ABSTRACT
Aim
This study aimed to determine whether exercise tolerance assessed by 6‐min walk distance (6MWD) predicts clinical outcomes in patients with connective tissue disease‐associated interstitial lung disease (CTD‐ILD).
Methods
This was an ambispective cohort study. We included patients in a stable condition with CTD‐ILD. The 6MWD during hospitalization was used to determine the exercise tolerance. The primary endpoint was all‐cause mortality, and the secondary endpoint was hospitalization for pulmonary disease. We examined the association between the 6MWD and each endpoint.
Results
Among the 224 patients evaluated {median age 66.5 [interquartile range (IQR) 55.0–74.0] years; 146 females}, there were 23 deaths and 56 hospitalizations for pulmonary disease during the median follow‐up period of 1.2 (IQR 0.6–2.3) years. The 6MWD of 310 m and 260 m were identified as optimal cut‐off points for the prediction of all‐cause mortality and hospitalization for pulmonary disease, respectively. The Kaplan–Meier survival curve showed that a higher 6MWD was associated with a lower rate of all‐cause mortality and hospitalization for pulmonary disease (log‐rank = 16.146, p < 0.001 and log‐rank = 9.065, p = 0.003, respectively). After adjusting for clinical confounding factors, the hazard ratios for all‐cause mortality and hospitalization for pulmonary disease per 10‐m increase in 6MWD were 0.962 [95% confidence interval (CI): 0.927–0.998] and 0.968 (95% CI 0.946–0.991), respectively.
Conclusion
Higher exercise tolerance, as assessed by 6MWD, was independently associated with a better prognosis in stable patients with CTD‐ILD.
Keywords: connective tissue disease, exercise tolerance, interstitial lung disease, prognosis
Practitioner Points
Higher 6MWD independently predicts better prognosis in patients with CTD‐ILD.
6MWD serves as a risk stratification tool and physical performance assessment for patients with CTD‐ILD.
Maintaining exercise tolerance is crucial for rehabilitation in patients with CTD‐ILD.
1. Introduction
Interstitial lung disease (ILD) is characterized by inflammation and fibrosis of the lung interstitium. The mechanisms of ILD development involve various factors, including idiopathic, occupational, iatrogenic, and autoimmune aetiologies [1, 2, 3]. Although ILD is classified as a rare disease, its prevalence has increased in recent years [4, 5, 6, 7]. Additionally, the onset and progression of ILD have been recognized as poor prognostic factors, with higher mortality rates reported than those of other diseases [8, 9, 10]. Consequently, numerous studies have been conducted to explore the treatments and factors that may improve prognosis.
Connective tissue diseases (CTDs) encompass a diverse range of disorders that affect connective tissues. These disorders often affect the joints, muscles, and skin but can also involve other organs and systems, such as the eyes, heart, lungs, kidneys, gastrointestinal tract, and blood vessels. With over 200 identified diseases affecting connective tissue, their causes and specific symptoms vary by type [11, 12]. Among them, connective tissue diseases are associated with a wide range of pulmonary complications, among which ILD is notably frequent [13]. While the prevalence of ILD varies depending on the type of CTD, it is observed in up to 60% of patients when subclinical cases are included, representing a significant unmet need due to its substantial impact on both survival and functional outcomes [14, 15, 16]. The pathogenesis of CTD‐ILD is fundamentally driven by autoimmune‐mediated tissue inflammation localized to the lungs, which triggers the autonomous activation of fibroblasts and progressive fibrosis [17]. Consequently, management strategies involve controlling primary disease activity while incorporating antifibrotic therapies, particularly for cases with progressive fibrosis.
Similar to other forms of ILD, CTD‐ILD is an inherently chronic and progressive condition, often leading to chronic pulmonary failure over time. Moreover, the prognosis of CTD‐ILD is highly heterogeneous and is influenced by pathological findings and the underlying CTD. Disease progression rates also vary significantly among patients. Regular monitoring through detailed clinical examinations, blood tests, high‐resolution computed tomography (HRCT), and pulmonary function tests is essential for estimating patient prognosis and optimizing treatment timing and intensity [1]. However, pathological examination is invasive and impractical for repeated assessment. Thus, noninvasive and systematic evaluations are critical for disease monitoring.
