Clinical profiles and risk predictors of drug-induced liver injury from pirfenidone and nintedanib used to treat idiopathic pulmonary fibrosis: a real-world analysis of a tertiary Chinese hospital cohort combined with FAERS data mining

Introduction

Drug-induced liver injury (DILI) is among the more prevalent adverse drug reactions (ADRs), and in severe instances, it can result in acute liver failure or even death (1). In China, DILI constitutes a greater public health burden than in many Western countries, and its complex pathogenesis often involves immune-mediated mechanisms (2).

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease with a median survival of only 3–5 years after diagnosis (3,4). Pirfenidone and nintedanib are currently the only approved antifibrotic agents in the European Union and United States, and are widely prescribed across different healthcare settings without major differences between university and non-university hospitals (5-7). Both drugs slow lung function decline but differ in their adverse reaction profiles, notably including pharmacologic liver injury that requires regular monitoring (8). Clinical and real-world data suggest nintedanib generally has a similar or lower discontinuation rate than pirfenidone, and dose reductions do not appear to compromise its efficacy. These considerations highlight the importance of further real-world evaluation of hepatic safety profiles for both agents. The majority of these ADRs are gastrointestinal in nature and typically present with mild to moderate symptoms that can generally be managed effectively (9,10). Although systematic investigations into the ADRs of both drugs have been conducted, comprehensive analyses regarding some rare ADRs—such as drug-induced hepatic injury—remain insufficient due to limited observation periods and small sample sizes. Available data indicate that hepatic impairment resulting from either pirfenidone or nintedanib is characterized by elevated levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and occasionally total bilirubin (TBIL) levels (11). In addition, previous studies reported fatalities associated with severe liver injury due to pirfenidone in 2018 and 2019 (12,13). Subsequently, in 2020, the United Kingdom’s Medicines and Healthcare Products Regulatory Agency (MHRA) issued an alert indicating that pirfenidone poses a risk of serious liver injury, with an incidence rate estimated at approximately 1 in 100 to 1 in 1,000 (14). In the same year, a case of severe hepatotoxicity secondary to nintedanib was also documented (15). Although hepatic injuries induced by pirfenidone and nintedanib are relatively rare compared to other ADRs, continuous post-marketing safety monitoring of these two medications is particularly crucial given their widespread clinical use globally. This monitoring is essential for the early identification and prevention of potential hepatotoxicity risks.

In this study, we conducted a comparative analysis of liver injury cases associated with the use of antifibrotic drugs at a large tertiary hospital and examined reports of hepatic adverse events (AEs) in the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) for pirfenidone and nintedanib. We summarize the risk profile of these medications concerning liver injury from a pharmacovigilance perspective. Due to the limited number of DILI cases observed in patients treated with nintedanib during this period, our risk factor analysis primarily focused on pirfenidone to identify its potential risk factors. The findings from this study provide valuable insights into the risk assessment for clinical applications of antifibrotic drugs, aiding healthcare professionals in developing more precise prevention and treatment strategies. We present this article in accordance with the STROBE reporting checklist (available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-104/rc).

Methods

A tertiary medical center

Clinical data

Clinical data on patients hospitalized between October 2011 and December 2022 were collected. The data included variables such as gender, age, body mass index (BMI), duration of hospitalization, manifestations of liver injury, dosage of medication administered, number of comorbid underlying diseases, timing of medication initiation and discontinuation, occurrence time of liver injury, treatment course, history of acute liver disease or liver surgery, laboratory indicators [including ALT, AST, TBIL, albumin (ALB), and ALP], history of cardiovascular disease, diabetes mellitus history, smoking habits, alcohol consumption history, cancer history, hepatoprotective drug treatment regimens, and treatment outcomes. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of The First Affiliated Hospital of Guangzhou Medical University (approval No. ES-2024-K064-01). For the hospital-based retrospective cohort, the requirement for informed consent was waived by the ethics committee due to the retrospective nature of the study.

DILI severity grading criteria

Liver injury was diagnosed and graded according to the National Institutes of Health’s Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 criteria, ensuring standardized assessment of injury severity (16).

