Skip to main content
Download PDF

A comprehensive comparison of the safety and efficacy of drugs in the treatment of idiopathic pulmonary fibrosis: a network meta-analysis based on randomized controlled trials

BMC Pulmonary Medicine volume 24, Article number: 58 (2024) Cite this article

Abstract

Objective

Randomized controlled trials(RCTs) of multiple drugs for Idiopathic pulmonary fibrosis(IPF) have been reported and achieved a certain degree of efficacy, however, the difference in safety and efficacy of them for IPF is not yet well understood. The aim of this network meta-analysis is to assess their safety and efficacy in the treatment of IPF and differences in this safety and efficacy comprehensively.

Methods

The PubMed, EMbase, CENTRAL and MEDLINE were retrieved to find out the RCTs of drugs in the treatment of IPF. The retrieval date is from construction to November 10, 2022. Stata 14.0 and RevMan 5.3 was used for statistical analysis. Registration number: CRD42023385689.

Results

Twenty-four studies with a total of 6208 patients were finally included, including RCTs of 13 drugs. The results of safety showed that there' s no difference in the incidence of SAEs of 13 drugs treated with IPF compared to placebo (P>0.05), and it’s also found that Warfarin had a higher all-cause mortality for IPF than placebo (OR = 5.63, 95% CI [1.54 to 20.55]). SUCRA' s scatterplot showed that Pirfenidone, Nintedanib, Sildenafil and Imatinib were lower than placebo, and Warfarin, Ambrisentan and N-acetylcysteine were higher than placebo. The results of effectiveness showed that Nintedanib (MD = -0.08, 95% CI [-0.12 to -0.04]) improved FVC (L)absolute change from baseline in patients better than placebo, and Nintedanib (OR=1.81, 95% CI [1.23 to 2.66]), Pirfenidone (OR=1.85, 95%CI [1.26 to 2.71]) and Pamrevlumab (OR=4.11, 95% CI [1.25 to 13.58]) improved the proportion of patients with a decline in FVC ≥10% predicted better than placebo. SUCRA' s scatterplot showed that Pamrevlumab, Pirfenidone and Nintedanib were lower than placebo, and Warfarin and Ambrisentan were higher than placebo.

Conclusion

Compared with other drugs, Nintedanib and Pirfenidone can significantly slow the decline of lung function in patients with IPF, and the safety is higher. Therefore, they can be further promoted in clinical practice. Warfarin and Ambrisentan shouldn’t be used clinically for IPF as the safety and efficacy of them are poor compared to other drugs and placebo. Pamrevlumab may become important drugs for the treatment of IPF in the future.

Peer Review reports

Introduction

Idiopathic pulmonary fibrosis (IPF) is a fibrosis interstitial pneumonia of unknown cause. IPF patients usually die within 3-4 years after the diagnosis [1,2,3]. The 5-year survival rate of IPF patients was 53.7%, with chronic respiratory failure being the leading cause of death in IPF patients and acute exacerbations(AEs) being the second leading cause of death in IPF patients (23.5%) [4]. It is characterized by high morbidity and high mortality [5], and the incidence tends to increase with age [6], among which the proportion of IPF in older males is higher [7]. It can lead to decreased lung function, increased dyspnea and cough, reduced exercise capacity, and deterioration of quality of life as it progresses [8, 9]. Its pathogenesis is closely related to the repair of abnormal alveolar injury [10]. Pirfenidone and Nintedanib are two drugs currently available for the treatment of IPF, both of which were approved by the US Food and Drug Administration in 2014 [11]. In the Phase 3 trial, two drugs slowed the decline in FVC of IPF patients over 1 year compared to placebo [12, 13]. In two other Randomized controlled trials (RCTs) [14, 15], patients with IPF in the Pirfenidone and Nintedanib groups experienced lower AEs than placebo (Pirfenidone:0% vs.Placebo:14.29%; Nintedanib:2.4% vs. Placebo:15.7%). Therefore, these two drugs appear to have good efficacy and safety. However, neither of them had a good effect on symptoms, quality of life, or HRCT of the chest in patients with IPF. In addition, both drugs have gastrointestinal adverse events that can affect long-term treatment adherence in patients [16, 17].

Except Pirfenidone and Nintedanib, some other RCTs of drugs for the treatment of IPF have been reported: In a phase 2 RCT, Pamrevlumab reduced the decline in FVC (% predicted) by 60.3% at week 48, but treatment-induced urgent serious adverse events(SAEs) were observed in 12 (24%) patients in the Pamrevlumab group and 8 (15%) patients in the placebo group [18]; In two RCTs, there was no difference in FVC (% predicted) changes in IPF patients in the Sildenafil group compared with those in the placebo group, and there were no significant differences in AEs (Sildenafil:2/89 vs. Placebo:4/91, P=0.68), SAEs (Sildenafil:13/89 vs. Placebo:15/91, P=0.73) and all-cause mortality (Sildenafil:2/89 vs. Placebo:4/91, P=0.43) [19, 20]; One RCT reported no significant difference between Imatinib and placebo in improving FVC (% predicted) at 96 weeks of follow-up and there were no differences in mortality (Imatinib: 8/59 vs. Placebo:10/60) and AEs (Imatinib:5/59 vs. Placebo:8/60) between the groups [21]; PRM-151 (Recombinant human pentatroxin 2) improved FVC (% predicted) from the baseline to week 28 in patients with IPF in one RCT (difference, +2.3 [90% CI, 1.1 to 3.5], P = 0.001), but there was a proportion of SAEs in both groups (Imatinib: 7.8% vs. Placebo: 10.3%) [22]; Results from a phase 2a RCT showed that GLPG1690 improved mean change from baseline in FVC at week 12 (GLPG1690: 25 mL vs. Placebo: -70 mL), and no patients died or had AE-IPFs, but some SAEs occurred in both groups (GLPG1690:1 vs. Placebo:2) [23]; The data from one RCT showed no difference in FVC reduction between the N-acetylcysteine (NAC) 600 mg tid group and the placebo group (60-week change in NAC -0.18 L vs. Placebo -0.19L, p = 0.77). In addition, there were no significant differences between NAC and placebo for mortality (6 [4.9%] vs. 3 [2.5%]events, p=0.50) or AEs (3 [2.3%] vs. 3 [2.3%] events, p > 0.99) [24]; In one RCT with a planned treatment duration of 48 weeks, there was an increase in all-cause mortality in patients with IPF treated with Warfarin (14/72 cases of Warfarin vs. 3/73 cases of Placebo death; P=0.005), thus the study was terminated prematurely [25]; One RCT was terminated after enrolling 492 patients (75% of expected enrollment) because the number of patients receiving Ambrisentan may meet pre-specified criteria for disease progression (Ambrisentan: 90 [27.4%] vs. Placebo: 28 [17.2%], patients; P=0.01) [26].

These data showed an important problem: the effectiveness of these drugs to treat IPF is different and there are also differences in safety, and it’s difficult to choose more effective and safer drugs among them for the treatment. Therefore, it is necessary to conduct rigorous, objective and systematic quality evaluation of clinical research of different drugs to obtain the safety and efficacy analysis evidence on this basis to guide the clinical use. This study collected all RCTs of IPF reported in literatures, and used systematic review methods to objectively evaluate the safety and efficacy of these drugs for IPF to seek more valuable drugs for the treatment of IPF.

Methods

This study has been registered in PROSPERO(https://www.crd.york.ac.uk/prospero/), registration number: CRD42023385689. The procedure of this protocol is based on PRISMA-P guidance [27].

Inclusion criteria

The included studies were all RCTs reported so far for the treatment of IPF with drugs, with or without blinding and allocation concealment, and their language was restricted to English. All studies must meet official diagnostic criteria [11] and the gender, age, race and nationality of participants were not restricted. The experimental group of these RCTs all used drugs independently to treat IPF, and the dose, dosage form and administration method of these drugs were not limited while the control group used placebo matched with the experimental group drugs. The course of treatment of drugs in the test group and the control group was not limited.

Exclusion criteria

① RCTs with 2 or more drugs for IPF in the experimental group were excluded; ② Literatures with non-RCTs, reviews, case reports, experimental studies, expert experience were excluded; ③ Literatures with duplicate publications and incomplete information were excluded; ④ For repeated publications of the same research results, only the one with the most complete information was retained.

Outcomes

①Safety outcomes: SAEs and all-cause mortality, and SAEs are defined in the Richeldi L 2014 [13]; ②Effectiveness outcomes: FVC (L) absolute change from baseline, FVC (% predicted)absolute change from baseline and the proportion of patients with decline in FVC≥10% predicted.

Retrieval strategy

PubMed, EMbase, CENTRAL and MEDLINE were retrieved by computer and the retrieval date was from the construction to November 10, 2022. Theme words and keywords were retrieved combining with literature retrospective and manual retrieval methods, etc. The search terms: “Idiopathic pulmonary fibrosis” OR “Pulmonary fibrosisor” OR “Pulmonary interstitial fibrosis” OR “Interstitial lung disease” OR “IPF”AND“medicine” OR “Drugs” OR “treatment” AND “randomized controlled trial” OR “RCT” OR “Clinical trial”. At the same time, manually retrieve were used to supplement and retrieve relevant documents on the Internet. The search strategy of PubMed is presented in Table S1 in supplemental content.

