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# Total lung capacity is predictive of disease severity and survival in systemic sclerosis: A longitudinal analysis in 2347 patients from the French National Cohort Study

Benjamin Chaigne<sup>1,2,*</sup>, Alexandre Bense<sup>1,2</sup>, Frédérique Aubourg<sup>3</sup>, Christian Agard<sup>4</sup>, Yannick Allanore<sup>5</sup>, Alice Berezne<sup>6</sup>, Grégory Pugnet<sup>7</sup>, Eric Hachulla<sup>8</sup>, Vincent Cottin<sup>9</sup>,<sup>10</sup> Arnaud Hot<sup>10</sup>, Bertrand Dunogue<sup>1</sup>, Anuxcy Kanagaratnam<sup>1</sup>, Sylvain Palat<sup>11</sup>, Alain Lescoat<sup>12</sup>, Sabine Berthier<sup>13</sup>, Emmanuel Chatelus<sup>14</sup>, Sébastien Rivière<sup>15</sup>, David Launay<sup>8</sup>, Marie-Elise Truchetet<sup>16</sup>, Anh Tuan Dinh-Xuan<sup>2,3</sup>, Luc Mouthon<sup>1,2</sup>, French Systemic Sclerosis Network<sup>#</sup>

## ARTICLE INFO

Handling Editor: C Selmi

Keywords:

Systemic sclerosis

Total lung capacity

Disease severity

Survival

Prognosis

Interstitial lung disease

Lung fibrosis

Forced vital capacity

## ABSTRACT

**Background:** Total lung capacity (TLC) is seldom assessed in the prediction of systemic sclerosis (SSc) disease severity.

**Objective:** To describe and analyse TLC in SSc.

**Methods:** We performed a retrospective multicentre study of SSc patients enrolled in the French national SSc cohort with at least one TLC assessment, described patients based on baseline TLC measurements, modelized TLC trajectories in SSc, and associated TLC measures with disease prognosis.

**Results:** Two thousand three hundred and forty-seven patients were included in the study. Baseline TLC was associated with disease severity and survival, as well as with the occurrence of interstitial lung disease (ILD), lung fibrosis (LF), and pulmonary arterial hypertension (PAH). Individual TLC trajectories varied among patients. Different models of TLC trajectories were assessed using latent process mixed models. The best model

<footnote n="1"><sup>1</sup> Service de Médecine Interne, Centre de Référence Maladies Autoimmunes Systémiques Rares d'Ile de France, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France</footnote>

<footnote n="2"><sup>2</sup> APHP-CUP, Hôpital Cochin, F-75014 Paris, Université Paris Cité, Paris</footnote>

<footnote n="3"><sup>3</sup> Department of Respiratory and Sleep Medicine, Hôpital Cochin, AP-HP</footnote>

<footnote n="4"><sup>4</sup> Nantes Université, CHU Nantes, Service de Médecine interne, Nantes, France</footnote>

<footnote n="5"><sup>5</sup> Rheumatology Department, Hôpital Cochin, AP-HP Université Paris Cité</footnote>

<footnote n="6"><sup>6</sup> Department of Internal Medicine and Infectious Diseases CHR Annecy-Genevois Annecy France</footnote>

<footnote n="7"><sup>7</sup> Centre Hospitalier Universitaire, Médecine Interne, Toulouse, France</footnote>

<footnote n="8"><sup>8</sup> Univ. Lille, Inserm, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Service de Médecine Interne et Immunologie Clinique, Centre de référence des Maladies Auto-Immunes et Auto-inflamatoires Systémiques rares de l'Adulte du Nord, Nord-Ouest, Méditerranée et Guadeloupe (CeRAINOM)</footnote>

<footnote n="9"><sup>9</sup> Unité Mixte de Recherche 754: Infections Virales et Pathologie Comparée, Hospices Civils de Lyon, Université Lyon 1-Institut National de la Recherche Agronomique-Centre National de Référence des Maladies Pulmonaires Rares, ERN-LUNG, Lyon, France</footnote>

<footnote n="10"><sup>10</sup> Service de Médecine interne et Immunologie Clinique, Centre Hospitalier Universitaire Édouard Herriot, Hospices Civils de Lyon, Lyon, France</footnote>

<footnote n="11"><sup>11</sup> CHU Limoges, Limoges, Limousin, France</footnote>

<footnote n="12"><sup>12</sup> Department of Internal Medicine, CHU Rennes, University of Rennes 1, Rennes, France</footnote>

<footnote n="13"><sup>13</sup> Department of internal medicine, University hospital of Dijon, Dijon, France</footnote>

<footnote n="14"><sup>14</sup> Rheumatology, Hôpitaux universitaires de Strasbourg, Strasbourg, France</footnote>

<footnote n="15"><sup>15</sup> Service de Médecine Interne and Inflammation-Immunopathology, Biotherapy Department (DMU 3iD), Sorbonne Université, Hôpital Saint-Antoine, AP-HP, 75012 Paris, France</footnote>

<footnote n="16"><sup>16</sup> Rheumatology Department, University Hospital of Bordeaux, Centre de Référence des Maladies Autoimmunes Systémiques Rares Du Sud-Ouest, Bordeaux, France</footnote>

<footnote>* Corresponding author: Dr Benjamin Chaigne, Department of Internal Medicine, Systemic Auto Immune Diseases Reference Center of Ile de France, Cochin University Hospital, Assistance Publique-Hôpitaux de Paris27 rue du Faubourg Saint Jacques, 75014 Paris, France. Tel: +33 (0) 1 58 41 22 15/ Fax: +33 (0) 1 58 41 14 50.</footnote>

<footnote>E-mail address: benjamin.chaigne@aphp.fr (B. Chaigne).</footnote>

<footnote># French Systemic Sclerosis Network Collaborators</footnote>
showed that the vast majority of SSc patients had stable TLC trajectories and clustered patients into three groups predictive of SSc survival, ILD, LF, and PAH. Lastly, a 10% decrease of TLC was found to be predictive of a 5% decrease in forced vital capacity (FVC), a 10% decrease in DLCO, and consequently an earlier predictive marker of ILD and LF than FVC.

