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A novel quantitative indicator for disease progression rate in amyotrophic lateral sclerosis

  • Yuko Kobayakawa
    Affiliations
    Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan

    Center for Clinical and Translational Research, Kyushu University Hospital, Fukuoka 812-8582, Japan
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  • Koji Todaka
    Affiliations
    Center for Clinical and Translational Research, Kyushu University Hospital, Fukuoka 812-8582, Japan
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  • Yu Hashimoto
    Affiliations
    Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
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  • Senri Ko
    Affiliations
    Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
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  • Wataru Shiraishi
    Affiliations
    Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
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  • Junji Kishimoto
    Affiliations
    Center for Clinical and Translational Research, Kyushu University Hospital, Fukuoka 812-8582, Japan
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  • Jun-ichi Kira
    Affiliations
    Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan

    Translational Neuroscience Center, Graduate School of Medicine, School of Pharmacy at Fukuoka, International University of Health and Welfare, Okawa, Fukuoka 831-8501, Japan

    Department of Neurology, Brain and Nerve Center, Fukuoka Central Hospital, International University of Health and Welfare, Fukuoka 810-0022, Japan
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  • Ryo Yamasaki
    Affiliations
    Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
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  • Noriko Isobe
    Correspondence
    Corresponding author at: 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan.
    Affiliations
    Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
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  • The Pooled Resource Open-Access ALS Clinical Trials Consortium
    Author Footnotes
    1 Data used in the preparation of this article were obtained from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. As such, the following organizations and individuals within the PRO-ACT Consortium contributed to the design and implementation of the PRO-ACT database and/or provided data, but did not participate in the analysis of the data or the writing of this report: ALS Therapy Alliance, Knopp Biosciences, Neuraltus Pharmaceuticals, Inc., Neurological Clinical Research Institute at Massachusetts General Hospital, Northeast ALS Consortium, Novartis, Prize4Life Israel, Regeneron Pharmaceuticals, Inc., Sanofi, Teva Pharmaceutical Industries, Ltd., The ALS Association.
  • Author Footnotes
    1 Data used in the preparation of this article were obtained from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. As such, the following organizations and individuals within the PRO-ACT Consortium contributed to the design and implementation of the PRO-ACT database and/or provided data, but did not participate in the analysis of the data or the writing of this report: ALS Therapy Alliance, Knopp Biosciences, Neuraltus Pharmaceuticals, Inc., Neurological Clinical Research Institute at Massachusetts General Hospital, Northeast ALS Consortium, Novartis, Prize4Life Israel, Regeneron Pharmaceuticals, Inc., Sanofi, Teva Pharmaceutical Industries, Ltd., The ALS Association.
Open AccessPublished:August 23, 2022DOI:https://doi.org/10.1016/j.jns.2022.120389

      Highlights

      • Novel FVC Decline Pattern scale (FVC-DiP) reflects %FVC decline patterns in ALS.
      • FVC-Dip scores are obtained by %FVC and disease duration at the time of assessment.
      • Individuals' FVC-DiP scores are relatively stable throughout the disease course.
      • Low FVC-DiP scores are associated with shorter survival and time to ventilation.
      • FVC-DiP could be a sensitive indicator of treatment efficacy.

      Abstract

      Objective

      The current study sought to develop a new indicator for disease progression rate in amyotrophic lateral sclerosis (ALS).

      Methods

      We used a nonparametric method to score diverse patterns of decline in the percentage of predicted forced vital capacity (%FVC) in patients with ALS. This involved 6317 longitudinal %FVC data sets from 920 patients in the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database volunteered by PRO-ACT Consortium members. To assess the utility of the derived scores as a disease indicator, we examined changes over time, the association with prognosis, and correlation with the Risk Profile of the Treatment Research Initiative to Cure ALS (TRICALS). Our local cohort (n = 92) was used for external validation.

      Results

      We derived scores ranging from 35 to 106 points to construct the FVC Decline Pattern scale (FVC-DiP). Individuals' FVC-DiP scores were determined from a single measurement of %FVC and disease duration at assessment. Although the %FVC declined over the disease course (p < 0.0001), the FVC-DiP remained relatively stable. Low FVC-DiP scores were associated with rapid disease progression. Using our cohort, we demonstrated an association between FVC-DiP and the survival prognosis, the stability of the FVC-DiP per individual, and a correlation between FVC-DiP scores and the TRICALS Risk Profile (r2 = 0.904, p < 0.0001).

      Conclusions

      FVC-DiP scores reflected patterns of declining %FVC over the natural course of ALS and indicated the disease progression rate. The FVC-DiP may enable easy assessment of disease progression patterns and could be used for assessing treatment efficacy.