Literature screening and data extraction

The literatures were cross-checked by two independent researchers (Wu XZ and Li W) after screening, and those with no unanimous opinion were decided by the 3rd party (Chen YZ). when the literature report is not detailed or the data are insufficient, they try to contact the author by email for details. The design of the data extraction table generally follows the principle of "PICOST" (participants, interventions, comparisons, outcomes, study design, time).

Quality assessment and risk of bias assessment of literature

The quality criteria of the literature were the modified Jadad scales [28], and risk of bias was recommended by Cochrane Assistance, including: (1) generation of a randomization protocol; (2) concealed grouping; (3) blinding of patients and doctors; (4) blinding of outcome evaluation; (5) incomplete result data; (6) selective results reporting; (7) other biases.

GRADE evaluates the results

Grading of Recommendations, Assessment, Development and Evaluations (GRADE) [29] was used to evaluate the results of NMA. Refer to the previously published literature [30, 31] for specific methods: For direct comparisons, the estimated starting point of certainty was “high”, and for indirect comparisons, the starting certainty was reduced to “moderate”.

Data synthesis and analysis

In this study, all network meta-analyses were conducted using a random effects model. Odds ratio (OR) and 95% confidence interval (95% CI) were used for statistical analysis for dichotomous variables and mean difference (MD), and 95% CI were used for continuous variables. P<0.05 was statistically significant. When exact mean and SD values were not reported in the included articles, we used the following methods and referred to the previous literature [32]: for Median (IQR) and Median (range), we used online tool (https://www.math.hkbu.edu.hk/~tongt/papers/median2mean.html) for format conversion; for mean (SE) and mean (95% CI), we used the built-in data conversion tool in Revman 5.3 for format conversion. When the included data were sufficiently similar (heterogeneity test: P>0.1, I2<50%), the NMA can be performed. And consistency models were used simultaneously to evaluate the consistency and inconsistency between data. Due to the inclusion of dual arm studies that directly compare drugs with placebo, only the consistency could be tested rather than the inconsistency.

We ranked the treatment using the surface under the cumulative ranking curve (SUCRA), which is the cumulative relative probability of a treatment being the best option [33, 34]. The higher the rank of SUCRA shows, the higher the level of risk is, for example, a high all-cause mortality value of SUCRA indicates a high all-cause mortality. Influence analysis were performed when there was significant heterogeneity between studies; the funnel plot analysis was used to analyze the publication bias. All the statistical analysis above used Revman 5.3 and Stata 14.0 software.

Results

Literature retrieval results

PubMed, EMbase, CENTRA Land MEDLINE searched 756 literatures initially, 22 of them, containing 24 studies with a total of 6208 patients, were finally included after layer-by-layer screening, including 3387 in the experimental group and 2821 in the control group and including RCTs of 13 drugs (5 of Nintedanib [13, 14, 35, 36], 4 of Pirfenidone [12, 37, 38], 2 of Sildenafil [19, 20], 1 of Ambrisentan [26], 1 of Pamrevlumab [18], 2 of Bosentan [39, 40], 1 of Macitentan [41], 1 of Imatinib [21], 1 of GLPG1690 [23], 1 of Simtuzumab [42], 1 of Warfarin [25], 2 of PRM-151 [22, 43], 2 of N-acetylcysteine [24, 44]). Figure 1 is a literature screening flowchart developed according to the requirements of the PRISMA statement [27]. The basic characteristics of the included studies were shown in Tables 1 and 2.

Fig. 1
figure 1

PRISMA literature screening flow chart

Full size image
Table 1 Basic features of the included study (1)
Full size table
Table 2 Basic features of the included study (2)
Full size table

Quality assessment

The 24 included studies were RCTs, all of which mentioned the use of a randomization method and described the comparability of baseline data between the two groups, and there were no incomplete data being reported or data missing. All of them also described the treatment and outcome measures in the experimental and control groups, and 22 studies described specific allocation concealment methods and blinding. The modified Jadad scale [28] was used to evaluate the 24 included studies, of which 19 studies were with 7 points, 3 studies were with 6 points, 1 study was with 5 points, and 1 study was with 3 points. There were 23 high-quality studies and 1 low-quality study. The results of the quality evaluation were shown in Table S2 in supplemental content.

Cochrane risk of bias assessment results

The results showed that the low risk proportion of random sequence generation in the selection bias of the 24 studies was about 79.76%, the moderate risk was about 17.26%, and the high risk was about 2.98% (Fig. 2), so the included studies had less selection, implementation and measurement bias, and the bias statistics of each study were shown in Fig. 3.

Fig. 2
figure 2

Bias risk percentage

Full size image
Fig. 3
figure 3

Bias risk summary chart

Full size image

Security analysis

SAEs

Of the 24 studies included, a total of 19 studies reported SAEs in the treatment of IPF with 13 drugs, as shown in Fig. 4. Statistical analyses were performed with OR and 95%CI as the effect size, and the results of heterogeneity test showed I2=0%, P=0.623, thus it met the criteria of P>0.1, I2<50%, and the effect sizes could be combined for meta-analysis. The consistency model results showed that the effect sizes (Log OR) of all study were approximately between 0 and 2, indicating that the consistency of the results was credible, as shown in Figure S1 in supplemental content. The results of the network meta-analysis (NMA) showed (Table 3, Figure S2 in supplemental content) that there was no difference in the incidence of SAEs between the 13 drugs and placebo (P>0.05). Comparisons between drugs showed that Warfarin had a higher incidence of SAEs than Bosentan (OR = 2.49, 95% CI [1.06 to 5.89], low certainty of evidence) and GLPG1690 (OR = 16.75, 95% CI [1.06 to 263.92], low certainty of evidence); Ambrisentan had a higher incidence of SAEs than Bosentan (OR=1.88, 95% CI [1.04 to 3.38], low certainty of evidence). The SUCRA ranking showed: Warfarin (89.4) > Ambrisentan(81.6) > Pamrevlumab(80.1) > N-acetylcysteine(66.1) > Simtuzumab(54.1) > Pirfenidone(48.5) > Placebo(48) > Imatinib(44) > Nintedanib(42.7) > Sildenafil(38.7) > Macitentan(37.6) > PRM151(34) > Bosentan(29) > GLPG1690(6.1). Higher values of SUCRA indicate higher incidence of SAEs. As shown in Table 4 and Figure S3 in supplemental content.

Fig. 4
figure 4

Network evidence map of SAEs. A total of 19 studies reported SAEs in the treatment of IPF with 13 drugs: 1 of Ambrisentan, 2 of Bosentan, 1 of GLPG1690, 1 of Imatinib, 1 of Macitentan, 1 of N-acetylcysteine, 5 of Nintedanib, 1 of Pamrevlumab, 2 of Pirfenidone, 1 of PRM-151, 1 of Sildenafil, 1 of Simtuzumab, 1 of Warfarin

Full size image
Table 3 Results of network meta-analysis of the incidence of SAEs
Full size table
Table 4 SUCRA ranking of the incidence of SAEs
Full size table

All-cause mortality

Of the 24 studies included, 16 reported the all-cause mortality of IPF treated with 11 drugs, as shown in Fig. 5. The results of heterogeneity tests showed I2=28.7% and P=0.136, which could be combined for meta-analysis. The consistency model results showed that all study effect sizes (Log OR) were approximately between 0 and 2, indicating that the consistency of the results was credible, as shown in Figure S4 in supplemental content. The results of the NMA (Table 5, Figure S5 in supplemental content) showed that Warfarin had higher all-cause mortality than placebo (OR = 5.63, 95% CI [1.54 to 20.55], moderate certainty of evidence), and there was no difference in all-cause mortality compared with placebo for the remaining 10 drugs (P>0.05). Comparisons between drugs showed that Warfarin had higher all-cause mortality than Bosentan (OR = 4, 73, 95% CI [1.17 to 19.06], low certainty of evidence), Simtuzumab (OR = 5.84, 95% CI [1.44 to 23.61], low certainty of evidence), Imatinib (OR=7.18, 95% CI[1.39,37.05], low certainty of evidence), Pirfenidone (OR=8.17, 95%CI[2.10,31.82], low certainty of evidence), Nintedanib (OR=8.38, 95%CI[2.14,32.84], low certainty of evidence), Sildenafil (OR=11.26, 95% CI [1.31 to 97.22], low certainty of evidence) and Pamrevlumab (OR=11.26, 95% CI [1.62 to 78.32], low certainty of evidence); Ambrisentan had higher all-cause mortality than Pirfenidone (OR = 3.26, 95% CI [1.20 to 8.85], low certainty of evidence) and Nintedanib (OR = 3.34, 95% CI [1.22 to 9.15], low certainty of evidence). The SUCRA ranking showed: Warfarin (96.6) > Ambrisentan(82.9) > N-acetylcysteine(75) > Bosentan(60.9) > Macitentan(54.1) > Placebo(51.3) > Simtuzumab(48.2) > Imatinib(36.4) > Pirfenidone(25.6) > Nintedanib(24.2) > Sildenafil(23.7) > Pamrevlumab(21.2). Higher values of SUCRA indicate higher all-cause mortality. As shown in Table 6, Figure S6 in supplemental content.

