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Investigation of clinical predictors of survival in idiopathic pulmonary fibrosis patients: A cohort study in Taiwan

Tseng, Ching-Mina,b; Chen, Mei-Yinc; Kao, Chen-Yud; Tao, Chi-Weid,*

Author Information
Journal of the Chinese Medical Association: May 2022 - Volume 85 - Issue 5 - p 578-583
doi: 10.1097/JCMA.0000000000000719
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Abstract

1. INTRODUCTION

Idiopathic pulmonary fibrosis (IPF) is a life-threatening, chronic fibrotic interstitial lung disease characterized by the progressive deterioration of lung function.1,2 The most common cause of death from IPF is respiratory failure, accounting for a substantial majority of IPF-related fatalities, although other causes of death from IPF, including infection, heart failure, ischemic heart disease, and pulmonary embolism, have also been identified.3 The prognosis of IPF is typically quite poor, with a lower median duration of survival among patients not treated with antifibrotic medications.4

Two antifibrotic medications, pirfenidone and nintedanib, have been approved as treatments for IPF in many countries over the past decade following various clinical trials successfully demonstrating their effectiveness in decreasing the loss of lung function experienced by patients with IPF.5–8 For example, in the A Study of Cardiovascular Events in Diabetes (ASCEND) and INPULSIS trials, where patients were treated for a total duration of 52 weeks, pirfenidone and nintedanib decreased the forced vital capacity (FVC) declined in by roughly 50%.7,8 In the Remote COVID-19 Assessment in Primary Care study, which was a follow-up for the ASCEND trial, It was reported that the median duration of survival for patients on pirfenidone was 6.4 years.9 Another two survival studies reported that pirfenidone achieved a mean life expectancy of 8.72 (7.65-10.15) years vs 6.24 (5.38-7.18) years with best supportive care, and nintedanib achieved a mean life expectancy of 11.6 (9.6-14.1) compared to 3.7 (2.5-5.4) years in placebo-treated patients.10,11

Relatedly, several past studies have sought to identify clinical predictors of survival for IPF. For example, numerous studies have found that a loss of FVC is both indicative of disease progression and predictive of decreased survival time.12–15 Among those studies, a 2003 study by Collard et al13 further found that 6-month changes in oxygen saturation, total lung capacity, dyspnea score, thoracic gas volume, 1-second forced expiratory volume (FEV1), partial pressure of arterial oxygen, diffusing capacity of carbon monoxide (DLCO), and alveolar-arterial oxygen gradient were also predictive of survival duration, with 12-month changes in oxygen saturation, total lung capacity, dyspnea score, partial pressure of arterial oxygen, and alveolar-arterial oxygen gradient likewise being predictive. A more recent study published by du Bois et al16 in 2011 undertook a similar analysis to identify independent predictors of 1-year mortality among patients with IPF and identified age, percent predicted FVC (%FVC), percent predicted DLCO (%DLCO), respiratory hospitalization, 24-week change in FVC, 24-week change in health-related quality of life, and 24-week change in %DLCO as such predictors.

Nevertheless, while those earlier studies were certainly of considerable value, the increasingly widespread use of nintedanib and pirfenidone in the intervening years, as well as the significantly longer survival duration of patients treated with those agents vs those not treated with either antifibrotic medication, has raised questions regarding how patients’ survival can be best predicted in the era of antifibrotics. Therefore, this study was conducted to provide updated data regarding the clinical predictors of mortality in patients with IPF by investigating a cohort of patients including both patients receiving antifibrotic treatments and patients not receiving such treatments.

2. METHODS

2.1. Study population

This retrospective observational study included all patients with IPF admitted at a general hospital in Taiwan between April 2017 and September 2019. The follow-up period extended to May 2020 or till the patient’s death, which is closer. Patients were diagnosed and treated per the 2011 version of the ATS/ERS/JRS/ALAT guidelines2 before September 2018, while patients seen after September 2018 were diagnosed and treated per the 2018 update to the ATS/ERS guidelines.17 All the patients’ diagnoses and treatment options were determined through multidisciplinary discussions, including a pulmonologist, a radiologist, and a rheumatologist. diagnosis through imaging met at least a definite or a probable usual interstitial pneumonia-IPF. If otherwise, a biopsy was performed.