Among these indicators, the 6‐min walk test (6MWT) has emerged as a valuable tool for objectively assessing exercise tolerance and predicting prognosis in chronic pulmonary diseases, including ILD, particularly idiopathic pulmonary fibrosis (IPF). Reduced 6‐min walk distance (6MWD) or desaturation during the test is associated with future initiation of home oxygen therapy and increased mortality risk [18, 19]. In idiopathic pulmonary fibrosis (IPF, previously classified under idiopathic interstitial pneumonias), a 6MWD of less than 200–300 m has been repeatedly shown to correlate directly with a higher mortality risk [20, 21, 22]. Similar to other pulmonary and internal medicine diseases, exercise tolerance assessed by 6MWD is also considered to be associated with prognosis in patients with CTD‐ILD. However, in patients with CTD‐ILD, data on the 6MWD remain limited and are primarily derived from small cohort studies [23].
Thus, we aimed to clarify whether exercise tolerance assessed by 6MWD predicts all‐cause mortality and the risk of rehospitalization in stable patients with CTD‐ILD.
2. Methods
2.1. Study Population
This was an ambispective (retrospective and prospective) cohort study. This study enrolled patients with CTD‐ILD from the Department of Rehabilitation, Rheumatology, and Infectious Diseases at our hospital database. We included patients who were admitted to the Department of Rheumatology for close examination and treatment of interstitial lung disease and connective tissue diseases. We measured 6MDT to evaluate the disease state, respiratory condition, and exercise tolerance during routine assessments between January 2018 and October 2024. We conducted the 6‐min walk distance test (6MDT) when the patients' underlying conditions were stable and there were no signs of acute exacerbation of ILD, such as infection or acute worsening of the disease. The exclusion criteria were as follows: patients who were unable to walk even with the use of a walking assistance aid or assisted walking, those who refused to perform the 6MWT, and those who did not consent to participate in the study. This study was conducted in accordance with the ethical principles of the Declaration of Helsinki and was approved by the Ethics Committee of our hospital (Approval Number. B23‐068).
2.2. Patient Characteristics
Information regarding age, sex, body mass index (BMI), type of connective tissue disease (rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjogren's syndrome (SS), polymyositis/dermatomyositis (PM/DM), systemic sclerosis (SSc), anti‐neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV), microscopic polyangiitis (MPA), granulomatosis with polyangiitis (GPA), and eosinophilic granulomatosis with polyangiitis (EGPA), and others), cardiac ultrasonography findings [left ventricular ejection fraction (LVEF) and tricuspid regurgitation peak gradient (TRPG)], smoking habit (current smoker or not), comorbidities (pulmonary hypertension, old myocardial infarction, congestive heart failure, peripheral arterial disease, cerebrovascular disease, chronic obstructive pulmonary disease, diabetes mellitus, chronic kidney disease, cancer, gastrointestinal ulcer, liver disease, leukemia, lymphoma, and acquired immune deficiency syndrome), medication use (steroids, methotrexate, janus kinase inhibitor, biological medical product, and other immunosuppressants), spirometry finding [percentage of forced vital capacity (%FVC), forced expiratory volume percentage in 1‐s (%FEV1.0), and percent predicted diffusing capacity of lung for carbon monoxide (DLCO)], exacerbation of interstitial lung disease on admission, and blood examination data [hemoglobin, albumin, creatinine, estimated glomerular filtration rate (eGFR), C‐reactive protein (CRP), Krebs von den Lungen (KL‐6), pulmonary surfactant protein D (SP‐D), and N‐terminal prohormone of brain natriuretic peptide levels (NT‐pro BNP)] were collected from electronic medical record. Furthermore, we calculated the Charlson Comorbidity Index (CCI) as a severity score for comorbidities [24, 25].
2.3. Assessment of Exercise Tolerance
To assess exercise capacity, the 6MWD was measured during hospitalization according to the guidelines established by the American Thoracic Society [26]. A 20‐m walkway was used, with chairs placed at both ends. Patients were instructed to walk at their own pace and cover as much distance as possible within 6 min. They were allowed to stop and rest or slow their pace if they experienced shortness of breath or fatigue but were asked to resume walking as soon as possible. The elapsed time was announced every minute. Coaching and enthusiastic encouragement were not allowed. The test was discontinued if the patients experienced chest pain, severe dyspnea, leg cramps, swelling, cyanosis, or facial pallor. After 6 min, the patients were instructed to stop, and the total walking distance was recorded. SpO2 was measured before, during, and after the 6‐min walk test; we recorded pre‐6MWT SpO2, the nadir SpO2, and ΔSpO2, calculated as pre‐6MWT SpO2 minus the nadir SpO2.
2.4. Clinical Outcomes
The primary endpoint was all‐cause mortality, and the secondary endpoint was hospitalization for pulmonary disease. The time of endpoints was calculated as the number of days from the date of discharge after scrutiny and treatment to the date of events.