Fig. 5
figure 5

Network evidence map of all-cause mortality. A total of 16 studies reported the all-cause mortality of IPF treated with 11 drugs: 1 of Ambrisentan, 2 of Bosentan,1 of Imatinib, 1 of Macitentan, 1 of N-acetylcysteine, 3 of Nintedanib, 1 of Pamrevlumab, 3 of Pirfenidone, 1 of Sildenafil, 1 of Simtuzumab, 1 of Warfarin

Full size image
Table 5 Results of network meta-analysis of all-cause mortality
Full size table
Table 6 SUCRA ranking of all-cause mortality
Full size table

Combining the results from SAEs and all-cause mortality, the scatterplot showed (Fig. 6): the SUCRA values of Pirfenidone, Nintedanib, Sildenafil and Imatinib were lower than those of placebo, the SUCRA values of Simtuzumab, Macitentan and Bosentan were approximately equal to those of placebo, and the SUCRA values of Warfarin, Ambrisentan and N-acetylcysteine were higher than those of placebo. In addition, the SUCRA value of all-cause mortality of Pamrevlumab was lower than placebo, but the SUCRA value of the incidence of SAEs was higher than placebo.

Fig. 6
figure 6

The scatterplot combining the results of the incidence of SAEs and all-cause mortality (SUCRA values). The horizontal coordinate represents SUCRA values for all-cause mortality and the vertical coordinate represents SUCRA values for SAEs.If drugs are positioned further to the upper right of the graph, it means that the higher their SUCRA values, the higher their risk; if drugs are positioned further to the lower left of the graph, it means that the lower their SUCRA values are lower, the lower the risk

Full size image

Effectiveness analysis

FVC (L) absolute change from baseline

A total of 11 of the 24 included studies reported on 9 drugs to treat FVC (L) absolute change from baseline in patients with IPF, as shown in Fig. 7. Statistical analyses were performed by using MD and 95%CI as effect sizes. The results of the heterogeneity test showed I2=6.5% and P=0.382, which could be combined for meta-analysis. The consistency model results showed that all study effect sizes (MD) were approximately between -2 and 0, indicating that the consistency of the results is credible, as shown in Figure S7 in supplemental content. The results of the NMA (Table 7, Figure S8 in supplemental content) showed that the improvement of FVC (L) absolute change from baseline by Nintedanib (MD=-0.08, 95% CI [-0.12 to -0.04], high certainty of evidence) and PRM151 (MD=-0.13, 95% CI [-0.25 to -0.01], moderate certainty of evidence) was better than that by placebo and there was no difference in improvement with placebo for the remaining 7 drugs (P>0.05). The results of the comparison between drugs showed: Nintedanib (MD=-0.12, 95% CI [-0.22 to -0.02], low certainty of evidence) and PRM151 (MD=-0.17, 95% CI [-0.32 to -0.01], very low certainty of evidence) improved FVC (L) absolute change from baseline better than Warfarin. The SUCRA ranking showed: Warfarin (85.2) > Imatinib (73.2) > Placebo(72.6) > Macitentan(61.3) > Bosentan(54.8) > N-acetylcysteine(47.1) > Nintedanib(36.2) > GLPG1690(34) > PRM151(22.7) > Pamrevlumab(13). Higher values of SUCRA indicate higher values of decline in FVC (L) absolute change from baseline. As shown in Table 8 and Figure S9 in supplemental content.

Fig. 7
figure 7

Network evidence map of FVC (L) absolute change from baseline. A total of 11 studies reported the FVC (% predicted) absolute change from baseline in patients with IPF treated with 9 drugs:1 of Bosentan, 1 of GLPG1690, 1 of Imatinib, 1 of Macitentan, 1 of N-acetylcysteine, 3 of Nintedanib, 1 of Pamrevlumab, 1 of PRM-151, 1 of Warfarin

Full size image
Table 7 Results of network meta-analysis of FVC (L) absolute change from baseline
Full size table
Table 8 SUCRA ranking of FVC (L) absolute change from baseline
Full size table

FVC (% predicted) absolute change from baseline

Among the 24 included studies, a total of 9 studies reported the FVC (% predicted) absolute change from baseline in patients with IPF treated with 7 drugs, as shown in Fig. 8. The results of the heterogeneity test showed I2=42.5% and P=0.084, which could be combined for meta-analysis. The consistency model results showed that all study effect sizes (MD) were approximately between -5 and 0, indicating that the consistency of the results was credible (Figure S10 in supplemental content). The results of the NMA (Table 9, Figure S11 in supplemental content) showed no difference in FVC (% predicted)absolute change from baseline improvement with placebo (P>0.05) for 7 drugs and so are the comparisons between drugs (P>0.05). The SUCRA ranking showed: Ambrisentan (84.9) > Warfarin (79.3) > Placebo(70.3) > Sildenafil(62.5) > Nintedanib(36.3) > Pirfenidone(30.8) > PRM151(19.3) > Pamrevlumab(16.6). Higher values of SUCRA indicate higher values of decline in FVC (% predicted) absolute change from baseline. As shown in Table 10 and Figure S12 in supplemental content.

Fig. 8
figure 8

Network evidence map of FVC (% predicted)absolute change from baseline. A total of 9 studies reported the FVC (% predicted) absolute change from baseline in patients with IPF treated with 7 drugs: 1 of Ambrisentan, 1 of Nintedanib, 1 of Pamrevlumab, 2 of Pirfenidone, 1 of PRM-151, 2 of Sildenafil, 1 of Warfarin

Full size image
Table 9 Results of network meta-analysis of FVC (% predicted) absolute change from baseline
Full size table
Table 10 SUCRA ranking of FVC (% predicted) absolute change from baseline
Full size table

The proportion of patients with decline in FVC≥10% predicted

Among the 24 included studies, a total of 10 reported the effect of the proportion of patients with decline in FVC≥ 10% predicted of 5 drugs, as shown in Fig. 9. Statistical analyses were performed by using OR and 95% CI as effect sizes. Although the heterogeneity test results showed that I2=62.7%, P=0.004, which had some heterogeneity, the consistency model results showed that the log OR of all studies were roughly between 0 and 2, indicating that the consistency of the results was reliable, as shown in Figure S13 in supplemental content. The results of the NMA(Table 11, Figure S14 in supplemental content) showed that Nintedanib (OR=1.81, 95% CI [1.23 to 2.66], high certainty of evidence), Pirfenidone (OR=1.85, 95% CI [1.26 to 2.71], high certainty of evidence), and Pamrevlumab (OR=4.11, 95% CI [ 1.25, 13.58], high certainty of evidence) improved the proportion of patients with the decline in FVC ≥10% predicted better than placebo, and the improvement of the remaining 2 drugs were not different from placebo (P> 0.05). the results of comparison between drugs showed: Nintedanib (OR=2.76, 95% CI [1.21 to 6.30], low certainty of evidence), Pirfenidone (OR=2.81, 95%CI [1.23 to 6.42], low certainty of evidence), and Pamrevlumab (OR=6.26, 95% CI [1.54 to 25.40], low certainty of evidence) improved the proportion of patients with decline in FVC ≥10% predicted better than Ambrisentan. The SUCRA ranking showed: Ambrisentan (96) > Placebo(80.4) > Nintedanib(41.8) > Pirfenidone(40.4) > Warfarin(31.3) > Pamrevlumab(10.2). Higher values of SUCRA indicate that the proportion of patients with decline in FVC≥ 10% predicted is higher. As shown in Table 12 and Figure S15 in supplemental content.

Fig. 9
figure 9

Network evidence map of the proportion of patients with decline in FVC≥10% predicted. A total of 10 studies reported the effect of the proportion of patients with decline in FVC≥ 10% predicted of 5 drugs: 1 of Ambrisentan, 4 of Nintedanib, 1 of Pamrevlumab, 3 of Pirfenidone, 1 of Warfarin

Full size image
Table 11 Results of network meta-analysis of the proportion of patients with decline in FVC≥10% predicted
Full size table
Table 12 SUCRA ranking of the proportion of patients with decline in FVC≥10% predicted
Full size table

Combining the results of FVC (% predicted) absolute change from baseline and the proportion of patients with decline in FVC ≥10% predicted, the scatterplot showed (Fig. 10): The SUCRA values of Pamrevlumab, Pirfenidone and Ninedanib were lower than those of placebo, and the SUCRA values of Warfarin and Ambrisentan were higher than those of placebo.

Fig. 10
figure 10

The scatterplot combining the results of FVC (% predicted)absolute change from baseline and the proportion of patients with decline in FVC≥10% predicted(SUCRA values). The horizontal coordinate represents SUCRA values for FVC (% predicted) absolute change from baseline and the vertical coordinate represents SUCRA values for the proportion of patients with decline in FVC ≥10% predicted. If drugs are positioned further to the upper right of the graph, it means that the higher their SUCRA values, the higher their risk; if drugs are positioned further to the lower left of the graph, it means that the lower their SUCRA values are lower, the lower the risk

Full size image

Publication bias

Figure 11 showed that the inverted funnel plots were symmetrical, suggesting that there’s no publication bias. The statistical results of Begg's test and Egger's test were used to detect bias for all outcomes, and the results showed that PBegg>0.05 and PEgger> 0.05, indicating that there was no obvious bias in this study. As shown in Figure S16 and Figure S17 in supplemental content.

Fig. 11
figure 11

The results of inverted funnel plots. a SAEs. b All-cause mortality. c FVC (L) absolute change from baseline. d FVC (% predicted)absolute change from baseline. e The proportion of patients with decline in FVC≥10% predicted. (PLA:Placebo; NIN:Nintedanib; PIR:Pirfenidone; SIL:Sildenafil; AMB:Ambrisentan; PAM:Pamrevlumab; BOS:Bosentan; MAC:Macitentan; IMA:Imatinib; GLPG:GLPG1690; SIM:Simtuzumab; WAR:Warfarin;PRM: PRM151;NAC:N-acetylcysteine.)