• Grading 1: ALT or AST >3 times the upper limit of normal (ULN) (for normal baseline values) or 1.5 to 3.0 times the baseline value (for abnormal baseline values); ALP >2.5× ULN (for normal baseline values) or 2.0 to 2.5 times the baseline value (for abnormal baseline values); TBIL >1.5× ULN (for normal baseline values) or 1.0 to 1.5 times the baseline value (for abnormal baseline values).
• Grading 2: ALT or AST 3 to 5 times ULN; ALP 2.5 to 5.0 times ULN; TBIL 1.5 to 3.0 times ULN.
• Grading 3: ALT or AST 5 to 20 times ULN; ALP 5 to 20 times ULN; TBIL 3.0 to 10 times ULN.
• Grading 4: ALT, ALP, and AST >20 times ULN; TBIL >10 times ULN.

DILI clinical staging criteria

DILI can be classified based on the R-value into three categories: hepatocellular injury type (R ≥5), mixed type (2< R <5), and cholestatic type (R ≤2) (17).

Inclusion and exclusion criteria

Inclusion criteria: (I) patients receiving drug therapy with pirfenidone or nintedanib; (II) levels of AST, ALT, ALP, and TBIL at admission did not indicate liver injury; (III) patients who met the clinical trial grading criteria for liver injury as defined by CTCAE v5.0, exhibiting more than one level of injury. Exclusion criteria: (I) hospitalization duration ≤48 hours; (II) evidence of liver injury prior to initiation of pirfenidone or nintedanib treatment; (III) absence of primary experimental data; (IV) patients under 18 years old. Ultimately, a total of 63 patients treated with pirfenidone met the inclusion criteria for natriuresis, while 4 patients treated with nintedanib also satisfied these criteria (Figure 1).

Figure 1 Patient screening process for inclusion in the analysis (source: tertiary hospital cohort).

Principle of control group matching

Control group patients were matched based on hospitalization duration (≥48 hours), age (>18 years), prior exposure to pirfenidone during hospitalization, and absence of pre-existing liver injury related to pirfenidone, to accurately compare liver injury risk. We matched four controls for each case group of patients. Once a patient has been successfully matched, they will no longer be considered as a potential match for subsequent case groups. In instances where more than four control patients are eligible for matching with a particular case, four control patients will be randomly selected from that pool.

Statistical analysis

Excel (Microsoft Corp., Redmond, WA, USA) was used for data collection, while SPSS version 27.0 (IBM Corp., Armonk, NY, USA) was employed for statistical analysis. Categorical variables were presented as counts and percentages. The impact of pirfenidone on liver injury was assessed through univariate analysis followed by multivariate conditional logistic regression modeling. Variables with P<0.05 in the univariate analysis were included in the multivariate conditional logistic regression to determine their association with the occurrence of pirfenidone-induced liver injury. Effects were evaluated by odds ratio (OR) along with 95% confidence interval (CI). All tests were two-sided, and P<0.05 was deemed statistically significant.

To contextualize our findings, a literature search was conducted in PubMed for studies published between 2020 and 2025 reporting on hepatotoxicity associated with pirfenidone and nintedanib (Table 1).

FAERS database

Sources of information

The FAERS database comprises seven sub-databases: Demographic Information (DEMO), Drug Information (DRUG), Adverse Event Information (REAC), Patient Outcome (OUTC), Reporting Sources (RPSR), Time to Error (THER), and Indications for Use of Drugs (INDI). FAERS database designed to collect data on AEs from across the globe. Researchers have the ability to access and leverage public data, which can be appropriately cleaned and anonymized in order to comply with ethical standards. Given its public accessibility and anonymized nature, the analysis of the FAERS database in this study did not require separate ethical approval or informed consent.

Data extraction and screening criteria

A comprehensive search of the FAERS database for adverse hepatic events was conducted from the first quarter of 2004 to the second quarter of 2024, with a specific focus on the drugs pirfenidone and nintedanib. These medications were identified as primary suspected causes of reported AEs. The screening process employed system organ class (SOCs) and preferred terms (PTs) derived from version 27.0 of the International Dictionary of Medical Terms. The retrieved data were subsequently sorted, cleaned, and analyzed for visualization purposes. Data processing was performed using SAS 9.4 to facilitate statistical analysis.