2.2. Predictors of mortality

Potential predictors of mortality were evaluated throughout the full study period from April 2017 to May 2020 based on the deaths that occurred among the study population during that period. More specifically, the medical records of the included patients regarding the potential predictors of mortality were pooled together in a single database to determine the relationship, if any, between a given potential predictor and subsequent death, with any of the study population patients who died within the study period being flagged accordingly.

The patient and clinical characteristics regarded as possible predictors of mortality were identified beforehand based on clinical rationale and biologic plausibility. More specifically, the characteristics evaluated as possible predictors of mortality were patient age, sex, smoking status, bronchiectasis status, coronary artery disease status, chronic obstructive pulmonary disease status, diabetes mellitus status, gastroesophageal reflux disease status, hypertension status, nausea, abnormal liver function, diarrhea, itchy skin, exhaustion, headache, acute exacerbation after medication, use of antidiarrheal drugs, FVC at baseline (baseline FVC), C-reactive protein level, %FVC, and %DLCO.

2.3. Statistical analyses

The patient data were analyzed using SPSS Statistics, version 25.0, and Jamovi, version 2.2.2. Continuous data were presented as means ± SDs, and categorical data were presented as numbers (%). Categorical data that were not normally distributed were presented as medians and interquartile ranges. Student’s t test and the Mann-Whitney U test were used for comparisons of the continuous data, while the Chi-square test was used for comparisons of the categorical data. Two-tailed p value <0.05 was considered significant.

A multivariate Cox proportional hazards model was built to identify predictors of all-cause mortality. For approaching such a model, independent variables with p values <0.1 in univariate analyses were included in the model. This model was approached for all patients with IPF and for the subgroup of patients who received antifibrotic medications.

A mortality risk scoring system was built using the methodology adopted by du Bios et al.16 β-coefficients from the final Cox model were converted to scores by multiplying each by 10. the baseline hazard function from the Cox model was then used to convert the total risk score to a 1-year probability of death using the following formula:

p(death) = 1 – 0.95 × experimental density(0.1 × total risk score), where 0.95 is the estimated 1-year probability of survival and thus 1 – 0.95 is the estimated 1-year probability of death for people with the lowest risk (ie, those with a total risk score equal to 0).

3. RESULTS

3.1. Patient characteristics

A total of 40 patients with IPF were treated during the study period. Their average age was 75.6 ± 8.3 years, and most of the patients (77.5%) were male. Nineteen (47.5%) of the patients were smokers. Twenty-seven (67.5%) of the patients were treated with antifibrotic drugs. In the entire cohort, 14 (35%) patients died, and the overall survival of the study population was 48.52 ± 5 months (median, not applicable (NA) [29-NA] months). The mean %FVC of the patients was 67.85 ± 14.09%, the mean percentage FEV1 (%FEV1) was 79 ± 17.2%, and the mean %DLCO was 38.4 ± 13.8%. The most common comorbidity was hypertension, affecting 57.5% of the patients. Thirty (75%) of the patients had a left ventricular ejection fraction >55%, and 15 (37.5%) of the patients had coronary artery disease. COPD affected 9 (22.5%) patients. Twenty-seven (67.5%) of the patients were treated with antifibrotic drugs and 13 (32.5%) were not. Of those 13 patients, 4 (30.77%) patients developed GIT adverse events (nausea and diarrhea) and could not tolerate antifibrotic medication, while 9 (69.23%) patients did not receive antifibrotic medication due to financial issues. Twenty-eight (70%) patients were treated with bronchodilators. The most common side effect of medication was diarrhea (52.5%), followed by nausea (12.5%), exhaustion (7.5%), itchy skin (2.5%), and headache (2.5%). Acute exacerbation after medication occurred in 15 (37.5%) patients. Fourteen (35%) of the patients died, and their median time from diagnosis to death was 34 months (Table 1).