Full size image

Influence analysis

Influence analyses for the 5 outcomes (Table S3-S7 and Figure S18 in supplemental content) showed that none of the included studies had clear sensitivity, indicating that there was no significant difference in the results after excluding any of the studies (except FVC (% predicted) absolute change from baseline). It’s proved that the effect size sensitivity of these outcomes was low, and it had good stability, reliability, and stable and reliable analysis results.

Discussion

The total of 24 RCTs on the clinical efficacy of 13 drugs for IPF were included in this NMA with the aim of comprehensively assessing their safety and efficacy in the treatment of IPF and differences in this safety and efficacy. Our results found that Nintedanib and Pirfenidone improved lung function (FVC (L) absolute change from baseline or the proportion of patients with the decline in FVC ≥10% predicted) better than placebo, and they improved lung function( FVC (L) absolute change from baseline or the proportion of patients with the decline in FVC ≥10% predicted) better than Warfarin or Ambrisentan. It’s also found that Pirfenidone and Nintedanib had lower all-cause mortality than Warfarin and Ambrisentan. The SUCRA values for the efficacy and safety of Nintedanib and Pirfenidone were also lower than those of placebo and many other drugs. Therefore, Our result confirmed that Nintedanib and Pirfenidone can significantly slow the decline of lung function in IPF patients with better safety profile than placebo and many other drugs.

Cell signaling pathways activated by tyrosine kinases, such as VEGF, FGF, and PDGF, had been shown to be involved in the pathogenesis of IPF [45,46,47]. Nintedanib (formerly BIBF 1120) is an intracellular inhibitor that targets a variety of tyrosine kinases, including receptors such as VEGF, FGF, and PDGF [48]. Some studies have reported that it can reduce the decline rate of FVC in IPF patients [13, 14]. In a previous phase 2 RCT [TOMORROW], compared with placebo, Nintedanib 150mg bid can better improve the FVC change rate of IPF patients (P=0.01), and the incidence of SAEs was lower (27.1% vs.30.6%) [14]. In two repeated RCTs (INPUTLIS-1 and INPUTLIS-2), it also achieved good results, and the incidence of SAEs and all-cause mortality of patients in the Nintedanib group were also lower than those in the placebo group [13]. In addition, similar results have been reported in two recent clinical trials [35, 36]. Pifenidone is an orally bioavailable synthetic molecule. It regulates the activity of TGF-β and TNF-α [49,50,51,52,53], and can inhibit collagen synthesis and fibroblast proliferation [50, 53,54,55,56]. In one trial, there was a statistically significant difference in VC decline at 9 months between placebo (-0.13 L) and Pirfenidone (-0.03 L) (p = 0.0366). One of the five patients in the placebo group died after an exacerbation episode while there were no deaths in the Pirfenidone group during the 9-month study period, and no SAEs were reported in the Pirfenidone group [15]. One literature later reported on two simultaneous studies (CAPACITY 004 and 006): two studies combined showed the effect of Pirfenidone treatment on predicted percentage FVC at week 72 (p=0.005): -8.5% in the Pirfenidone 2403 mg/day group and -11.0% in the placebo group. In terms of security, the rates of SAEs and mortality were lower in the group with Pirfenidone than in the placebo group [37]. In addition, similar results have been reported in two clinical trials [12, 38]. All these findings showed that Nintedanib and Pirfenidone had good effect on slowing the decline of lung function in patients with IPF and had lower incidence of SAEs and all-cause mortality. Therefore, Nintedanib and Pirfenidone can continue to be vigorously promoted in clinical practice.

It’s also found that Pamrevlumab improved the proportion of patients with decline in FVC≥10% predicted better than placebo and Ambrisentan, and it had lower all-cause mortality than Warfarin. In addition, the SUCRA values for the lung function and all-cause mortality of Pamrevlumab were lower than placebo and all other drugs, but the SUCRA value of the incidence of SAEs was higher than placebo. Pamrevlumab (FG-3019) is a fully human recombinant monoclonal antibody against CTGF [57]. In the mice with pulmonary fibrosis, Pamrevlumab improved lung function and lung airway remodeling, and inhibited collagen production [58, 59]. In an open-label study, 89 patients with IPF were given two doses of Pamrevlumab every 3 weeks for 48 weeks, and good results were shown in lung function and quantitative HRCT changes [60]. In another phase 2 RCT, Pamrevlumab can delay the decline rate of the predicted FVC percentage of patients with IPF at 48th week (Pamrevlumab:–2.9% vs. Placebo:–7.2% ). Of the 3 (6%) deaths in the Pamrevlumab group and 6 (11%) deaths in the placebo group, none were considered as treatment-related. However, a higher proportion of treatment-induced urgent SAEs occurred in the Pamrevlumab group than in the placebo group (Pamrevlumab: 24% vs. Placebo: 15%) [18]. Our study confirmed that Pamrevlumab had a very good slowing effect in the declining of lung function and low all-cause mortality in patients with IPF compared to other drugs, and it’s currently in Phase 3 development and may become an important drug for the treatment of IPF in the future. However, it’s also confirmed in our study that the incidence of SAEs is still relatively high, therefore it should be used clinically according to the actual situation of patients.

The results showed no difference in lung function improvement with placebo for Imatinib (FVC (L) absolute change from baseline) and Sildenafil (FVC (% predicted) absolute change from baseline) , and the SUCRA values were also roughly equal to placebo. It’s also found that Imatinib and Sildenafil had lower all-cause mortality than Warfarin, and the SUCRA values for the safety of Imatinib and Sildenafil were also lower than those of placebo and some other drugs. Sildenafil is a phosphodiesterase-5 inhibitor that has been approved by the U.S. Food and Drug Administration for the treatment of idiopathic pulmonary hypertension (IPAH) [61]. It stabilizes cyclic guanosine monophosphate, the second messenger of nitric oxide, which leads pulmonary vasodilation in patients with IPF and thereby improve gas exchange [62]. In addition, sildenafil also reduced the production of superoxide in the mouse model of pulmonary fibrosis [63]. A previous study reported that Sildenafil (20–50 mg orally 3 times daily for 3 months) resulted in an improvement in 6-MWT distances of patients with IPF [64]. However, in one RCT, there was no difference in FVC (% predicted) changes in 89 patients with advanced IPF in the Sildenafil group compared with 91 patients in the placebo group (mean change=0.32, 95% CI [−1.12 to 1.76], P=0.66), and there was also no significant difference in SAEs and all-cause mortality [19]. In another RCT, there was no significant difference in FVC (% predicted) in IPF patients (P=0.79) between Sildenafil and placebo, and there were few SAEs [20]. Imatinib was approved by the U.S. Food and Drug Administration in 2001 for the treatment of chronic myeloid leukemia and has proven to be very effective. It is a TKI with activity against the PDGFR, DDR, c-kit and c-Abl [65, 66]. Current studies have demonstrated that imatinib inhibits bleomycin-induced IPF [67, 68], and the mechanism of action is closely related to inhibition of lung FMT and inhibition of the ECM produced by PDGF and TGF-β signaling [69]. One phase 2 RCT reported no significant difference between Imatinib and placebo at 96 week’s follow-up in terms of time to disease progression (predicted 10% reduction in FVC percentage from baseline) or time to death, and there was no significant difference in SAEs and mortality [21]. Thus, Sildenafil and Imatinib appear to have lower rates of SAEs and all-cause mortality, but do not have much effect in improving FVC in patients. Our study confirmed that Sildenafil and Imatinib had a better safety profile than other drugs, but their efficacy was less obvious than placebo, so further clinical studies are needed to confirm their effectiveness.

It’s found that PRM151 improved FVC (L) absolute change from baseline in patients with IPF better than placebo and Warfarin. In addition, the SUCRA values for the lung function (FVC (L) absolute change from baseline or FVC (% predicted) absolute change from baseline) and SAEs of PRM151 were lower than placebo and most other drugs. Current clinical study had found very low plasma concentrations of Pentraxin 2 in patients with IPF [70] and had demonstrated in experimental studies that PRM-151 (Recombinant human pentraxin-2) inhibited TGF-β1 and bleomycin-induced pulmonary fibrosis [70,71,72]. Its mechanism of improving pulmonary fibrosis was closely related to inhibition of TGF-β1 production and inhibition of monocytes differentiation into pro-inflammatory macrophages and prefibrous fibroblasts [73,74,75]. In a phase 1 RCT of increasing doses of PRM-151, the results showed a trend towards improvement in FVC and 6-MWT in the combined dose group of PRM-151 and no SAEs [43]. In another phase 2 RCT, PRM-151 was also found to improve FVC from baseline to week 28 as a percentage of predicted value (difference, +2.3 [90% CI, 1.1 to 3.5], P = 0.001) in patients with IPF, and a lower incidence of SAEs [22]. Therefore, PRM151 appears to improve lung function well in patients with IPF, as well as a low incidence of SAEs, and our findings confirmed these views, and it may be a good targeted new drug for the treatment of IPF. However, due to the lack of data on all-cause mortality, further clinical studies are needed to confirm its safety and efficacy.

