line 100)

4. Paragraph 5: The importance of age is loosely referred to when interpreting the NSAA, but it may be worthwhile to include an explicit statement and what longitudinal studies of the NSAA have shown in DMD, and the impact of age dependency when interpreting NSAA results in this paragraph.

Author response: Thank you for raising this important point. We agree with the reviewer in indicating that the NSAA captures information over a relatively wide spectrum of disease in the ambulant patients. We have revised accordingly (page 5, lines 102-105):

“Studies have also shown a wide range of scores reflecting heterogeneity in disease progression such that important factors when interpreting an individual NSAA scores are not only age, but also scores at previous assessments, enabling better interpretation of functional trajectory11.”

5. Is it possible at all to combine cohort one and two? Certainly this may not be possible given differences in data collected of each of the groups, but may simplify latter analysis.

Author response: Thank you for this excellent suggestion. Early drafts of the manuscript included other measures which necessitated separate cohorts. However, the aim of the current manuscript allows us to combine the two cohorts in a meaningful way, which we agree simplifies latter analysis. Results for the combined cohorts are present in Tables 1-3

6. Table 1: This table can be made much clearer, and should include information such as age, baseline NSAA scores, baseline 6 minute walk test data, clinical trial involvement, type of mutation (and location if known), age of diagnosis. If keeping two cohorts, statistical information comparing the two cohorts would be warranted To show if there are significant differences between the two groups.

Author response: Thank you for this suggestion. Table 1 has been revised to provide descriptive information for the single cohort. No patient with a current involvement in a trial was included in the analysis.

7. Table 2: What does “Age band” mean? This is an interesting word choice. Table 2 is Overall hard to interpret with multiple empty boxes, repeated rows of “1/3 SD” and “SEM”, and no clear separator between “NSAA – Cohort 1” and “NSAA – Cohort 2”, and “6MWD – Cohort 2”. For the reader, I think this table can be significantly cleaned up to improve its visual appearance. Also, please remain consistent when abbreviations “SD” vs “sd” throughout the chart.

Author response: We created age intervals corresponding to age +/- 6 months and used the age closest to the midpoint. Tables 2 and 3 are now revised to improve its presentation with consistent abbreviations.

8. Table 3: Please put a space between “1/3SD” to read “1/3 SD”. try to not have words split between lines such as MCID/Mea ---- n” but rather MCID/Mean”. Similar to Table 2, this table is not very visually appearing, and though important, can be cleaned up for visual purposes for the readers, As it has multiple empty spaces, unusually spaced rows (very large “SEM” and very small “1/3 SD” rows, for instance.

Author response: The revised tables attempt to better the presentation as suggested.

9. Table 4: In the “N” column (2nd column), you say (% of sample), but only a few data points have percentages included. In NSAA, you list 34/34; I assume it means 34 of 34 patients did the NSAA?

Author response: Thank you for pointing this out. 34/34 means maximum score of 34/total score of 34. Revised table 4 attempts to better the presentation as suggested.

10. Figures 2-4: these figures are very important and I am glad that the authors included them, however I think that they can be improved. First the resolution is blurry, please consider uploading higher resolution images. Imaging software such as Prism may be able to make more visually appealing figures. Consider changing the Y axis to say “Number of Responses” rather than “Count” to sound more professional.

Author response: These changes have been made as recommended.

11. What do you think accounts for discrepancies between participant responses between patients and parents?

At this point may be worthwhile to elaborate on. Would the variability amongst patient responses be an important factor to report for clinical trial outcome measure purposes? This may suggest that the objective current outcome measures (such as NSAA) it could be better than patient reported outcomes. This would also highlight the different patterns of patient perceived disease progression (such as losing complete function and two items versus partial function in four items).

Author response: Overall there was good concordance between parents and patients responses. In our study there were 7 pairs of patient-parent of the same patient. There were small differences in 3 pairs which we have now noted in the results section (page 22, lines 376-381)

While the numbers are limited, these results overall appear to point to the fact that if differences exist they appear to suggest that the threshold for considering a difference is lower in affected boys compared to their parents. We have now highlighted is point in the discussion (page 24, lines 434-436).

12. Is it worth discussing the point that clinical trials are being targeted for younger populations and how this will impact NSAA interpretation?

Author response: We agree with this suggestion. The NSAA scale has been validated from the age of 5 years onwards, so we have not captured the younger patient population. This study was initiated in slightly older children who had a fuller understanding of their condition, and who had already experienced some loss of function. The dynamics in younger children, who have not as yet experienced deterioration of function will inevitably be different. This would be an interesting concept to explore further in future studies. We have highlighted this point in our discussion (page 26, lines 486-493)

13. Forgive me if I misinterpret or misunderstand the author is methodology, but the linearized scale method may weigh all contributing parts equally which may not be clinically relevant.