Table 1 - Patients’ baseline, clinical, pulmonary, and treatment characteristics
Characteristics All patients with IPF (n = 40)
Age, y 75.6 ± 8.3
Sex: male 31 (77.5%)
BMI 25.2 ± 3.3
Smoking
 Nonsmoker 21 (52.5%)
 Smoker 18 (45%)
 Ex-smoker 1 (2.5%)
 Smoking index 46.7 ± 29.4
Pulmonary function
 %FVC 67.9 ± 14.1
 %FEV1 79 ± 17.2
 %DLCO 38.4 ± 13.8
 %DLCO/VA 62.1 ± 16.2
 RVSP 34.9 ± 10.2
 LVEF (>55%) 30 (75.0%)
Diagnosis
 Imaging 32 (80%)
 Biopsy 8 (20%)
Using bronchodilators: yes 28 (70%)
Using antifibrotic drugs: yes 27 (67.5%)
Time from diagnosis to death, mo 34 (23-55)
Survival outcomes
 Overall survival (time from diagnosis  to death, mo) Mean, 48.52 ± 5; median, NA (29-NA)
 Deaths 14 (35%)
Symptoms
 Cough 36 (90.0%)
 Sputum 16 (40.0%)
 Chest tightness 29 (72.5%)
 Breath shortness after exertion 40 (100.0%)
 Limited daily activities 25 (62.5%)
 Tiredness 21 (52.5%)
 Clubbing digits 8 (20.0%)
 Bibasilar crackles 35 (87.5%)
Comorbidity
 CAD 15 (37.5%)
 HTN 23 (57.5%)
 COPD 9 (22.5%)
 Bronchiectasis 6 (15.0%)
 TB 1 (2.5%)
 DM 9 (22.5%)
 CKD 6 (15.0%)
 GERD 9 (22.5%)
 Others 13 (32.5%)
Dose regulation 5 (12.5%)
Side effects
 Diarrhea 21 (52.5%)
 Nausea 5 (12.5%)
 Itchy skin 1 (2.5%)
 Headache 1 (2.5%)
 Exhaustion 3 (7.5%)
Abnormal liver function 5 (12.5%)
Using antidiarrheal drugs 20 (50.0%)
Acute exacerbation after medicationa 15 (37.5%)
%DLCO = percent predicted carbon monoxide diffusing capacity; %FEV1 = percentage 1-second forced expiratory volume; %FVC = percentage forced vital capacity; BMI = body mass index; CAD = coronary artery disease; CKD = chronic kidney disease; COPD = chronic obstructive pulmonary disease; DLCO/VA = diffusing capacity divided by the alveolar volume; DM = diabetes mellitus; GERD = Gastroesophageal reflux disease; HTN = hypertension; IPF = idiopathic pulmonary fibrosis; LVEF = left ventricular ejection fraction; NA = not available; TB = tuberculosis.
aAcute exacerbation after medication is defined as the need to use oral steroids, seek emergency treatment, or hospitalization due to IPF-induced respiratory tract illnesses.

3.2. Predictors of mortality

Thirty-eight independent variables were initially investigated as potential predictors of all-cause mortality using univariate Cox proportional hazard model (Table 2). Of those variables, only 5 were statistically significant, namely chest tightness (HR, 5.79 [0.76-44.38]; p = 0.09), finger clubbing (HR, 6.3 [2.18-18.29]; p < 0.001), %FVC (HR, 0.95 [0.91-0.99]; p = 0.03), %FEV1 (HR, 0.97 [0.93-1]; p = 0.06), and acute attack after medication (HR, 4.54 [1.42-14.56]; p = 0.01). Use of antifibrotic medication was not a significant predictor for mortality (p = 0.15). For subgroup of patients who received antifibrotic medications, two variables were statistically significant in the univariate analysis, which were finger clubbing (HR, 5.96 [1.96-18.13]; p = 0.002) and %FVC (HR, 0.95 [0.90-0.99]; p = 0.02).