      Keywords

      1. Introduction

      Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that progressively affects both upper and lower motor neurons. ALS exhibits substantial phenotypic heterogeneity and variability in progression rates [
      • van Es M.A.
      • Hardiman O.
      • Chio A.
      • et al.
      Amyotrophic lateral sclerosis.
      ]. The median survival time from onset to death ranges from 20 to 48 months and approximately 10%–20% of ALS patients survive for >10 years after onset [
      • Chio A.
      • Logroscino G.
      • Hardiman O.
      • et al.
      Prognostic factors in ALS: a critical review.
      ]. Although there is no radical treatment for ALS, evaluation of disease severity throughout the disease course is essential for patient care management, including the use of riluzole and edaravone, the timing and content of nutrition support, and respiratory assistance [
      • Miller R.G.
      • Jackson C.E.
      • Kasarskis E.J.
      • et al.
      Practice parameter update: the care ofthe patient with amyotrophic lateral sclerosis: drug, nutritional, and respiratory therapies (an evidence-based review) report of the quality standards Subcommittee of the American Academy of neurology.
      ]. Evaluation of disease severity in patients with ALS involves two components: functional state at assessment and disease progression rate. Most indicators of ALS activity focus on the functional state at the time of assessment; evaluation of the disease progression rate using these indicators requires longitudinal observation [
      • Simon N.G.
      • Turner M.R.
      • Vucic S.
      • et al.
      Quantifying disease progression in amyotrophic lateral sclerosis.
      ]. Patterns of functional decline in ALS patients are not uniform and are not necessarily linear during the disease course [
      • Ackrivo J.
      • Hansen-Flaschen J.
      • Jones B.L.
      • et al.
      Classifying patients with amyotrophic lateral sclerosis by changes in FVC. A group-based trajectory analysis.
      ,
      • Sato K.
      • Iwata A.
      • Kurihara M.
      • Nagashima Y.
      • Mano T.
      • Toda T.
      Estimating acceleration time point of respiratory decline in ALS patients: a novel metric.
      ,
      • Watanabe H.
      • Atsuta N.
      • Hirakawa A.
      • et al.
      A rapid functional decline type of amyotrophic lateral sclerosis is linked to low expression of TTN.
      ,
      • Proudfoot M.
      • Jones A.
      • Talbot K.
      • Al-Chalabi A.
      • Turner M.R.
      The ALSFRS as an outcome measure in therapeutic trials and its relationship to symptom onset.
      ]. Thus, it is difficult to assess the rate of disease progression in an individual patient based on a single assessment of the functional indicators. A number of prognostic models have recently been developed to determine the rate of disease progression in individual patients [
      • Westeneng H.J.
      • Debray T.P.A.
      • Visser A.E.
      • et al.
      Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model.
      ,
      • Ackrivo J.
      • Hansen-Flaschen J.
      • Wileyto E.P.
      • Schwab R.J.
      • Elman L.
      • Kawut S.M.
      Development of a prognostic model of respiratory insufficiency or death in amyotrophic lateral sclerosis.
      ,
      • Elamin M.
      • Bede P.
      • Montuschi A.
      • Pender N.
      • Chio A.
      • Hardiman O.
      Predicting prognosis in amyotrophic lateral sclerosis: a simple algorithm.
      ,
      • Gomeni R.
      • Fava M.
      The pooled resource open-access ALS clinical trials consortium. Amyotrophic lateral sclerosis disease progression model.
      ,
      • Jahandideh S.
      • Taylor A.A.
      • Beaulieu D.
      • et al.
      Longitudinal modeling to predict vital capacity in amyotrophic lateral sclerosis.
      ,
      • Wei Q.Q.
      • Chen Y.
      • Chen X.
      • et al.
      Prognostic nomogram associated with longer survival in amyotrophic lateral sclerosis patients.
      ,
      • Talbot K.
      Clinical tool for predicting survival in ALS: do we need one?.
      ,
      • Zhou N.
      • Manser P.
      Does including machine learning predictions in ALS clinical trial analysis improve statistical power?.
      ]. However, the relationships between these models have not been examined in detail [
      • Xu L.
      • He B.
      • Zhang Y.
      • et al.
      Prognostic models for amyotrophic lateral sclerosis: a systematic review.
      ].
      Irrespective of the site of onset, respiratory failure is the major cause of death in patients with ALS [
      • Spataro R.
      • Lo Re M.
      • Piccoli T.
      • Piccoli F.
      • La Bella V.
      Causes and place of death in Italian patients with amyotrophic lateral sclerosis.
      ]. Forced vital capacity (FVC) is the most commonly used measure for evaluating the functional state of respiratory muscles. It has been reported that the rate of FVC decline and measurements of the percentage of predicted FVC (%FVC) at the initial visit are significant predictors of survival in patients with ALS [
      • Traynor B.J.
      • Zhag H.
      • Schoenfeld J.M.
      • Cudkowicz M.E.
      On behalf of the NEALS consortium. Functional outcome measures as clinical trial endpoints in ALS.
      ,
      • Czaplinski A.
      • Yen A.A.
      • Appel S.H.
      Forced vital capacity (FVC) as an indicator of survival and disease progression in an ALS clinic population.
      ]. A method enabling the evaluation of disease progression rate using a single measurement of FVC, irrespective of measurement timing, would be valuable for patient management.
      In the current study, we aimed to develop a new method for evaluating the disease progression rate using a single FVC measurement that could be taken at any point throughout the disease course. We developed a scale with scores reflecting different patterns of decline in the %FVC over the course of the disease, based on longitudinal %FVC data from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database [
      • Atassi N.
      • Berry J.
      • Shui A.
      • et al.
      The PRO-ACT database design, initial analyses, and predictive features.
      ]. The measure is called the FVC Decline Pattern scale (FVC-DiP). We examined the utility of the FVC-DiP as an indicator of the disease progression rate using the PRO-ACT database, and our local cohort was used for external validation. We also examined the association between FVC-DiP scores and an existing prognostic model, the Risk Profile proposed by the Treatment Research Initiative to Cure ALS (TRICALS), which is based on a well-validated prognostic model developed by the European Network for the Cure of ALS [
      • Westeneng H.J.
      • Debray T.P.A.
      • Visser A.E.
      • et al.
      Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model.
      ,
      • van Eijk R.P.A.
      • Westeneng H.J.
      • Nikolakopoulos S.
      • et al.
      Refining eligibility criteria for amyotrophic lateral sclerosis clinical trials.
      ].

      2. Methods

      2.1 Patient data

      The PRO-ACT database was constructed in 2011 from multiple Phase II/III clinical trials for ALS and has been continuously updated to contain over 10,700 patient records [
      • Atassi N.
      • Berry J.
      • Shui A.
      • et al.
      The PRO-ACT database design, initial analyses, and predictive features.
      ]. We obtained the dataset in September 2020 via a web-based application (available at https://ncri1.partners.org/ProACT). We included only patients that were categorized in placebo groups and excluded patients without %FVC data. %FVC data that were measured at <5 months or >62 months from onset were excluded because of the small number of cases. Patients were allowed to have missing values for other variables in the following analyses. Finally, 920 patients with 6317 %FVC measurements were included for analysis.
      For external validation, we used our single-center cohort of Japanese patients with ALS. This cohort dataset was constructed by retrospective and prospective observational studies of ALS patients at Kyushu University Hospital. A total of 92 patients who met the following three criteria were included: 1) Patients who were diagnosed as ALS according to the revised El Escorial criteria [
      • Brooks B.R.
      • Miller R.G.
      • Swash M.
      • Munsat T.L.
      El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis.
      ] by board-certified neurologists at Kyushu University Hospital from January 2012 to December 2020; 2) Patients with a record of %FVC measurement at ALS diagnosis; 3) Patients with at least one follow-up visit after ALS diagnosis. We obtained data of %FVC, age at onset and diagnosis, onset site, presence or absence of frontotemporal dementia, grade of the revised El Escorial criteria at diagnosis, sex, family history of ALS, score of the revised ALS Functional Rating Scale (ALSFRS-R) [
      • Cedarbaum J.M.
      • Stambler N.
      • Malta E.
      • et al.
      The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function.
      ], and use of riluzole and edaravone. This study was approved by the Kyushu University institutional ethics review board (approval number: 2020–104). Informed consent was obtained via an opt-out method on our website for retrospective observational data collection, and written informed consent was obtained from participants for prospective observation data collection.

