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. 2020 Jul 29;15(7):e0236346. doi: 10.1371/journal.pone.0236346

Evaluation of health-related quality of life and the related factors in a group of Chinese patients with interstitial lung diseases

Xue-Yan Yuan 1,#, Hui Zhang 1,#, Li-Ru Huang 1,, Fan Zhang 1,, Xiao-Wen Sheng 1,, Ai Cui 1,2,*
Editor: Paola Faverio3
PMCID: PMC7417083  PMID: 32726327

Abstract

Introduction

Interstitial lung diseases (ILDs) include a wide variety of chronic progressive pulmonary diseases characterized by lung inflammation, fibrosis and hypoxemia and can progress to respiratory failure and even death. ILDs are associated with varying degrees of quality of life impairments in affected people. Studies on the quality of life in patients with ILDs are still limited, and there are few studies with long-term follow-up periods in these patients.

Methods

Data from patients who were clinically diagnosed with ILDs in the Respiratory Department, Beijing Chaoyang Hospital, Capital Medical University from January 2017 to February 2018 were collected. Clinical status and HRQoL were assessed at baseline and subsequently at 6- and 12-month intervals with the LCQ, mMRC, HADS, SF-36, and SGRQ. Multivariate linear regression was used to evaluate the determinants of the decline in HRQoL.

Results

A total of 139 patients with idiopathic interstitial pneumonia (IIP) and 30 with connective tissue disease-associated ILD (CTD-ILD) were enrolled, 140 of whom completed the follow-up. The mean age was 63.7 years, and 92 patients were men. At baseline, the decline in HRQoL assessed by the SF-36 and SGRQ was significantly associated with the mMRC, LCQ and HADS depression score. In the follow-up, changes in FVC%, DLco%, mMRC and LCQ were significantly associated with changes in HRQoL.

Conclusions

HRQoL in both IIP and CTD-ILD patients deteriorates to varying degrees, and the trend suggests that poor HRQoL in these patients is associated with many determinants, primarily dyspnea, cough and depression. Improving HRQoL is the main aim when treating patients living with ILDs.

Introduction

Interstitial lung diseases (ILDs) are a group of chronic and progressive fibrotic lung parenchyma diseases resulting in substantial morbidity and mortality [1, 2]. ILDs include more than 200 subtypes with different etiologies and courses, among which idiopathic interstitial pneumonia (IIP) and connective tissue disease-associated ILD (CTD-ILD) are common subtypes. As the diseases progress, patients' activities of daily living become irreversibly impaired, accompanied by a high symptom burden and significant comorbidities [3]. Meanwhile, the prognosis of these diseases is often poor, which seriously impairs the quality of life (QoL) in affected people due to the insidious onset, lack of typical symptoms, limited therapeutic methods and obvious side effects of medicines [4].

QoL refers to the experience of individuals in different cultures and value systems relating to their goals, expectations, standards and concerns, and it reflects the patient’s evaluation of functionality. Health-related quality of life (HRQoL) concerns a person's life satisfaction and happiness as affected by health, including physical, psychological and social functions [5]. Quantifying HRQoL may be helpful in determining patients' subjective understanding of the disease and the disease burden on various aspects of their lives and providing information that cannot be captured by physiologic or radiologic measures.

Previous studies on HRQoL in patients with ILDs focused on idiopathic pulmonary fibrosis (IPF) and sarcoidosis [57]. IPF is characterized by an irreversible decline in lung function and death resulting from respiratory failure within 2–3 years [8]. Acute exacerbations of IPF usually have an unidentifiable cause and prodrome, making the clinical course more difficult to predict [9]. As the disease progresses, dyspnea often leads to severe mobility limitations, significantly reducing patients' emotional well-being and independence [5]. Chronic symptoms, poor lung function, and common drug side effects may contribute to the decline in HRQoL [1012]. Previous studies have shown that HRQoL in these patients deteriorates at various rates [5, 13]. Sarcoidosis is a systemic granulomatous disease with no known cause. As another common subset of ILDs, pulmonary sarcoidosis is associated with a wide range of physical symptoms, such as cough, dyspnea on exertion, and fatigue [14]. Marked deterioration in HRQoL is common in patients with sarcoidosis [7, 15].

Currently, studies about HRQoL in patients with other types of ILDs, such as CTD-ILD and chronic hypersensitivity pneumonia, are rare [1618]. Few of those conducted were prospective follow-up studies, and most were relatively small cohort studies [1719]. Research on the HRQoL of Chinese ILD patients is very limited. Additionally, no study has compared the level of HRQoL impairment in IIP and CTD-ILD patients. The aim of this study was to investigate HRQoL in Chinese patients with ILDs including IIP and CTD-ILD and to identify any factors influencing HRQoL among these patients.

Methods

Patients and study design

Patients aged ≤85 years who were diagnosed with ILDs including IIP and CTD-ILD at the Department of Respiratory and Critical Medicine of Capital Medical University affiliated with Beijing Chaoyang Hospital from January 2017 to February 2018 were included in the present prospective study. The diagnosis of IIP or CTD-ILD was based on clinical characteristics and high-resolution computed tomography (HRCT) presentation according to the American Thoracic Society international consensus definition [20]. Patients with the following conditions were excluded: hemorrhagic diseases, New York Heart Association (NYHA) class III to IV heart failure, hepatic insufficiency (alanine aminotransferase level 2 times the upper limit of normal), renal insufficiency (creatinine clearance less than 50 milliliters/minute), and pregnancy or lactation.

A cross-sectional and longitudinal study was conducted, and HRQoL and the factors influencing it were assessed in the patients who were eligible for this study. Then, a prospective cohort study was conducted to follow the changes in the subjects’ quality of life, symptoms and physiological indicators every 6 months, and the follow-up lasted for 12 months. Questionnaires were implemented within one week after physiological indicators were measured through face-to face or telephone interviews. All patients were treated according to routine clinical practice, with no additional intervention.

This study was approved by the Institutional Review Board and Ethics Committee of Beijing Chaoyang Hospital, Capital Medical University (2016-Science-149). All patients provided approval and informed consent prior to study entry.

Clinical data collection

Sociodemographic and disease information was obtained with a standardized questionnaire during clinical examinations at baseline. The following characteristics were included in this questionnaire: the date of birth, age, sex, nationality, height and weight, smoking status, marital status, education, occupation, disease duration, comorbidities, and therapeutic drugs.

Forced expiratory spirometry (forced vital capacity (FVC)), the forced expiratory volume in 1 s (FEV1)) and the diffusing capacity of the lung for carbon monoxide (DLco) were measured according to American Thoracic Society (ATS)/European Respiratory Society (ESR) recommendations (MasterScreen, CareFusion Jaeger, Germany) [21, 22]. The previously established references for FVC, FEV1 and DLco were used [2325].

Pre-existing recent HRCT images were retrospectively evaluated and scored by two researchers who were blinded to the clinical information [8]. HRCT scoring was originally described by Kazerooni EA et al. and modified according to the actual situation [26]. Briefly, three sections (the section of the aortic arch, the section between the aortic arch and the inferior pulmonary vein, and the section between the inferior pulmonary vein and the diaphragmatic plane) were scored on a scale of 0–5 for ground glass opacities and fibrosis, separately. The percentage was scored as 0 (no finding), 1 (<5%), 2 (5–24%), 3 (25–49%), 4 (50–75%), or 5 (>75%), and interlobular septa thickening was scored as 1 (fibrosis score). The scores for each section were averaged to obtain the final results.

The interstitial lung disease-gender-age-physiology index (ILD-GAP Index) was also assessed from data obtained at the initial evaluation in accordance with the methods proposed by Ryerson et al. [27]. ILD-GAP is an accurate model for predicting mortality in patients with most subtypes and all stages of disease and contains four sets of variables, namely, ILD subtype, sex, age and physiological function. The overall score ranges from 0 to 8; higher scores are associated with higher mortality.

Questionnaire tests

Dyspnea was measured using the Modified Medical Research Council Dyspnea Scale (mMRC), which has been previously validated. The mMRC is a 5-point scale that asks respondents to rate their dyspnea from 0 (no breathlessness except during strenuous exercise) to 4 (too breathless to leave the house or breathless when dressing or undressing) after receiving an explanation from the staff [28, 29].