**Limitations:** Retrospective study.

**Conclusion:** TLC is predictive of disease severity and survival in SSc and SSc-ILD. This work suggests TLC as an earlier risk factor for ILD and LF than FVC in SSc.

## Abbreviations

ACA anti-centromere antibodies

ACR American College of Rheumatology

ARA anti-RNA polymerase III antibodies

ATA anti-topoisomerase I antibodies

CRP C-reactive protein

dcSSc diffuse cutaneous systemic sclerosis

DLCO diffusing capacity of the lungs for carbon monoxide

EULAR European Alliance of Associations for Rheumatology

FDA food and drug administration

FVC forced vital capacity

HAQ-DI health assessment questionnaire-disability index

HRCT high resolution computed tomography

ILD interstitial lung disease

IQR interquartile range

ISD immunosuppressant drugs

lcSSc limited cutaneous systemic sclerosis

LF lung fibrosis

mRSS modified Rodnan skin score

PAH pulmonary arterial hypertension

PFTs pulmonary function tests

RP Raynaud's phenomenon

SRC scleroderma renal crisis

SSc systemic sclerosis

SSc-ILD systemic sclerosis associated interstitial lung disease

TLC total lung capacity

vs versus

## Key-messages (64 words)

* Lower TLC is associated with more severe disease

* Three trajectories of TLC were identified

* Most patients with SSc have a stable TLC trajectory

* Baseline TLC and TLC trajectories predict survival and lung involvement

* A 10% TLC decrease predicts interstitial lung disease (ILD) and lung fibrosis (LF)

* A 10% TLC decrease is a better predictor of ILD and LF onset than a 5% FVC decrease

## 1. Introduction

Systemic sclerosis (SSc) is a connective tissue disease characterized by vasculopathy, fibrosis, and autoimmunity [1,2]. Fibrosis and vasculopathy mainly affect the skin but any internal organ can be involved. Lung involvement is the main cause of morbidity and mortality in SSc, including lung fibrosis (LF) or interstitial lung disease (ILD) and pulmonary arterial hypertension (PAH). PAH affects about 15% of patients with SSc, particularly those with limited cutaneous SSc. Patients with SSc are at high risk of ILD, which occurs in 35-52% of patients and accounts for 20-40% of mortality [1,2]. Only 25-30% of patients will develop progressive ILD. Risk factors for the development and progression of SSc-ILD include male sex, age over 60 years old, Afro-American ethnicity, diffuse cutaneous SSc (dcSSc), early disease (first 5-7 years after onset), anti-topoisomerase I antibody (ATA), and inflammatory syndrome. Pathobiologically, SSc-ILD results from the replacement of normal pulmonary architecture by scarring following injury to the alveolar epithelium, leading to a restrictive pathological defect and impaired gas exchange [3].

Screening and monitoring SSc-ILD is essential in the care of SSc patients, as the course of SSc-ILD course is variable and highly heterogeneous. Following consensus and recent recommendations, assessing SSc-ILD relies on high resolution computed tomography (HRCT) and

pulmonary function tests (PFTs). PFTs, which reflect the physiological properties of the lungs, have been used for decades in lung diseases, including SSc-ILD. PFTs play a pivotal role in the diagnosis of SSc-ILD, providing the investigators a reliable tool to assess severity and progression of the disease. In clinical practice, these assessments rely mainly, if not exclusively, on forced vital capacity (FVC) measured by spirometry, and diffusing capacity of the lungs for carbon monoxide (DLCO), using either absolute values, variations from baseline, or percentage predicted values. FVC is not a simple measure to obtain, as it represents the maximum volume of air exhaled forcefully after maximum inspiration. Importantly, FVC is recognised as a meaningful endpoint and a Food and Drug Administration (FDA) accepted outcome measure in SSc clinical trials. However, in the early phase of SSc-ILD, FVC and DLCO can be normal [4].

In addition to spirometry that does not measure residual volume (RV), one can rely on plethysmography to assess whole lung volumes. Plethysmography measures RV, hence functional residual capacity (FRC) and total lung capacity (TLC), whilst also assessing slow (inspiratory) vital capacity. TLC is simpler to obtain than FVC, as it measures the total volume of air in the lungs after maximum inspiration. As restrictive lung disease is defined by reduction of all lung volumes including vital capacity and RV, reduced TLC less than 80% predicted or lower limits of normal is theoretically required to diagnose a restrictive ventilatory defect. Notably, lung volumes measurements are not impacted by slow respiratory manoeuvres unlike forced expiration made by the patient to yield FVC values. Although lung volumes are necessary to confirm a restrictive defect suggested by spirometry, to the best of our knowledge, no data is available regarding TLC in SSc.