2.5. Statistical Analysis
Continuous variables are expressed as median [interquartile range (IQR)] and categorical variables as numbers and percentages, respectively. We constructed receiver operating characteristic (ROC) curves of the 6MWD for clinical outcomes (all‐cause mortality and hospitalization for pulmonary disease) for all individuals in this study, and the area under the curve (AUC) was calculated. Based on the AUCs, we calculated the Youden index to determine the cut‐off points of the 6MWD for clinical outcomes. The patients were divided into low 6MWD group and high 6MWD groups according to the cut‐off points.
The baseline characteristics were compared between the groups using the Mann–Whitney U test for continuous variables and the chi‐square test for categorical variables for each group. We compared the differences in the cumulative incidence of clinical outcomes during the follow‐up period for each group using Kaplan–Meier survival curves and the log‐rank test. The independent prognostic effects of 6MWD on clinical outcomes in all patients were estimated using univariate and multivariate Cox proportional hazards regression analyses. The Cox proportional hazards model was adjusted for age, sex, BMI < 18.5 kg/m2, KL‐6 at admission, and CCI score (Model 1). As sensitivity analyses, in addition to the primary model described above, we fitted Cox proportional hazards regression models with the following covariate sets: Model 2 adjusted for age, sex, BMI < 18.5 kg/m2, and %FVC; Model 3 adjusted for age, sex, BMI < 18.5 kg/m2, and DLCO. Furthermore, to assess any potential effect modification of the association between exercise tolerance and the incidence of clinical outcomes, we performed subgroup analyses of 6MWD in various subgroups relevant to the prognosis in patients with interstitial lung disease, including age (stratified at 65 years old), sex, saturation of percutaneous oxygen decreasing during the 6‐min walking test (stratified at 90%), presence of RA, presence of PM/DM, presence of SSc, and presence of AAV, with adjustment for the same confounding factors as above. Multiple imputations were performed to handle missing covariate data before constructing the multivariate Cox regression models. Fifteen datasets were generated using a chained‐equation procedure. Parameter estimates were obtained for each dataset and then combined to produce an integrated result using the method described based on a previous study [27]. Analyses were performed using SPSS version 29.0 (IBM Corp., Armonk, NY, USA). In all analyses, a two‐tailed p < 0.05 was considered statistically significant.
3. Results
3.1. Study Population
The study population consisted of 224 patients, and their overall characteristics were shown in Table 1. The participants had a median age of 66.5 years (IQR 55.0–74.0), and 65.2% were women. The median BMI of the participants was 21.9 kg/m2 (IQR 19.2–25.0). The types of connective tissue disease included 40 patients with RA (17.9%), 5 with SLE (2.2%), 10 with SS (4.5%), 70 with PM/DM (31.3%), 43 with SSc (20.5%), 32 with AAV (14.3%), and 24 with other CTD (10.6%). The median values of LVEF, TRPG, CCI score, %FVC, %FEV1.0, KL‐6, SP‐D, and DLCO, pre‐6MDT SpO2, nadir SpO2, ΔSpO2 were 66.4%, 25.7 mmHg, 4.0 points, 80.3%, 79.2%, 728.0 U/mL, 163.0 ng/mL, and 11.1 mL/min/Torr, 97.0%, 91.0%, 6.0%, respectively. Additionally, the median 6MWD was 348.5 m (IQR 244.5–431.0).
TABLE 1.
Patient characteristics stratified by 6‐min walking distance cut‐off based on receiver operating characteristic curve.