The results showed no difference in FVC (L)absolute change from baseline improvement with placebo for GLPG1690, but it had lower SUCRA values than placebo and many other drugs. It’s also found that GLPG1690 had lower incidence of SAEs than Warfarin, and GLPG1690 had lower SUCRA values than placebo and all other drugs. GLPG1690 is a potent and selective autoclassifier protein inhibitor and is well tolerated orally in humans [76, 77]. The results showed that GLPG1690 could improve the Ashcroft fibrosis score of mice with pulmonary fibrosis well and inhibit the profibrotic mediator in IPF fibroblasts [76, 78, 79]. In a phase 2a RCT, patients with IPF received either placebo (n=6) or oral GLPG1690 600 mg (n=7) once daily for 12 weeks, and the results showed that at week 12, patients in the GLPG1690 group had an average change in FVC of 25 mL versus -70 mL of placebo. SAEs occurred in 2 patients in the placebo group and 1 in the GLPG1690 group, and no patients died [23]. Combined with our findings, these data showed that although GLPG1690 had a low incidence of SAEs and had a certain effect on improving lung function, the patient sample size was too small, and there’s a lack of data on all-cause mortality, therefore further clinical studies are needed to confirm its safety and efficacy.

The results showed no difference in FVC (L)absolute change from baseline improvement with placebo for N-acetylcysteine (NAC), but it had lower SUCRA values than placebo and some other drugs. It’s also found that there’s no difference in the incidence of SAEs and all-cause mortality of N-acetylcysteine treated with IPF compared to placebo. In addition, the SUCRA values for the incidence of SAEs and all-cause mortality of NAC were also higher than those of placebo and many other drugs. Current studies had shown that NAC was able to directly scavenge oxygen radicals [80], and can inhibit TGF-β signaling in IPF [81]. No difference in NAC 600 mg tid versus placebo was found in one RCT in improving FVC and mortality in people with IPF [24]. Another multicentre RCT also found no difference in efficacy or safety between inhaled NAC and placebo [44]. In addition, a RCT(IFIGENIA), compared NAC + therapy including Prednisone and Azathioprine with Prednisone + Azathioprine + Placebo, found that NAC group can better improve VC and DLCO in IPF patients [82]. However, another study (PANTHER-IPF ) reported that the simultaneous use of these three drugs increased mortality and the incidence of SAEs in patients with IPF [83]. Our study also showed that NAC alone wasn’t evident in terms of effectiveness and there may be a number of adverse events, thus NAC alone is not recommended clinically for IPF.

Procoagulases may directly stimulate fibrosis through cell surface receptor-mediated responses [84]. A previous unblinded study reported a 1-year survival benefit with anticoagulation (Heparin + Warfarin) in patients with IPF [85]. However, in a later RCT, warfarin was associated with an increase in all-cause mortality (14 warfarin versus 3 Placebo deaths; P = 0.005), and the study had to be terminated early due to excessive mortality [25]. Data from preclinical models suggested that the expression of endothelin receptors in IPF lung tissue increased while antagonizing endothelin receptors may reduce the severity of pulmonary fibrosis [86, 87]. Ambrisentan is a selective ETA receptor antagonist that had been approved for treatment of pulmonary arterial hypertension(PAH) [88]. One RCT reported that Ambrisentan treatment for IPF increased mortality (Ambrisentan: 7.9% vs. Placebo: 3.7%) and an increase in the proportion of patients with IPF with decreased lung function (Ambrisentan: 16.7% vs. Placebo: 11.7%). As a result, the study was terminated early [26]. Our findings also confirmed that the safety and efficacy of Warfarin and Ambrisentan were very poor compared to other drugs and placebo. Combing with previous findings that Warfarin and Ambrisentan should not be used clinically for IPF. In addition, several other drugs (Bosentan, Macitentan and Simtuzumab) are less outstanding than placebo in terms of safety and efficacy, and further clinical studies are needed to confirm their efficacy.

Limitations of Inclusion: The 24 studies we included described the outcomes of the experimental group and the control group in detail, but there are some problems remained:1) All the 24 studies reported on randomization, but 5 studies only mentioned randomization and did not give a clear randomization method; 2 studies did not report allocation concealment and 1 did not use blinding. These factors will influence the overall quality of the study to some extent; 2) The evaluation outcomes of the 24 studies were not exactly the same, and the criteria for evaluating the results were not exactly the same, so the results of this study may have some heterogeneity and sensitivity; 3) There were some small studies in the included studies, and there was some clinical heterogeneity (different doses administered, different administration methods, different courses of treatment, different course of disease, different interventions and different disease severity, etc.), which all affected the reliability of the results; 4) Some studies did not perform statistical analysis of important observation outcomes such as FEV1%, FVC%, TLC%, 6MWD, SGRQ, HRCT, inflammatory factors, pulmonary fibrosis factors, etc., which will affect the overall quality of the literature included in the statistics; 5) All the studies were in English instead of other languages.

Conclusion

Nintedanib and Pirfenidone can significantly slow the decline of lung function in IPF patients and have a better safety profile, they can continue to be vigorously promoted in clinical practice. Pamlumumab has a good slowing effect on lung function decline and low all-cause mortality in IPF patients and is currently in phase 3 development, it may become an important drug for the treatment of IPF in the future. Sildenafil and Imatinib have a good safety profile, but their effectiveness is not obvious, and further clinical studies are needed to confirm their effectiveness. Both PRM151 and GLPG1690 seem to have the effect of improving lung function of IPF patients, and the incidence of SAEs is low. However, due to the lack of data on all-cause mortality, further clinical studies are needed for comprehensive evaluation. N-acetylcysteine alone is not evident in terms of efficacy, and there may be a number of adverse events, so NAC alone is not recommended clinically for IPF. Warfarin and Ambrisentan have poor safety and efficacy, therefore they are not recommended for clinical use in the treatment of IPF.

In addition to the above drugs, some other drugs such as Nalbuphine [89], pembrolizumab [90], and Treprostinil [91] have shown good efficacy in clinical and animal experimental studies in IPF or interstitial lung disease. In the future, if there are high-quality RCTs of these drugs for IPF, they can be included and evaluated comprehensively. In addition, in future network meta-analysis, various molecular biomarkers in the field of precision medicine can be considered as efficacy evaluation indicators [92] to screen out more effective drugs for the treatment of IPF.

Availability of data and materials

Data supporting our findings are contained within the manuscript.

Abbreviations

IPF:

Idiopathic Pulmonary Fibrosis

AE:

Acute exacerbation

FVC:

Forced vital capacity

HRCT:

High-resolution computed tomography

RCT:

Randomized controlled trial

SAE:

Serious adverse effect

NAC:

N-acetylcysteine

GRADE:

Grading of Recommendations Assessment, Development and Evaluation

NMA:

Network meta analysis

MD:

Mean difference

OR:

Odds ratio

95% CI:

95% confidence interval

VEGF:

Vascular endothelial growth factor

FGF:

Fibroblast growth factor

PDGF:

Platelet-derived growth factor

TGF-β:

Transforming growth factor-β

TNF-α:

Tumour necrosis factor-α

VC:

Vital capacity

CTGF:

Connective tissue growth factor

IPAH:

Idiopathic pulmonary hypertension

6-MWT:

6-minute walk test

TKI:

Tyrosine kinase inhibitor

PDGFR:

Platelet-derived growth factor receptors

DDR:

Discoidin domain receptors

FMT:

Fibroblast to myofibroblast transformation

ECM:

Extracellular matrix

DLCO:

Carbon monoxide diffusivity

ETA:

Endothelin A

PAH:

Pulmonary arterial hypertension

References

  1. Strongman H, Kausar I, Maher TM. Incidence, prevalence, and survival of patients with idiopathic pulmonary fibrosis in the UK. Adv Ther. 2018;35:724–36.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Raghu G, Chen SY, Yeh WS, et al. Idiopathic pulmonary fibrosis in US Medicare beneficiaries aged 65 years and older: incidence, prevalence, and survival, 2001–11. Lancet Respir Med. 2014;2:566–72.

    Article  PubMed  Google Scholar 

  3. Koudstaal T, Wijsenbeek MS. Idiopathic pulmonary fibrosis. Presse Med. 2023;52(3): 104166.

    Article  PubMed  Google Scholar 

  4. Tsubouchi K, Hamada N, Tokunaga S, et al. Survival and acute exacerbation for patients with idiopathic pulmonary fibrosis (IPF) or non-IPF idiopathic interstitial pneumonias: 5-year follow-up analysis of a prospective multi-institutional patient registry. BMJ Open Respir Res. 2023;10(1):e001864.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Raghu G, Remy-Jardin M, Myers JL, et al. Diagnosis of Idiopathic Pulmonary Fibrosis. An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline. Am J Respir Crit Care Med. 2018;198(5):e44–68.

    Article  PubMed  Google Scholar 

  6. Xie BB, Ren YH, Geng J, et al. Idiopathic Pulmonary Fibrosis Registry China study(PORTRAY): Protocol for a prospective, multicentre registry study. BMJ Open. 2020;10(11):e036809.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Raghu G, Chen SY, Hou Q, Yeh WS, Collard HR. Incidence and prevalence of idiopathic pulmonary fibrosis in US adults 18–64 years old. Eur Respir J. 2016;48(1):179–86.

    Article  PubMed  Google Scholar 

  8. Glaspole IN, Chapman SA, Cooper WA, et al. Health-related quality of life in idiopathic pulmonary fibrosis: Data from the Australian IPF Registry. Respirology. 2017;22(5):950–6.