Herein, we utilized the French SSc national database to analyse TLC in SSc patients, examine its longitudinal trajectories, and explore its associations with organ involvement and patient survival.
<table><caption>**Table 1**
Baseline characteristics of systemic sclerosis patients according to total lung capacity study.</caption><thead><tr><th></th><th>All patients (n = 2347)</th><th>&lt;80 % (n = 565)</th><th>≥80 % - &lt; 90 % (n = 376)</th><th>≥90 % - &lt; 100 % (n = 407)</th><th>≥100 % (n = 999)</th><th>p</th></tr></thead><tbody><tr><td>Male, n (%)</td><td>467 (19.9)</td><td>158 (28.0)</td><td>91 (24.2)</td><td>89 (21.9)</td><td>129 (12.9)</td><td>&lt;0.0001</td></tr><tr><td>Age at diagnostic, years, median [IQR]</td><td>52 [41–63]</td><td>50 [39–62]</td><td>52 [41–64]</td><td>53 [43–65]</td><td>51 [41–60]</td><td>&lt;0.05</td></tr><tr><td>Time from first non-Raynaud's phenomenon, years, median [IQR]</td><td>0 [0–2]</td><td>0 [0–2]</td><td>0 [0–1]</td><td>0 [0–1]</td><td>0 [0–2]</td><td>0.75</td></tr><tr><td>dcSSc, n (%)</td><td>709 (30.2)</td><td>257 (45.5)</td><td>130 (34.6)</td><td>127 (31.2)</td><td>195 (19.5)</td><td>&lt;0.0001</td></tr><tr><td>Asthenia, n (%)</td><td>535 (22.8)</td><td>135 (23.9)</td><td>95 (25.3)</td><td>104 (25.6)</td><td>201 (20.1)</td><td>0.06</td></tr><tr><td>Weight loss, n (%)</td><td>333 (14.2)</td><td>118 (20.9)</td><td>67 (17.8)</td><td>57 (14.0)</td><td>91 (9.1)</td><td>&lt;0.0001</td></tr><tr><td>Weight, kg, median [IQR]</td><td>63 [55–73]</td><td>65 [56–75]</td><td>65 [57–76]</td><td>64 [55–73]</td><td>60 [54–70]</td><td>&lt;0.0001</td></tr><tr><td>BMI, kg/m², median [IQR]</td><td>25.0 [20.0–29.8]</td><td>24.3 [21.0–27.6]</td><td>24.3 [21.8–27.3]</td><td>23.7 [20.8–27.3]</td><td>22.8 [20.4–25.8]</td><td>&lt;0.0001</td></tr><tr><td>Mouth opening, mm, median [IQR]</td><td>40 [30–42]</td><td>35 [28–40]</td><td>35 [30–41]</td><td>40 [34–43]</td><td>40 [35–45]</td><td>&lt;0.0001</td></tr><tr><td>mRSS, IU, median [IQR]</td><td>5 [2–14]</td><td>11 [4–20]</td><td>7 [2–17]</td><td>6 [2–15]</td><td>3 [2–9]</td><td>&lt;0.0001</td></tr><tr><td>Puffy fingers, n (%)</td><td>1117 (47.8)</td><td>249 (44.0)</td><td>161 (42.8)</td><td>217 (53.3)</td><td>490 (49.0)</td><td>&lt;0.01</td></tr><tr><td>Sclerodactyly, n (%)</td><td>1041 (44.3)</td><td>275 (48.7)</td><td>161 (42.8)</td><td>193 (47.4)</td><td>412 (41.2)</td><td>&lt;0.05</td></tr><tr><td>Fingertip pitting scars, n (%)</td><td>654 (27.9)</td><td>183 (32.4)</td><td>100 (26.6)</td><td>130 (31.9)</td><td>241 (24.1)</td><td>&lt;0.01</td></tr><tr><td>Digital ulcers, n (%)</td><td>388 (16.5)</td><td>130 (23.0)</td><td>52 (13.8)</td><td>60 (14.7)</td><td>146 (14.6)</td><td>&lt;0.0001</td></tr><tr><td>Telangiectasia, n (%)</td><td>1186 (50.5)</td><td>259 (45.8)</td><td>170 (45.2)</td><td>223 (54.8)</td><td>534 (53.5)</td><td>&lt;0.01</td></tr><tr><td>Abnormal naifold capillaries, n (%)</td><td>1091 (46.5)</td><td>241 (42.7)</td><td>147 (39.1)</td><td>223 (54.8)</td><td>480 (48.0)</td><td>&lt;0.0001</td></tr><tr><td>Calcinosis, n (%)</td><td>372 (15.8)</td><td>79 (13.9)</td><td>55 (14.6)</td><td>64 (15.7)</td><td>174 (17.4)</td><td>0.29</td></tr><tr><td>Muscle symptoms, n (%)</td><td>472 (20.1)</td><td>159 (28.1)</td><td>78 (20.7)</td><td>77 (18.9)</td><td>158 (15.8)</td><td>&lt;0.0001</td></tr><tr><td>Increased CK, n (%)</td><td>157 (6.7)</td><td>62 (11.0)</td><td>29 (7.7)</td><td>26 (6.4)</td><td>40 (4.0)</td><td>&lt;0.0001</td></tr><tr><td>Arthralgia, n (%)</td><td>873 (37.2)</td><td>305 (54.0)</td><td>172 (45.7)</td><td>195 (47.9)</td><td>412 (41.2)</td><td>&lt;0.0001</td></tr><tr><td>Synovitis, n (%)</td><td>212 (9.0)</td><td>54 (9.6)</td><td>52 (12.8)</td><td>32 (7.9)</td><td>74 (7.4)</td><td>&lt;0.01</td></tr><tr><td>TFR, n (%)</td><td>59 (2.5)</td><td>19 (3.4)</td><td>12 (3.2)</td><td>13 (3.2)</td><td>15 (1.5)</td><td>0.06</td></tr><tr><td>Shortness of breath, n (%)</td><td>1306 (55.6)</td><td>460 (81.4)</td><td>219 (58.2)</td><td>222 (54.5)</td><td>405 (40.5)</td><td>&lt;0.0001</td></tr><tr><td>NYHA classification, median [IQR]</td><td>2 [1–2]</td><td>2 [2–3]</td><td>2 [1–2]</td><td>2 [1–2]</td><td>1 [1–2]</td><td>&lt;0.0001</td></tr><tr><td>Interstitial lung syndrome, n (%)</td><td>924 (39.4)</td><td>409 (72.4)</td><td>165 (43.9)</td><td>138 (33.9)</td><td>212 (21.2)</td><td>&lt;0.0001</td></tr><tr><td>Lung fibrosis, n (%)</td><td>646 (27.5)</td><td>319 (56.5)</td><td>119 (31.6)</td><td>84 (20.6)</td><td>124 (12.4)</td><td>&lt;0.0001</td></tr><tr><td>FVC %, median [IQR]</td><td>97 [80–111]</td><td>68 [57–79]</td><td>87 [78–96]</td><td>97 [89–105]</td><td>111 [101–121]</td><td>&lt;0.0001</td></tr><tr><td>TLC %, median [IQR]</td><td>96 [80–108]</td><td>69 [60–75]</td><td>85 [82–87]</td><td>95 [92–97]</td><td>110 [105–118]</td><td>&lt;0.0001</td></tr><tr><td>DLCO %, median [IQR]</td><td>66 [51–79]</td><td>46 [34–58]</td><td>58 [46–71]</td><td>69 [57–80]</td><td>75 [64–85]</td><td>&lt;0.0001</td></tr><tr><td>PAH, n (%)</td><td>265 (11.3)</td><td>132 (23.4)</td><td>46 (12.2)</td><td>37 (9.1)</td><td>50 (5.0)</td><td>&lt;0.0001</td></tr><tr><td>Scleroderma renal crisis, n (%)</td><td>110 (4.7)</td><td>47 (8.3)</td><td>20 (5.3)</td><td>16 (3.9)</td><td>27 (2.7)</td><td>&lt;0.0001</td></tr><tr><td>CRP, mg/L, median, [IQR]</td><td>3 [2–8]</td><td>6 [3–15]</td><td>4 [2–9]</td><td>3 [1–6]</td><td>3 [1–5]</td><td>&lt;0.0001</td></tr><tr><td>Hb, g/dL, median, [IQR]</td><td>13.1 [12.2–14.0]</td><td>12.8 [11.7–13.8]</td><td>13.0 [12.0–14.1]</td><td>13.2 [12.3–14.0]</td><td>13.2 [12.5–14.0]</td><td>&lt;0.0001</td></tr><tr><td>Albumin, g/L, median, [IQR]</td><td>41 [38–43]</td><td>39 [35–42]</td><td>40 [36–42]</td><td>42 [38–44]</td><td>42 [39–44]</td><td>&lt;0.0001</td></tr><tr><td>Creatinine, µmol/L, median, [IQR]</td><td>70 [60–81]</td><td>70 [58–82]</td><td>71 [59–86]</td><td>70 [61–81]</td><td>70 [60–80]</td><td>0.25</td></tr><tr><td>Anti-topoisomerase I antibodies, n (%)</td><td>693 (29.5)</td><td>274 (48.5)</td><td>134 (35.6)</td><td>103 (25.3)</td><td>182 (18.2)</td><td>&lt;0.0001</td></tr><tr><td>Anti-RNA polymerase III antibodies, n (%)</td><td>88 (3.7)</td><td>18 (3.2)</td><td>15 (4.0)</td><td>15 (3.7)</td><td>40 (4.0)</td><td>0.86</td></tr><tr><td>Anti-centromere antibodies, n (%)</td><td>883 (37.6)</td><td>71 (12.6)</td><td>87 (23.1)</td><td>203 (49.9)</td><td>522 (52.3)</td><td>&lt;0.0001</td></tr></tbody></table>