| Missing data | Overall (n = 224) | Cut‐off value of 6MWD for all‐cause mortality | Cut‐off value of 6MWD for hospitalization for pulmonary disease | |||
|---|---|---|---|---|---|---|
| 6MWD < 310 m (n = 92) | 6MWD ≧ 310 m (n = 132) | 6MWD < 260 m (n = 60) | 6MWD ≧ 260 m (n = 164) | |||
| Age, years | 0 | 66.5 (55.0–74.0) | 73.0 (64.0–77.0) | 61.5 (53.0–72.0) b | 73.0 (64.0–77.0) | 63.5 (54.0–73.0) d |
| Females, n (%) | 0 | 146 (65.2) | 63 (68.5) | 83 (62.9) | 42 (70.0) | 104 (63.4) |
| Body mass index, kg/m2 | 2 | 21.9 (19.2–25.0) | 21.3 (18.3–24.3) | 22.2 (19.6–25.6) | 21.1 (18.2–24.2) | 22.2 (19.5–25.3) |
| Current smoker, n (%) | 0 | 12 (5.4) | 2 (2.1) | 10 (7.6) | 1 (1.7) | 11 (6.7) |
| Type of connective tissue disease, n (%) | ||||||
| Rheumatoid arthritis | 0 | 40 (17.9) | 21 (22.8) | 19 (14.4) | 17 (28.3) | 23 (14.0) |
| Systemic lupus erythematosus | 0 | 5 (2.2) | 0 (0.0) | 5 (3.8) | 0 (0.0) | 5 (3.0) |
| Sjogren's syndrome | 0 | 10 (4.5) | 3 (3.3) | 7 (5.3) | 0 (0.0) | 10 (6.1) |
| Polymyositis/dermatomyositis | 0 | 70 (31.2) | 28 (30.4) | 42 (31.8) | 15 (25.0) | 55 (33.5) |
| Systemic sclerosis | 0 | 43 (20.5) | 18 (19.6) | 25 (18.9) | 10 (16.7) | 33 (20.1) |
| ANCA associated vasculitis | 0 | 32 (14.2) | 12 (13.0) | 20 (15.2) | 11 (18.3) | 21 (12.8) |
| Others | 0 | 24 (10.6) | 10 (10.9) | 14 (10.6) | 7 (11.7) | 17 (10.4) |
| Cardiac ultrasonography findings | ||||||
| LVEF, % | 42 | 66.4 (63.2–69.4) | 67.1 (63.1–69.2) | 66.3 (63.2–69.5) | 65.7 (62.2–68.6) | 66.5 (63.5–69.6) |
| TRPG, mmHg | 51 | 25.7 (21.6–33.7) | 28.5 (23.4–37.1) | 24.2 (20.7–28.7) b | 30.5 (23.9–39.8) | 24.6 (21.1–30.9) d |
| Comorbidities, n (%) | ||||||
| Pulmonary hypertension | 0 | 14 (6.3) | 7 (7.6) | 7 (5.3) | 6 (10.0) | 8 (4.9) |
| History of myocardial infarction | 0 | 8 (3.6) | 4 (4.3) | 4 (3.0) | 3 (5.0) | 5 (3.0) |
| Congestive heart failure | 0 | 16 (7.1) | 9 (9.8) | 7 (5.3) | 8 (13.3) | 8 (4.9) c |
| Peripheral arterial disease | 0 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
| Cerebrovascular disease | 0 | 8 (3.6) | 5 (5.4) | 3 (2.3) | 4 (6.7) | 4 (2.4) |
| COPD | 0 | 8 (3.6) | 2 (2.2) | 6 (4.5) | 2 (3.3) | 6 (3.7) |
| Diabetes mellitus | 0 | 49 (21.9) | 26 (28.3) | 23 (17.4) | 17 (28.3) | 32 (19.5) |
| Chronic kidney disease | 0 | 23 (10.3) | 13 (14.1) | 10 (7.6) | 8 (13.3) | 15 (9.1) |
| Cancer | 0 | 31 (13.8) | 12 (13.0) | 19 (14.4) | 7 (11.7) | 24 (14.6) |
| Gastrointestinal ulcer | 0 | 9 (4.0) | 1 (1.1) | 8 (6.1) | 1 (1.7) | 8 (4.9) |
| Liver disease | 0 | 12 (5.4) | 7 (7.6) | 5 (3.8) | 4 (6.7) | 8 (4.9) |
| Leukemia | 0 | 2 (0.9) | 1 (1.1) | 1 (0.8) | 0 (0.0) | 2 (1.2) |
| Lymphoma | 0 | 3 (1.3) | 1 (1.1) | 2 (1.5) | 1 (1.7) | 2 (1.2) |
| AIDs | 0 | 2 (0.9) | 0 (0.0) | 2 (1.5) | 0 (0.0) | 2 (1.2) |
| CCI, point | 0 | 4.0 (3.0–5.0) | 5.0 (4.0–6.0) | 3.0 (2.0–5.0) b | 5.0 (4.0–6.0) | 4.0 (2.0–5.0) d |
| Medications, n (%) | ||||||
| Steroid | 0 | 154 (68.8) | 65 (70.7) | 89 (67.4) | 40 (66.7) | 114 (69.5) |
| Methotrexate | 0 | 20 (8.9) | 7 (7.6) | 13 (9.8) | 3 (5.0) | 17 (10.4) |