    Article  PubMed  Google Scholar 

  9. Kreuter M, Swigris J, Pittrow D, et al. Health related quality of life in patients with idiopathic pulmonary fibrosis in clinical practice: insights-IPF registry. Respir Res. 2017;18(1):139.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Wolter PJ, Collard HR, Jones KD, et al. Pathogenesis of idiopathic pulmonary fibrosis. Annu Rev Pathol. 2014;9:157–79.

    Article  Google Scholar 

  11. Raghu G, Rochwerg B, Zhang Y, et al. An official ATS/ERS/JRS/ALAT clinical practice guideline: treatment of idiopathic pulmonary fibrosis. An update of the 2011 clinical practice guideline. Am J Respir Crit Care Med. 2015;192:e3-19.

    Article  PubMed  Google Scholar 

  12. King TE Jr, Bradford WZ, Castro-Bernardini S, et al. A phase 3 trial of pirfenidone in patients with idiopathic pulmonary fibrosis. N Engl J Med. 2014;370:208392.

    Article  Google Scholar 

  13. Richeldi L, du Bois RM, Raghu G, et al. Efficacy and safety of nintedanib in idiopathic pulmonary fibrosis. N Engl J Med. 2014;370:207182.

    Article  Google Scholar 

  14. Richeldi L, Costabel U, Selman M, et al. Efficacy of a tyrosine kinase inhibitor in idiopathic pulmonary fibrosis. N Engl J Med. 2011;365(12):1079–87.

    Article  PubMed  CAS  Google Scholar 

  15. Azuma A, Nukiwa T, Tsuboi E, et al. Double-blind, placebo-controlled trial of pirfenidone in patients with idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2005;171(9):1040–7.

    Article  PubMed  Google Scholar 

  16. Galli JA, Pandya A, Vega-Olivo M, Dass C, Zhao H, Criner GJ. Pirfenidone and nintedanib for pulmonary fibrosis in clinical practice: tolerability and adverse drug reactions. Respirology. 2017;22:11718.

    Article  Google Scholar 

  17. Hughes G, Toellner H, Morris H, Leonard C, Chaudhuri N. Real world experiences:pirfenidone and nintedanib are effective and well tolerated treatments for idiopathic pulmonary fibrosis. J Clin Med. 2016;5:E78.

    Article  Google Scholar 

  18. Richeldi L, Fernández Pérez ER, Costabel U, et al. Pamrevlumab, an anti-connective tissue growth factor therapy, for idiopathic pulmonary fibrosis (PRAISE): a phase 2, randomised, double-blind, placebo-controlled trial. Lancet Respir Med. 2020;8(1):25–33.

    Article  PubMed  CAS  Google Scholar 

  19. Idiopathic Pulmonary Fibrosis Clinical Research Network, Zisman DA, Schwarz M, et al. A controlled trial of sildenafil in advanced idiopathic pulmonary fibrosis. N Engl J Med. 2010;363(7):620-628.

  20. Jackson RM, Glassberg MK, Ramos CF, Bejarano PA, Butrous G, Gómez-Marín O. Sildenafil therapy and exercise tolerance in idiopathic pulmonary fibrosis. Lung. 2010;188(2):115–23.

    Article  PubMed  CAS  Google Scholar 

  21. Daniels CE, Lasky JA, Limper AH, et al. Imatinib treatment for idiopathic pulmonary fibrosis: Randomized placebo-controlled trial results. Am J Respir Crit Care Med. 2010;181(6):604–10.

    Article  PubMed  CAS  Google Scholar 

  22. Raghu G, van den Blink B, Hamblin MJ, et al. Effect of Recombinant Human Pentraxin 2 vs Placebo on Change in Forced Vital Capacity in Patients With Idiopathic Pulmonary Fibrosis: A Randomized Clinical Trial. JAMA. 2018;319(22):2299–307.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Maher TM, van der Aar EM, Van de Steen O, et al. Safety, tolerability, pharmacokinetics, and pharmacodynamics of GLPG1690, a novel autotaxin inhibitor, to treat idiopathic pulmonary fibrosis (FLORA): a phase 2a randomised placebo-controlled trial. Lancet Respir Med. 2018;6(8):627–35.

    Article  PubMed  CAS  Google Scholar 

  24. Idiopathic Pulmonary Fibrosis Clinical Research Network, Martinez FJ, de Andrade JA, Anstrom KJ, King TE Jr, Raghu G. Randomized trial of acetylcysteine in idiopathic pulmonary fibrosis. N Engl J Med. 2014;370(22):2093-2101.

  25. Noth I, Anstrom KJ, Calvert SB, et al. A placebo-controlled randomized trial of warfarin in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2012;186(1):88–95.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Raghu G, Behr J, Brown KK, et al. Treatment of idiopathic pulmonary fibrosis with ambrisentan: a parallel, randomized trial. Ann Intern Med. 2013;158(9):641–9.

    Article  PubMed  Google Scholar 

  27. Moher D, Shamseer L, Clarke M, et al. Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4:1.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Jadad AR, Moore RA, Carroll D, et al. Acc seeing the quality of reports of randomized clinical trails is blinding necessary. Control Clin Trails. 1996;17(1):1–12.

    Article  CAS  Google Scholar 

  29. Puhan MA, Schunemann HJ, Murad MH, Li T, Brignardello-Petersen R, Singh JA, et al. A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ. 2014;349:g5630.

    Article  PubMed  Google Scholar 

  30. Rochwerg B, Neupane B, Zhang Y, Garcia CC, Raghu G, Richeldi L, Brozek J, Beyene J, Schünemann H. Treatment of idiopathic pulmonary fibrosis: a network meta-analysis. BMC Med. 2016;3(14):18.

    Article  Google Scholar 

  31. Wu X, Li W, Qin Z, Luo Z, Xue L, Chen Y. Comparison of 4 kinds of traditional Chinese medicine injections to assist in improving clinical indicators of patients with idiopathic pulmonary fibrosis: a systematic review and network meta-analysis. Medicine (Baltimore). 2022;101(47):e31877.

    Article  PubMed  Google Scholar 

  32. Challoumas D, Biddle M, McLean M, Millar NL. Comparison of treatments for frozen shoulder: a systematic review and meta-analysis. JAMA Netw Open. 2020;3(12):e2029581.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Salanti G, Ades AE, Ioannidis JP. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol. 2011;64(2):163–71.

    Article  PubMed  Google Scholar 

  34. Yang CP, Liang CS, Chang CM, et al. Comparison of New Pharmacologic Agents With Triptans for Treatment of Migraine: a Systematic Review and Meta-analysis. JAMA Netw Open. 2021;4(10):e2128544.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Lancaster L, Goldin J, Trampisch M, et al. Effects of Nintedanib on Quantitative Lung Fibrosis Score in Idiopathic Pulmonary Fibrosis. Open Respir Med J. 2020;14:22–31.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Maher TM, Stowasser S, Nishioka Y, et al. Biomarkers of extracellular matrix turnover in patients with idiopathic pulmonary fibrosis given nintedanib (INMARK study): a randomised, placebo-controlled study. Lancet Respir Med. 2019;7(9):771–9.

    Article  PubMed  CAS  Google Scholar 

  37. Noble PW, Albera C, Bradford WZ, et al. Pirfenidone in patients with idiopathic pulmonary fibrosis (CAPACITY): two randomised trials. Lancet. 2011;377(9779):1760–9.

    Article  PubMed  CAS  Google Scholar 

  38. Taniguchi H, Ebina M, Kondoh Y, et al. Pirfenidone in idiopathic pulmonary fibrosis. Eur Respir J. 2010;35(4):821–9.

    Article  PubMed  CAS  Google Scholar 

  39. King TE Jr, Behr J, Brown KK, et al. BUILD-1: a randomized placebo-controlled trial of bosentan in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2008;177(1):75–81.

    Article  PubMed  CAS  Google Scholar 

  40. King TE Jr, Brown KK, Raghu G, et al. BUILD-3: a randomized, controlled trial of bosentan in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2011;184(1):92–9.

    Article  PubMed  Google Scholar 

  41. Raghu G, Million-Rousseau R, Morganti A, Perchenet L, Behr J; MUSIC Study Group. Macitentan for the treatment of idiopathic pulmonary fibrosis: the randomised controlled MUSIC trial. Eur Respir J. 2013;42(6):1622-1632.

  42. Raghu G, Brown KK, Collard HR, et al. Efficacy of simtuzumab versus placebo in patients with idiopathic pulmonary fibrosis: a randomised, double-blind, controlled, phase 2 trial. Lancet Respir Med. 2017;5(1):22–32.

    Article  PubMed  CAS  Google Scholar 

  43. van den Blink B, Dillingh MR, Ginns LC, et al. Recombinant human pentraxin-2 therapy in patients with idiopathic pulmonary fibrosis: safety, pharmacokinetics and exploratory efficacy. Eur Respir J. 2016;47(3):889–97.

    Article  PubMed  Google Scholar 

  44. Homma S, Azuma A, Taniguchi H, et al. Efficacy of inhaled N-acetylcysteine monotherapy in patients with early stage idiopathic pulmonary fibrosis. Respirology. 2012;17(3):467–77.

    Article  PubMed  Google Scholar 

  45. Chaudhary NI, Roth GJ, Hilberg F, et al. Inhibition of PDGF, VEGF and FGF signalling attenuates fibrosis. Eur Respir J. 2007;29:976–85.