BMI: body mass index; CK: creatinine kinase; CRP: C-reactive protein; dcSSc: diffuse cutaneous systemic sclerosis; DLCO: diffusing capacity of the lungs for carbon monoxide; FVC: functional vital capacity; Hb: hemoglobin; IQR: interquartile range; IU: international unit; kg: kilogram; mRSS: modified Rodnan skin score; ns: non significant; NYHA: New York heart association; PAH: pulmonary arterial hypertension; TFR: tendon friction rubs; TLC: total lung capacity.

## 2. Patients and methods

### 2.1. Study design

The French SSc national cohort study is a multicentre observational study conducted in 42 French hospital centers [5]. Adult SSc patients have been enrolled since 2010. Data were retrospectively collected before 2010 and then prospectively collected in an online database. For the present study, data were extracted in April 2022. All patients with SSc included before 2022 were eligible and only patients who met the 2013-American College of Rheumatology (ACR)/European Alliance of Associations for Rheumatology (EULAR) SSc classification criteria [6] and had baseline TLC measure available were included in the study.

### 2.2. Data collection

Baseline was defined as the date of inclusion in the database, and follow-up was the time between the inclusion and the last available visit at the time of the extraction. Data on demographics, SSc clinical and biological characteristics, as well as autoantibody status were collected. Recorded parameters included sex, weight, body mass index, age, age at first symptoms, disease duration (defined as the time between the first non-Raynaud's phenomenon symptom by patient report and inclusion

visit), disease subset (limited cutaneous SSc (lcSSc) or dcSSc), sclerodactyly, modified Rodnan skin score (mRSS), mouth opening measured in millimeters, digital ulcers, fingertip pitting scars, telangiectasia, calcinosis, arthralgia, synovitis, tendon friction rubs, ILD with or without lung fibrosis. ILD was defined by the presence of at least one of the following imaging findings: honeycombing, traction bronchiectasis, ground-glass opacity, or reticulations. Evidence of lung fibrosis included the presence of honeycombing or traction bronchiectasis. Other organ involvements were defined as previously reported [7].

### 2.3. PFTs variables and definitions

PFTs parameters recorded were TLC, FVC, and DLCO. For the study, absolute declines in TLC, FVC, and DLCO were measured as percentages of the predicted values.

### 2.4. Study objectives

The main objective of this study was to analyse TLC in SSc. First, we differentiated and described patients included in the study based on baseline TLC measurements. Second, we delineated groups of patients according to TLC trajectories and highlighted group specificities. Thirdly and lastly, we sought a practical cutoff value for TLC decrease.
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Baseline correlations and trajectories of total lung capacity in patients with systemic sclerosis.</figcaption></figure>

Panel 1A. Correlation between baseline total lung capacity (TLC) and forced vital capacity. Panel 1B. Correlation between baseline TLC and diffusing capacity of the lungs for carbon monoxide (DLCO).

Panel 1C. Correlation between baseline TLC and modified Rodnan skin score (mRSS).

Panel 1D. Correlation between baseline TLC and mouth opening (MO).

Panel 1E. Individual trajectories of TLC in 988 SSc patients.

Panel 1F. Clustered trajectories of TLC in SSc patients following latent process mixed modeling.

## 2.5. Ethical approval

The French SSc national cohort study database received ethical approval from CCTIRS (approval no. 13.145; Advisory Committee on Information Processing in Material Research in the Field of Health). Data protection complied with the requirements of the National Information science and Liberties Commission and recorded under no. 914607. All included patients provided informed consent.