| Janus kinase inhibitor | 0 | 6 (2.8) | 1 (1.1) | 5 (3.8) | 1 (1.7) | 5 (3.0) |
| Biological medical product | 0 | 13 (5.8) | 8 (8.7) | 5 (3.8) | 7 (11.7) | 6 (3.7) c |
| Antifibrotic drug | 0 | 49 (21.9) | 20 (21.7) | 29 (22.0) | 17 (28.3) | 32 (19.5) |
| Other immunosuppressants | 0 | 83 (37.1) | 30 (32.6) | 53 (40.2) | 18 (30.0) | 65 (39.6) |
| Spirometry findings | ||||||
| %FVC, % | 33 | 80.3 (69.0–96.3) | 75.6 (62.1–94.9) | 79.1 (66.6–94.2) b | 72.3 (53.1–85.4) | 72.8 (71.9–99.4) d |
| %FEV1.0, % | 100 | 79.2 (64.5–94.6) | 80.3 (62.1–94.9) | 79.1 (66.6–94.2) | 74.9 (57.6–96.6) | 81.7 (67.7–94.5) |
| DLCO, mL/min/Torr | 73 | 11.1 (9.1–14.8) | 9.6 (7.8–11.6) | 12.4 (10.1–16.5) b | 9.4 (7.2–10.4) | 12.2 (9.8–16.2) d |
| Blood examination | ||||||
| Hemoglobin, g/dL | 0 | 12.4 (11.5–13.6) | 12.0 (10.5–13.3) | 12.5 (11.7–13.9) b | 11.8 (10.4–13.0) | 12.5 (11.7–13.7) d |
| Albumin, g/dL | 0 | 3.7 (3.3–4.0) | 3.6 (3.1–4.0) | 3.6 (3.4–4.1) b | 3.7 (3.2–4.0) | 3.7 (3.3–4.1) |
| eGFR, mL ・min−1・1.73 m−2 | 0 | 67.0 (53.0–79.8) | 60.5 (43.5–76.0) | 70.0 (59.0–81.8) b | 58.5 (43.5–73.0) | 68.0 (57.0–82.8) d |
| CRP, mg/dL | 2 | 0.4 (0.1–2.1) | 0.6 (0.2–4.4) | 0.3 (0.1–1.1) b | 0.8 (0.2–4.8) | 0.3 (0.1–1.4) |
| KL‐6, U/mL | 17 | 728.0 (466.0–1265.0) | 889.0 (500.0–1550.0) | 679.5 (459.0–1113.3) | 782.0 (445.0–1402.0) | 716.5 (486.3–1223.5) |
| SP‐D, ng/mL | 48 | 163.0 (83.4–225.3) | 163.0 (101.5–231.0) | 163.0 (74.3–223.0) | 158.5 (64.8–237.8) | 166.5 (85.2–223.8) |
| NT‐pro BNP, pg/mL | 106 | 195.0 (75.0–564.8) | 360.5 (163.5–895.5) | 118.0 (54.5–396.8) | 408.5 (153.0–949.3) | 171.0 (66.0–461.8) d |
| Exercise tolerance | ||||||
| Six‐minute walk distance, m | 0 | 348.5 (244.5–431.0) | 230.5 (152.3–275.5) | 410.5 (375.8–458.0) b | 180.0 (140.8–228.3) | 393.0 (328.5–450.0) d |
| Pre‐6MWT SpO2 | 4 | 97.0 (95.0–98.0) | 97.0 (95.0–98.0) | 97.0 (96.0–98.0) | 96.0 (95.0–98.0) | 97.0 (96.0–98.0) |
| Nadir SpO2 | 4 | 91.0 (86.0–94.0) | 88.5 (82.0–93.0) | 91.0 (87.0–94.0) a | 88.0 (82.0–93.0) | 91.0 (87.0–94.0) c |
| ΔSpO2 | 4 | 6.0 (3.0–10.8) | 7.0 (3.0–13.0) | 6.0 (3.0–9.0) | 7.0 (3.5–13.5) | 6.0 (2.0–9.0) |
Note: Values are median (lower quartile—upper) or n (%).
Abbreviations: %FEV1.0, forced expiratory volume percentage in 1 s; %FVC, percentage of forced vital capacity; AIDs, acquired immune deficiency syndrome; ANCA, anti‐neutrophil cytoplasmic antibody; CCI, charlson comorbidity index; COPD, chronic obstructive pulmonary disease; CRP, C‐reactive protein; DLco, percent predicted diffusing capacity of lung for carbon monoxide; eGFR, estimated glomerular filtration rate; KL‐6, krebs von den lungen; LVEF, left ventricular ejection fraction; NT‐pro BNP, N‐terminal prohormone of brain natriuretic peptide levels; SP‐D, pulmonary surfactant protein D; TRPG, tricuspid regurgitant pressure gradient.
p < 0.05 versus “6MWD < 310 m” group.
p < 0.01 versus “6MWD < 310 m” group.
p < 0.05 versus “6MWD < 260 m” group.
p < 0.01 versus “6MWD < 260 m” group.