Author response: Thank you, this is an important point to clarify. The raw scale (ordinal level data) awards 0, 1 or 2 so all items contribute equally to the total score but the total scores have a non-linear relationship with the clinical construct (ambulatory function). In contrast, for the linearised scale (interval level data), which are Rasch-derived person estimates, changes across the scale mean the same i.e., a one-point change represents an equivalent clinical change across the full range of the scale (Mayhew et al 2013). We have highlighted this point in the methods section (page 8, lines 177-180).

14. Using the anchor based approach, annual decline of 30 meters for the six minute walk test may not be appropriate for all age groups, as boys naturally improve their strength until plateauing before precipitous decline. Age differences of NSAA assessment are an important limitation to consider, given age dependency of all functional tests.

Author response: Our approach was based on previous work available on an MCID for 6MWD and the sample that was available for this study. Only evidence on MCID for 6MWD is based on the work by McDonald et al 2013 which presents a single estimate, not differentiated for different age groups. We agree that estimates MCID for NSAA using the anchor approach would benefit from consideration of age differences, however, our sample was limited in numbers to be able to estimate MCID for different age groups. We have noted this limitation in the discussion (page 26, lines 494-495).

15. Please include a brief statement about other outcome measures that are used in clinical trials, such as biopsy, other functional tests, magnetic resonance imaging/spectroscopy, ultrasound, and electrical impedance myography.

Author response: Thank you for this suggestion. Yes, we agree that there are several outcomes measures used in DMD trials, however, to clearly present the outcome under evaluation in this study, we focus of our manuscript on functional outcome as measured by NSAA. There is indeed no information on MCID for any of the instrumental methodologies could be indicated above.

Responses to comments from Reviewer #2:

1. “This leads to progressive loss of motor function with loss of the ability to walk typically by the age of 12 years…” This is a minor point, but the way this sentence is phrased makes it seem like all but a few patients lose ambulation by age 12. However, 12 is actually the mean age of loss of ambulation, meaning that many patients remain ambulatory beyond this age. Recent data from the TREAT-NMD cohort suggests that among steroid-treated Duchenne patients, a large percentage of patients remain ambulatory until the age of 16.

Author response: Thank you for pointing this out. We have re-phrased this sentence to keep it focussed and prevent misinterpretation to (page 4, lines 74-76):

“This leads to progressive loss of motor function with eventual loss of the ability to walk, progressing to respiratory insufficiency, cardiomyopathy and premature death”.

2. Please include the dates during which the data for these analyses was collected.

Author response: Thank you for pointing this out. Data collection period has been added in the revised manuscript (see page 13, lines 276-278).

3. It seems more common to have ½ the SD be the cutoff in distribution-based MCID calculations. What was the rationale for selecting ⅓ SD in the distribution based approach?

Author response: Earlier work by Norman et al (2003) suggests 0.5 SD for generic HRQOL which is widely use in distribution-based methods, however, many studies since have assessed different multiple of SD for various generic and disease specific measures. ⅓ SD (corresponding to an effect size of 0.33 thus adequately falling between small and moderate effect) was chosen primarily to be able to compare with McDonald et al (2013) on ⅓ SD for 6MWD in DMD. The actual standard deviations are also presented in the table.

4. The survey questions ask what degree of change would justify participation in a two-year trial. I’m not sure how useful these survey responses are in a practical sense because the premise is not a realistic one. Trial design is predicated on the fact that the degree of efficacy is unknown, and a key element of informed consent for trials is that the participant understands that no benefit is possible (even probable) and is willing to participate anyway. We have also seen in past trials in DMD that participants/families were willing to support any amount of change that could be perceived as improvement, whether it corresponded with change in the NSAA or not. A more common approach for using patient/parent impressions to determine MCID would be to measure the NSAA at different time intervals and then ask if respondents have perceived improvement, worsening, or no change during those intervals.

Author response: Thank you for this comment. The survey questions were framed in a way that could be addressed in line with the study aim and design. It is important to note that the questions were elaborated with the direct contribution of families of boys with DMD who framed several of the questions for this study, and we have now indicated this in the revised manuscript (page 10, line 224). We believe a prospective approach at multiple time points as suggested would benefit future research.

5. Table 1: A large percentage of patients are on an intermittent steroid regimen. This is somewhat surprising, as there is evidence that intermittent dosing is not as effective as daily dosing and this schedule is rarely seen in practice now. Are there any unusual features about these cohorts that could explain this?

