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Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.

ABSTRACT: Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findings from 206 patients with IPF and 36 controls. Differential protein expression analysis was also performed by edgeR and incorporated into the constructed network. We have successfully visualized the relationship between biomolecules and clinical findings with this approach. The IPF-specific network included modules associated with TGF-β signaling (TGFB1 and LRC32), fibrosis-related (A2MG and PZP), myofibroblast and inflammation (LRP1 and ITIH4), complement-related (SAA1 and SAA2), as well as serum markers, and clinical symptoms (KL-6, SP-D and fine crackles). Notably, it identified SAA2 associated with lymphocyte counts and PSPB connected with the serum markers KL-6 and SP-D, along with fine crackles as clinical manifestations. These results contribute to the elucidation of the pathogenesis of IPF and potential therapeutic targets.

SUBMITTER: Tomoto M

PROVIDER: S-EPMC10789725 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.

Tomoto Mei M Mineharu Yohei Y Sato Noriaki N Tamada Yoshinori Y Nogami-Itoh Mari M Kuroda Masataka M Adachi Jun J Takeda Yoshito Y Mizuguchi Kenji K Kumanogoh Atsushi A Natsume-Kitatani Yayoi Y Okuno Yasushi Y

Scientific reports 20240115 1

Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findin ...[more]

PMID: 38225283

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Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with poor prognosis and a high economic burden for individuals and healthcare resources. Studies of the costs associated with the efficiency of IPF medications are scarce. We aimed to conduct a network meta-analysis (NMA) and cost-effectiveness analysis to identify the optimum pharmacological strategy among all currently available IPF regimens.MethodsWe first performed a systematic review and network meta-analysis. We searched eight databases for eligible randomised controlled trials (RCTs) published, in any language, between January 1, 1992 and July 31, 2022, that investigated the efficacy or tolerability (or both) of drug therapies for the treatment of IPF. The search was updated on February 1, 2023. Eligible RCTs were enrolled, with no restriction on dose, duration, or length of follow-up, if they included at least one of: all-cause mortality, acute exacerbation rate, disease progression rate, serious adverse events, and any adverse events under investigation. A subsequent Bayesian NMA within random-effects models was performed, followed by a cost-effectiveness analysis using the data obtained from our NMA, by developing a Markov model from the US payer's perspective. Assumptions were checked by deterministic and probabilistic sensitivity approaches to identify sensitive factors. We prospectively registered the protocol (CRD42022340590) in PROSPERO.Findings51 publications comprising 12,551 participants with IPF were analysed for the NMA, and the findings indicated that pirfenidone and N-acetylcysteine (NAC) + pirfenidone were the most efficacious and tolerable. The pharmacoeconomic analysis showed that NAC + pirfenidone was associated with the highest potentiality of being cost-effective at willingness-to-pay (WTP) thresholds of US$150,000 and $200,000, on the basis of quality-adjusted life years (QALYs), disability-adjusted life years (DALYs) and mortality, with the probability ranging from 53% to 92%. NAC was the minimum cost agent. Compared with placebo, NAC + pirfenidone improved effectiveness by increasing QALYs by 7.02, and reducing DALYs by 7.10 and deaths by 8.40, whilst raising overall costs by $516,894.InterpretationThis NMA and cost-effectiveness analysis suggests that NAC + pirfenidone is the most cost-effective option for treatment of IPF at WTP thresholds of $150,000 and $200,000. However, given that clinical practice guidelines have not addressed the application of this therapy, large well-designed and multicentre trials are warranted to provide a better picture of IPF management.FundingNone.

Project description:BackgroundThe antifibrotics pirfenidone and nintedanib are both approved for the treatment of idiopathic pulmonary fibrosis (IPF) by regulatory agencies and are recommended by health technology assessment bodies. Other treatments such as N-acetylcysteine are used in clinical practice but have not received regulatory approval. No head-to-head trials have been conducted to directly compare the efficacy of these therapies in IPF.ObjectiveTo compare the efficacy of treatments for IPF.MethodsA systematic review was conducted up to April 2015. Phase II/III randomized controlled trials in adults with IPF were eligible. A Bayesian network meta-analysis (NMA) was used to compare pirfenidone, nintedanib, and N-acetylcysteine with respect to forced vital capacity (FVC) and mortality.ResultsNine studies were included in the NMA. For change from baseline in FVC, the NMA indicated that pirfenidone and nintedanib were more effective than placebo after 1 year (pirfenidone vs. placebo: difference = 0.12 liter (L), 95% credible interval [CrI] = 0.03-0.21 L; nintedanib vs. placebo: difference = 0.11 L, 95% CrI = 0.00-0.22 L). There was no evidence that N-acetylcysteine had an effect on FVC compared with placebo (N-acetylcysteine vs. placebo: difference = 0.01 L, 95% CrI = -0.15-0.17 L). Patients treated with pirfenidone also had a lower risk of experiencing a decline in percent predicted FVC of ≥ 10% over 1 year (odds ratio [OR]: 0.58, 95% CrI = 0.40-0.88), whereas there was no conclusive evidence of a difference between nintedanib and placebo (OR: 0.65, 95% CrI = 0.42-1.02). The NMA indicated that pirfenidone reduced all-cause mortality relative to placebo over 1 year (hazard ratio [HR]: 0.52, 95% CrI = 0.28-0.92). There was no evidence of a difference in all-cause mortality between nintedanib and placebo (HR: 0.70, 95% CrI = 0.32-1.55), or N-acetylcysteine and placebo (HR: 2.00, 95% CrI=0.46-8.62).ConclusionsOur primary analysis of the available evidence indicates that over 1 year, pirfenidone and nintedanib are effective at reducing lung-function decline, and pirfenidone may reduce the odds of experiencing a decline in percent predicted FVC of ≥10% compared with placebo in the first year of treatment. The results of our analysis also suggest that pirfenidone improves survival.DisclosuresFleetwood is an employee of Quantics Consulting. McCool and Glanville are employees of York Health Economics Consortium (YHEC). Quantics and YHEC received funding from F. Hoffmann-La Roche for conducting the systematic review and network meta-analysis reported in this paper. Edwards, Gsteiger, and Daigl are employees of F. Hoffmann-La Roche. Fisher was employed by InterMune UK, a wholly owned Roche subsidiary, until July 2015. He is currently employed by FIECON, which has received funding from F. Hoffmann-La Roche for consulting services. The systematic review and network meta-analysis reported in this paper were conducted by Fleetwood (Quantics Consulting) and McCool and Glanville (YHEC), funded by F. Hoffmann-La Roche. The original network analysis was funded by InterMune. Study concept and design were contributed by Edwards, Gsteiger, and Daigl, along with Fleetwood, McCool, and Glanville. Fleetwood, McCool, and Glanville collected the data, with assistance from Edwards, Gsteiger, and Daigl. Data interpretation was performed by Fleetwood and Fisher, with assistance from the other authors. The manuscript was written by Fleetwood, McCool, and Glanville, with assistance from Edwards, Daigl, and Fisher, and revised by all the authors.

Dataset Information

Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.

Publications

Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.

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