3.2. Association of Exercise Tolerance With Clinical Outcome
A total of 23 deaths (10.2%) and 56 hospitalizations for pulmonary disease (25.0%) occurred during the follow‐up period (median 1.2 years, IQR 0.6–2.3). The ROC curves of the 6MWD for all‐cause mortality and hospitalization for pulmonary disease are depicted in Figure 1. The AUCs were 0.678 (95% confidence interval [CI]: 0.574–0.782; p = 0.005) for all‐cause mortality (Figure 1A) and 0.609 (95% CI: 0.526–0.691) due to hospitalization for pulmonary disease (Figure 1B). The 6MWD of 310 m and 260 m were identified as optimal cut‐off points for prediction of all‐cause mortality and hospitalization for pulmonary disease, respectively. The sensitivity and specificity values for all‐cause mortality at a 6MWD of 310 m were 0.783 and 0.632, respectively. Additionally, the sensitivity and specificity for hospitalization for pulmonary disease at a 6MWD of 260 m were 0.378 and 0.778, respectively. The Kaplan–Meier survival curve showed that a higher 6MWD was associated with a lower rate of all‐cause mortality and hospitalization for pulmonary disease (Figure 2) (log‐rank = 16.146, p < 0.001 and log‐rank = 9.065, p = 0.003, respectively).
FIGURE 1.
Receiver‐operating characteristics curves of the 6MWD. The cut‐off value of the 6MWD for all‐cause mortality was 310 m in patients in this study (A). The cut‐off value of the 6MWD for hospitalization for pulmonary disease was 260 m (B). 6MWD, 6‐min walking distance; AUC, area under the curve; CI, confidence interval.
FIGURE 2.
Kaplan–Meier curves for mortality (A) and hospitalization for pulmonary disease (B) by 6‐min walking distance. The rates of all‐cause mortality and hospitalization for pulmonary disease were significantly higher in the group with the 6MWD below the cut‐off value than in the group with the 6MWD above the cut‐off value. 6MWD, 6‐min walking distance.
The results of the univariate and multivariate Cox proportional regression analyses for all‐cause mortality and hospitalization for pulmonary disease in each model are presented in Figure 3. In the univariate analysis, higher 6MWD was significantly associated with a lower incidence of all‐cause mortality [HR per 10‐m increase of 6MWD = 0.950 (95% CI = 0.919–0.982)] and hospitalization for pulmonary disease [HR per 10‐m increase of 6MWD = 0.967 (95% CI = 0.947–0.987)].
FIGURE 3.
Forest plots showing 6‐min walking distance and all‐cause mortality (A) and hospitalization for pulmonary disease (B). Both analyses were adjusted for age, sex, presence of BMI < 18.5, KL‐6 at admission, and CCI score. 6MWD, 6‐min walking distance; BMI, body mass index; CCI, Charlson Comorbidity Index; CI, confidence interval; HR, hazard ratio; KL‐6, Kreb von den Lunge.
In the multivariate analysis, higher 6MWD was significantly associated with a lower risk of all‐cause mortality in Model 1 and 3 [HR per 10‐m increase in 6MWD = 0.962, 0.957 (95% CI = 0.927–0.998, 0.917–0.997), respectively]. In Model 2, 6MWD was not significantly associated with all‐cause mortality [HR per 10‐m increase in 6MWD = 0.967 (95% CI = 0.930–1.005)]. For hospitalization for pulmonary disease, higher 6MWD was significantly associated with a lower risk in Model 1 and 2 [HR per 10‐m increase in 6MWD = 0.968, 0.973 (95% CI = 0.946–0.991, 0.949–0.997), respectively]. In Model 3, 6MWD was not significantly associated with hospitalization for pulmonary disease [HR per 10‐m increase in 6MWD = 0.979 (95% CI = 0.953–1.006)].
A higher 6MWD was consistently associated with a decreased risk of all‐cause mortality without significant statistical interaction across various subgroups, including age (stratified at 65 years old), sex, saturation of percutaneous oxygen decreasing during the 6‐min walking test (stratified at 90%), presence of RA, presence of PM/DM, presence of SSc, and presence of AAV (Figure 4). However, interaction analysis revealed that the association between 6MWD and hospitalization for pulmonary disease differed between patients aged ≥ 65 and < 65 years (P for interaction = 0.004). In addition, a significant interaction was observed between 6MWD and AAV status with respect to hospitalization for pulmonary disease (P for interaction = 0.013) (Figure 5).