Author response: Thank you for this comment. The reviewer is correct that a proportion of patients are on intermittent steroids; but we would not consider this highly unusual as the study includes patients born between 1996 and March 2014 with physio assessments between 2005 and 2020. Additionally, the clinical efficacy of the different steroid regimens has been extensively reported not only on ambulatory function (which clearly favour the daily steroids), but also on the long term cardiac and respiratory data, in which there is really no difference between the different regimens. A major difference is however on the safety profile and adverse event profile for the different steroids. So, many families when offered a choice, do prefer the option of intermittent steroids especially when facing the severe burden adverse effects from long term daily steroids.

6. Was there any assessment of whether or not the data points within each age stratum were normally distributed? This would be important to know when implementing measures based on standard deviations and standard errors.

Author response: Visual inspection of the data showed there was no evidence of skewness within each age stratum, and this can be seen when comparing the size of the standard deviation relative to the mean at each age strata in Tables 2 & 3.

7. The organization of Table 2 is a bit unusual. Since the data is being summarized based on age, I would expect to see age as the first column, followed by the N, mean, SD, ⅓ SD, SEM (with the row split here), MCID, and MCID/Mean.

Author response: We have revised Tables 2 and 3 to improve presentation. Based on a suggestion from reviewer 1, we now present analysis for a combined cohort.

8. Within cohorts and 1 and 2, are there any patients who were measured multiple times at different ages? It seems that there must have been, since cohort 1 is listed as having 626 participants, but the sum total of all the participants in each age group is 1,166. If there are a significant number of non-independent data points, this could lead to underestimation of the variability between age bands.

Author response: The reviewer is correct in that some patients contribute information for more than one age strata. We have presented descriptions of the data only for each age strata separately and are not making any formal comparisons. If we had explored changes between ages or investigated trajectories then we agree with the reviewer and it would have been important to account for clustering and the longitudinal structure of the data accordingly. Please note, based on the suggestion from reviewer 1, we now present analysis for a combined cohort.

9. “Responses from 40 patients including 7 boys with DMD and 33 parents (7 parents of the boys that participated and 26 parents) were obtained…” This section could be clarified in a couple ways. I would avoid referring to the survey respondents as “patients” since the parents are presumably not being seen as patients and readers may interpret this to mean that 40 Duchenne patients participated when there were only 7. The phrase “7 parents of boys that participated and 26 parents” also sounds a bit incomplete. Consider changing to something like “...33 parents (7 of whom were parents of boys that participated).”

Author response: Thank you for this suggestion. We agree that this text needs clarification. We have revised Table 4 and the corresponding text in the results (page 19, lines 346-349).

10. Since there are only 33 distinct DMD patients being described in the survey analysis, the descriptive statistics in Table 4 should not merge the patient and parent responses as if there were 40 distinct DMD patients. I would expect both the parent and the DMD patient to give similar answers with regards to their mobility status, but if there are discordant answers, this should be noted.

Author response: Thank you for this suggestion. We have added a revised Table 4 (page 20-21) to better present the responses and any differences.

11. The Discussion section includes an explanation of the linearised NSAA scale. I would recommend moving this to the Methods. Otherwise, the rationale for using the linearised scale isn’t really clear at the time it is presented in the Results. It might also be useful to discuss in greater detail the reasons or scenarios in which the raw scores or the linearised scores might be preferred.

Author response: Thank you for this suggestion. The linearised scale is a transformation of the original raw scale which allows for equivalent clinical interpretation per unit change, across the full range of the scale. While the use of the linearise scale is limited currently, for completeness we include MCID estimates for both raw and linearised NSAA scales, as we believe this is useful for the reader. We have added information in methods (page 8, lines 177-180) to address this.

12. It might be useful to discuss how the MCID estimates from this analysis should be applied to clinical trial design, particularly as it relates to power and sample size calculations. The authors also point out that complete loss of function (1 to 0) may be assigned a different level of clinical importance compared to the deterioration of function (2 to 1). However, both would result in a change in the NSAA of 1 point. How would the authors suggest analyzing the NSAA data such that these distinctions can be recognized?

Author response: Thank you for this suggestion. We highlight some exploratory approaches that have been recently for trials including phase 3 trial for Ataluren. We have also added another recent example (Muntoni et al. 2022) with exploratory analysis on data from a phase 2 trial (page 26, lines 498-506), with its reference updated within the manuscript.