Coughing was evaluated with the Chinese version of the Leicester Cough Questionnaire (LCQ), which is a valid instrument for assessing the impact of cough and the ability to detect a response to change. The LCQ is a 19-item self-administered chronic cough QoL questionnaire that includes physical, psychological and social domains, and each represents adverse events caused by cough [30, 31]. It is scored by summing the responses across the three items to form a total score ranging from 3 to 21, with higher scores reflecting less severe cough.

Depression and anxiety were rated using the Hospital Anxiety and Depression Scale (HADS). The HADS is a 14-item questionnaire that contains two subscales with scores on each subscale ranging from 0 to 21 points for anxiety and depression; a score between 8 and 10 indicates borderline caseness, and a score >10 indicates caseness for anxiety and depression [32].

HRQoL was measured using the St. George’s Respiratory Questionnaire (SGRQ) and the Short Form-36 (SF-36). The SGRQ is a self-administered, 50-item questionnaire for assessing HRQoL in patients with respiratory diseases; it has previously been used in patients with COPD and IPF [3335]. It covers three domains: symptoms, activity and impact. The scores for each domain and the total score range from 0 to 100, with higher scores indicating worse quality of life. The SF-36 is a generic questionnaire that contains 36 items categorized into eight domains (vitality, physical functioning, general health, role physical, bodily pain, social functioning, role emotional and mental health) and two psychometrically established summary scores: the physical component score (PCS, constituted by the domains of physical functioning, role physical, general health, and bodily pain) and the mental component score (MCS, constituted by the domains of mental health, emotional role, social functioning, and vitality) [36]. The scores for each domain and summary scores range from 0 to 100, with higher scores indicating better quality of life [37].

Statistical analysis

In this study, all available data collected at baseline and longitudinally were summarized. Continuous variables are expressed as the mean±standard deviation (SD). Continuous variables with a skewed distribution are expressed as the median and interquartile range (IQR). Categorical variables are expressed as counts and percentages. The characteristics of ILD subtypes (IIP and CTD-ILD) were compared using an unpaired t test, a Chi-squared test or the Mann-Whitney’s U-test as appropriate. The relationships between the selected variables and baseline HRQoL were characterized by univariate and multivariate linear regression analyses. Variables with a P value <0.10 in the univariate linear regression analysis were included in the multivariate linear model. Multivariate models were constructed using stepwise selection and inverse elimination methods prior to the final assessment of clinical and biological plausibility. In the follow-up, the relationships between changes in HRQoL and clinical characteristics, such as lung function tests and respiratory symptoms, were measured using linear regression analysis. The relationships between changes in the SGRQ total domain and changes in clinical characteristics (stratified into quintiles) were assessed using one-way analysis of variance (ANOVA) followed by pairwise comparisons according to the Least Significant Difference method. A P value <0.05 was considered statistically significant. All statistical analyses were performed with IBM SPSS statistics version 19.

Results

Patient characteristics

A total of 169 patients were enrolled in this study, with a median age of 63.7±10.9 years. Sixteen (8%) patients died, and 14 (7%) patients were lost to follow-up; these patients were excluded from the cohort (Fig 1). Among the included patients, 139 were diagnosed with IIP (101 idiopathic non-specific interstitial pneumonia (NSIP) cases, 18 unclassifiable IIP cases, 11 respiratory-bronchiolitis-ILD cases, 7 IPF cases, and 2 others), and 30 were diagnosed with CTD-ILD (12 Sjögren’s syndrome (SS) cases, 6 undifferentiated CTD cases, 4 polymyositis/dermatomyositis (PM/DM) cases, 3 scleroderma (SSc) cases, 2 rheumatoid arthritis (RA) cases, and 3 others) (S1 Table). No significant sex predominance was noted (male, 54.4%), and most of the included patients (53.8%) were nonsmokers. The duration of symptoms of ILDs was (21.7±28.9) months. Most patients had one (39.6%) or more than one comorbidity. Compared to patients with CTD-ILD, patients with IIP were more likely to be male and to be smokers (Table 1).

Fig 1. Flowchart of the study.

Fig 1

Table 1. Demographics and disease-related characteristics (n = 169).

Characteristics Value/number (percentage) P value
All patients IIP CTD-ILD
N 169 139 30
Age, years 63.7±10.9 64.3±11.0 61.1±10.3 0.143
Gender, male 92 (54.4%) 86 (61.9%) 6 (20.0%) 0.000
Ethnic group 0.203
 Han 156 (92.3%) 130 (93.5%) 26 (86.7%)
 Other 13 (7.7%) 9 (6.5%) 4 (13.3%)
BMI, kg/m 2 25.2±4.1 25.4±4.0 24.4±4.3 0.227
Education level* 0.203
 Low 41 (24.3%) 31 (22.3%) 10 (33.3%)
 Middle-High 128 (75.7%) 108 (77.7%) 20 (66.7%)
Economic situation, RMB/year/family 0.026
 <5000 99 (58.6%) 77 (55.4%) 22 (73.3%)
 5000–10000 53 (31.4%) 46 (33.1%) 7 (23.3%)
 >10000 17 (10.1%) 16 (11.5%) 1 (3.3%)
Smoking history 0.003
 Current 22 (13.0%) 22 (15.8%) 0 (0.0%)
 Former 56 (33.1%) 50 (36.0%) 6 (20.0%)
 Never 91 (53.8%) 67 (48.2%) 24 (80.0%)
Disease duration, months 21.7±28.9 20.7±26.9 26.3±37.3 0.442
Number of comorbidities** 0.218
 0 56 (33.1%) 42 (30.2%) 14 (46.7%)
 1 67 (39.6%) 58(41.7%) 9 (30.0%)
 ≥2 46 (27.2%) 39 (28.1%) 7 (23.3%)
Therapeutic drugs used previously 0.072
 Corticosteroids or/and immunosuppressants 34 (20.1%) 24 (17.3%) 10 (33.3%)
 Antifibrotic drugs 5 (3.0%) 4 (2.9%) 1 (3.3%)
 No intervention 113 (66.9%) 99 (71.2%) 14 (46.7%)
 Others*** 17 (10.1%) 12 (8.6%) 5 (16.7%)

Data are expressed as a number (%) or the mean±SD. BMI, body mass index; IIP, idiopathic interstitial pneumonia; CTD, connective tissue disease; CTD-ILD, CTD-associated ILD; HP, hypersensitivity pneumonitis; COPD, chronic obstructive pulmonary disease

* A low education level indicates that patients received only primary education, while a middle-high education level indicates that patients received secondary education or above.

** Comorbidities included asthma, pulmonary hypertension, COPD/emphysema, lung cancer, pulmonary embolism, gastro-esophageal reflux disease, cardiovascular disease and metabolic diseases.

*** Other drugs included traditional Chinese medicine and antioxidants

The baseline physiological, symptom and psychological characteristics of the patients are presented in Table 2. Compared with patients with IIP, patients with CTD-ILD had more severe lung function impairment as demonstrated by the mean FVC% predicted (mean, 86.9±22.2 vs 74.4±19.1; P = 0.017). The mean scores for ground glass opacities and honeycombing were similar in both IIP and CTD-ILD patients. The severity of dyspnea varied greatly in the two groups of patients; 39 patients with IIP were categorized as mMRC 2, closely followed by mMRC 1 (38). Eleven CTD-ILD patients were categorized as mMRC 2. No significant difference in the severity of dyspnea was found between the two groups (P = 0.075). The average severity of cough measured by the LCQ was moderate in both IIP and CTD-ILD patients, with average scores of 16.7±3.7 and 16.3±3.7, respectively. A total of 168 patients completed the evaluation of their psychological problems, and no difference was found between the two groups in the mean HADS-A and HADS-D scores.

Table 2. Clinical data of the ILD patients at the time of enrollment.