    Article  PubMed  CAS  Google Scholar 

  46. Coward WR, Saini G, Jenkins G. The pathogenesis of idiopathic pulmonary fibrosis. Ther Adv Respir Dis. 2010;4:367–88.

    Article  PubMed  CAS  Google Scholar 

  47. Wollin L, Maillet I, Quesniaux V, Holweg A, Ryffel B. Anti-fibrotic and anti-inflammatory activity of the tyrosine kinase inhibitor nintedanib in experimental models of lung fibrosis. J Pharmacol Exp Ther. 2014;349:209–20.

    Article  PubMed  Google Scholar 

  48. Hilberg F, Roth GJ, Krssak M, et al. BIBF 1120: triple angiokinase inhibitor with sustained receptor blockade and good antitumor efficacy. Cancer Res. 2008;68:4774–82.

    Article  PubMed  CAS  Google Scholar 

  49. Iyer SN, Gurujeyalakshmi G, Giri SN, et al. Eff ects of pirfenidone on transforming growth factor-beta gene expression at the transcriptional level in bleomycin hamster model of lung fi brosis. J Pharmacol Exp Ther. 1999;291:367–73.

    PubMed  CAS  Google Scholar 

  50. Hirano A, Kanehiro A, Katsuichiro O, et al. Pirfenidone modulates airway responsiveness, infl ammation, and remodeling after repeated challenge. Am J Respir Cell Mol Biol. 2006;35:366–77.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Nakazato H, Oku H, Yamane S, et al. A novel anti-fi brotic agent pirfenidone suppresses tumor necrosis factor-α at the translational level. Eur J Pharmacol. 2002;446:177–85.

    Article  PubMed  CAS  Google Scholar 

  52. Oku H, Nakazato H, Horikawa T, et al. Pirfenidone suppresses tumor necrosis factor-alpha, enhances interleukin-10 and protects mice from endotoxic shock. Eur J Pharmacol. 2002;446:167–76.

    Article  PubMed  CAS  Google Scholar 

  53. Oku H, Shimizu T, Kawabata T, et al. Antifi brotic action of pirfenidone and prednisolone: different effects on pulmonary cytokines and growth factors in bleomycin-induced murine pulmonary fi brosis. Eur J Pharmacol. 2008;590:400–8.

    Article  PubMed  CAS  Google Scholar 

  54. Iyer SN, Wild JS, Schiedt MJ, et al. Dietary intake of pirfenidone ameliorates bleomycin-induced lung fibrosis in hamsters. J Lab Clin Med. 1995;125:779–85.

    PubMed  CAS  Google Scholar 

  55. Iyer SN, Margolin SB, Hyde DM, et al. Lung fi brosis is ameliorated by pirfenidone fed in diet after second dose in a three-dose bleomycin-hamster model. Exp Lung Res. 1998;24:119–32.

    Article  PubMed  CAS  Google Scholar 

  56. Iyer SN, Gurujeyalakshmi G, Giri SN, et al. Eff ects of pirfenidone on procollagen gene expression at the transcriptional level in bleomycin hamster model of lung fi brosis. J Pharmacol Exp Ther. 1999;289:211–8.

    PubMed  CAS  Google Scholar 

  57. Lipson KE, Wong C, Teng Y, Spong S. CTGF is a central mediator of tissue remodeling and fibrosis and its inhibition can reverse the process of fibrosis. Fibrogenesis Tissue Repair. 2012;5:S24.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Bickelhaupt S, Erbel C, Timke C, et al. Effects of CTGF blockade on attenuation and reversal of radiation-induced pulmonary fibrosis. J Natl Cancer Inst. 2017; 109: djw339.

  59. Wang Q, Usinger W, Nichols B, et al. Cooperative interaction of CTGF and TGF-beta in animal models of fibrotic disease. Fibrogenesis Tissue Repair. 2011;4:4.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Raghu G, Scholand MB, de Andrade J, et al. FG-3019 anti-connective tissue growth factor monoclonal antibody: results of an open-label clinical trial in idiopathic pulmonary fibrosis. Eur Respir J. 2016;47:148191.

    Article  Google Scholar 

  61. Galie N, Ghofrani H, Torbicki A, Barst RJ, Rubin L, Badesch D, Fleming T, Parpia T, Burgess G, Branzi A, Grimminger F, Kurzyna M, Simonneau G. Sildenafil citrate therapy for pulmonary arterial hypertension. N Engl J Med. 2005;353:2148–57.

    Article  PubMed  CAS  Google Scholar 

  62. Ghofrani HA, Wiedemann R, Rose F, et al. Sildenafil for treatment of lung fibrosis and pulmonary hypertension: a randomised controlled trial. Lancet. 2002;360:895–900.

    Article  PubMed  CAS  Google Scholar 

  63. Hemnes A, Zaiman A, Champion H. PDE5A inhibition attenuates bleomycin-induced pulmonary fibrosis and pulmonary hypertension through inhibition of ROS generation and RhoA/Rho kinase activation. Am J Physiol Lung Cell Mol Physiol. 2008;294:L24–33.

    Article  PubMed  CAS  Google Scholar 

  64. Collard H, Anstrom K, Schwarz M, Zisman D. Sildenafil improves walk distance in idiopathic pulmonary fibrosis. Chest. 2007;131:897–9.

    Article  PubMed  Google Scholar 

  65. Day E, Waters B, Spiegel K, Alnadaf T, Manley PW, Buchdunger E, Walker C, Jarai G. Inhibition of collagen-induced discoidin domain receptor 1 and 2 activation by imatinib, nilotinib and dasatinib. Eur J Pharmacol. 2008;599:44–53.

    Article  PubMed  CAS  Google Scholar 

  66. Buchdunger E, O’Reilly T, Wood J. Pharmacology of imatinib (STI571). Eur J Cancer. 2002;38:S28–36.

    Article  PubMed  Google Scholar 

  67. Azuma M, Nishioka Y, Aono Y, Inayama M, Makino H, Kishi J, Shono M, Kinoshita K, Uehara H, Ogushi F, et al. Role of alpha1-acid glycoprotein in therapeutic antifibrotic effects of imatinib with macrolides in mice. Am J Respir Crit Care Med. 2007;176:1243–50.

    Article  PubMed  CAS  Google Scholar 

  68. Aono Y, Nishioka Y, Inayama M, Ugai M, Kishi J, Uehara H, Izumi K, Sone S. Imatinib as a novel antifibrotic agent in bleomycin-induced pulmonary fibrosis in mice. Am J Respir Crit Care Med. 2005;171:1279–85.

    Article  PubMed  Google Scholar 

  69. Daniels CE, Wilkes MC, Edens M, Kottom TJ, Murphy SJ, Limper AH, Leof EB. Imatinib mesylate inhibits the profibrogenic activity of TGF-beta and prevents bleomycin-mediated lung fibrosis. J Clin Invest. 2004;114:1308–16.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Murray LA, Chen Q, Kramer MS, et al. TGF-beta driven lung fibrosis is macrophage dependent and blocked by serum amyloid P. Int J Biochem Cell Biol. 2011;43(1):154–62.

    Article  PubMed  CAS  Google Scholar 

  71. Pilling D, Roife D, Wang M, et al. Reduction of bleomycin-induced pulmonary fibrosis by serum amyloid P. J Immunol. 2007;179:4035–44.

    Article  PubMed  CAS  Google Scholar 

  72. Murray LA, Rosada R, Moreira AP, et al. Serum amyloid P therapeutically attenuates murine bleomycin-induced pulmonary fibrosis via its effects on macrophages. PLoS One. 2010;5: e9683.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Naik-Mathuria B, Pilling D, Crawford JR, et al. Serum amyloid P inhibits dermal wound healing. Wound Repair Regen. 2008;16(2):266–73.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Pilling D, Buckley CD, Salmon M, Gomer RH. Inhibition of fibrocyte differentiation by serum amyloid P. J Immunol. 2003;171(10):5537–46.

    Article  PubMed  CAS  Google Scholar 

  75. Moreira AP, Cavassani KA, Hullinger R, et al. Serum amyloid P attenuates M2 macrophage activation and protects against fungal spore-induced allergic airway disease. J Allergy Clin Immunol. 2010;126(4):712–21.

    Article  PubMed  CAS  Google Scholar 

  76. Desroy N, Housseman C, Bock X, et al. Discovery of 2-[[2-Ethyl-6-[4-[2-(3-hydroxyazetidin-1-yl)- 2-oxoethyl]piperazin-1-yl]-8-methylimidazo[1,2-a]pyridin-3-yl]methylamino]-4-(4-fluorophenyl)thiazole-5-carbonitrile (GLPG1690), a first-in-class autotaxin inhibitor undergoing clinical evaluation for the treatment of idiopathic pulmonary fibrosis. J Med Chem. 2017;60:3580–90.

    Article  PubMed  CAS  Google Scholar 

  77. van der Aar EM, Fagard L, Desrivot J, et al. Favorable human safety, pharmacokinetics and pharmacodynamics of the autotaxin inhibitor GLPG1690, a potential new treatment in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2016;193:A2701.

    Google Scholar 

  78. van der Aar EM, Heckmann B, Blanque R, et al. Pharmacological profile and efficacy of GLPG1690, a novel autotaxin inhibitor for the treatment of idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2016;193:A4532.