Table 2 - Univariate Cox hazard proportional model for potential predictors of all-cause mortality among patients with IPF
Among all patients with IPF Among IPF received antifibrotic medications
Variable HR Lower CI Upper CI p HR Lower CI Upper CI p
Age, y 0.97 0.91 1.03 0.34 0.97 0.90 1.04 0.37
Sex: male-female 0.92 0.26 3.33 0.90 1.56 0.34 7.07 0.56
BMI 0.92 0.77 1.10 0.36 0.93 0.79 1.10 0.42
Smoking: smoker 1.31 0.45 3.81 0.62 1.44 0.48 4.30 0.52
Smoking: ex-smoker NA NA NA NA NA NA NA NA
Bronchodilator: yes 0.69 0.21 2.22 0.53 0.73 0.22 2.39 0.61
Cough: yes >10 0.00 Inf 1.00 >10 0.00 Inf 1.00
Phlegm: yes 2.13 0.74 6.16 0.16 2.12 0.69 6.53 0.19
Chest tightness: yes 5.79 0.76 44.38 0.09 3.92 0.51 30.26 0.19
Restricted daily activities: yes 1.23 0.41 3.73 0.71 1.34 0.41 4.36 0.63
Fatigue: yes 1.42 0.47 4.24 0.53 1.30 0.40 4.22 0.67
Clubbing fingers: yes 6.31 2.18 18.29 <0.001 5.96 1.96 18.13 0.002
Moist crackles: yes 1.25 0.16 9.62 0.83 1.01 0.13 7.81 0.99
CHF: yes 0.00 0.00 Inf 1.00 0.00 0.00 Inf 1.00
CAD: yes 0.29 0.06 1.29 0.10 0.39 0.09 1.78 0.23
HTN: yes 0.76 0.26 2.16 0.60 0.89 0.30 2.66 0.84
COPD: yes 1.23 0.33 4.54 0.76 2.53 0.66 9.74 0.18
Bronchiectasis: yes 0.92 0.25 3.34 0.90 0.92 0.25 3.37 0.90
Old TB: yes 0.00 0.00 Inf 1.00 0.00 0.00 Inf 1.00
DM: yes 0.51 0.11 2.27 0.37 0.70 0.15 3.16 0.64
CKD: yes 1.28 0.28 5.80 0.75 1.23 0.27 5.61 0.79
GERD: yes 0.92 0.26 3.32 0.90 0.68 0.15 3.08 0.62
%FVC 0.95 0.91 0.99 0.03 0.95 0.90 0.99 0.02
%FEV1 0.97 0.93 1 0.06 0.97 0.94 1.01 0.16
FEV1 L 0.51 0.13 2.04 0.34 0.63 0.15 2.73 0.54
FEV1/FVC L 0.32 0.0 792.57 0.78 0.32 0.00 2258.97 0.80
%DLCO 0.99 0.95 1.04 0.72 1.02 0.96 1.07 0.59
%DLCO/VA 0.99 0.95 1.02 0.41 1.00 0.96 1.03 0.86
CRP 1.23 0.90 1.68 0.19 1.14 0.83 1.57 0.43
Antifibrotic medication: yes 4.56 0.59 35.27 0.15 NA NA NA NA
Diarrhea: yes 0.68 0.23 1.99 0.48 0.49 0.16 1.52 0.22
Nausea: yes 1.45 0.40 5.23 0.57 1.27 0.35 4.66 0.71
Itchy skin: yes 0.00 0.00 Inf 1.00 0.00 0.00 Inf 1.00
Headache: yes 0.00 0.00 Inf 1.00 0.00 0.00 Inf 1.00
General weakness: yes 2.86 0.60 13.58 0.19 3.31 0.68 15.98 0.14
Abnormal liver function: yes 2.00 0.55 7.21 0.29 1.53 0.42 5.61 0.52
Antidiarrheals: yes 0.94 0.33 2.73 0.91 0.82 0.27 2.53 0.73
Acute attack after medication: yes 4.54 1.42 14.56 0.01 2.57 0.79 8.38 0.12
%DLCO = percent predicted carbon monoxide diffusing capacity; %FEV1 = percentage 1-second forced expiratory volume; %FVC = percentage forced vital capacity; BMI = body mass index; CAD = coronary artery disease; CHF = congestive heart failure; CKD = chronic kidney disease; CRP = C-reactive protein; FEV = forced expiratory volume; COPD = chronic obstructive pulmonary disease; DLCO/VA=diffusing capacity divided by the alveolar volume; DM = diabetes mellitus; FVC = forced vital capacity; GERD = gastroesophageal reflux disease; HR = hazard ratio; HTN = hypertension; Inf = inference; IPF = idiopathic pulmonary fibrosis; NA = not available; TB = tuberculosis.