## 2.6. Statistical analysis

Continuous variables were compared using the *t*-test or the Kruskal-Wallis test, and categorical variables using Fisher's exact or chi-square tests. To analyse TLC trajectory heterogeneity, we modeled TLC trajectories by linear or quadratic functions of time. We selected patients who had at least two TLC measures available during follow-up and applied a univariate latent process mixed modeling method, which is a continuous extension of a linear mixed process modeling method coupled with a monotonically increasing function [8]. The likelihood of the proposed models was maximized using an extended iterative Marquardt

algorithm. To compare the models and determine the optimal number of trajectories (i.e; clusters), we minimised the Bayesian information criterion. Survival rates (overall survival and organ-involvement-free survival) in all clusters were estimated using the Kaplan-Meier method and compared using Cox regression. Stepwise multiple logistic regression analysis was used to assess independent associations between SSc characteristics and TLC decrease based on univariate analyses (p < 0.1). All statistical analyses were performed using STATA software version stata/MP13.0 StataCorp® and the R software (Package LCMM).

# 3. Results

## 3.1. Patients' characteristics

Of the 2353 patients included in the SSc French national database, 2347 had at least one TLC measure and were included in the study (Supplemental Fig. 1). Their baseline characteristics are detailed in Table 1. Median [interquartile] (IQR) age at SSc diagnosis was 52 [41–63] years. The proportion of females was 81 %, and the proportion of dcSSc patients was 30 %. Thirty percent, 38 %, and 4 % of patients
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 2.** Overall probability of survival according to total lung capacity in patients with systemic sclerosis. Panel 2A, 2B, 2C, and 2D, depict the Kaplan-Meier curves showing respectively the overall 20-year probabilities of survival without interstitial lung disease, lung fibrosis, pulmonary arterial hypertension (PAH) and overall survival in 1168 patients with systemic sclerosis according to baseline total lung capacity (TLC).</figcaption></figure>

were positive for ATA, anti-centromere (ACA), and anti-RNA polymerase III antibody (ARA), respectively. Thirty-nine percent and 28%, had ILD and LF, respectively.

## 3.2. Baseline TLC

Forty-three percent had a TLC above or equal to 100% and 24% had a TLC below 80%. TLC correlated well with FVC (r = 0.59, p < 0.0001) but poorly with mRSS (r = 0.08, p < 0.0001), mouth opening (r = 0.07, p < 0.0001), and DLCO (r = 0.01, p < 0.0001), (Fig. 1 - Panel A–D). Patients with lower TLC had more severe disease, as shown in Table 1. Total lung capacity was significantly lower in patients with dcSSc than in patients with lcSSc (86 [73–101] versus (vs) 99 [85–110]; p < 0.0001), lower in patients with SSc-ILD than in patients without SSc-ILD (82 [70–98] vs 101 [91–112]; p < 0.0001), and differed significantly in patients with ATA, ARA, or ACA (85 [70–100]; 98 [83–106]; and 103 [93–113]; p < 0.0001). In the 1034 (43.9%) patients with ILD or LF, a lower TLC was more prevalent in males, diffuse SSc, or positive ATA antibody SSc ((p < 0.0001) with more severe disease characterized by a higher mRSS (p < 0.0001), lower mouth opening (p < 0.05), more muscle symptoms (p < 0.01), worse FVC or DLCO (p < 0.0001), and more frequent LF (p < 0.0001) (Supplemental Table 1).

## 3.3. Patients' follow-up

Among the 2347 patients included, 1168 (50%) had available follow-up. During a median [IQR] follow-up of 4.6 [2.5–7.9] years, 190 (16%) patients died, 617 (53%) developed de novo interstitial lung disease (ILD), 499 (43%) developed de novo LF, 175 (15%) were diagnosed with PAH following right heart catheterization (115 of them had concomitant ILD), and 69 (6%) developed scleroderma renal crisis (SRC). Kaplan-Meier curves showing the overall 20-year probabilities of

survival and survival without ILD, LF, and PAH after SSc diagnosis according to baseline TLC showed that a lower TLC was associated with worse survival and a higher risk of ILD, LF, or PAH occurrences (p < 0.001) (Fig. 2).

## 3.4. TLC trajectories and model evaluation

Among 2347 patients with at least one TLC measure, 988 (42%) patients had at least 2 TLC measures. Individual trajectories of TLC in these patients are depicted in Fig. 1 - Panel E, confirming heterogeneity among patient TLC trajectories. Models using the univariate latent process mixed modeling method are shown in Supplemental Fig. 2. The best model, which included a linear time function and a linear link function, highlighted three clusters of TLC trajectories (Fig. 1F).

## 3.5. Characteristics of patients based on total lung capacity trajectory clusters

Three trajectories of TLC were identified, revealing 3 clusters of patients (Fig. 1F–Table 2). Cluster 1 comprised 1.5% of patients characterized by a high baseline TLC that rapidly decreased over time. Cluster 2 comprised 74.1% of patients characterized by a baseline TLC above 100% that remained stable over time. Cluster 3 comprised 24.4% of patients characterized by a baseline TLC below 100% that decreased over time. Patients in Cluster 2 were more frequently lcSSc patients and less frequently ATA positive compared to patients in Cluster 1 and 3.

Every patient analyzed to perform TLC trajectories models had available follow-up. During a median [IQR] follow-up of 5.1 [3.0–8.4] years, 145 (15%) patients died, 143 (15%) developed PAH, 540 (55%) ILD, 439 (44%) LF, and 48 (5%) SRC. Kaplan-Meier curves showing the 20-year probabilities of survival and survival without ILD, LF, and PAH after SSc diagnosis according to TLC trajectories showed that TLC
<caption>**Table 2**</caption>

Baseline characteristics of systemic sclerosis patients according to total lung capacity study trajectories.