    Google Scholar 

  79. Coornaert B, Duys I, Van Der Schueren J, van der Aar E, Heckmann B. Autotaxin inhibitor GLPG1690 affects TGFβ-induced production of the pro-fibrotic mediators CTGF, IL-6 and ET-1 in fibroblasts. Am J Respir Crit Care Med. 2017;195:A2404.

    Google Scholar 

  80. Glissen A, Nowak D. Characterization of N-acetylcysteine and ambroxol in anti-oxidant therapy. Respir Med. 1998;92:609–23.

    Article  Google Scholar 

  81. Zafarullah M, Li WQ, Sylvester J, et al. Molecular mechanisms of N-acetylcysteine actions. Cell Mol Life Sci. 2003;60:6–20.

    Article  PubMed  CAS  Google Scholar 

  82. Demedts M, Behr J, Buhl R, et al. High-dose acetylcysteine in idiopathic pulmonary fibrosis. N Engl J Med. 2005;353:2229–42.

    Article  PubMed  CAS  Google Scholar 

  83. Raghu G, Anstrom KJ, King TE Jr, Lasky JA, Martinez FJ. Prednisone, azathioprine, and N-acetylcysteine for pulmonary fibrosis. N Engl J Med. 2012;366:1968–77.

    Article  PubMed  CAS  Google Scholar 

  84. Chambers RC. Procoagulant signalling mechanisms in lung inflammation and fibrosis: novel opportunities for pharmacological intervention? Br J Pharmacol. 2008;153:S367–78.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  85. Kubo H, Nakayama K, Yanai M, Suzuki T, Yamaya M, Watanabe M, Sasaki H. Anticoagulant therapy for idiopathic pulmonary fibrosis. Chest. 2005;128:1475–82.

    Article  PubMed  CAS  Google Scholar 

  86. Park SH, Saleh D, Giaid A, Michel RP. Increased endothelin-1 in bleomycininduced pulmonary fibrosis and the effect of an endothelin receptor antagonist. Am J Respir Crit Care Med. 1997;156:600–8.

    Article  PubMed  CAS  Google Scholar 

  87. Henderson WR, Ye X, Tien YT, Wright CD. Anti-fibrogenic effects of the endothelin-A receptor antagonist ambrisentan in a mouse pulmonary fibrosis model [Abstract]. Presented at the European Respiratory Society Annual Congress, Barcelona, Spain, 18–22 September 2010. Abstract 5642.

  88. Galie N, Olschewski H, Oudiz RJ, Torres F, Frost A, Ghofrani HA, et al;Ambrisentan in Pulmonary Arterial Hypertension, Randomized, DoubleBlind, Placebo-Controlled, Multicenter, Efficacy Studies (ARIES) Group. Ambrisentan for the treatment of pulmonary arterial hypertension: results of the ambrisentan in pulmonary arterial hypertension, randomized, double-blind, placebo-controlled, multicenter, efficacy (ARIES) study 1 and 2. Circulation.2008;117:3010-9.

  89. Maher, T. M., Avram, C., Bortey, E., Hart, S. P., Hirani, N., Molyneux, P. L., Porter, J. C., Smith, J. A., & Sciascia, T.. Nalbuphine tablets for cough in patients with idiopathic pulmonary fibrosis. NEJM Evidence. 2023, 2(8), EVIDoa2300083.

  90. Karampitsakos T, Galaris A, Chrysikos S, et al. Expression of PD-1/PD-L1 axis in mediastinal lymph nodes and lung tissue of human and experimental lung fibrosis indicates a potential therapeutic target for idiopathic pulmonary fibrosis. Respir Res. 2023;24(1):279.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  91. Waxman A, Restrepo-Jaramillo R, Thenappan T, et al. Inhaled Treprostinil in Pulmonary Hypertension Due to Interstitial Lung Disease. N Engl J Med. 2021;384(4):325–34.

    Article  PubMed  CAS  Google Scholar 

  92. Karampitsakos T, Juan-Guardela BM, Tzouvelekis A, Herazo-Maya JD. Precision medicine advances in idiopathic pulmonary fibrosis. EBioMedicine. 2023;95:104766.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

Not applicable.

Ethics and dissemination

This review does not require ethical approval because the included studies are published data and do not involve the patients’ privacy. The results of this review will be reported in accordance with the PRISMA extension statement and disseminated to a peer-reviewed journal.

Funding

This work is supported by Guizhou Provincial Basic Research Program(Natural Science) (Qiankehe Foundation-ZK[2023]General 411),Academic New Seedling Project of Guizhou University of Traditional Chinese Medicine (Guike Cooperative Academic New Seedling [2023]-22), Innovation and Entrepreneurship Training Program for College Students of Guizhou University of Traditional Chinese Medicine, China (Gui Zhong Yi Da Chuang He Zi (2022) No. 90) ,and Project of Education Department of Guizhou Province, China (Guizhou Education Technology 2022-023).

Author information

Authors and Affiliations

  1. Department of Preclinical medicine, Guizhou University of Traditional Chinese Medicine, Guiyang, 510025, China

    Xiaozheng Wu, Wen Li, Zhenliang Luo & Yunzhi Chen

Authors
  1. Xiaozheng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wen Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhenliang Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yunzhi Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

This study is initiated by Xiaozheng Wu. Xiaozheng Wu will develop the search strategies, conduct data collection, and analyze independently. Wen Li, Zhenliang Luo and Yunzhi Chen will revise it. All authors have approved the fifinal manuscript. Conceptualization: Xiaozheng Wu. Methodology: Xiaozheng Wu, Wen Li. Software: Xiaozheng Wu. Supervision: Yunzhi Chen. Writing – original draft: Xiaozheng Wu. Writing – review & editing: Wen Li, Zhenliang Luo, Yunzhi Chen.

Corresponding author

Correspondence to Yunzhi Chen.

Ethics declarations

Ethics approval and consent to participate

The authors declare that there is no conflict of interests regarding the publication of this paper.

Consent for publication

Not applicable.

Competing interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Figure S1.

The forest plot of consistency test of SAEs. Figure S2. Forest plot of pairwise comparison of the incidence of SAEs.  (PLA: Placebo; NIN:Nintedanib; PIR: Pirfenidone; SIL: Sildenafil; AMB: Ambrisentan; PAM: Pamrevlumab; BOS: Bosentan; MAC: Macitentan; IMA: Imatinib; GLPG:GLPG1690; SIM: Simtuzumab; WAR: Warfarin; PRM: PRM151;NAC:N-acetylcysteine.). Figure S3. SUCRA ranking chart of the incidence of SAEs. Figure S4. The forest plot of consistency test of all-cause mortality. Figure S5. Forest plot of pairwise comparison of all-cause mortality, (PLA: Placebo; NIN: Nintedanib; PIR:Pirfenidone; SIL: Sildenafil; AMB: Ambrisentan; PAM: Pamrevlumab; BOS: Bosentan; MAC:Macitentan; IMA: Imatinib; SIM: Simtuzumab; WAR: Warfarin; NAC:N-acetylcysteine.). Figure S6. SUCRA ranking chart of all-cause mortality. Figure S7. The forest plot of consistency test of FVC (L) absolute change from baseline. Figure S8. Forest plot of pairwise comparison of FVC (L) absolute change from baseline. (PLA: Placebo; NIN: Nintedanib; PAM: Pamrevlumab; BOS: Bosentan; MAC: Macitentan; IMA:Imatinib; GLPG:GLPG1690;WAR:Warfarin; PRM: PRM151;NAC:N-acetylcysteine.). Figure S9. SUCRA ranking chart of FVC (L) absolute change from baseline. Figure S10. The forest plot of consistency test of FVC (% predicted)absolute change from baseline. Figure S11. Forest plot of pairwise comparison of FVC (% predicted) absolute change from baseline. (PLA: Placebo; NIN: Nintedanib; PIR: Pirfenidone; SIL: Sildenafil; AMB: Ambrisentan; PAM: Pamrevlumab; WAR:Warfarin; PRM: PRM151.). Figure S12. SUCRA ranking chart of FVC (% predicted) absolute change from baseline. Figure S13. The forest plot of consistency test of the proportion of patients with decline in FVC≥10% predicted. Figure S14. Forest plot of pairwise comparison of the proportion of patients with decline in FVC≥10% predicted.  (PLA:Placebo; NIN: Nintedanib; PIR: Pirfenidone; AMB: Ambrisentan; PAM: Pamrevlumab; WAR:Warfarin.). Figure S15. SUCRA ranking chart of the proportion of patients with decline in FVC≥10% predicted. Figure S16. The funnel chart of bias generation detected by Begg rank correlation. Figure S17. The funnel chart generated by Egger's test. Figure S18. Influence analysis results of the five main outcomes. Table S1. The search strategy of PubMed. Table S2. Quality evaluation of the 24 included studies. Table S3. Influence analysis results data of the incidence of SAEs. Table S4. Influence analysis results data of all-cause mortality. Table S5. Influence analysis results data of FVC (L) absolute change from baseline. Table S6. Influence analysis results data of FVC (% predicted)absolute change from baseline. Table S7. Influence analysis results data of the proportion of patients with decline in FVC≥10% predicted.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, X., Li, W., Luo, Z. et al. A comprehensive comparison of the safety and efficacy of drugs in the treatment of idiopathic pulmonary fibrosis: a network meta-analysis based on randomized controlled trials. BMC Pulm Med 24, 58 (2024). https://doi.org/10.1186/s12890-024-02861-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12890-024-02861-w

Keywords

BMC Pulmonary Medicine

ISSN: 1471-2466

Contact us