A multivariate Cox model was then constructed to predict all-cause mortality using the abovementioned five predictors (Table 3). In this model, chest tightness, finger clubbing, and occurrence of acute attack after medication were risk factors for mortality (HR for death, >1) without statistical significance (p > 0.05). Patients with chest tightness had a 3.56 (0.39-32.64) times risk of death when other factors were constant (p = 0.26). Patients with finger clubbing had 3.75 (0.69-20.45) times mortality risk than patients without clubbing (p = 0.13). Patients who developed acute attack after medication (defined as the need to use oral steroids, seek emergency treatment, or hospitalization due to IPF-induced respiratory tract illnesses) had 2.01 (0.5-8.14) times the mortality risk of patients who did not develop an attack (p = 0.33). Each 1% decrease in FVC was associated with increase in mortality risk by 4% (multivariate HR, 0.96 [0.88-1.05]; p = 0.39). Each 1% decrease in FEV1 was associated with increase in mortality risk by 1% (multivariate HR, 0.99 [0.96-1.1]; p = 0.42).

Table 3 - Predictive Cox model for all-cause mortality among patients with IPF
Among all patients with IPF Among IPF received antifibrotic medications
Univariate analysis Multivariate analysisa Univariate analysis Multivariate analysisa
Variable HR (95% CI) p HR (95% CI) p HR (95% CI) p HR (95% CI) p
Chest tightness: yes 5.79 (0.76-44.38) 0.09 3.56 (0.39-32.64) 0.26
Clubbing fingers: yes 6.3 (2.18-18.29) <0.001 3.75 (0.69-20.45) 0.13 5.96 (1.96-18.13) 0.002 4.69 (1.03-21.39) 0.05
Acute attack after medication: yes 4.54 (1.42-14.56) 0.01 2.01 (0.5-8.14) 0.33
%FVC 0.95 (0.91-0.99) 0.03 0.96 (0.88-1.05) 0.39 0.95 (0.9-0.99) 0.02 0.98 (0.93-1.05) 0.65
%FEV1 0.97 (0.93-1) 0.06 0.99 (0.96-1.1) 0.42
%FEV1 = percentage 1-second forced expiratory volume; %FVC = percentage forced vital capacity; HR = hazard ratio; IPF = idiopathic pulmonary fibrosis.
aR2 = 0.317; p = 0.009.

For patients with IPF who received antifibrotic medications, patients with finger clubbing had 4.69 (1.03-21.39) times mortality risk than patients without clubbing (p = 0.05). Each 1% decrease in FVC was associated with an increase in mortality risk by 2% (multivariate HR, 0.98 [0.93-1.05]; p = 0.65).

A mortality risk scoring system was established based on the multivariate Cox predictive model. In this system (Table 4), both chest tightness and finger clubbing had a risk score of 13 points. Occurrence of acute exacerbation after medication had a risk score of 7. One percent decrease in %FVC increased the risk score by 5 points. Notably, %FEV did not affect risk score and was hence excluded from the scoring system. For a patient with all four risk factors, his total risk score would be 36. The 1-year probability of death was estimated from risk scores and compared against actual 1-year mortality rates of corresponding subgroups from the study cohort. This system overestimated the probability of death by only 0.85% for patients with chest tightness and underestimated it by only 2.06% for finger clubbing and 1.98% for acute attack after an exacerbation.