      2.2 Development of the FVC-DiP

      We performed a nonparametric approach using longitudinal %FVC data of the PRO-ACT database to develop the FVC-DiP (Fig. 1A ). First, we divided %FVC data into 19 groups according to the duration from symptom onset to measurement in 3-month intervals (Fig. 1B). For example, measurements between 5 and 7 months from symptom onset were clustered as data at a duration of 6 months. When there were multiple measurements for a patient within an interval, the median was calculated so that one interval contained a single measurement per patient. Second, we categorized %FVC data at each duration using the following ranges: ≥100, 90–100, 80–90, 70–80, 60–70, 50–60, and < 50. As a reference, we defined the median %FVC value in each range at a duration of 24 months as FVC-DiP score at 24 months (Fig. 1C). Third, we extracted patients with %FVC data available at both of the two consecutive disease durations (e.g., patients with %FVC data at the duration windows of 24 and 27 months) and plotted the patient distribution according to their %FVC values at each duration (Fig. 1D). For example, the FVC-DiP score for the %FVC range of 80%–90% at 27 months was calculated as the population-weighted average of FVC-DiP score at 24 months, which was one previous disease duration window, within patients that were categorized in the %FVC range of 80%–90% at a duration of 27 months (Fig. 1E). FVC-DiP scores after a duration of 30 months were calculated sequentially up to 60 months, following a similar process to that used for the calculation for 27 months. In addition, FVC-DiP score at 21 months was calculated by referring to the %FVC distribution at the standard 24 months and the calculation continued sequentially down to 6 months, based on the next duration window.
      Fig. 1
      Fig. 1Development of the FVC-DiP.
      (A) Individual differences in patterns of %FVC decline over the course of the disease. The lines show individual data for 920 patients with ALS. (B) Longitudinal %FVC measurements in 3-month intervals, starting at 6 months from symptom onset. The box and whisker plots show the minimum, first quartile, median, third quartile, and maximum values. The arrow points to the lowest median %FVC, which was at 24 months. The number of patients included at each duration is shown above the graph. (C) Median %FVC values at 24 months for each of the following ranges: ≥100, 90–100, 80–90, 70–80, 60–70, 50–60, and < 50 %FVC. These values were taken as the FVC-DiP scores at 24 months (numbers in the box). (D) The number of patients with %FVC values within each range at 24 and 27 months (dotted zone: stable between 24 and 27 months; white zone: deterioration at 27 months; striped zone: improvement at 27 months). (E) The procedure for calculating the FVC-DiP score, shown here for the 80–90 %FVC range at 27 months. The FVC-DiP score was calculated as the population-weighted average of the FVC-DiP scores at 24 months in patients with a 80–90 %FVC at 27 months. The boxes with numbers correspond to those in (C) and (D). (F) FVC-DiP scores for all durations from symptom onset to measurement. The numbers with a border in bold correspond to those in (C). The score with the symbol ※ corresponds to that in (E). Abbreviations: FVC, forced vital capacity; FVC-DiP, FVC Decline Pattern scale; %FVC, percentage of predicted FVC; ALS, amyotrophic lateral sclerosis.

      2.3 Utility examination of FVC-DiP and validation in an external cohort

      Using the PRO-ACT database and our single-center cohort data, we examined changes in FVC-DiP scores during the disease course and the association with disease prognosis. Day 0 in clinical trials was considered as the baseline for patients in the PRO-ACT database, and the time at diagnosis was set as the baseline for patients in our single-center cohort. Changes in %FVC and FVC-DiP scores, depending on duration from baseline, were examined using longitudinal follow-up measurements. Patients' characteristics and disease prognosis were compared according to FVC-DiP scores at baseline. For survival analysis, time to death from symptom onset or baseline was assessed for patients in the PRO-ACT database, and ventilation-free survival (including non-invasive ventilation) from baseline was assessed for patients in our single-center cohort. In addition, we examined the correlation between FVC-DiP and the TRICALS Risk Profile using our single-center cohort data. The TRICALS Risk Profile was calculated by entering the following data on the website (https://tricals.shinyapps.io/risk-profile/): grade of the revised El Escorial criteria at diagnosis, site of onset, presence or absence of frontotemporal dementia, date of birth, onset, diagnosis, and screening, and scores of ALSFRS-R and %FVC at screening.

      2.4 Data management

      Patient data in the PRO-ACT database and our single-center cohort were managed using Research Electronic Data Capture (REDCap) hosted at Kyushu University. REDCap is a secure, web-based software platform designed to support data capture for research studies, providing: 1) an intuitive interface for validated data capture; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for data integration and interoperability with external sources [
      • Harris P.A.
      • Taylor R.
      • Thielke R.
      • Payne J.
      • Gonzalez N.
      • Conde J.G.
      Research electronic data capture (REDCap)-a metadata-driven methodology and workflow process for providing translational research informatics support.
      ,
      • Harris P.A.
      • Taylor R.
      • Minor B.L.
      • et al.
      The REDCap consortium: building an international community of software platform partners.
      ].

      2.5 Statistical analysis

      Comparisons of patients' characteristics between groups by baseline FVC-DiP scores were performed using Pearson's chi-square test for categorical variables and Student's t-test for continuous variables. For analysis of survival, the log-rank test and Cox proportional hazard test were performed. The effect of baseline FVC-DiP score on the slope of change in ALSFRS-R and the effect of time on changes in %FVC and FVC-DiP scores during disease course were analyzed using a linear mixed effects model with duration as a fixed effect and patient as a random effect. For analysis of the correlation between FVC-DiP score and the Risk Profile of TRICALS, coefficients of determination were calculated using a linear mixed effects model.
      A value of p < 0.05 was considered to indicate statistical significance. All statistical analyses were carried out using JMP Pro 16 software (SAS Institute, Cary, NC, USA).