Variable Value P value
IIP CTD-ILD
HRQoL Questionnaire
 mMRC (0/1/2/3/4) (n = 169) 37/38/39/16/9 4/7/11/8//0 0.075
 LCQ domain (n = 168)
  Physical domain 5.4±1.3 5.3±1.3 0.555
  Psychological domain 5.5±1.3 5.4±1.3 0.574
  Social domain 5.8±1.3 5.7±1.3 0.699
  Total domain 16.7±3.7 16.3±3.7 0.566
 SF-36 (n = 169)
  Physical functioning 80.0[60.0, 90.0] 65.0[40.0, 80.0] 0.010
  Role physical 25.0[0.0, 81.2] 50.0[0.0, 100.0] 0.158
  Bodily pain 72.0[40.0, 100.0] 56.5[40.0, 88.0] 0.419
  General health 45.0[30.0, 55.0] 30.0[15.0, 57.0] 0.049
  Vitality 60.0[45.0, 75.0] 55.0[40.0, 60.0] 0.023
  Social functioning 75.0[62.5, 100.0] 68.7[50.0, 90.6] 0.216
  Role emotional 66.7[0.0, 100.0] 100.0[33.3, 100.0] 0.134
  Mental health 64.0[53.0, 72.0] 68.0[52.0, 80.0] 0.129
  PCS 37.2±12.0 31.1±14.2 0.015
  MCS 48.3±11.6 45.6±11.1 0.231
 SGRQ (n = 169)
  Symptom 37.4±23.9 40.7±25.8 0.494
  Activity 40.0±26.0 54.2±29.0 0.009
  Impact 26.8±19.2 37.2±20.3 0.008
  Total 32.9±19.1 43.3±20.6 0.009
Symptom score
 Pulmonary function (n = 139)
  FVC, % predicted 86.9±22.2 74.4±19.1 0.017
  FEV1/FVC 82.3±9.7 81.3±6.8 0.658
  DLco, % predicted 60.9±18.1 52.9±13.6 0.058
 ILD-GAP index (n = 135) 2.0[1.0, 3.2] 0.0[0.0, 1.0] 0.000
 Chest CT image (n = 168)
  Ground glass opacity score 2.7±1.1 2.9±0.9 0.304
  Honeycombing score 1.4±1.1 1.4±0.8 0.953
 HADS-A (n = 168) 5.0[3.0, 7.0] 6.0[3.0, 9.0] 0.245
 HADS-D (n = 168) 5.0[1.0, 7.0] 5.5[2.7, 9.2] 0.086

Data are expressed as a number, the mean±SD, or the median (interquartile range). ILD, interstitial lung disease; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; DLco, diffusing capacity of the lung for carbon monoxide; ILD, interstitial lung disease; ILD-GAP, The interstitial lung disease-gender-age-physiology index; HRQoL, Health-related Quality of Life; mMRC, modified Medical Research Council dyspnea scale; LCQ, Leicester Cough Questionnaire; HADS, Hospital Anxiety and Depression Scale; HADS-A, HADS-Anxiety; HADS-D, HADS-Depression; SF-36, the Medical Outcomes Study Short Form 36; PCS, physical component score; MCS, mental component score; SGRQ, St. George’s Respiratory Questionnaire

HRQoL

The decline in HRQoL was significant in most dimensions in both IIP and CTD-ILD patients (Table 2). Regarding the SF-36, patients with CTD-ILD had more impaired HRQoL than patients with IIP as assessed by the SF-36 PCS (mean, 31.1±14.2 vs 37.2±12.0; P = 0.015). HRQoL, as measured by the SF-36 MCS, was similar in the two groups. At baseline, patients with CTD-ILD had higher scores in all SGRQ dimensions except for the symptom domain (mean, 40.7±25.8 vs 37.4±23.9; P = 0.494). The different dimensions of HRQoL measured with the SF-36 at baseline for all patients are presented in Fig 2. Compared to the other three dimensions in the PCS, the mean score was the lowest for general health. On average, the score was lowest in the vitality domain and highest in the social functioning domain on the MCS.

Fig 2. HRQoL scores at baseline by the SF-36 for all patients (n = 169).

Fig 2

A. The mean scores for dimensions related to physical health; B. The mean scores for dimensions related to mental health (SF-36, the Medical Outcomes Study Short Form 36; PCS, physical component score; MCS, mental component score).

Factors influencing HRQoL assessed at the time of enrollment

As shown in Table 3, HRQoL was found to be significantly affected by multiple factors. ILD subtype was negatively associated with the SF-36 PCS and positively associated with most dimensions of the SGRQ in the univariate liner regression analyses. As previously mentioned, patients with CTD-ILD had a lower quality of life as measured by the SF-36 PCS and SGRQ activity, impact, and total domains when compared with patients with IIP. Sociodemographic factors, such as sex, age, education level and smoking history, were found to be associated to some degree with part of the dimensions of HRQoL calculated by the SGRQ and SF-36. Disease durations and therapeutic drugs were associated with most dimensions of HRQoL according to the SGRQ results. The FVC% predicted and DLCO% predicted were strongly associated with most dimensions of the SGRQ except for the symptom domain and the SF-36 PCS. Ground glass opacity on chest CT was associated with one dimension of HRQoL (the SF-36 PCS), and honeycombing was independently associated with most dimensions of HRQoL (SGRQ). Typical symptoms of disease, including dyspnea and cough, were strongly associated with most dimensions of HRQoL (SGRQ and SF-36 PCS). Psychological factors were demonstrated to be associated with some dimensions of HRQoL (SGRQ and SF-36). The ILD-GAP score was also found to be associated with all dimensions of the SGRQ and the SF-36 PCS.

Table 3. Association between HRQoL and other measures at baseline: Results of the univariate linear regression analysis (n = 169).

Characteristics SGRQ SF-36
Total Symptom Activity Impact PCS MCS
ILD subtypes 10.302** 3.322 14.023** 10.342** -6.091* -2.868
Sex 4.710 -1.941 9.844* 3.606 -5.597** -0.334
Age, years 0.231 0.067 0.389* 0.185 -0.126 0.033
BMI, kg/m2 -0.317 0.870 -0.585 -0.522 0.392 0.302
Education level -13.05*** -12.09** -14.39** -12.67*** 7.228*** -0.995
Economic level -2.860 -2.422 -3.300 -2.823 1.428 0.455
Smoking history 2.571 -2.675 4.757 2.903 -2.795* -1.631
Disease duration, months 0.141** 0.152* 0.197** 0.103 -0.079* 0.051
Therapeutic drug -3.383* -4.406* -1.265 -4.358** -0.152 0.417
Pulmonary function
 FVC, % predicted -0.346*** -0.133 -0.497*** -0.323*** 0.195*** 0.051
 FEV1/FVC -0.057 -0.423 0.112 -0.056 -0.133 -0.103
 DLco, % predicted -0.546*** -0.278* -0.812*** -0.469*** 0.313*** 0.006
Chest CT image
 Ground glass opacity 1.043 1.216 3.038 -0.187 -1.869* -0.030
 Honeycombing 3.285* 3.632* 3.014 3.401* -0.945 0.691
Number of comorbidities 0.488 1.913 -0.040 0.361 -0.133 -0.028
mMRC 13.224*** 7.890*** 19.974*** 10.762*** -8.347*** -0.616
LCQ total domain -3.549*** -3.053*** -3.580*** -3.694*** 1.340*** 0.554*
HADS
 HADS-A 1.863*** 1.319* 1.609** 2.170*** -0.339 -1.483***
 HADS-D 2.156*** 0.791 2.712*** 2.228*** -0.897*** -1.336***
ILD-GAP 4.398*** 2.962* 5.208*** 4.317*** -4.299*** -0.023

Data are presented as the beta estimates of regression coefficients. BMI, body mass index; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; DLco, diffusing capacity of the lung for carbon monoxide; mMRC, modified Medical Research Council dyspnea scale; LCQ, Leicester Cough Questionnaire; HADS, Hospital Anxiety and Depression Scale; HADS-A, HADS-Anxiety; HADS-D, HADS-Depression; ILD-GAP, The interstitial lung disease-gender-age-physiology index.

* P≤0.05,

** P≤0.01,

*** P≤0.001

Multivariate linear regression analysis showed that several dimensions of the SGRQ were significantly associated with the mMRC score, LCQ total domain, and HADS-D, whereas dimensions of the SGRQ were weakly associated with clinical variables including sex, BMI, disease duration, and the DLco% predicted. After adjustment for mMRC, ILD subtype (IIP vs CTD-ILD) remained independently associated with SF-36 PCS (P≤0.05). A significant association between the SF-36 PCS and mMRC score was identified. The SF-36 MCS was significantly associated with both the HADS-A and HADS-D (Table 4).

Table 4. Associations between HRQoL and other measures at baseline: Results of the multivariate linear regression analysis (n = 169).