<table><thead><tr><th></th><th>Cluster 1 (n = 15)</th><th>Cluster 2 (n = 732)</th><th>Cluster 3 (n = 241)</th><th>p</th></tr></thead><tbody><tr><td>Male, n (%)</td><td>1 (6.7)</td><td>111 (15.2)</td><td>64 (26.6)</td><td>&lt;0.001</td></tr><tr><td>Age at diagnostic, years, median [IQR]</td><td>55 [47–65]</td><td>49 [39–58]</td><td>45 [35–57]</td><td>0.02</td></tr><tr><td>Time from first non-Raynaud's symptom, years, median [IQR]</td><td>1 [0–4]</td><td>1 [0–2]</td><td>1 [0–2]</td><td>&gt;0.99</td></tr><tr><td>dcSSc, n (%)</td><td>5 (33.3)</td><td>212 (29.0)</td><td>136 (56.4)</td><td>&lt;0.0001</td></tr><tr><td>Asthenia, n (%)</td><td>1 (6.7)</td><td>160 (21.9)</td><td>58 (24.1)</td><td>0.29</td></tr><tr><td>Weight loss, n (%)</td><td>1 (6.7)</td><td>83 (11.3)</td><td>46 (19.1)</td><td>&lt;0.01</td></tr><tr><td>Weight, kg, median [IQR]</td><td>62 [58–70]</td><td>62 [54–70]</td><td>67 [58–76]</td><td>&lt;0.001</td></tr><tr><td>BMI, kg/m², median [IQR]</td><td>23.8 [23.3–25.5]</td><td>23.0 [20.5–26.2]</td><td>24.5 [21.5–28.0]</td><td>&lt;0.001</td></tr><tr><td>Mouth opening, mm, median [IQR]</td><td>36 [21–40]</td><td>40 [34–45]</td><td>34 [26–40]</td><td>&lt;0.0001</td></tr><tr><td>mRSS, IU, median [IQR]</td><td>7 [2–22]</td><td>4 [2–12]</td><td>11 [4–20]</td><td>&lt;0.0001</td></tr><tr><td>Puffy fingers, n (%)</td><td>10 (66.7)</td><td>327 (44.7)</td><td>96 (39.8)</td><td>0.09</td></tr><tr><td>Sclerodactyly, n (%)</td><td>6 (40)</td><td>291 (39.8)</td><td>109 (45.2)</td><td>0.33</td></tr><tr><td>Fingertip pitting scars, n (%)</td><td>2 (13.3)</td><td>194 (26.5)</td><td>93 (38.6)</td><td>&lt;0.001</td></tr><tr><td>Digital ulcers, n (%)</td><td>1 (6.7)</td><td>104 (14.2)</td><td>73 (30.2)</td><td>&lt;0.0001</td></tr><tr><td>Telangiectasia, n (%)</td><td>3 (20)</td><td>385 (52.6)</td><td>104 (43.2)</td><td>&lt;0.01</td></tr><tr><td>Abnormal naifold capillaries, n (%)</td><td>8 (53.3)</td><td>349 (47.7)</td><td>115 (47.7)</td><td>0.93</td></tr><tr><td>Calcinosis, n (%)</td><td>0 (0)</td><td>115 (15.7)</td><td>32 (13.3)</td><td>0.19</td></tr><tr><td>Muscle symptoms, n (%)</td><td>2 (13.3)</td><td>138 (18.9)</td><td>73 (30.3)</td><td>&lt;0.001</td></tr><tr><td>Increased CK, n (%)</td><td>0 (0)</td><td>37 (5.1)</td><td>31 (12.9)</td><td>&lt;0.001</td></tr><tr><td>Arthralgia, n (%)</td><td>4 (26.7)</td><td>343 (46.9)</td><td>137 (56.8)</td><td>&lt;0.01</td></tr><tr><td>Synovitis, n (%)</td><td>0 (0)</td><td>74 (10.1)</td><td>16 (6.6)</td><td>0.14</td></tr><tr><td>TFR, n (%)</td><td>0 (0)</td><td>16 (2.2)</td><td>6 (2.5)</td><td>0.86</td></tr><tr><td>Shortness of breath, n (%)</td><td>9 (60)</td><td>340 (46.4)</td><td>189 (78.4)</td><td>&lt;0.0001</td></tr><tr><td>NYHA classification, IU, median [IQR]</td><td>2 [1–2]</td><td>2 [1–2]</td><td>2 [2–3]</td><td>&lt;0.0001</td></tr><tr><td>Interstitial lung syndrome, n (%)</td><td>8 (53.3)</td><td>202 (27.6)</td><td>173 (71.8)</td><td>&lt;0.0001</td></tr><tr><td>Lung fibrosis, n (%)</td><td>2 (13.3)</td><td>122 (16.7)</td><td>158 (65.6)</td><td>&lt;0.0001</td></tr><tr><td>FVC, median [IQR]</td><td>108 [78–118]</td><td>103 [92–116]</td><td>71 [60–84.8]</td><td>&lt;0.0001</td></tr><tr><td>TLC, median [IQR]</td><td>127 [107–138]</td><td>102 [93–113]</td><td>74 [63.5–82]</td><td>&lt;0.0001</td></tr><tr><td>DLCO, median [IQR]</td><td>78 [53.5–95.5]</td><td>71.8 [60–81]</td><td>47.2 [37–61]</td><td>&lt;0.0001</td></tr><tr><td>PAH, n (%)</td><td>0 (0)</td><td>33 (4.5)</td><td>37 (15.3)</td><td>&lt;0.0001</td></tr><tr><td>Scleroderma renal crisis, n (%)</td><td>0 (0)</td><td>25 (3.4)</td><td>11 (4.6)</td><td>0.68</td></tr><tr><td>CRP, mg/L, median, [IQR]</td><td>3 [1–6]</td><td>3 [1–5]</td><td>4 [3–10.8]</td><td>&lt;0.0001</td></tr><tr><td>Hb, g/dL, median, [IQR]</td><td>12.5 [12.4–13.4]</td><td>13.1 [12.4–14.0]</td><td>13.0 [11.9–13.8]</td><td>0.06</td></tr><tr><td>Albumin, g/L, median, [IQR]</td><td>41 [38.4–42]</td><td>41 [38.3–43.6]</td><td>39.5 [36–42]</td><td>&lt;0.0001</td></tr><tr><td>Creatinine, µmol/L, median, [IQR]</td><td>75 [57–84.5]</td><td>67 [58–79]</td><td>70.4 [58–79.3]</td><td>0.16</td></tr><tr><td>Anti-topoisomerase I antibodies, n (%)</td><td>8 (53.3)</td><td>156 (21.3)</td><td>126 (52.3)</td><td>&lt;0.0001</td></tr><tr><td>Anti-RNA polymerase III antibodies, n (%)</td><td>2 (13.3)</td><td>29 (4.0)</td><td>5 (2.1)</td><td>0.05</td></tr><tr><td>Anti-centromere antibodies, n (%)</td><td>5 (33.3)</td><td>317 (43.3)</td><td>21 (8.7)</td><td>&lt;0.0001</td></tr></tbody></table>