      3. Results

      3.1 Development of the FVC-DiP

      The characteristics of the patients who were included in the development of the FVC-DiP are summarized in Table 1. There were large interindividual differences in the patterns of decline in %FVC, and the rates of decrease were not constant within individual patients over time (Fig. 1A). When longitudinal %FVC data were divided into 19 groups according to the duration from symptom onset to measurement in 3-month intervals, more than half of the %FVC measurements in each duration were distributed between 50% and 100% (Fig. 1B). Median %FVC values within each duration declined from 6 to 24 months and slightly increased after 24 months. At a duration of 24 months, the median %FVC values in each range were as follows (range of %FVC [median]): ≥100 [106], 90–100 [93], 80–90 [85], 70–80 [74], 60–70 [64], 50–60 [55], and <50 [35] (Fig. 1C). These values were taken as the FVC-DiP scores at 24 months and used as standard values. We derived FVC-DiP scores at all durations from 6 to 60 months by sequential comparison of the patient distribution with adjacent durations (Fig. 1D–F). The resulting FVC-DiP scores did not differ between adjacent cells in a consistent manner in either the vertical or horizontal directions (Fig. 1F). However, within the same disease duration, FVC-DiP scores decreased as the %FVC dropped, whereas, within the same range of %FVC, FVC-DiP scores increased as the disease duration became longer. To maintain these gradations, we added to or subtracted from the derived scores at 10 cells, with changes ranging from −3 to +2; the number of patients within these cells ranged from 5 to 29. In two other cells where no patients were located, we complemented scores to maintain the gradation described above. Each patient's FVC-DiP score at a certain point was determined by a single measurement of the %FVC and disease duration at assessment. For example, for an individual with a %FVC value of 85 at 12 months from symptom onset, the FVC-DiP score would be 55 (Fig. 1F). FVC-DiP scores were lower than the actual %FVC for durations of <24 months, and FVC-DiP scores were higher than the actual %FVC for durations longer than 24 months.
      Table 1Baseline characteristics in the PRO-ACT database.
      VariablePatients (n = 920)
      Age at onset, years, mean (SD)52.3 (12.4)
      Age at baseline, years, mean (SD)54.2 (12.2)
      Men, n (%)573 (62.2)
      Racial group, White, n (%)854 (92.8)
      Disease duration from symptom onset, months, mean (SD)21.1 (11.6)
      Bulbar onset, n (%)195 (21.2)
      %FVC, %, mean (SD)83.0 (20.8)
      ALSFRS-R score, mean (SD)37.8 (5.2)
      BMI, kg/m2, mean (SD)26.3 (5.1)
      Use of riluzole, n (%)
      Calculated for patients with data concerning the use or non-use of riluzole (n = 568).
      409 (72.0)
      Abbreviations: ALS, amyotrophic lateral sclerosis; PRO-ACT, Pooled Resource Open-Access ALS Clinical Trials Cohort; %FVC, percentage of predicted forced vital capacity; ALSFRS-R, revised ALS Functional Rating Scale; BMI, body mass index; SD, standard deviation.
      a Calculated for patients with data concerning the use or non-use of riluzole (n = 568).

      3.2 Utility of FVC-DiP

      Baseline %FVC values for 907 patients in the PRO-ACT database, with baseline disease durations ranging from 5 to 62 months, were converted into FVC-DiP scores. The resulting FVC-DiP scores were widely distributed, even with equivalent values of %FVC (Fig. 2A ). When the patients were divided into groups according to the baseline FVC-DiP scores, it was found that the scores related to the survival time from symptom onset, with lower scores being associated with a shorter survival time (Fig. 2B). The rates of %FVC decline at baseline were also related to the survival time (Fig. 2C), but the baseline FVC-DiP scores more successfully separated patients into groups with incrementally longer survival. This difference between these baseline measures (rate of %FVC decline and FVC-DiP score) was especially apparent for patients with lower rate of %FVC decline, as also shown by the discordancy in patient distribution (Fig. S1).
      Fig. 2
      Fig. 2Associations between the FVC-DiP scores, %FVC, and disease durations in the PRO-ACT database.
      (A) Scatter plot of the %FVC at baseline and the FVC-DiP score (n = 907). Equivalent values of %FVC and FVC-DiP are shown as a gray line. (B) Survival rates from symptom onset for patient groups with different FVC-DiP baseline scores. Patients with lower FVC-DiP scores had significantly shorter survival. (C) Survival rates from symptom onset for patient groups with different rates of %FVC decline at baseline. The rate of %FVC decline at baseline was obtained by subtracting the %FVC at baseline from 100, and then dividing this value by the number of months from symptom onset. In patients with lower rates of %FVC decline, they were not well separated into groups with incrementally longer survival. (D) Changes in %FVC over time from baseline. The light gray lines show data for individual patients (n = 864). The dark gray line shows the slope of the linear mixed effects model for change in %FVC, with a fixed effect of duration from baseline and a random effect of patients (slope ± standard error: −2.08 ± 0.03). The decline in %FVC over time was statistically significant (p < 0.0001). (E) Changes in FVC-DiP scores over time from baseline. The light gray lines show data for individual patients (n = 864). The dark gray line shows the slope of the linear mixed effects model for change in FVC-DiP socre, with a fixed effect of duration from baseline and a random effect of patients (slope ± standard error: −0.02 ± 0.02). There was no significant change in the FVC-DiP scores over time (p = 0.3880). (F) Variability in FVC-DiP scores for each individual against the FVC-DiP scores at baseline. Each line represents the mean (thick horizontal line) and standard deviation (thin vertical line) of each individual's FVC-DiP scores over the observation period. The mean FVC-DiP scores for individual patients reflected their baseline FVC-DiP scores, and the variability (standard deviation) differed according to the baseline FVC-DiP scores. (G) Survival rates over time for patients with a %FVC ≥80 at baseline. A subgroup of patients with a FVC-DiP score < 80 at baseline had significantly shorter survival (median: 18.4 months; 95% confidence interval: 16.8–20.8; n = 229) than patients with a FVC-DiP score ≥ 80 at baseline (median: 24.3 months; 95% confidence interval: 20.9–29.9; n = 295; log-rank p = 0.0004). Abbreviations: FVC, forced vital capacity; FVC-DiP, FVC Decline Pattern scale; %FVC, percentage of predicted FVC; ALS, amyotrophic lateral sclerosis; PRO-ACT, Pooled Resource Open-Access ALS Clinical Trials Cohort.