SGRQ SF-36
Total Symptom Activity Impact PCS MCS
R2 0.727 0.392 0.770 0.617 0.528 0.269
ILD subtypes -2.300*
Sex 6.584**
BMI 0.962*
Disease duration 0.153*
DLco, % predicted -0.171*
mMRC 9.098*** 4.826** 16.131*** 4.868*** -0.694***
LCQ total domain -2.233*** -2.725*** -0.976** -2.825***
HADS-A -0.230**
HADS-D 0.690** 0.768** 0.897*** -0.351***

Data are presented as the beta estimates of regression coefficients. BMI, body mass index; DLco, diffusing capacity of the lung for carbon monoxide; mMRC, modified Medical Research Council dyspnea scale; LCQ, Leicester Cough Questionnaire; HADS, Hospital Anxiety and Depression Scale; HADS-A, HADS-Anxiety; HADS-D, HADS-Depression; ILD-GAP, The interstitial lung disease-gender-age-physiology index.

* P≤0.05,

** P≤0.01,

*** P≤0.001

Relationship between the change in HRQoL and changes in clinical characteristics

Changes in pulmonary function, the dyspnea score and the cough score were assessed at 6 months and 12 months (S2 Table). At 6 months, 24 patients’ FVC% predicted and 35 patients’ DLco% predicted were stable. A total of 31 patients had improvements in dyspnea, and 62 patients had experienced relief from coughing. Similarly, 14 patients’ FVC% predicted and 23 patients’ DLco% predicted were stable at the 12-month follow-up. A total of 32 patients experienced relief from dyspnea, and 54 patients experienced relief from coughing at the 12-month follow-up.

At the 6-month follow-up, the changes in HRQoL measured by the SF-36 MCS and SGRQ impact domains revealed a mild improvement in quality of life among patients with IIP. Patients with CTD-ILD had mildly improved HRQoL, as measured by all SF-36 and SGRQ domains except for the symptom domain. Furthermore, IIP patients had mildly improved quality of life as measured by the SF-36 MCS and SGRQ impact domains at the 12-month follow-up. The change in HRQoL measured by the SGRQ activity domain demonstrated a mild decrease in IIP patients. Changes in HRQoL among CTD-ILD patients revealed a mild to moderate improvement in quality of life as measured by all SF-36 domains and the SGRQ total and impact domains (Fig 3).

Fig 3. HRQoL scores measured by the SF-36 and SGRQ at the 6-month follow-up (n = 147) and the 12-month follow-up (n = 140).

Fig 3

A. Changes in HRQoL from baseline to the 6-month follow-up; B. Changes in HRQoL from baseline to the 12-month follow-up. (SF-36, the Medical Outcomes Study Short Form 36; PCS, physical component score; MCS, mental component score; SGRQ, St. George’s Respiratory Questionnaire. * P≤0.05, ** P≤0.01, *** P≤0.001).

The associations between longitudinal changes in HRQoL and clinical characteristics, including the FVC% predicted, DLco% predicted, mMRC and LCQ total score, are shown in Table 5. At 6 months, the change in clinical characteristics was associated with changes in the SGRQ activity domain, impact domain, and total domain. A relationship between changes in clinical characteristics (the FVC% predicted, DLco% predicted, mMRC) and changes in SGRQ symptoms was not found. At the 12-month follow-up, the moderately significant relationship between changes in clinical characteristics and changes in all dimensions of the SGRQ were confirmed. Changes in pulmonary function (FVC% predicted, DLco% predicted) and the LCQ total score were negatively associated with changes in all dimensions of the SGRQ, while changes in the mMRC score were positively associated with changes in all dimensions of the SGRQ.

Table 5. Association between the change in HRQoL and clinical characteristics at the 6-month follow-up and the 12-month follow-up.

ΔSGRQ total ΔSGRQ symptom ΔSGRQ activity ΔSGRQ impact
6-month follow-up 12-month follow-up 6-month follow-up 12-month follow-up 6-month follow-up 12-month follow-up 6-month follow-up 12-month follow-up
ΔFVC% predicted -0.481*** -0.412*** -0.059 -0.223* -0.551*** -0.484*** -0.377*** -0.318**
ΔDLco% predicted -0.458*** -0.554*** 0.013 -0.253* -0.559*** -0.553*** -0.355** -0.514***
ΔmMRC 0.641*** 0.706*** 0.082 0.399*** 0.692*** 0.755*** 0.537*** 0.578***
ΔLCQ -0.562*** -0.584*** -0.239** -0.420*** -0.404*** -0.411*** -0.559*** -0.595***

Data are presented as the beta estimates of regression coefficients. At the 6-month follow-up, 81 patients completed the pulmonary function assessment, although ΔDLco% predicted data were not available for 4 patients. A total of 147 patients completed the LCQ assessment, and 146 patients completed the mMRC assessment. All data were available. At the 12-month follow-up, 79 patients completed the pulmonary function assessment, although ΔDLco% predicted data were not available for 6 patients. A total of 140 patients completed the mMRC and LCQ assessments, and all data were available. FVC, forced vital capacity; ΔFVC% predicted, FVC change from baseline at 6-month follow-up; DLco, diffusing capacity of the lung for carbon monoxide; ΔDLco % predicted, DLco change from baseline at the 6-month follow-up; mMRC, modified Medical Research Council dyspnea scale; ΔmMRC, mMRC change from baseline at the 6-month follow-up; LCQ, Leicester Cough Questionnaire; ΔLCQ, LCQ change from baseline at the 6-month follow-up.

* P≤0.05,

** P≤0.01,

*** P≤0.001

Clinical characteristics and HRQoL of patients who died during follow-up

Of the 169 included patients, 16 patients died during the follow-up (S3 Table). The age at death was 66.7±8.3 years, 10 patients (62.5%) were male, and the duration from the onset of the first symptom to death was 27.8±21.0 months. The diagnosis of most patients who died (15, 93.8%) was IIP, and the main cause of death (10, 62.5%) was pulmonary infection, followed by AE-ILD (5, 31.25%). Differences in clinical characteristics including age, sex, and duration since the first symptoms were not significant between the survivors and non-survivors. In addition, the ILD subtype was not associated with the prognosis in the study population. The HRQoL in patients who died was significantly worse than that in survivors as measured by the SF-36 and SGRQ. The mean SF-36 PCS score in non-survivors was significantly lower than that in survivors (27.1 vs 38.1, P = 0.000). The mean SGRQ total score was significantly higher in non-survivors than in survivors (53.8 vs 28.5, P = 0.000).

Discussion

ILDs include more than 200 subtypes with different prognoses, which not only significantly shorten the survival time but also impair quality of life in patients [4, 19, 37]. According to the present data, most aspects of HRQoL in patients with IIP and CTD-ILD, as measured by the SF-36 and SGRQ, were moderately to severely reduced, and impairment of HRQoL was even more pronounced in patients with CTD-ILD compared with patients with IIP. Physical aspects measured by the SF-36 PCS and SGRQ activity domains were the most impaired in all included patients. Meanwhile, the results of the comprehensive data analysis suggested that the cause of the decline in HRQoL in patients with ILDs was complex and multifactorial. Close associations between HRQoL and symptom severity and psychological deficits was found. In addition, other factors, including ILD subtypes (IIP and CTD-ILD), sex, BMI, disease duration and the DLco% predicted, had mild to moderate associations with HRQoL in these patients. In our study, the data further showed that changes in HRQoL were significantly associated with changes in pulmonary function and symptoms, including predicted FVC%, predicted DLco%, dyspnea and cough.

ILDs represent a heterogeneous group of conditions characterized by varying degrees of inflammation and pulmonary fibrosis. They may either appear as an idiopathic condition termed IIP or in association with CTD. The present study supported previous studies that showed IIP and CTD-ILD are clinically similar, with insidious onset of dyspnea as the main clinical manifestation [38, 39]. ILDs remain difficult to treat and are associated with reduced quality of life and mortality [40]. As shown in the present study, the quality of life decreased significantly in all patients, although impairment was more severe in patients with CTD-ILD than patients with IIP.

Similar to our finding that the mean SGRQ total score in IIP patients was 32.9 at baseline, a previous study conducted by Furukawa et al. [41] reported that the mean SGRQ total score in patients with IPF was 34.5. Michael et al. [42] reported that the mean SGRQ total score in 623 IPF patients (48.3) was significantly higher than our result, which indicated a worse quality of life. This could be partly explained by the differences in age, race, duration of disease and ILD subtypes in the cohorts. Patients with CTD-ILD often experience impaired HRQoL. In a previously published study, the quality of life of 193 patients with CTD-ILD was significantly decreased with a SGRQ total score of 36.3. In one study of 177 patients with SSc, the SGRQ total score for the SSc-ILD subgroup was 30.2, which is lower than the present result (43.3) [43]. A comparison of quality of life between IIP and CTD-ILD patients was not available before the present study, and further exploration is needed.