FIGURE 4.
Forest plots of adjusted HR of 6MWD in various subgroups for all‐cause mortality. All analyses were adjusted for age, sex, BMI < 18.5, KL‐6 at admission, and CCI score. 6MWD, 6‐min walking distance; 6MWT, 6‐min walking test; BMI, body mass index; CCI, Charlson Comorbidity Index; CI, confidence interval; DM, dermatomyositis; HR, hazard ratio; KL‐6, Kreb von den Lunge; RA, rheumatoid arthritis; SpO2, saturation of percutaneous oxygen.
FIGURE 5.
Forest plots of adjusted HR of 6MWD in various subgroups for hospitalization for pulmonary disease. All analyses were adjusted for age, sex, presence of BMI < 18.5, KL‐6 at admission, and CCI score. 6MWD, 6‐min walking distance; 6MWT, 6‐min walking test; BMI, body mass index; CCI, Charlson Comorbidity Index; CI, confidence interval; DM, dermatomyositis; HR, hazard ratio; KL‐6, Kreb von den Lunge; RA, rheumatoid arthritis; SpO2, saturation of percutaneous oxygen.
4. Discussion
This study is the first to evaluate the association between exercise tolerance, assessed using the 6MWD, and clinical outcomes in individuals with CTD‐ILD. Our results demonstrated that a higher 6MWD was independently associated with lower rates of all‐cause mortality and hospitalization for pulmonary disease, even after adjusting for several confounding factors in individuals with CTD‐ILD. These findings suggest that 6MWD assessment of exercise tolerance predicts all‐cause mortality and hospitalization for pulmonary disease in individuals with CTD‐ILD, similar to findings in patients with other diseases. Moreover, we conclude that the evaluation and maintenance of 6MWD is crucial in the rehabilitation of individuals with CTD‐ILD.
The mechanism underlying the association between 6MWD and all‐cause mortality may involve physical activity. Lower exercise tolerance assessed using 6MWT is associated with lower physical activity in various individuals [28, 29, 30]. Lower physical activity is associated with a higher rate of all‐cause mortality and incidence of disease in patients with cancer [31], chronic obstructive pulmonary disease (COPD) [32], ILD [33], cardiovascular disease [34], and heart failure [35]. In this study, physical activity levels were not measured; however, we believe that lower exercise tolerance may be associated with higher rates of all‐cause mortality and hospitalization for pulmonary disease by inducing lower physical activity. The results of the present study indicated that a 6MWD of more than 310 m in patients with CTD‐ILD is associated with a favorable prognosis. Conversely, a 6MWD below 310 m may identify patients at higher risk of all‐cause mortality, and this threshold may help select patients who require closer monitoring and more intensive multidisciplinary management. Several studies have reported that the cut‐off values for 6MWD in patients with COPD are more than 334 m or 361 m, with a favorable prognosis [19, 36]. In patients with other pulmonary diseases, such as IPF, the cut‐off value is reported to be 250 meters [22], and in patients with RA‐ILD, it is 345 meters [23]. Additionally, many reports have indicated that the cut‐off value for 6MWD in patients with pulmonary arterial hypertension and heart failure is 300 m. Compared to these previous studies, the 6MWD value of 310 m in patients with CTD‐ILD in this study is considered reasonable and reliable as an indicator of reduced exercise tolerance, and we believe that it may be useful as a factor in predicting prognosis [37, 38, 39]. For all‐cause mortality, the non‐significant estimate for 6MWD in the model adjusting for %FVC (Model 2) likely reflects limited statistical power rather than a true absence of association, as the point estimate and confidence interval were very similar to those of the other models. This is particularly plausible given the relatively small number of deaths, which constrains the effective events‐per‐parameter ratio and can lead to reduced precision and instability in multivariable Cox regression estimates.
For hospitalization for pulmonary disease, the association of 6MWD was statistically significant when adjusting for KL‐6 or %FVC (Models 1–2) but became borderline when adjusting for DLCO (Model 3). In addition to the event‐count constraint, this attenuation may reflect partial overlap in the information captured by 6MWD and DLCO. In ILD, both 6MWT outcomes and DLCO can be influenced by interstitial and pulmonary vascular components, making it plausible that including DLCO in the model reduces the incremental prognostic information contributed by 6MWD. Importantly, despite these differences in statistical significance, the magnitude of the 6MWD effect remained highly similar across models. Therefore, our findings support a robust, directionally consistent association between better functional exercise capacity and more favorable outcomes, while highlighting that borderline p‐values may be sensitive to model specification in the setting of limited events.