      To determine whether the FVC-DiP scores reflected the individual patterns of decline in %FVC, irrespective of the measurement timing, we investigated changes in %FVC and FVC-DiP scores throughout the follow-up period using a series of longitudinal measurements. We included 5403 follow-up %FVC data points from 864 patients, and the raw data were successfully converted into FVC-DiP scores. The median follow-up period for these patients was 8.9 months (range: 0.1–45.2 months). A significant decline in %FVC was observed over time (p < 0.0001), with a slope of −2.08 ± 0.03 per month (slope ± standard error; Fig. 2D). However, there was no significant change in the FVC-DiP scores over time (p = 0.3880), with a slope of −0.02 ± 0.02 per month (slope ± standard error; Fig. 2E). The mean FVC-DiP score was determined for each patient over the observation period, and the values were found to be similar to the baseline FVC-DiP scores. The standard deviation was also determined for each patient's FVC-DiP scores, and this was found to differ according to the baseline FVC-DiP scores (Fig. 2F). Specifically, the variability (standard deviation) was smaller for individuals with baseline FVC-DiP scores below 40 or above 100, while the variability was somewhat larger for those with intermediate baseline scores (particularly 60–70). These results suggest that FVC-DiP scores reflect patterns of decline in %FVC and remain relatively constant, within a certain range, throughout the disease course.
      Next, we compared the characteristics of patients with a FVC-DiP score ≥ 80 and those with a score < 80 at baseline in the PRO-ACT database. The group with a FVC-DiP score < 80 were older at disease onset and had a shorter disease duration, a higher proportion with bulbar onset, and a lower %FVC at baseline (Table 2). There were no significant group differences in sex, race, or body mass index at baseline. ALSFRS-R scores at baseline did not differ between the two groups, but there was a significantly greater decrease in the ALSFRS-R scores over time in the group with FVC-DiP scores <80. The survival time from baseline was significantly shorter in patients with a FVC-DiP score < 80 compared with those with a score ≥ 80. Because a low %FVC is known to be associated with a high risk of death, we extracted patients with a %FVC ≥80 at baseline to assess the survival times for groups with different FVC-DiP scores. The analyses revealed that the survival times from baseline were significantly shorter in patients with a FVC-DiP score < 80 compared with those with a FVC-DiP score ≥ 80 (Fig. 2G). Cox proportional hazards analysis in patients with a %FVC ≥80 at baseline revealed that the %FVC at baseline and bulbar onset were not associated with the risk of death. However, older age at onset and low FVC-DiP scores at baseline significantly increased the risk of death, as seen in both univariate and multivariate analyses (Table 3). When the analyses were restricted to patients over 60 years old with a %FVC ≥80 at baseline, bulbar onset, age at onset, and %FVC at baseline were not associated with the risk of death, but a low FVC-DiP score at baseline significantly increased the risk of death (hazard ratio for death per 10-point decline in FVC-DiP score: 1.19; 95% confidence interval: 1.02–1.39; p = 0.0282; n = 109).
      Table 2Patient characteristics in the PRO-ACT database according to the FVC-DiP score at baseline.
      VariableFVC-DiP score at baselinep value
      ≥80 (n = 354)<80 (n = 553)
      Baseline
      Age at onset, years, mean (SD)49.2 (13.2)54.4 (11.4)< 0.0001
      Age at baseline, years, mean (SD)51.8 (13.1)55.7 (11.4)< 0.0001
      Men, n (%)228 (64.2)335 (60.6)0.2464
      Racial group, White, n (%)332 (93.5)509 (92.2)0.4101
      Disease duration from symptom onset to baseline, months, mean (SD)30.0 (11.6)15.8 (7.3)< 0.0001
      Bulbar onset, n (%)36 (10.1)156 (28.2)< 0.0001
      %FVC at baseline, %, mean (SD)95.0 (18.2)75.0 (18.5)< 0.0001
      ALSFRS-R score at baseline, mean (SD)37.6 (4.8)37.8 (5.5)0.7071
      BMI at baseline, kg/m2, mean (SD)26.7 (5.4)26.0 (4.9)0.0615
      Use of riluzole, n (%)
      Calculated for patients with data concerning the use or non-use of riluzole (n = 558).
      152 (68.5)250 (74.4)0.1262
      Follow-up
      Follow-up period, months, mean (SD)12.5 (8.2)11.8 (7.3)0.1554
      Change in ALSFRS-R score from baseline, per month, mean (SE)−0.51 (0.01)−0.95 (0.01)< 0.0001
      Survival time, months from baseline, median (95% CI)23.9 (19.0–28.8)15.6 (14.1–16.7)< 0.0001
      Abbreviations: ALS, amyotrophic lateral sclerosis; PRO-ACT, Pooled Resource Open-Access ALS Clinical Trials Cohort; FVC, forced vital capacity; FVC-DiP, FVC Decline Pattern scale; %FVC, percentage of predicted FVC; ALSFRS-R, revised ALS Functional Rating Scale; BMI, body mass index; SD, standard deviation; SE, standard error; CI, confidence interval.
      a Calculated for patients with data concerning the use or non-use of riluzole (n = 558).
      Table 3Risk of death assessed using Cox proportional hazards analyses in patients with a %FVC ≥80 at baseline in the PRO-ACT database (n = 524).
      VariableUnivariateMultivariate
      HR (95% CI)p valueHR (95% CI)p value
      Age at baseline (per 5-year increase)1.18 (1.08–1.30)0.00051.19 (1.08–1.31)0.0005
      Bulbar onset1.11 (0.73–1.69)0.6285
      %FVC at baseline (per 10% decline)1.10 (0.97–1.27)0.1619
      FVC-DiP score at baseline (per 10-point decline)1.21 (1.12–1.32)< 0.00011.13 (1.02–1.24)0.0141
      Abbreviations: ALS, amyotrophic lateral sclerosis; PRO-ACT, Pooled Resource Open-Access ALS Clinical Trials Cohort; FVC, forced vital capacity; %FVC, percentage of predicted FVC; FVC-DiP, FVC Decline Pattern scale; HR, hazard ratio; CI, confidence interval.
      Finally, we examined whether the association between FVC-DiP scores and the survival prognosis was comparable between patients with limb-onset and bulbar-onset ALS. Although survival times from baseline were shorter in patients with bulbar-onset ALS (Fig. S2A), the FVC-DiP scores at baseline related to the rate of disease progression, irrespective of the onset pattern (Fig. S2B).