Dyspnea and cough are common symptoms in ILD patients, and previously published studies have indicated that cough, dyspnea and depression are potentially associated with HRQoL in ILD patients [4446]. In the study involving the Australian IPF Registry, Glaspole et al. [11] compiled and analyzed the data from 516 patients and found that dyspnea, cough and depression were three major contributors to HRQoL. Multivariate analysis of our study data corroborated previous results, finding that dyspnea, cough and depression were the major determinants. Furthermore, mild to moderate associations between HRQoL and other measures, including ILD subtypes, sex, BMI, disease duration and the DLco% predicted, were demonstrated in our study, unlike in earlier studies. To the best of our knowledge, ventilatory impairment suggested by poor pulmonary function in ILD may further impair quality of life [4]. However, there is no consensus on the relationship between HRQoL and pulmonary function. Based on multivariate analysis of HRQoL at baseline, a mild association was identified between HRQoL and the DLco% predicted in our study, which is inconsistent with the study result from the insights-IPF registry, which showed moderately strong associations between HRQoL and the FVC% predicted and DLco% predicted [42]. Similar to our results, the results from the INPULSIS trials demonstrated that HRQoL measured by the SGRQ was weakly associated with FVC% predicted at baseline [47].

Although earlier studies had demonstrated a decline in HRQoL in ILD patients and multifactorial interactions between HRQoL and clinical characteristics, few of them explored changes in HRQoL in ILD patients during long-term follow-up [47, 48]. In our cohort, longitudinal data on HRQoL assessed by the SF-36 and SGRQ revealed that HRQoL had weakly improved from baseline at both the 6-month follow-up and the 12-month follow-up in contrast to the results of a recently completed longitudinal study conducted by Rajala et al. [49]. The difference may be explained in part by the different subtypes, phases of diseases and pharmacotherapy. Despite the lack of an association between HRQoL and pulmonary function at baseline, our results demonstrated that changes in HRQoL measured by the SGRQ had a significant association with changes in pulmonary function, and the associations among SGRQ activity, impact, and total scores and FVC% predicted and DLco% predicted were statistically strong. Our result is consistent with the results from the INPULSIS trial and the insights-IPF registry [10, 43], both of which showed that the change in HRQoL assessed by the SGRQ total score was significantly associated with a decline in the FVC% predicted of >10%. In addition, the decline in HRQoL was significant in patients who experienced a decline in the FVC% predicted that was >5% in our analysis.

In our cohort, the study found that patients who died during follow-up had a worse HRQoL regardless of the subtype and phase of disease at baseline compared to patients who survived. There have been few studies on HRQoL and survival in patients with ILDs. A previous study including 182 IPF patients demonstrated that HRQoL assessed by the SGRQ total score and the FVC% predicted at baseline were independent prognostic predictors of mortality (HR, 1.012; P = 0.029) [44]. In the Finnish IPF study, 37% of the 247 included patients died during follow-up, and in those patients, HRQoL as measured by the RAND-36 deteriorated significantly in all dimensions except physical role [49].

There were several notable limitations in our study that need to be addressed. First, our study did not include the 6-minute walking distance (6MWD) and the NYHA functional status, which are the tools used to assess functional exercise capacity. Previous studies have demonstrated that both missing indicators are clinically meaningful predictors of HRQoL in patients with ILDs. The absence of these indicators may affect our analysis to some extent. Second, some patients did not complete each of the HRQoL questionnaires during follow-up. Additionally, pulmonary function data were incomplete during follow-up. All of these factors may lead to skewing of the analysis. Third, the patient-reported outcome measures (PROs) used in this study (the mMRC, LCQ, HADS, SGRQ and SF-36) were not originally developed for IPF and ILDs, and the minimal clinically significant differences of the PROs are currently unknown, suggesting that further studies are needed to confirm the validity of the PROs in IPF and ILDs. Fourth, the lack of therapeutic factors during the follow-up in our study may be responsible for the improved quality of life in some patients at the follow-up visits. Finally, although the finding that the decline in HRQoL was significantly associated with clinical symptoms, depression and changes in pulmonary function, further study regarding whether management of these determinants could improve HRQoL was not performed.

Conclusions

In conclusion, our findings show that HRQoL in patients with IIP and CTD-ILD deteriorates at various rates, and the decline of patients with CTD-ILD was more significant. Moreover, our findings demonstrate that the determinants of the decline in HRQoL are multifactorial; the major determinants are dyspnea, cough and depression. Furthermore, changes in HRQoL are significantly associated with changes in pulmonary function. Improving HRQoL is the main aim when treating patients living with ILDs.

Supporting information

S1 Table. IIP and CTD-ILD subgroups.

(DOCX)

S2 Table. Associations between changes in HRQoL and clinical characteristics.

(DOCX)

S3 Table. Comparison of the main demographics, clinical characteristics and HRQoL according to the prognosis.

(DOCX)

Acknowledgments

We are thankful for the efforts of all the participants and physicians who contributed to this study, as well as the patients who participated in this study.

Data Availability

All relevant data are within the manuscript.

Funding Statement

This study was supported from Scientific Research Cultivation Project of Beijing Municipal Hospital, Beijing Municipal Administration of Hospitals (No. PX201741) and the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Paola Faverio

2 Mar 2020

PONE-D-20-00941

Evaluation of health-related quality of life and the related factors in a group of Chinese patients with interstitial lung diseases

PLOS ONE

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In particular, the heterogeneity of the population analysed. Given the high number of diagnoses, with different clinical characteristics and prognosis, that can be included in the family of interstitial lung diseases, I suggest to restrict the study to the main diagnoses. Furthermore, the statistical analysis need a complete revision by an expert statistician.

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: General comments

1. The researchers have collected an impressive amount of data, but the study lacks both structure and focus. The analytical approach is questionable and there are methodological limitations, in particular with respect to the study population. The manuscript contains large amounts of information, but adds little new knowledge. It is not easily accessible to the reader.

2. My main concern is the heterogeneous patient population. The material comprises a mix of diagnoses including idiopathic interstitial pneumonias (IIP), hypersensitivity pneumonitis (HP), CTD-ILD and sarcoidosis - all well-defined diseases with disease-specific clinical characteristics and disease-specific prognosis. To analyze such a variety of diseases under the same ILD-umbrella is not meaningful.

3. The study lacks an appropriate purpose. The aim is to “investigate HRQL in patients with ILD and identify factors influencing HRQL among these patients”. To what end? What do the researchers want to find out? What is the hypothesis? ILD is a common denominator for various diseases with different courses, different responses to therapy and different prognosis. To assess HRQL in a mixed ILD-population is not useful. I would advise the research group to focus on disease-specific HRQL. Based on the number of patients in the various disease-groups, it may be an idea to confine the study to the two largest groups - IIP (69.5%) and CTD-ILD (15%) - and compare HRQL in those two diseases.

4. The study lacks generalizability. The results of the study may be relevant to the Chinese medical community, but they cannot be generalized to other parts of the world. The study was carried out in 2017/18. At that time, anti-fibrotic treatment was commonly prescribed to patients with IPF in North-America, Europe, Australia and Japan. In the present study, only 5 patients received such drugs (table 1) while “other drugs” were used by 74% – presumably drugs that are not generally prescribed outside of China. Since drugs will affect symptoms, course of disease, side-effects and prognosis, they will also invariably affect measures of HRQL. This adds to the difficulties in interpreting and generalizing the results of the study.

Specific comments

Introduction.

Lines 53-64, 65-67 and 67-68. Three statements that all need references.

Methods.

1. The prospective cohort was followed up though “face-to-face or telephone interviews”. How could “physiological indicators” (like PFTs) be registered by telephone? What was the procedure for follow-up with respect to the questionnaires? (lines 84-87)

2. ILDs have insidious onset. How was “date of ILD-diagnosis” defined? (line 96)

3. Equipment, guidelines and ref.values for PFTs should be specified. (lines 98-100)

4. Were the two radiologists blinded to clinical information? (line 101)

5. The minimum clinically important differences in scores should be given for each of the questionnaires.

Statistics

1. Predictors cannot be identified in a cross-sectional study (lines 152-154)

2. The model seems overloaded (table 3)

3. Multiple correlations are probably not the method of choice for analyzing between-group changes in the prospective study (lines 157-160).

4. An expert statistician should be consulted with respect to analytical approach.

Results

1. In general, I suggest dropping the use of two decimal places (text and tables). It indicates a precision level that is not real. Example: duration of symptoms 19.89 +27.34 months (line 168 + tab1).