In this study, interactions were observed between 6MWD and hospitalization for pulmonary disease when comparing subgroups defined by age (stratified at 65 years old) and by the presence or absence of AAV. We believe that in older patients and patients with AAV‐ILD, factors contributing to the interaction between 6MWD and hospitalization for pulmonary disease include the complexity of prognostic determinants, which differ from those in other populations. For example, the presence of multiple extrapulmonary complications may be a contributing factor. These elements could explain the interactions observed in our study. However, owing to the difficulty of conducting a detailed analysis in this study, we consider this a subject for future investigation.
A major strength of this study was the identification of the association between exercise tolerance (assessed using 6MWD) and clinical outcomes (all‐cause mortality and hospitalization for pulmonary disease) in patients with CTD‐ILD, as well as the establishment of cut‐off values for 6MWD. The clinical implication of these findings is that 6MWD serves as both a risk stratification marker for prognosis and a valuable tool for assessing exercise tolerance in these patients. Moreover, 6MWD may be a potential therapeutic target for improving the prognosis in patients with CTD‐ILD.
This study has several limitations. First, its observational nature and single‐center design introduced selection bias, despite our use of multiple imputation techniques to mitigate this. Our study population was limited to those who could perform the 6MWD, potentially representing a more stable subset of patients with CTD‐ILD. This suggests that our findings may have limited generalizability to patients with more severe CTD‐ILD. Therefore, future research should evaluate the utility of the 6MWD in severe cases of CTD‐ILD.
Second, the follow‐up period was relatively limited. Although 23 deaths occurred during the median follow‐up period of 1.2 years, suggesting that 6MWD may have a clinically meaningful impact on short‐ to mid‐term prognosis, CTD‐ILD is a chronic and heterogeneous disease with variable disease trajectories according to the underlying CTD and patient‐specific factors. Therefore, further studies with longer follow‐up periods are warranted to determine whether 6MWD predicts long‐term prognosis in patients with CTD‐ILD.
Third, this study assessed 6MWD only at a single time point and did not include follow‐up data on longitudinal changes in 6MWD. Although previous studies have recommended monitoring temporal changes in 6MWD as an indicator of ILD progression, reports examining the association between single‐time‐point 6MWD assessment and clinical outcomes in patients with CTD‐ILD, as in the present study, remain very limited. CTD‐ILD has heterogeneous disease trajectories depending on the underlying connective tissue disease and patient‐specific factors, and a decline in 6MWD during follow‐up may reflect disease progression and be associated with poor prognosis. Therefore, future longitudinal studies are warranted to determine whether declines in 6MWD over time provide additional prognostic information beyond baseline 6MWD in patients with CTD‐ILD.
Finally, we excluded patients who were unable to perform the 6‐min walking test, including those with reduced physical performance and walking disabilities. Consequently, our study population likely had relatively high levels of physical function, and it remains unclear whether the same correlations would be observed in populations with physical dysfunction or disabilities in activities of daily living (ADL). Therefore, caution should be exercised when applying our findings to patients with CTD‐ILD, physical dysfunction, or ADL impairment. Further research is needed to evaluate the utility of 6MWD or alternative physical function assessments in groups with decreased physical function or ADL limitations.
In conclusion, a higher 6MWD was independently associated with a better prognosis in patients with CTD‐ILD. We demonstrated that 6MWD could serve as both a risk stratification factor and a valuable physical performance assessment tool for patients with CTD‐ILD. As the global prevalence of patients with CTD‐ILD increases, the importance of addressing reduced physical function becomes increasingly critical, which underscores the significance of our findings. Therefore, maintaining a higher exercise tolerance should be a key therapeutic target in physical rehabilitation programs for these patients.
Author Contributions
Hidenori Kariya: conceptualization, data curation, formal analysis, investigation, methodology, validation, visualization, writing – original draft. Kenji Oku: methodology, project administration, supervision, validation, writing – review and editing. Yoshikazu Suzuki: investigation, methodology, validation, writing – review and editing. Yohei Yamato: investigation, writing – review and editing. Shuken Kobayashi: investigation, writing – review and editing. Kunihiro Yamaoka: supervision, writing – review and editing.
Funding
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgments
The authors thanks the staff of the Department of Rehabilitation and the Department of Rheumatology, Kitasato University Hospital, for their sincere support.
Data Availability Statement
Research data are not shared.
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Data Availability Statement
Research data are not shared.