Data mining

This study utilized the reporting odds ratio (ROR) method to extract AE signals. The criteria for AE signals were number of reports ≥3 and ROR 95% CI lower limit >1. A larger ROR represents a stronger association of the target drug with a suspected AE.

Results

A tertiary medical center analysis result

We first report the findings from our tertiary medical center cohort, followed by FAERS database results to examine whether the clinical patterns observed in hospitalized patients were also reflected in large-scale real-world AE reports.

Fundamental patient information

The incidence of hepatic injury was 3.18% for pirfenidone (63 patients: 76.2% male; median age 63 years; median daily dose 1,200 mg) and 3.20% for nintedanib (4 patients: 75.0% female; median age 63.5 years; standard daily dose 300 mg). To contextualize these findings, we compared the characteristics of hepatotoxicity in our cohort with those from recent key studies, as summarized in Table 1.

Characteristics of pirfenidone dosing

Pirfenidone treatment lasted 1–44 days (median 9 days), with liver injury symptoms appearing 2–41 days after initiation (median onset 11 days). Most cases (66.7%) occurred within 2 weeks, presenting as acute DILI with shorter latency (Figure 2A). All 63 affected patients showed elevated liver function markers, and the most common single-day dose was 1,800 mg (Figure 2B).

Figure 2 Clinical presentation and management of pirfenidone-associated DILI (source: tertiary hospital cohort). (A) Time trend of drug-induced liver injury onset after pirfenidone initiation (N=63). The curve shows that most cases occurred within 2 weeks. (B) Distribution of CTCAE grades for DILI, stratified by daily pirfenidone dosage. The majority of cases occurred at a dosage of 1,800 mg/day, followed by 900 and 600 mg/day, with most events being Grade 2 in severity. (C) Association between CTCAE severity grades of liver injury and subsequent clinical outcomes. The majority of cases were moderate in severity, and most patients achieved recovery or improvement across all grades. (D) Utilization patterns of hepatoprotective agents in the cohort of 63 patients with DILI. Glutathione-based regimens were the most frequently administered (40 cases, 52.6%), followed by magnesium isoglycyrrhizinate (13 cases, 17.1%) and adenosylmethionine (10 cases, 13.2%). CTCAE, Common Terminology Criteria for Adverse Events; DILI, drug-induced liver injury.

Clinical staging and severity grading of DILI in patients with pirfenidone

Pirfenidone-related DILI was predominantly moderate in severity, with 63.5% of cases classified as grade 2 adverse reactions according to CTCAE criteria (Figure 2C). Higher grades were generally associated with lower daily doses, but no statistically significant correlation between injury severity and dosage was found.

Among 40 patients with complete biochemical data, 27 had cholestatic injury, 10 had hepatocellular injury, and 3 presented with a mixed injury pattern. Classification for Drug-Induced Autoimmune Hepatitis (DIAIH) could not be performed due to incomplete serological and histological data. Furthermore, liver injury pattern classification could not be performed in 23 patients due to missing ALP values, as the R value could not be calculated. Severity grading was conducted in all patients, irrespective of ALP availability (Figure 2C).

Causality assessment was performed for the 40 patients with complete data using the RUCAM. As shown in Table 2, all cholestatic cases were classified as “possible” (score ≥3), in accordance with the corresponding injury pattern-specific RUCAM criteria. Among patients with hepatocellular injury, 5 were categorized as “probable” and 5 as “possible”, while all mixed cases were “possible”. No cases fell into the “highly probable” or “unlikely” categories.

For the nintedanib group, RUCAM scoring was not performed due to the small number of cases and absence of key laboratory parameters required for R value calculation, precluding standardized causality assessment.

Management strategies and treatment adjustments following liver injury induced by pirfenidone

Of the 63 patients, 47 received hepatoprotective therapy—most commonly glutathione-based regimens—while 16 did not (Figure 2D). Overall, 3.2% achieved complete recovery, 46.0% improved, 23.8% showed no recovery, and 27.0% died. Among the 16 deceased patients, the causes of death were primarily related to severe pulmonary complications, including pneumonia, respiratory failure, sepsis, and acute exacerbations of underlying interstitial lung diseases; one case was associated with advanced malignant melanoma with metastases.