2. Tab 2. All variables have large SDs, simply reflecting the fact that wide ranges will always be found in very heterogeneous study populations. To what end is such information useful?

3. In the longitudinal study, relatively large proportions of patients had improvements in both symptoms (dyspnea, cough) and PFTs, and also in HRQ scores. Patients with ILD tend to deteriorate or remain stable over time, not improve. Presumably the unexpected findings reflect that in a mixed study population - including patients with a broad variety of diagnoses/diseases - some will respond to therapy/drugs while others will not. (lines 246-257).

Reviewer #2: The original research article by Yuan and co-authors assessed longitudinally the quality of life of 200 ILD patients at baseline, and at 6- and 12-month follow up correlating the changes in HRQoL with the changes in pulmonary function tests. The authors found that HRQoL deteriorates during the follow up of ILD patients and seems to be associated with determinants such as dyspnea, cough, and depression.

Overall the manuscript is well written and comprehensive; therefore I suggest only minor revisions.

1. Abstract – Introduction – Lines 16-18. The sentence “There are limited therapeutic options and strong side effects, which eventually lead to respiratory failure and affect the quality of life of patients” seems to suggest that the treatment-related side effects cause respiratory failure.

2. Abstract – Results – Line 27. Correct “The mean age was 60.7 years old, …” with “The mean age was 60.7 years, …”.

3. Introduction – Lines 65-68. I suggest quoting the few available studies dealing with HRQoL in ILD patients.

4. Results – Line 164. I suggest using the same number of decimals for the median age and its standard deviation, as it has been done in the whole manuscript for continuous variables.

5. Results – Table 1. Correct “Ethmic group” with “Ethnic group”.

6. Results – Lines 251-252. Does the sentence “Similarly, 42.4% of patients’ FVC% predicted and 48.8% of patients’ DLco% predict were improved or stable” refer to the 12-month follow up? If so, it should be specified in the text.

7. Results – Lines 263-264. “The associations between longitudinal changes 263 in HRQoL and clinical characteristics is shown in Table 4”. I suggest indicating in the text which clinical characteristics were tested in this analysis.

8. Results – Line 284. Change “the emergence of the first symptom” with “the onset of the first symptom”.

9. Discussion. This paper is an example of the raising interest in the patient-reported outcome measures (PROs) in IPF and ILDs in general. However, the minimal clinically significant difference of the PROs used in this paper (mMRC, LCQ, HADS, SGRQ and SF-36 questionnaire) is currently unknown. This should be mentioned among the limitations of this paper.

**********

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

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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PLoS One. 2020 Jul 29;15(7):e0236346. doi: 10.1371/journal.pone.0236346.r002

Author response to Decision Letter 0


10 Apr 2020

Dear Prof. Paola Faverio,

Thank you for your kind letter. We revised the manuscript in accordance with your and the reviewers’ comments and advices, and carefully proof-read the manuscript to correct spelling, expression and statistical analytical approach errors. Here below is our description on revision according to your and the reviewers’ comments and advices.

Thank you for your submission to PLOS ONE. Both the reviewers highlighted the originality of the data and the importance of the topic. However some fundamental methodological pitfalls need to be addressed.

In particular, the heterogeneity of the population analysed. Given the high number of diagnoses, with different clinical characteristics and prognosis, that can be included in the family of interstitial lung diseases, I suggest to restrict the study to the main diagnoses. Furthermore, the statistical analysis need a complete revision by an expert statistician.

We appreciate all the comments and suggestions from the editors and reviewers, these will be great of help to improve our present work. We appreciate the suggestion and totally agreed with your opinion about the heterogeneity of the population. We restrict the population in our study to idiopathic interstitial pneumonias (IIP) and CTD-ILD, and then we reanalyzed the data. We also appreciate your reminding about the statistical analysis. We specifically consulted the expert statistician and improved the defects in our study.

Reviewer #1:

General comments

1. The researchers have collected an impressive amount of data, but the study lacks both structure and focus. The analytical approach is questionable and there are methodological limitations, in particular with respect to the study population. The manuscript contains large amounts of information, but adds little new knowledge. It is not easily accessible to the reader.

Response: Thank you for the comments. We agreed with the reviewer’s opinion on the defects in data processing and statistical analysis. The data of the study were from patients with ILDs in china, and there is a large space for study on the quality of life in these patients in china. In present study, We adjusted the study population to focus on patients with IIP and CTD-ILD, and we revised the writing of the manuscript to make it easier for the reader to access the important information (Line 236-243, Line 282-294, Line 444-452, Table 1, Table 2 ).

2. My main concern is the heterogeneous patient population. The material comprises a mix of diagnoses including idiopathic interstitial pneumonias (IIP), hypersensitivity pneumonitis (HP), CTD-ILD and sarcoidosis - all well-defined diseases with disease-specific clinical characteristics and disease-specific prognosis. To analyze such a variety of diseases under the same ILD-umbrella is not meaningful.

Response: Thank you for the comments. At first, we look forward to exploring a universal predictive model for ILDs, so we collected all patients clinically diagnosed with ILDs and followed them up for 12 months. Since ILD belongs to a group of diseases and the heterogeneity is very significant, it is obviously inappropriate. We think your views on the heterogeneous patient population are very reasonable and Based on your suggestion, we have eliminated HP, sarcoidosis and other types of ILD, and re-analyzed the data (Line 236-521, Table 1, Table 2, Figure 1, Figure 3 ).

3. The study lacks an appropriate purpose. The aim is to “investigate HRQL in patients with ILD and identify factors influencing HRQL among these patients”. To what end? What do the researchers want to find out? What is the hypothesis? ILD is a common denominator for various diseases with different courses, different responses to therapy and different prognosis. To assess HRQL in a mixed ILD-population is not useful. I would advise the research group to focus on disease-specific HRQL. Based on the number of patients in the various disease-groups, it may be an idea to confine the study to the two largest groups - IIP (69.5%) and CTD-ILD (15%) - and compare HRQL in those two diseases.

Response: Thanks for your comments and suggestions on our study. We agreed with the opinion on the aim of the study, and we focused on IIP and CTD-ILD according to your suggestion. We re-analyzed sociodemographic, disease-related characteristics in both ILD subtypes and compared HRQL in them.

4. The study lacks generalizability. The results of the study may be relevant to the Chinese medical community, but they cannot be generalized to other parts of the world. The study was carried out in 2017/18. At that time, anti-fibrotic treatment was commonly prescribed to patients with IPF in North-America, Europe, Australia and Japan. In the present study, only 5 patients received such drugs (table 1) while “other drugs” were used by 74% – presumably drugs that are not generally prescribed outside of China. Since drugs will affect symptoms, course of disease, side-effects and prognosis, they will also invariably affect measures of HRQL. This adds to the difficulties in interpreting and generalizing the results of the study.

Response: We appreciate your comment on the generalizability of the research. We are sorry that our way of expression may has interfered with you. In our study, “others” included “no intervention”, “antioxidants” and “traditional Chinese medicine”, which “no intervention” was used in 113 patients (56.2%). We refined the presentation of data to separate “no intervention” from “others” (table 1). Meanwhile, anti-fibrotic treatment is not commonly prescribed to patients with IPF due to the price problem, and anti-fibrotic treatment is only applicable to patients with IPF, not all patients with ILDs. Theses factors finally leads to the low application of anti-fibrotic treatment in present study. We agreed with your opinion that drugs may be the confounding factor affecting HRQL in ILDs. In present study, we focused on the impact of disease severity on quality of life. Although drugs may have an impact on quality of life, it is mainly a change in the severity of the diseases after treatment. We analyzed the effect of drugs factor on HRQL with ILD by linear regression analysis (table 3), but we are sorry that the statistical analysis cannot fully explain the real-world problems.

Specific comments

Introduction.

Lines 53-64, 65-67 and 67-68. Three statements that all need references.

Response: We appreciate for your advice, several publications have been added in corresponding statements of the article (Line 67-68, Curr Opin Pulm Med. 2013; 19: 474–479, Sarcoidosis Vasc Diffuse Lung Dis. 2016; 33: 341–348, Respirology. 2014; 19: 1019–1924; Line 69-72, Am J Respir Crit Care Med. 2007; 176: 636–643; Line 74-75, Respir Res. 2019; 20: 59–72, Respirology. 2017; 22: 950–956, Respir Res. 2020; 21: 36–47; Line 79-80, Respirology. 2014; 19: 1019–1924, Respiration. 2007; 74: 401–405; Line 81-84, Respir Med. 2017; 127: 1–6, Respirology. 2018, Chest. 2014; 145: 1333–1338, J Bras Pneumol. 2010; 36: 562–570).