13. The section on strengths and limitations doesn’t seem to list any limitations. The sample size, particularly in the patient group, is a significant limitation in the survey study and should be noted. The analysis also doesn’t include patients younger than 7, who are the primary target population for ongoing gene therapy studies. Similarly, the MCID estimates would not apply to patients who are older.

Author response: Thank you for this suggestion. We have detailed limitation as suggested in the revised manuscript (page 26, lines 486-496).

14. Figure 4: The labeling of the y-axis should extend at least as high as the tallest column.

Author response: The figure has been revised as recommended.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(37.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0283669.r003

Decision Letter 1

Stephen E Alway

2 Jan 2023

PONE-D-22-17578R1Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy.PLOS ONE

Dear Dr. Ayyar Gupta,

Please respond and revise the manuscript to address the minor issues remaining that have been identified by one reviewer. I think this should be a small modification to your manuscript for clarification.

Please submit your revised manuscript by Feb 16 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

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Stephen E Alway, Ph.D.

Academic Editor

PLOS ONE

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Partly

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Reviewer #2: Most of my comments have been addressed. I did have some additional comments on the revision.

In the new Table 1, the range for the NSAA score is listed as 2-34. Please verify that the low score of 2 is correct. Given that the oldest participant in the cohort is listed as being 10.5 years old, this would be an unexpectedly low NSAA score for a group of Duchenne patients this age.

It was not apparent in the original manuscript that only 31 participants were included in the distribution-based MCID analysis of the six-minute walk test. Since the original cohort from the IMDEX natural history study had 56 participants, only about half of the cohort is represented in this analysis. This rather alters my perception of the robustness of this analysis. It would be useful to get a better understanding of the reasons that so much of the data is missing from this cohort. Has there been any analysis to determine how representative these 31 participants are with respect to the larger cohort being described here? Is there any reason to believe that participants were excluded for reasons relating to their physical function?

Results: “Based on 62 observed annual changes in 24 boys (54 observations) above the ages of seven years….” Please clarify how the 62 changes were counted from 54 observations. If the 24 participants were each measured at baseline and after 1 year, that would be 48 observations. If 6 of those participants had an additional measurement after year 2, that would make 54 observations, but this would only end up being 30 annual changes, not 62. There also appear to be more than 62 points plotted in Figure 1, which is supposed to correspond to this analysis. If participants are contributing multiple data points to the analysis, please describe any adjustment for non-independent data used in the correlation analysis.

Reviewer #3: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #2: No

Reviewer #3: Yes: Jennifer L Lammers

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PLoS One. 2023 Apr 26;18(4):e0283669. doi: 10.1371/journal.pone.0283669.r004

Author response to Decision Letter 1

10 Jan 2023

Thank you for giving us the opportunity to address further comments from the reviewer for our manuscript “Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy” for publication.

Reponses to reviewer comments

1. Reviewer #2: Most of my comments have been addressed. I did have some additional comments on the revision. In the new Table 1, the range for the NSAA score is listed as 2-34. Please verify that the low score of 2 is correct. Given that the oldest participant in the cohort is listed as being 10.5 years old, this would be an unexpectedly low NSAA score for a group of Duchenne patients this age.

Author response: Previous and recent data checks did not find any errors in the study dataset. While this is not necessarily typical, given that average age of loss of ambulation in DMD patients is 12 years, a score of 2 at the age of 10.5 years is plausible and can be expected in a large cohort. Indeed, our previous studies evaluating large cohort in DMD do not contradict this finding (see NSAA distribution scores and loss of ambulation in the large cohort study published in 2019: Muntoni F, Domingos J, Manzur AY, et al. Categorising trajectories and individual item changes of the North Star Ambulatory Assessment in patients with Duchenne muscular dystrophy. PLoS One. 2019 Sep 3;14(9):e0221097. doi: 10.1371/journal.pone.0221097. PMID: 31479456; PMCID: PMC6719875)

2. Reviewer #2: It was not apparent in the original manuscript that only 31 participants were included in the distribution-based MCID analysis of the six-minute walk test. Since the original cohort from the IMDEX natural history study had 56 participants, only about half of the cohort is represented in this analysis. This rather alters my perception of the robustness of this analysis. It would be useful to get a better understanding of the reasons that so much of the data is missing from this cohort. Has there been any analysis to determine how representative these 31 participants are with respect to the larger cohort being described here? Is there any reason to believe that participants were excluded for reasons relating to their physical function?