Statistical analysis of risk factors for pirfenidone

Univariate analysis identified seven variables with P<0.05: gender, age, BMI, comorbidity count, pre-existing liver disease, cardiovascular disease, and alcohol consumption (Table 3). Multivariate analysis showed BMI ≤23.9 kg/m² (OR =7.32), ≥4 comorbidities (OR =7.18), pre-existing liver disease (OR =3.31), and alcohol consumption (OR =4.52) as independent risk factors for pirfenidone-induced liver injury (Table 4).

To validate and contextualize these hospital-based findings, we subsequently analyzed post-marketing hepatic AE data from the FAERS database.

Results of FAERS database analysis

This section presents the FAERS analysis, aimed at determining whether similar demographic patterns and event profiles were present in a larger, global dataset.

Basic information on the reporting of hepatic AEs

Analysis of FAERS data identified 904 hepatic system-related AE reports for pirfenidone and 2,114 for nintedanib. Liver injury was more frequent in males than females for both drugs (pirfenidone: 55.4% vs. 36.2%; nintedanib: 49.5% vs. 34.0%), with median ages of 73 and 71 years, respectively. Most reports originated from physicians, were classified as serious, and occurred within 30 days of treatment initiation (Table 5).

From 2014–2016, pirfenidone had more hepatic AEs than nintedanib. For both drugs, AE reports rose initially then declined, peaking in 2016 for pirfenidone (122 cases) and in 2018 for nintedanib (225 cases) (Figure 3). In addition to descriptive trends, further signal detection analysis was performed to identify specific AE terms most strongly linked to each drug.

Figure 3 Reporting on years of AEs in the liver associated with pirfenidone and nintedanib (source: FAERS database). AEs, adverse events; FAERS, FDA Adverse Event Reporting System; FDA, Food and Drug Administration.

Liver AEs correlation analysis

Pirfenidone generated 59 hepatic system-related AE signals from 904 reports, with 5 positive risk signals—hepatic enzyme increased, liver function test increased, hepatotoxicity, blood bilirubin decreased, and liver function test decreased—accounting for 338 reports. Nintedanib yielded 75 signals from 2,114 reports, including 23 positive signals (1,634 reports). The most frequent were liver function tests, liver function test increased, gamma-glutamyltransferase abnormal, hepatic enzyme increased, and blood bilirubin decreased (Table 6; Figures 4,5).

Figure 4 Correlation analysis of positive AE signals in the liver system associated with pirfenidone (source: FAERS database). AE, adverse event; FAERS, FDA Adverse Event Reporting System; FDA, Food and Drug Administration; LCI, lower confidence interval; N, number of reported cases; PTs, preferred terms; ROR, reporting odds ratio; UCI, upper confidence interval.

Figure 5 Correlation analysis of positive AE signals in the liver system associated with nintedanib (source: FAERS database). AE, adverse event; FAERS, FDA Adverse Event Reporting System; FDA, Food and Drug Administration; LCI, lower confidence interval; N, number of reported cases; PTs, preferred terms; ROR, reporting odds ratio; UCI, upper confidence interval.

Discussion

Overall findings and patient characteristics

This study aimed to integrate retrospective tertiary hospital data with FAERS post-marketing surveillance findings to elucidate the clinical features and risk signals of DILI associated with pirfenidone and nintedanib. In our real-world cohort, the observed DILI incidence was approximately 3.2% for both agents. As detailed in Table 1, this finding is situated within a broad spectrum of reported incidences in the literature, which highlights significant variability depending on study design and likely reflects the inherent reporting biases in pharmacovigilance databases (18-24). In contrast to our incidence data, our FAERS analysis identified a stronger safety signal for nintedanib, which showed disproportionately higher reporting of severe hepatic AEs. This finding of an elevated risk with nintedanib is corroborated by a large Taiwanese cohort study (20). Crucially, our study addresses a key gap by providing the granular clinical details, such as CTCAE grading and time to onset, which are essential for risk characterization but are frequently unreported in the literature (Table 1).