Table 4 - Proposed mortality risk scoring system and 1-year probability of death for patients with IPF
Variable Mortality risk scorea Cumulative risk score The 1-y probability of death The expected cumulative 1-y probability of death, % The observed cumulative 1-y mortality rate, % Difference in probability
Chest tightness: yes 13 13 18.35% 18.35% 17.5% 0.85%
Clubbing fingers: yes 13 26 18.35% 36.68% 38.74% −2.06%
%FVC 5 (for each 1% decrease) 29 3.03% 39.89%
Acute attack after medication: yes 7 36 10.1% 54.9% 56.88% −1.98%
FEV1 = 1-second forced expiratory volume; %FVC = percentage forced vital capacity; IPF = idiopathic pulmonary fibrosis.
aMortality score for each 1% decrease in FEV1 was nearly zero and hence omitted.

Comparing our model with that developed by du Bois et al16 (Table 5), the latter depended on four predictors: age, history of respiratory hospitalization, basal %FVC, and 24-week change in %FVC. Our model had a higher level of statistical significance (p = 0.009 vs p = 0.011) and could account for higher percent of variations in all-cause mortality for patients with IPF (32% vs 20%).

Table 5 - Comparison between our model and that of du Bois
Present model du Bois’s model
Risk scoring system Chest tightness: 13 Age >60 y: 4-8
Finger clubbing: 13 H/o of respiratory hospitalization: 14
Decrease FVC by 1%: 5 %FVC <80: 8-18
Acute exacerbation after medication: 7 24-wk change in %predicted FVC by >−4.9: 10-21
1-y probability of death for each increase in score by 1 point = (1 − 0.950) × EXP(risk score × 0.1) = (1 − 0.988) × EXP(risk score × 0.1)
R2 0.317 0.2
p 0.009 0.011
%FVC = percentage forced vital capacity; exp = experimental density; FVC = forced vital capacity; H/o = null hypothesis.

4. DISCUSSION

Previous studies have demonstrated the effective mechanisms by which nintedanib and pirfenidone can improve the outcomes of patients with IPF.18–22 Both drugs have been reported to successfully prolong survival and decrease the likelihood of sudden declines in lung function by slowing the speed with which IPF progresses.10,11,23–26 Another point that should favor nintedanib and pirfenidone is the absence of “absolute contraindications” for their prescription in patients with IPF.27

The present study was established to revisit the clinical predictors of IPF survival, being necessitated by the growing use of such new and clinically effective antifibrotic therapies over the past decade. Several recent studies have emerged to fulfill this purpose, providing updated real-world evidence through comparison of patients treated and not treated with antifibrotic medications. Our study came to fulfill the same purpose and to add to its predecessors.

While 67.5% of patients in our cohort received antifibrotic therapy, other recent studies reported a lower percentage of 60%,28–30 suggesting different treatment considerations from our study. Such considerations include the potential side effects of antifibrotic medications such as nausea and diarrhea,31 relative contraindications including moderate-to-severe hepatic,11 cost/reimbursement issues, uncertainty regarding the diagnosis of IPF, and/or underestimation of the patient’s need to antifibrotic medication.27,29