      3.3 Application to our ALS cohort

      To validate the usability of the FVC-DiP, we applied it to our single-center cohort of 92 patients with ALS. The median follow-up period was 12.8 months (range: 0.4–105 months) and the demographic features are summarized in Table 4. Our cohort had an older mean age of onset than in the PRO-ACT database (mean years ± SD: 64.9 ± 11.4 vs 52.3 ± 12.4; p < 0.0001). In addition, our cohort exhibited a higher proportion of cases with a bulbar onset than in the PRO-ACT database (38% vs. 21.1%, respectively; p = 0.0002). A total of 155 %FVC data points from 92 patients were converted into FVC-DiP scores (Fig. 3A ).
      Table 4Baseline characteristics of our cohort.
      VariablePatients (n = 92)
      Age at onset, years, mean (SD)64.9 (11.4)
      Age at diagnosis, years, mean (SD)66.4 (11.3)
      Men, n (%)42 (45.6)
      Disease duration from symptom onset to diagnosis, months, mean (SD)17.7 (11.6)
      Revised El Escorial criteria at diagnosis, definite or probable, n (%)38 (41.3)
      Family history of ALS, n (%)5 (5.4)
      Bulbar onset, n (%)35 (38.0)
      Frontotemporal dementia at diagnosis, n (%)6 (6.5)
      %FVC at diagnosis, %, mean (SD)87.2 (26.8)
      ALSFRS-R score at diagnosis, mean (SD)39 (6.3)
      TRICALS Risk Profile at diagnosis, mean (SD)−4.89 (1.64)
      Abbreviations: ALS, amyotrophic lateral sclerosis; %FVC, percentage of predicted forced vital capacity; ALSFRS-R, revised ALS Functional Rating Scale; TRICALS, Treatment Research Initiative to Cure ALS; SD, standard deviation.
      Fig. 3
      Fig. 3Application of FVC-DiP to our cohort.
      (A) Scatterplot of the %FVC and FVC-DiP scores (155 measurements from 92 patients). The gray line shows equivalent %FVC and FVC-DiP values. (B) Scatterplot of the changes in %FVC and length of time from the baseline (61 measurements from 53 patients). The gray line shows the slope of the linear mixed effects model for change in %FVC, with a fixed effect of duration from baseline and a random effect of patients (slope ± standard error: −1.52 ± 0.21). A significant decline in %FVC was observed over time from the baseline (p < 0.0001). (C) Scatterplot of the changes in FVC-DiP scores and length of time from the baseline (61 measurements from 53 patients). The gray line shows the slope of the linear mixed effects model for the change in FVC-DiP score, with a fixed effect of duration from baseline and a random effect of patients (slope ± standard error: −0.15 ± 0.15). There was no significant change in the FVC-DiP scores over time from the baseline (p = 0.3322). (D) Scatterplot showing the strong correlation between the FVC-DiP scores and TRICALS Risk Profile scores. The gray line shows the slope of the linear mixed effects model for the TRICALS Risk Profile, with a fixed effect of FVC-DiP score and a random effect of patients (155 measurements from 92 patients, r2 = 0.904, p < 0.0001). Abbreviations: FVC, forced vital capacity; FVC-DiP, FVC Decline Pattern scale; %FVC, percentage of predicted FVC; ALS, amyotrophic lateral sclerosis; TRICALS, Treatment Research Initiative to Cure ALS.
      We investigated changes in %FVC and FVC-DiP scores during the disease course using 61 follow-up %FVC data points from 53 patients who had the longitudinal data that were needed to obtain the changes in both parameters. A significant decline in %FVC was observed over time from diagnosis (p < 0.0001), with a slope of −1.52 ± 0.21 per month (Fig. 3B). However, no significant change in the FVC-DiP score was detected over time from diagnosis (p = 0.3322; Fig. 3C), in line with the PRO-ACT database finding that the FVC-DiP scores were relatively stable in individuals, irrespective of the measurement timing, and reflected patterns of %FVC decline.
      Next, patient characteristics were compared between the groups with a FVC-DiP score ≥ 80 or < 80 at diagnosis (Table 5). The group of patients with a score < 80 exhibited a shorter disease duration from symptom onset, a higher proportion of bulbar onset ALS, and a lower %FVC at diagnosis than the group of patients with a FVC-DiP score ≥ 80. No other significant differences were observed between the two groups in terms of their characteristics at diagnosis, including the ALSFRS-R scores. During the follow-up period (which was shorter in the group with a FVC-DiP score < 80), although the change in ALSFRS-R scores was similar in the two groups, the ventilator-free survival time from diagnosis was significantly shorter in the group with FVC-DiP scores <80. A Cox proportional hazards analysis restricted to patients with a baseline %FVC ≥80 revealed that lower FVC-DiP scores at baseline significantly increased the risk of death or use of ventilation (hazard ratio for death per 10-point FVC-DiP score decline: 1.36; 95% confidence interval: 1.09–1.72; p = 0.0075; n = 62). In contrast, the age at onset, bulbar onset, and %FVC at baseline were not associated with the risk of death or use of ventilation.
      Table 5Patient characteristics in our cohort according to the FVC-DiP score at diagnosis.
      VariableFVC-DiP score at diagnosisp value
      ≥80 (n = 26)<80 (n = 66)
      At diagnosis
      Age at onset, years, mean (SD)62.0 (10.1)66.1 (11.8)0.1261
      Age at diagnosis, years, mean (SD)64.5 (10.0)67.2 (11.8)0.3152
      Men, n (%)13 (50.0)29 (43.9)0.5992
      Disease duration from symptom onset, months, mean (SD)30.2 (12.7)12.8 (6.3)< 0.0001
      Revised El Escorial criteria at diagnosis, definite or probable, n (%)8 (30.8)30 (45.4)0.1977
      Family history of ALS, n (%)2 (7.7)3 (4.5)0.5488
      Bulbar onset, n (%)5 (19.2)30 (45.5)0.0197
      Frontotemporal dementia, n (%)2 (7.7)4 (6.1)0.7753
      %FVC at diagnosis, mean (SD)102.0 (18.7)81.4 (27.4)0.0007
      ALSFRS-R score at diagnosis, mean (SD)39.7 (5.2)39.2 (6.7)0.7361
      TRICALS Risk Profile at diagnosis, mean (SD)−6.67 (1.11)−4.19 (1.22)< 0.0001
      Follow-up
      Follow-up period, months, mean (SD)29.3 (28.1)14.0 (13.3)0.0006
      Use of riluzole, n (%)18 (69.2)35 (53.0)0.1568
      Use of edaravone, n (%)7 (26.9)11 (16.7)0.2642
      Change in ALSFRS-R score from diagnosis, per month, mean (SE)
      n = 15 for the group with a FVC-DiP score ≥ 80, and n = 36 for the group with a FVC-DiP score < 80.
      −0.49 (0.08)−0.53 (0.10)0.5643
      Time to death or use of ventilation from diagnosis, months, 25th percentile / median (95% CI)28.3/NA4.3/17.5 (10.1–24.5)0.0006
      Abbreviations: FVC, forced vital capacity; FVC-DiP, FVC Decline Pattern scale; %FVC, percentage of predicted FVC; ALS, amyotrophic lateral sclerosis; ALSFRS-R, revised ALS Functional Rating Scale; TRICALS, Treatment Research Initiative to Cure ALS; SD, standard deviation; SE, standard error; CI, confidence interval; NA, not available.
      a n = 15 for the group with a FVC-DiP score ≥ 80, and n = 36 for the group with a FVC-DiP score < 80.
      Finally, we examined the association between the FVC-DiP and the TRICALS Risk Profile, a previously-developed prognostic summary measure based on a well-validated prognostic model. At diagnosis, the TRICALS Risk Profile was significantly higher in the group with FVC-DiP scores <80, indicating faster predicted progression compared with the group with FVC-DiP scores ≥80 (Table 5). A significant correlation was observed between the FVC-DiP scores and the TRICALS Risk Profile, using all of the follow-up data (n = 155, r2 = 0.904, p < 0.0001, Fig. 3D). A strong correlation was still observed when the analysis only included the data at diagnosis (n = 92, r2 = 0.648, p < 0.0001).