BMI: body mass index; CK: creatinine kinase; CRP: C-reactive protein; dcSSc: diffuse cutaneous systemic sclerosis; DLCO: diffusing capacity of the lungs for carbon monoxide; FVC: functional vital capacity; Hb: hemoglobin; IQR: interquartile range; IU: international unit; kg: kilogram; mRSS: modified Rodnan skin score; ns: non significant; NYHA: New York heart association; PAH: pulmonary arterial hypertension; TFR: tendon friction rubs; TLC: total lung capacity.

trajectories were associated with survival and occurrences of ILD, LF, or PAH (p < 0.0001) (Fig. 3). Patients in cluster 2 (i.e., patients with high and stable TLC) had better survival and lower risk of developing ILD, LF, and PAH than patients in clusters 1 and 3.

### 3.6. TLC decrease cutoff value assessment with regard to FVC and DLCO

As TLC trajectories were associated with survival and lung involvement in SSc, we further sought a practical cutoff value for TLC decrease and consecutively chose a 10% decrease in TLC as of interest for clinical use (Supplementary Fig. 3). This decrease was predictive of FVC and DLCO decline in SSc. Kaplan-Meier curves showing the 20-year probabilities of survival without 5% FVC decrease or 10% DLCO decrease according to TLC decreases showed that a 10% TLC decrease was associated with a 5% FVC (p < 0.0001) or a 10% DLCO (p < 0.001) decrease (Fig. 4). Kaplan-Meier curves showing the 20-year probabilities of survival and survival without ILD or LF after SSc diagnosis according to a 10% TLC decrease or a 5% FVC decrease showed that TLC trajectories were associated with the development of ILD and LF (p < 0.0001), whereas a 5% FVC decrease was not (Fig. 5). For instance, after 3 years of follow-up, among patients who developed ILD, 60 (68.2%) had lost 10% TLC whereas 41 (48.2%) had lost 5% FVC (p < 0.01). After 5 years of follow-up, among patients who developed ILD, 87 (65.4%) had lost 10% TLC whereas 57 (45.2%) had lost 5% FVC (p < 0.01). In patients with SSc-ILD, a 10% TLC decrease was also associated with a 5% FVC decrease (Supplementary Fig. 4).

Multivariate analysis revealed that baseline TLC (p < 0.0001) and the presence of muscle symptoms (p < 0.01) were independent factors positively associated with a 10% TLC decrease, whereas baseline FVC (p < 0.01) and anti-centromere antibodies (p < 0.01) were independent factors negatively associated with a 10% TLC decrease in SSc (Supplementary Table 2). Along the same line, FVC decrease was associated with dcSSc and baseline FCV (Supplementary Table 3).

## 4. Discussion

In the present study, we provide an extensive cross-sectional and longitudinal analysis of TLC in a large cohort of SSc patients. We first demonstrated that TLC is transversally associated with disease severity, survival, and lung involvement occurrence. Additionally, we identified three distinct trajectories of TLC, including a stable trajectory comprising most SSc patients, and showed that a decrease in TLC was predictive of survival and lung involvement. Lastly, we determined that a 10% decrease in TLC was a practical and early cutoff value, predictive of ILD and LF occurrence in SSc.

SSc-ILD is the leading cause of death in SSc, especially in cases of progressive SSc-ILD. Despite 27% of patients with SSc-ILD experiencing disease progression and 67% of those with progressive SSc-ILD experiencing FVC decline over a 5-year follow-up [9], the course of SSc-ILD remains heterogeneous and unpredictable. Current recommendations emphasize the need for screening SSc patients for SSc-ILD using HRCT and monitoring disease progression using HRCT and PFTs [10]. However, there is no consensus on disease severity, progression, and outcome definitions for SSc-ILD [11]. Recent studies have used the INBUILD trial criteria for progressing SSc-ILD, which include a relative FVC decline ≥10%, or any two of the following: FVC decline ≥5% and <10%, worsening respiratory symptoms, or worsening fibrosis on HRCT [12]. FVC is commonly used as a primary FDA-acceptable endpoint in therapeutic trials for SSc and other fibrotic ILD including IPF and is being incorporated into the revised composite response index in SSc, which also includes mRSS and disability assessment [13]. In the absence of fully accepted consensual disease predictors, other biomarkers and clinical markers are under consideration, such as FVC or DLCO decline [14], mRSS [15], and the SPAR model (including SpO₂ after a 6-min walk test and arthritis) [16]. To the best of our knowledge and despite its recognised performance in SSc-ILD [17], TLC has not been previously
<figure><img src="image_8.png" /><figcaption>**Fig. 3.** Overall probability of survival according to total lung capacity trajectories in patients with systemic sclerosis. Panel 3A, 3B, 3C, and 3D, depict the Kaplan-Meier curves showing respectively the overall 20-year probabilities of survival without interstitial lung disease, lung fibrosis, pulmonary arterial hypertension (PAH), and overall survival in 988 patients with systemic sclerosis according to baseline total lung capacity trajectories.</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>**Fig. 4.** Probability of survival without FVC or DLCO decline according to total lung capacity 10 % decrease in patients with systemic sclerosis. Panel 4A, and 4B, 3C, and 3D, depict the Kaplan-Meier curves showing respectively the overall 20-year probabilities of survival without have 5 % forced vital capacity decrease or 10 % diffusing capacity of the lungs for carbon monoxide decrease in 988 patients with systemic sclerosis according to 10 % total lung capacity decrease.</figcaption></figure>

reported as an outcome measure or biomarker for SSc and SSc-ILD due to higher measurement variability and limited availability outside of large/academic hospital clinics. Our findings suggest that TLC may be a predictor of patient outcomes, including survival, and should be further evaluated as part of SSc-ILD progression and SSc outcome definitions, especially since TLC decline precedes FVC deterioration in SSc-ILD.