Our study investigated 38 independent factors as potential predictors of all-cause mortality among patients with IPF. Baseline pulmonary function tests were among the included factors but follow-up pulmonary tests were not; as IPF is a chronic, irreversible, progressively destructive lung disease, many patients have a poorer status after preventing them from performing the follow-up test. Antifibrotic medications are mainly used to decrease the loss of lung function experienced by patients with IPF. For example, in the INPULSIS trial, nintedanib significantly reduced the decline in FVC, which is consistent with a slowing of disease progression.25 The remaining number of patients who completed their follow-up was too statistically low to be included in the model. Among the 38 included factors, 3 clinical factors and 2 pulmonary functions were significantly correlated in the univariate analysis, namely chest tightness, finger clubbing, acute attack after medication, lower %FVC, and lower %FEV1. However, all of those factors failed to reach statistical significance in the multivariate model. In addition, the mortality score of %FEV1 was found to be nearly zero and hence excluded from our proposed mortality scoring system. Regarding the subgroup of patients who received antifibrotic medication, only finger clubbing and decrease in %FVC were significantly correlated at the univariate level, and only finger clubbing was a significant mortality predictor at the multivariate level. To furtherly validate our model, we compared the expected and the observed cumulative 1-year probability of death (%) for the study population, and they were very close (Table 4).

Findings in this study shared ground of agreement with those reported by du Bois et al,16 2011, who conducted their study on 1156 patients pooled from two clinical trials, investigating 20 independent variables, and using a very similar methodology to ours. In concordance with this study, the severity of respiratory illness was an important mortality predictor, where the history of respiratory hospitalization hurt a patient’s survival chances. In addition, %FVC <80 and/or declining %FVC were also associated with a higher risk of mortality.

However, this study differed from that of du Bois in some points. First, our study investigated mortality predictors among patients with IPF treated with antifibrotic medications, while patients in the study by du Bois were treated with interferon-gamma. Second, acute attack after medications was not reported in the study by du Bois as a separate entity. Furthermore, unlike the current study, age was a significant mortality predictor in the model by du Bois. In addition, clinical predictors in our study had more impact on mortality risk score than pulmonary functions, which was not the case in the model by du Bois. Our model achieved more statistical significance than that of du Bois (p = 0.009 vs p = 0.011) and a higher predictive power (R2 = 0.317 vs R2 = 0.2).

Alhamad et al31 conducted a retrospective study investigating 212 patients with IPF and provided closely similar results to ours where antifibrotic therapy, final saturation <85%, acute exacerbation, and walking distance <300 m were all predictors of IPF survival. Furthermore, Kang et al conducted a retrospective analysis on 1213 patients with IPF. They used propensity score matching to compare those who received antifibrotic medications with those who did not. Their results indicated that the risks of hospitalization, acute exacerbation, all-cause mortality, and mortality after acute exacerbation were all significantly reduced by antifibrotic treatment.32

The mere intake of antifibrotic medications was not a significant mortality predictor in our study. This might be owed to the retrospective nature of the study, where many patients started the medications after the deterioration of their pulmonary function rather than from the start. Hence, it should be stressed that drug treatment should be administered as early as possible following diagnosis.

Relatedly, the sample size of this study was relatively small. Therefore, further studies utilizing data from other populations of IPF patients are warranted to validate the applicability of our mortality risk model, especially as the utilization of antifibrotic medications may increase still further in the future.

In conclusion, this study came to investigate potential factors affecting all-cause mortality among patients with IPF in general and those treated with antifibrotic medications in particular. The univariate and multivariate Cox proportional hazard models indicated that chest tightness, finger clubbing, acute exacerbation after medication, decreased %FVC, and decreased %FEV1 were clinical factors linked to all-cause mortality among all patients, although without statistical significance at the multivariate level. Meanwhile, only finger clubbing was a significant mortality predictor among patients who received antifibrotic medications. A mortality scoring system was built upon the aforementioned risk factors, with the exclusion of %FVC, whose individual mortality score was nearly zero. Such a system was internally validated by comparing the expected and the observed cumulative 1-year probability of death (%) for the study population and externally validated by comparing it with that developed by du Bois et al.

The two main limitations of this study were its retrospective nature and relatively small sample size. Many patients in this study started antifibrotic medications after the deterioration of pulmonary functions, which might explain the fact that the mere intake of those medications was not a significant mortality predictor in this study.

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Keywords:

Humans; Idiopathic pulmonary fibrosis; Medical records; Mortality; Risk factors

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