      4. Discussion

      In the current study, we developed the FVC-DiP, a novel quantitative scale that reflects the diverse patterns of decline in %FVC over the course of ALS. FVC-DiP scores in individuals were determined from a single measurement of %FVC and disease duration at assessment. The baseline FVC-DiP scores separated patients into groups with incrementally longer survival more clearly than the rate of %FVC decline at baseline. Although a significant decline in %FVC was observed over time, the FVC-DiP scores remained relatively stable, within a certain range, over the observation period. Lower FVC-DiP scores at baseline were associated with faster disease progression in both patients with limb-onset and bulbar-onset ALS. These results suggest that FVC-DiP scores reflect each individual's pattern of %FVC decline, in contrast to the changes seen at a population level. The FVC-DiP is therefore a suitable candidate for indicating disease progression rates in ALS (Fig. 4A and B ).
      Fig. 4
      Fig. 4Illustration of the characteristics and expected utility of the FVC-DiP.
      (A) Illustration of the large individual differences in patterns of %FVC decline over the course of the disease. (B) Illustration showing that the FVC-DiP scores indicate the rate of disease progression and remain relatively stable, within a certain range of variability, over the course of the disease in each patient. (C) Illustration showing that the %FVC can still decline, even if a treatment ameliorates the rate of disease progression, thus making it difficult to detect a treatment effect. (D) Plot showing that the FVC-DiP score will increase beyond the usual range of variability if a treatment ameliorates the disease progression rate, even if the %FVC declines. Abbreviations: FVC, forced vital capacity; FVC-DiP, FVC Decline Pattern scale; %FVC, percentage of predicted FVC.
      To derive FVC-DiP scores, we used longitudinal %FVC measurements from the PRO-ACT database. Median %FVC values were determined for a series of 3-month intervals and were found to be lowest at 24 months. This indicates that earlier time periods mainly included data for patients with rapid disease progression, who would have died or drastically deteriorated by 24 months, while data for patients with relatively slow disease progression would have been included after 24 months. We used the values at 24 months as the standard, and sequentially compared data at adjacent 3-month intervals. The FVC-DiP scores were lower than the actual %FVC at durations of <24 months, while the FVC-DiP scores were higher than the actual %FVC at durations longer than 24 months. By determining both the FVC-DiP score and the %FVC for patients at a particular point in time, it may therefore be easier to evaluate the disease severity; for example, a FVC-DiP score lower than the actual %FVC may indicate rapid disease progression, while a FVC-DiP score higher than the actual %FVC may indicate slow disease progression. As differences in FVC-DiP scores between adjacent cells were variable and the change in FVC-DiP scores between two timepoints differed even when there were similar slopes of %FVC decline, the FVC-DiP score can be seen to represent a new measure for determining the rate of disease progression based on the %FVC.
      We used our Japanese cohort for external validation of the FVC-DiP. These patients had an older mean age of onset and a higher proportion of cases with bulbar-onset ALS compared with the patients in the PRO-ACT database. Nonetheless, the association between the FVC-DiP score and the survival prognosis was replicated in our cohort, as was the FVC-DiP's stability over the course of the disease. Recently, TRICALS proposed the Risk Profile to select patients in clinical trials, based on the survival prediction model developed by the European Network to Cure ALS [
      • Westeneng H.J.
      • Debray T.P.A.
      • Visser A.E.
      • et al.
      Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model.
      ,
      • van Eijk R.P.A.
      • Westeneng H.J.
      • Nikolakopoulos S.
      • et al.
      Refining eligibility criteria for amyotrophic lateral sclerosis clinical trials.
      ]. The Risk Profile indicates a predicted progression rate without estimating the absolute survival time or probability, with higher values indicating faster disease progression. In our cohort, the FVC-DiP was strongly correlated with the TRICALS Risk Profile, and low FVC-DiP scores were associated with high TRICALS Risk Profile values. These findings suggest that the FVC-DiP can be used to assess the rate of disease progression with a comparable level of accuracy to the TRICALS Risk Profile, but with fewer parameters.
      Most of the current ALS disease indicators or staging systems focus on the patient's functional state at the time of assessment [
      • Simon N.G.
      • Turner M.R.
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      Quantifying disease progression in amyotrophic lateral sclerosis.
      ,
      • Chio A.
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      ,
      • Corcia P.
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      Staging amyotrophic lateral sclerosis: a new focus on progression.
      ]. The ALSFRS-R assesses the degree of disability for 12 different items that relate to bulbar, limb, and respiratory function symptoms; the measure is a common functional indicator that is used in addition to the FVC [
      • Cedarbaum J.M.
      • Stambler N.
      • Malta E.
      • et al.
      The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function.
      ]. Rates of decline in the %FVC and ALSFRS-R have been found to independently predict survival in patients with ALS [
      • Traynor B.J.
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      On behalf of the NEALS consortium. Functional outcome measures as clinical trial endpoints in ALS.
      ], but longitudinal observation is required to obtain these rates. It has been reported that the ALSFRS-R score at diagnosis and the %FVC at the initial visit can also predict disease progression [
      • Czaplinski A.
      • Yen A.A.
      • Appel S.H.
      Forced vital capacity (FVC) as an indicator of survival and disease progression in an ALS clinic population.
      ,
      • Kimura F.
      • Fujimura C.
      • Ishida S.
      • et al.
      Progression rate of ALSFRS-R at time of diagnosis predicts survival time in ALS.
      ]. However, in the current study, we showed that the disease duration considerably affects how well the %FVC values can determine the disease progression. Here, we developed a new method to determine the disease progression rate using a single measurement of functional indicators, irrespective of the measurement timing. Previously, prognostic models have been developed that assess the rate of disease progression in individual patients. However, these models often require multiple parameters, and can be somewhat complicated to use in clinical practice. Furthermore, most prognostic models include invariant factors, such as the onset age or site of onset, and are considered to be useful for predicting the prognosis in the early stages of the disease rather than at follow-up. The FVC-DiP score in the current study is determined using a single measurement of %FVC and can be adopted throughout the disease course, thus providing benefits for clinical practice. In the future, its use may enable the evaluation of treatments that slow down disease progression; this is currently difficult using other measures, such as the %FVC, which vary over time (Fig. 4C and D).
      Indicators of the disease progression rate are important from the perspective of drug development. Guidelines for drug development and clinical trials describe enrichment strategies, such as the enrollment of certain patients, which is expected to increase the likelihood of demonstrating a drug effect, and encourage the development of new outcome measures capable of assessing clinically meaningful effects [
      • U.S. Department of Health and Human Services Food and Drug Administration
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      ,
      • van den Berg L.H.
      • Sorenson E.
      • Gronseth G.
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      ,
      • Andrews J.A.
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      ]. In a phase 3 trial of edaravone, patients were only included who fulfilled strict criteria including the disease progression rate, defined by a range of decline in ALSFRS-R scores during the pre-observational period. A significantly smaller decline in ALSFRS-R scores was demonstrated in the edaravone group compared with the placebo group [
      • Abe K.
      • Aoki M.
      • Tsuji S.
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      Safety and efficacy of edaravone in well defined patients with amyotrophic lateral sclerosis: a randomised, double-blind, placebo-controlled trial.
      ]. In a phase 2 trial of reldesemtiv, post hoc analyses revealed that the decline in ALSFRS-R scores was significantly reduced in patients in the fastest progressing tertile (decline in ALSFRS-R scores >0.67 per month), but not in patients in the slowest tertile (decline in ALSFRS-R scores ≤0.37 per month) [
      • Shefner J.M.
      • Andrews J.A.
      • Genge A.
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      A phase 2, double-blind, randomized, dose-ranging trial of Reldesemtiv in patients with ALS.
      ]. These findings suggest that the power to detect an effect on disease progression increased by targeting patients who exhibited a certain progression rate (i.e., cases with rapid disease progression). The FVC-DiP could be of benefit for determining eligibility for inclusion in clinical trials because the disease progression rate can be evaluated in a single visit. In addition, the FVC-DiP score could be used to enable the detection of clinically meaningful changes in the rate of disease progression that are not apparent using the slope of %FVC decline. In this way, the FVC-DiP could be used as an outcome measure to evaluate changes in the disease progression rate (i.e., as a surrogate endpoint for survival). It could also be used as a randomization stratification factor for trials with a broader target population (i.e., where patients are not preselected according to the disease progression rate). Furthermore, the FVC-DiP could be used in both clinical trials and clinical practice, which may be helpful for the generalizability of trial results.
      The current study has several limitations. First, we were not able to calculate FVC-DiP scores for a duration from symptom onset of 5 months or >61 months, because the sample size in those ranges was too small. In general, the typical time from symptom onset to diagnosis is 10–16 months, and patients diagnosed within <5 months are considered to be rare [
      • Richards D.
      • Morren J.A.
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      ]. However, new diagnostic criteria were recently proposed, which show high diagnostic sensitivity [
      • Shefner J.M.
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      ,
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      ]. If the diagnostic delay is shortened using these new criteria, the average pattern of %FVC decline, particularly in the early stages, may need to be re-evaluated. Second, our method was not able to derive the gradation of scores for a %FVC ≥100 from 24 to 60 months or < 50 from 6 to 24 months. In addition, we corrected scores in some cells to maintain the gradation of FVC-DiP scores, and we complemented scores for two cells because of a lack of patients with available data. Examining a larger cohort, particularly if patients with a longer disease duration were included, might enable modification of these cells. Third, there was a potential selection bias because the PRO-ACT database consisted of patients who fulfilled the selection criteria for clinical trials, including age limits. The mean age of patients in the PRO-ACT database was slightly lower than in some other large ALS cohorts [
      • Westeneng H.J.
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      • Visser A.E.
      • et al.
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      • Dimitrakopoulos A.
      Serum levels of soluble intercellular adhesion molecule-1 (s-ICAM-1) and soluble endothelial leukocyte adhesion molecule-1(s-ELAM-1) in amyotrophic lateral sclerosis.
      ,
      • Shahrizaila N.
      • Sobue G.
      • Kuwabara S.
      • et al.
      Amyotrophic lateral sclerosis and motor neuron syndromes in Asia.
      ]. In addition, most of the patients in the PRO-ACT database were White. Some genetic differences across racial groups have been reported, such as the frequency of the C9orf72 repeat expansion, which is a genetic predictor of short survival and is the most common mutation in White ALS patients for both familial and sporadic ALS, but is rare in Asian ALS patients [
      • Chio A.
      • Logroscino G.
      • Hardiman O.
      • et al.
      Prognostic factors in ALS: a critical review.
      ,
      • Shahrizaila N.
      • Sobue G.
      • Kuwabara S.
      • et al.
      Amyotrophic lateral sclerosis and motor neuron syndromes in Asia.
      ,
      • Rademakers R.
      • van Blitterswijk M.
      Motor neuron disease in 2012: novel causal genes and disease modifiers.
      ,
      • van Rheenen W.
      • van Blitterswijk M.
      • Huisman M.H.
      • et al.
      Hexanucleotide repeat expansions in C9ORF72 in the spectrum of motor neuron diseases.
      ]. Comparison with FVC-DiP values derived from other cohorts may reveal factors that require adjustment in the future. Fourth, there was no significant difference between the change in ALSFRS-R scores for patients with a baseline FVC-DiP score ≥ 80 and those with a score < 80 in our cohort. This may have been caused by insufficient statistical power, because there were <65 participants with ALSFRS-R scores in our cohort, which was the estimated sample size required to detect such differences with 80% statistical power. Alternatively, as the group with a FVC-DiP score < 80 had a significantly shorter time to death or ventilation than the group with a score ≥ 80, the FVC-DiP could potentially be capable of detecting differences in the rate of disease progression that cannot be detected by changes in the ALSFRS-R scores. Finally, the variability in FVC-DiP scores over the observation period was particularly large for patients with baseline FVC-DiP scores between 60 and 70. This could be due to the large differences in scores for cells adjacent to those with FVC-DiP scores between 60 and 70 (Fig. 1F). The difference in FVC-DiP score variability should be taken into account when defining meaningful changes in the FVC-DiP scores for monitoring treatment effects. In the future, it may be possible to reduce the variability in FVC-DiP scores by narrowing the disease duration ranges and %FVC divisions used for deriving the FVC-DiP scores.