To the best of our knowledge, this is the first large study to report TLC trajectories in SSc. Our group previously reported analyses of skin sclerosis trajectories based on mRSS trajectories and mouth opening trajectories in SSc patients [5,18]. These previous studies identified five mRSS and three mouth opening trajectories, confirmed that skin sclerosis trajectories predict morbidity and mortality, and demonstrated the utility of these trajectories in daily practice and trial designs for SSc. The present work underscores the importance of PFT trajectories as predictors of morbidity and mortality in SSc. Patients with decreasing TLC over one year were at higher risk of death, new onset of ILD, LF, and PAH. Man et al. identified 7 FVC trajectories, with four trajectories,

including the majority (65.3 %) of 254 patients, being stable or improved over time [19] while Ramahi et al. showed that a longitudinal percent-predicted FVC decline in 184 SSc patients was a marker of survival [20]. Conversely, Guler et al. showed that recent changes in FVC cannot be used to predict future changes of FVC within short follow-up intervals and questioned FVC as a reliable outcome measure in SSc-ILD [21]. These findings, combined with ours, reaffirm the value of PFTs over time and highlight that TLC measurements should be performed longitudinally and monitored closely, as they might influence clinical management of SSc patients.

As previously mentioned, the physiological impairment associated with ILD and LF in SSc is assessed using PFTs, including spirometry, and plethysmography which measures TLC. Although spirometry is more readily available than plethysmography, both techniques are routinely used for SSc patients and have been extensively described in the literature to ensure accurate measurement, standardized technical quality, and reproducibility [22–25]. Although FVC decline has an important
<figure><img src="image_10.png" /><figcaption>**Fig. 5.** Overall probability of time to interstitial lung disease and lung fibrosis onset according to total lung capacity and forced vital capacity decrease in patients with systemic sclerosis.</figcaption></figure>

Panel 5A and 5B depict the Kaplan-Meier curves showing respectively the overall 20-year probabilities of survival without interstitial lung disease and lung fibrosis in 988 patients with systemic sclerosis according to total lung capacity trajectories 10 % decrease.

Panel 5C and 5D depict the Kaplan-Meier curves showing respectively the overall 20-year probabilities of survival without interstitial lung disease and lung fibrosis in 988 patients with systemic sclerosis according to forced vital capacity 5 % decrease.

role in monitoring ILD and LF, additional measures of disease progression are needed [26]. FVC measurement may be affected by lung elasticity, thoracic cage anatomy, and respiratory muscle function, technique and patient effort [27]. This is particularly true in SSc, where patients may develop systemic sclerosis-associated myopathy, malnutrition, or thoracic skin fibrosis, impacting spirometry results. This may also explain why we found that TLC is not only a marker of ILD occurrence but also a marker of survival and disease severity. TLC measurement is less subject to measurement errors, potentially due to being less affected by technique and patient effort [27]. Our work also suggests that TLC may be an earlier marker of lung involvement than FVC, which can stay spuriously within normal limits of predicted value in early SSc-ILD [4]. This could hypothetically be explained by the fact that RV is likely affected earlier than FVC in SSc-ILD. Taken together, these findings support further study about the use of TLC versus FVC in evaluating and monitoring SSc-ILD, and to evaluate TLC sensitivity to changes in SSc-ILD and explore its potential use as an outcome measure in clinical trials.

Our study has some limitations. First, although we used prospective data from a French multicentre cohort of SSc patients, it is a retrospective analysis with inherent biases, including inconsistencies in data collection across centers and variability in patients visits. Second, RV measurements were not available for this study, which would have been valuable. Third, we were unable to evaluate the relationship between HRCT extent or structural changes and TLC impairment. Fourth, the reproducibility of TLC measurements, both within and between individuals or across centers, was not assessed. External validation is therefore needed to confirm a 10 % decrease in TLC as a critical threshold in SSc. Fifth, our work lacks correlations between TLC and patients' disability index of health assessment questionnaire (HAQ-DI) or patient/physician global assessment PGA or others patient-reported outcomes in SSc and SSc-ILD, which would have further

contextualized the clinical significance of TLC decrease. Lastly, the influence of immunosuppressant or antifibrotic treatments on TLC trajectories could not be assessed.

In conclusion, the present study shows that TLC measurement is associated with SSc severity and prognosis. It suggests that TLC may be an early marker of ILD and PF development, and that a 10 % TLC decrease is a useful and early marker of FVC or DLCO decreases, as well as ILD or LF occurrence. Overall, our findings support the use of TLC along with FVC in monitoring and assessing ILD and LF in both clinical practice and clinical trials.

### CRediT authorship contribution statement

**Benjamin Chaigne:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. **Alexandre Bense:** Writing – review & editing, Writing – original draft, Methodology, Formal analysis. **Frédérique Aubourg:** Writing – review & editing, Writing – original draft, Investigation. **Christian Agard:** Writing – review & editing, Writing – original draft, Investigation, Data curation. **Yannick Allanore:** Writing – review & editing, Data curation. **Alice Berezne:** Writing – review & editing, Data curation. **Grégory Pugnet:** Writing – original draft, Data curation. **Eric Hachulla:** Writing – review & editing, Data curation. **Vincent Cottin:** Writing – original draft, Data curation. **Arnaud Hot:** Writing – original draft, Data curation. **Bertrand Dunogue:** Writing – original draft, Data curation. **Anuxcy Kanagaratnam:** Writing – original draft, Supervision, Data curation. **Sylvain Palat:** Writing – original draft, Data curation. **Alain Lescoat:** Writing – original draft, Data curation. **Sabine Berthier:** Writing – original draft, Data curation. **Emmanuel Chatelus:** Writing – original draft, Data curation. **Sébastien Rivière:** Writing – original draft, Data curation.
**David Launay:** Writing – original draft, Data curation. **Marie-Elise Truchetet:** Writing – original draft, Data curation. **Anh Tuan Dinh-Xuan:** Writing – original draft, Validation, Data curation. **Luc Mouthon:** Writing – original draft, Visualization, Validation, Supervision, Resources, Investigation, Data curation.

## Funding sources

None.

## Declaration of competing interest

None.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jaut.2025.103391.

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