Methods.

1. The prospective cohort was followed up though “face-to-face or telephone interviews”. How could “physiological indicators” (like PFTs) be registered by telephone? What was the procedure for follow-up with respect to the questionnaires? (lines 84-87)

Response: Thank you for your comments, it is indeed our unclear expression in previous manuscript. During the follow-up, some patients did not complete the questionnaires for personal reasons after pulmonary function test in our hospital. We registered the questionnaires by telephone within one week after the completion of the pulmonary function test. We corrected the inaccurate expression (Line 103-107).

2. ILDs have insidious onset. How was “date of ILD-diagnosis” defined? (line 96)

Response: Thank you for the remind. “Date of ILD-diagnosis” was defined as the time from symptom onset to the diagnosis of ILD in our hospital. We are sorry for the ambiguous expression and modified “Date of ILD-diagnosis” to “disease duration” (Line 116).

3. Equipment, guidelines and ref.values for PFTs should be specified. (lines 98-100)

Response: Thank you for your advice, we added relevant information in the manuscript (Line 123-128).

4. Were the two radiologists blinded to clinical information? (line 101)

Response: Yes, we are sorry for our negligence of this information and added it into the manuscript (Line 129-131).

5. The minimum clinically important differences in scores should be given for each of the questionnaires.

Response: Thank you for the remind, the minimum clinically important differences of PROs using in our manuscript is currently unknow. We mentioned this fact among the limitations of this paper (Line 778-786).

Statistics

1. Predictors cannot be identified in a cross-sectional study (lines 152-154)

Response: Thank you for the remind, we modified the presentation of this part (Line 195-196).

2. The model seems overloaded (table 3)

Response: We appreciate for your advice, and we simplified the model and described the results of univariate and multivariate linear regression analysis separately (table 3, table 4).

3. Multiple correlations are probably not the method of choice for analyzing between-group changes in the prospective study (lines 157-160).

Response: Thank you for the remind, we changed the statistical method from multiple correlations to linear regression analysis and we further assessed HRQoL using one-way analysis of variance (ANOVA) followed by pairwise comparisons according to the Least-Significant-Difference method (Line 213-218).

4. An expert statistician should be consulted with respect to analytical approach.

Response: Thank you for your advice, we consulted the expert statistician and corrected the deficiencies (Line 191-195, Line 213-218). In addition, we re-analyzed the data (Table 1, Table 2, Table 5, S1 Table).

Results

1. In general, I suggest dropping the use of two decimal places (text and tables). It indicates a precision level that is not real. Example: duration of symptoms 19.89 +27.34 months (line 168 + tab1).

Response: Thank you for your suggestion, we totally agreed that two decimal places indicates a precision level that is not real. We changed the use of two decimal places to one decimal place in all text and tables.

2. Tab 2. All variables have large SDs, simply reflecting the fact that wide ranges will always be found in very heterogeneous study populations. To what end is such information useful?

Response: We agreed that variables that have large SDs reflect the very heterogeneous populations in our study. So, we limited the study population to IIP and CTD-ILD patients and re-analyzed the data. The results for the two group was added.

3. In the longitudinal study, relatively large proportions of patients had improvements in both symptoms (dyspnea, cough) and PFTs, and also in HRQ scores. Patients with ILD tend to deteriorate or remain stable over time, not improve. Presumably the unexpected findings reflect that in a mixed study population - including patients with a broad variety of diagnoses/diseases - some will respond to therapy/drugs while others will not. (lines 246-257).

Response: Thank you for your comments. We agreed that the heterogeneous study populations in our study led to the unexpected findings, so we excluded Sarcoidosis, HP and other ILD subtypes in our analysis. After reanalyzing the data, we found that symptoms including dyspnea and cough deteriorated or remained stable or in most patients at follow-up (S1 table). At 6-month and 12-month follow-up, patients with IIP had a stable quality of life compared with baseline in HRQoL measured by SF-36 PCS, SGRQ total domains. However, the HRQOL in patients with CTD-ILD had a valuable improvement at 6-month and 12-month follow-up. The reason for the fact is likely to be the therapy or drugs. We are sorry for our negligence in this factor at follow-up and we explained this in the discussion (Line 792-793).

Reviewer #2:

The original research article by Yuan and co-authors assessed longitudinally the quality of life of 200 ILD patients at baseline, and at 6- and 12-month follow up correlating the changes in HRQoL with the changes in pulmonary function tests. The authors found that HRQoL deteriorates during the follow up of ILD patients and seems to be associated with determinants such as dyspnea, cough, and depression.

Overall the manuscript is well written and comprehensive; therefore I suggest only minor revisions.

1. Abstract – Introduction – Lines 16-18. The sentence “There are limited therapeutic options and strong side effects, which eventually lead to respiratory failure and affect the quality of life of patients” seems to suggest that the treatment-related side effects cause respiratory failure.

Response: Thank you for the remind, it is indeed our mistake in the expression. The sentence (Line 16-19) was modified.

2. Abstract – Results – Line 27. Correct “The mean age was 60.7 years old, …” with “The mean age was 60.7 years, …”.

Response: Thank you for pointing out the error, we have corrected it.

3. Introduction – Lines 65-68. I suggest quoting the few available studies dealing with HRQoL in ILD patients.

Response: Thank you for your advice, several available studies have been added in corresponding statements of the manuscript (Line 81-84, Respir Med. 2017; 127: 1–6, Respirology. 2018. https://doi.org/10.1111/ resp. 13293, Chest. 2014; 145: 1333–1338, J Bras Pneumol. 2010; 36: 562–570)

4. Results – Line 164. I suggest using the same number of decimals for the median age and its standard deviation, as it has been done in the whole manuscript for continuous variables.

Response: Thank you for your advice, we have unified all the median±SD to one number of decimals in the whole manuscript.

5. Results – Table 1. Correct “Ethmic group” with “Ethnic group”.

Response: Thank you for pointing out the error, we have corrected it.

6. Results – Lines 251-252. Does the sentence “Similarly, 42.4% of patients’ FVC% predicted and 48.8% of patients’ DLco% predict were improved or stable” refer to the 12-month follow up? If so, it should be specified in the text.

Response: Yes, thank you for your suggestion. We have made additional explanations in the text (Line 427-429).

7. Results – Lines 263-264. “The associations between longitudinal changes in HRQoL and clinical characteristics is shown in Table 4”. I suggest indicating in the text which clinical characteristics were tested in this analysis.

Response: We appreciate for your advice, and specific clinical characteristics including FVC% predicted, DLco% predicted, mMRC and LCQ total score have been described in the manuscript (Line 498-500).

8. Results – Line 284. Change “the emergence of the first symptom” with “the onset of the first symptom”.

Response: Thank you for your advice, we have corrected it.

9. Discussion. This paper is an example of the raising interest in the patient-reported outcome measures (PROs) in IPF and ILDs in general. However, the minimal clinically significant difference of the PROs used in this paper (mMRC, LCQ, HADS, SGRQ and SF-36 questionnaire) is currently unknown. This should be mentioned among the limitations of this paper.

Response: Thank you for your advice, we have elaborated this limitation in the discussion of the manuscript (Line 778-786).

We acknowledge the editors’ and reviewers’ comments and suggestions very much, which are

valuable in improving the quality of our manuscript. Thank you again for the guidance and

help.

Sincerely yours,

Xue-Yan Yuan, Ai Cui

2020-04-07

Attachment

Submitted filename: Response to Reviewers.docx

Decision Letter 1

Paola Faverio

27 May 2020

PONE-D-20-00941R1

Evaluation of health-related quality of life and the related factors in a group of Chinese patients with interstitial lung diseases

PLOS ONE

Dear Dr. Ai Cui,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The quality of the research article have much improved after the revisions made.

I agree with the minor revisions proposed by Reviewer 3.

I also suggest the authors to have the abstract of the manuscript, particularly the sentences changed during the review, rechecked by an English translator.

Please submit your revised manuscript by June 20th, 2020. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Paola Faverio

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Partly

**********

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

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #2: (No Response)

Reviewer #3: Xue-yan Yuan and collaborators wrote a research article trying to clarify the role of health-related quality of life factors in a cohort of Chinese patients affected by ILD.