      5. Conclusions

      We propose that the FVC-DiP provides a novel quantitative indicator for the disease progression rate in ALS. This indicator is derived from the diverse patterns of %FVC decline in a large pooled cohort of ALS patients. We were able to determine each individual's FVC-DiP score from a single measurement of %FVC and disease duration at assessment. This provided a rapid and convenient evaluation of a patient's progression pattern, which is otherwise difficult to achieve using %FVC values alone. Future investigation of the relationship between the FVC-DiP and other surrogate endpoints or biomarkers could determine the FVC-DiP's reliability as a tool for monitoring treatment effects.

      Funding

      This study was financially supported by the Japan Agency for Medical Research and Development (Grant number JP19mk0101164 ), and Grants-in Aid from the Research Committee of CNS Degenerative Diseases, Research on Policy Planning and Evaluation for Rare and Intractable Diseases, Health, Labour and Welfare Sciences Research Grants, the Ministry of Health, Labour and Welfare, Japan (Grant number 20FC1049).

      Disclosures

      J.K. received a research fund from Mitsubishi Tanabe and honoraria from Mitsubishi Tanabe Pharma and Sanofi KK. N.I. received honoraria from Sanofi KK. The remaining authors report no conflicts of interest.

      Acknowledgments

      We thank Mr. Sakanashi and Mr. Sakai from the Center for Clinical and Translational Research at Kyushu University Hospital for data processing. We thank Jessica Foxton, PhD, Benjamin Knight, MSc., and RJ Frampton from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.

      Appendix A. Supplementary data

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