Author response: The study data is limited in six-minute walk distance data (this had been noted within study limitations). On evaluating characteristics across the overall IMDEX sample (N=56) and the six minute walk distance sample in the study (N= 31), we found the smaller cohort of 31 patients with six minute walk distance data available to be representative of the overall IMDEX sample in the study, and thus did not find evidence of systematic bias relating to physical function (please see the table attached below).

Overall IMDEX cohort (N=56) Cohort with 6MWD available (N=31)

Age, mean (sd) 7.6 (2.5) 7.6 (1.1)

NSAA at first visit, mean (SD), range 22.8 (7.8), 7-34 25.0 (7.6), 8-34

% on steroids 96% 97%

% on daily steroids 62% 60%

% on intermittent steroids 32% 33%

% unknown regime 6% 7%

We have added the sentence below in the methods section (lines 182-184) to indicate representativeness of the six-minute walk distance sample.

“The patient characteristics of the cohort for whom the 6MWD data was available for this study was representative of patient characteristics in the wider iMDEX natural history cohort.”

3. Reviewer #2: Results: “Based on 62 observed annual changes in 24 boys (54 observations) above the ages of seven years….” Please clarify how the 62 changes were counted from 54 observations. If the 24 participants were each measured at baseline and after 1 year, that would be 48 observations. If 6 of those participants had an additional measurement after year 2, that would make 54 observations, but this would only end up being 30 annual changes, not 62. There also appear to be more than 62 points plotted in Figure 1, which is supposed to correspond to this analysis. If participants are contributing multiple data points to the analysis, please describe any adjustment for non-independent data used in the correlation analysis.

Author response: Thank you for this comment. We agree that this section appears inconsistent and requires clarification. To address this and account for multiple changes per patient, we have made the following changes to the manuscript:

Lines 312-316 have been revised to:

“Based on 36 non-overlapping observed annual changes in 24 boys above the ages of 7 years, a positive correlation of 0.50 (p=0.002) was observed between change in NSAA and change in 6MWD (Fig 1). Using mixed methods regression analysis to account for multiple changes per patient and the previously reported MCID for 6MWD as a decline of 30m17, the equivalent decline in NSAA was observed as -3.5 points (95% CI= -1.9, -5.0).”

In addition, Figure 1 has been revised to display non-overlapping changes. MCID for NSAA by the anchor method has been corrected to 3.5 (previously noted at 3.3) in the abstract and discussion.

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PLoS One. doi: 10.1371/journal.pone.0283669.r005

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Stephen E Alway

14 Mar 2023

Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy.

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PLoS One. doi: 10.1371/journal.pone.0283669.r006

Acceptance letter

Stephen E Alway

14 Apr 2023

PONE-D-22-17578R2

Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy.

Dear Dr. Ayyar Gupta:

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Appendix. Participant tailored questionnaire.

(DOCX)

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S2 Appendix. NSAA questionnaire manual.

(PDF)

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Data Availability Statement

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PERMALINK

Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy

Vandana Ayyar Gupta

Jacqueline M Pitchforth

Joana Domingos

Deborah Ridout

Mario Iodice

Catherine Rye

Mary Chesshyre

Amy Wolfe

Victoria Selby

Anna Mayhew

Elena S Mazzone

Valeria Ricotti

Jean-Yves Hogrel

Erik H Niks

Imelda de Groot

Laurent Servais

Volker Straub

Eugenio Mercuri

Adnan Y Manzur

Francesco Muntoni

Roles

Abstract

Introduction

Methods

1. Distribution based approach

2. Anchor based approach

3. Participant tailored questionnaire

Construction of participant questionnaires

Evaluation of responses

Results

Table 1. Patient characteristics at first NSAA assessment.

Distribution based approach

Table 2. Estimates of MCID for NSAA (raw score) and 6MWD based on distribution methods.

Table 3. Estimates of MCID for NSAA (linearized scale) based on distribution methods.

Anchor based approach, NSAA

Fig 1. Scatter plot of annual changes in 6MWD vs NSAA total score (non-overlapping changes).

Participant questionnaires, NSAA

Table 4. Patient (boys with DMD) characteristics and perceived mobility status.

Fig 2. Preventing loss of function.

Fig 3. Maintaining function.

Trial participation

Fig 4. Participant responses for minimum requirements for participating in a clinical trial lasting 2 years based on improvement of motor function, slowing the decline of motor function, or stopping the decline of motor function of items in the NSAA.

Discussion

Comparison with other studies

Strengths and limitations of the study

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Katrien Janin

Roles

Author response to Decision Letter 0

Decision Letter 1

Stephen E Alway

Roles

Author response to Decision Letter 1

Decision Letter 2

Stephen E Alway

Roles

Acceptance letter

Stephen E Alway

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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