This topic has been widely discussed in literature, however it is still a subject of interest. 

Some minor revisions need to be made.

Methods

Line 80. In this section I suggest you to add which ILDs you include in your cohort (lately in the section Results you state you have considered only ILD patients with a diagnosis of CTD-ILD or IIP).

Results

Line 180 since idiopathic interstitial pneumonias include different entities as well as CTD-ILD (Am J Respir Crit Care Med. 2013 Sep 15;188(6):733-48) I suggest you to specify the composition of your cohort. This could help better understand your results since in both groups are included entities with different evolution and prognosis. Moreover it could help understanding why antifibrotic drug were administered in only 2.9% of the IPP group (were IPF patients the minority of this group?)

Line 238. “ILD subtype (IIP vs CTD-ILD) was associated with most dimensions of the SGRQ and the SF-36 PCS” I suggest you to deepen this statement. Are there significant differences in the results of this questionnaires in IPP patients compared to CTD-ILD?

In section Results the comparison between IPP and CTD-ILD is clear only in the first and second paragraphs (patient characteristics and HRQoL) while in the other paragraphs (factors influencing HRQoL assessed at the time of enrollment; relationship between the change in HRQoL and changes 274 in clinical characteristics and clinical characteristics and HRQoL of patients who died during follow-up) the comparison is absent. In these last paragraphs you consider “ILD subtypes” as a factor influencing or not HRQoL while I think it could be of interest analyze not only the whole cohort but also if there are differences between the two groups in terms of HRQoL.

Moreover, a better focus on differences between the two groups should be highlighted in the section Discussion and in the section Conclusion.

**********

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

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: Yes: Anna Stainer

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Jul 29;15(7):e0236346. doi: 10.1371/journal.pone.0236346.r004

Author response to Decision Letter 1


14 Jun 2020

Dear Prof. Paola Faverio,

Thank you for your kind letter. We have revised our manuscript after reading the comments and suggestions provided by you and the reviewers. The following is what we have modified in response to your and the reviewers’ comments and advice.

I agree with the minor revisions proposed by Reviewer 3.

I also suggest the authors to have the abstract of the manuscript, particularly the sentences changed during the review, rechecked by an English translator.

We appreciate all your and the reviewers’ comments and advice. According to your suggestion, we employed an English-language editing service, Academic English Editors (AJE) to polish our wording of the changed sentences and abstract, and the revised parts were marked in the red in the “Revised Manuscript with Track Changes”. We also elaborated on the diagnosis of the included patients in this study.

Responds to the reviewer’s comments:

Reviewer #3:

Xue-yan Yuan and collaborators wrote a research article trying to clarify the role of health-related quality of life factors in a cohort of Chinese patients affected by ILD.

This topic has been widely discussed in literature, however it is still a subject of interest.

Some minor revisions need to be made.

Methods

1. Line 80. In this section I suggest you to add which ILDs you include in your cohort (lately in the section Results you state you have considered only ILD patients with a diagnosis of CTD-ILD or IIP).

Response: Thank you for the comment and suggestion. The specific ILDs subtypes have been described in the manuscript (Line 84, Line 89, and Line 91: “Patients aged ≤85 years who were diagnosed with ILDs including IIP and CTD-ILD at the Department of Respiratory and Critical Medicine of Capital Medical University”, “The diagnosis of IIP or CTD-ILD”).

Results

1. Line 180 since idiopathic interstitial pneumonias include different entities as well as CTD-ILD (Am J Respir Crit Care Med. 2013 Sep 15;188(6):733-48) I suggest you to specify the composition of your cohort. This could help better understand your results since in both groups are included entities with different evolution and prognosis. Moreover it could help understanding why antifibrotic drug were administered in only 2.9% of the IPP group (were IPF patients the minority of this group?)

Response: Thank you for the remind. According to your suggestion, we have revised our manuscript and the specific composition of our included patients has been increased in the manuscript (Line 200-204: “139 were diagnosed with IIP (101 idiopathic non-specific interstitial pneumonia (NSIP) cases, 18 unclassifiable IIP cases, 11 respiratory-bronchiolitis-ILD cases, 7 IPF cases, and 2 others), and 30 were diagnosed with CTD-ILD (12 Sjögren’s syndrome (SS) cases, 6 undifferentiated CTD cases, 4 polymyositis/dermatomyositis (PM/DM) cases, 3 scleroderma (SSc) cases, 2 rheumatoid arthritis (RA) cases, and 3 others) (S1 Table)”).

2. Line 238. “ILD subtype (IIP vs CTD-ILD) was associated with most dimensions of the SGRQ and the SF-36 PCS” I suggest you to deepen this statement. Are there significant differences in the results of this questionnaires in IIP patients compared to CTD-ILD?

Response: Yes, patients with IIP had significantly better quality of life than patients with CTD-ILD in terms of SF-36 PCS, SGRQ activity, SGRQ impact, and SGRQ total domains in our study which were showed in Table 2. We appreciate your suggestion, and we have further elaborated the relevant information in the manuscript (Line 262-267: “As shown in Table 3, HRQoL was found to be significantly affected by multiple factors. ILD subtype was negatively associated with the SF-36 PCS and positively associated with most dimensions of the SGRQ in the univariate liner regression analyses. As previously mentioned, patients with CTD-ILD had a lower quality of life as measured by the SF-36 PCS and SGRQ activity, impact, and total domains when compared with patients with IIP”).

3. In section Results the comparison between IIP and CTD-ILD is clear only in the first and second paragraphs (patient characteristics and HRQoL) while in the other paragraphs (factors influencing HRQoL assessed at the time of enrollment; relationship between the change in HRQoL and changes in clinical characteristics and clinical characteristics and HRQoL of patients who died during follow-up) the comparison is absent. In these last paragraphs you consider “ILD subtypes” as a factor influencing or not HRQoL while I think it could be of interest analyze not only the whole cohort but also if there are differences between the two groups in terms of HRQoL.

Response: Thanks for your comments and suggestions. In this study, we mainly focused on the quality of life of all patients with ILDs and their influencing factors. Meanwhile, ILD subtypes were weakly associated with SF-36 PCS. So, we did not analyze the influencing factors in HRQoL of IIP and CTD-ILD patients, respectively. We compared the quality of life of IIP and CTD-ILD patients, and found HRQoL of patients with IIP was better than that of patients with CTD-ILD.

4. Moreover, a better focus on differences between the two groups should be highlighted in the section Discussion and in the section Conclusion.

Response: We appreciate for your advice and agree with the opinion. We had an in-depth discussion of the differences between the two groups. (Line 376-378, Line 402-409, Line 415, Line 419-424, Line 504-506)

Finally, we acknowledge the editor’ and reviewers’ comments and suggestions very much, which are valuable in improving the quality of our manuscript. Thank you again for the guidance and help.

Sincerely yours,

Xue-Yan Yuan, Ai Cui

2020-06-14

Attachment

Submitted filename: Response to Reviewers.docx

Decision Letter 2

Paola Faverio

7 Jul 2020

Evaluation of health-related quality of life and the related factors in a group of Chinese patients with interstitial lung diseases

PONE-D-20-00941R2

Dear Dr. Ai Cui,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Paola Faverio

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The issues reasonably raised by the reviewers have been addressed.

Reviewers' comments:

Reviewer's Responses to Questions

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Reviewer #3: All comments have been addressed

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Reviewer #3: Yes

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Reviewer #3: Yes

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Reviewer #3: Xue-yan Yuan and collaborators wrote a research article trying to clarify the role of

health-related quality of life factors in a cohort of Chinese patients affected by ILD.

This topic has been widely discussed in literature, however it is still a subject of

interest.

All requested corrections were made by the Authors. No further revisions are required

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Reviewer #3: Yes: Anna Stainer

Acceptance letter

Paola Faverio

17 Jul 2020

PONE-D-20-00941R2

Evaluation of health-related quality of life and the related factors in a group of Chinese patients with interstitial lung diseases

Dear Dr. Cui:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Associated Data

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

    Supplementary Materials

    S1 Table. IIP and CTD-ILD subgroups.

    (DOCX)

    S2 Table. Associations between changes in HRQoL and clinical characteristics.

    (DOCX)

    S3 Table. Comparison of the main demographics, clinical characteristics and HRQoL according to the prognosis.

    (DOCX)

    Attachment

    Submitted filename: Response to Reviewers.docx

    Attachment

    Submitted filename: Response to Reviewers.docx

    Data Availability Statement

    All relevant data are within the manuscript.


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