Both hospital and FAERS datasets revealed a predominance of elderly male patients among DILI cases, consistent with previous real-world evidence suggesting that elderly males may have increased susceptibility to pirfenidone-related AEs and DILI in general (25,26). Conversely, a prospective study did not confirm age as an independent predictor, suggesting that risk profiles may be drug-specific (27). In the context of pirfenidone, diminished hepatic metabolic capacity and reduced tolerance to drug toxicity in older patients may indirectly increase DILI risk, even if chronological age is not a direct determinant.

Integrated analysis indicated that DILI induced by both agents predominantly presents as elevations in AST and ALT (28). However, FAERS signal mining identified important differences in AE spectra: pirfenidone signals were mainly related to liver enzyme changes, whereas nintedanib signals encompassed more severe outcomes, including bilirubin abnormalities, cirrhosis, hepatocellular carcinoma, and toxic hepatitis. These findings underscore the need for heightened vigilance regarding the potential severity of nintedanib-associated liver injury in clinical practice.

Clinical typing of pirfenidone-induced liver injury

Among 40 patients with pirfenidone-related DILI, cholestatic injury was the predominant pattern (67.5%), with elderly patients (≥61 years) representing the majority (66.7%). This pattern was consistent with WHO Safety Reporting Database analyses and was associated with higher mortality compared with hepatocellular or mixed types (17.5% vs. 2.5%) (29). The mean age of our DILI cohort was 61 years, indicating an elderly-dominated population. Given the slower recovery observed in cholestatic DILI, clinicians should exercise caution when prescribing pirfenidone to older adults.

Risk factors for pirfenidone-related DILI

Our analysis identified BMI ≤23.9 kg/m², ≥4 comorbidities, underlying liver disease, and alcohol history as significant risk factors. Low-BMI patients demonstrated higher DILI incidence and mortality, consistent with European studies linking underweight status to poorer outcomes (30). Multiple comorbidities often require polypharmacy, increasing the risk of hepatotoxic drug-drug interactions (31). Patients with hepatic impairment or alcohol use are especially vulnerable to accelerated DILI progression when exposed to hepatotoxic medications.

Analysis of pirfenidone and hepatoprotective agents

In our case-matched analysis, prophylactic hepatoprotective agents failed to reduce the incidence of DILI. The DILI rate was, in fact, numerically higher in the prophylactic cohort (50.0% vs. 17.3%), a finding likely attributable to a higher baseline prevalence of pre-existing liver disease in this group. These results therefore reinforce current guideline recommendations against the routine prophylactic use of these medications to mitigate DILI risk (32).

While this study did not assess therapeutic interventions for established DILI, current clinical practice dictates an individualized management strategy tailored to the injury phenotype and severity. For instance, magnesium isoglycyrrhizinate is indicated for severe acute hepatocellular or mixed DILI (typically CTCAE Grade 3–4) with marked ALT elevation. In contrast, bisabolol is generally reserved for milder, inflammatory cases (CTCAE Grade 1–2), while ursodeoxycholic acid remains the standard of care for cholestatic DILI characterized by hyperbilirubinemia (33-35). Prioritizing such a stratified, monotherapy-based approach is critical for effectively managing established DILI.

Clinical and regulatory implications

FAERS data indicate that nearly 80% of hepatic AEs emerge within 30 days of treatment initiation, a period associated with severe outcomes and readmissions. This underscores the need for intensive early monitoring. In regions with low pharmacovigilance awareness, standardized AE reporting and targeted healthcare provider education could improve patient outcomes and strengthen drug safety surveillance.

Limitations

This study acknowledges several limitations in its investigation of the hepatic adverse effects associated with pirfenidone and nintedanib. Firstly, the data sourced from the FAERS database predominantly arises from spontaneous reporting by a diverse array of contributors, which may introduce biases related to the quality and completeness of these reports. Specifically, there are regional disparities within medication-using populations, and the data available for Asia is notably limited, potentially impacting the generalizability of our findings. Secondly, the signals detected through the ROR method indicate only statistical associations between these drugs and AEs; they do not establish a definitive causal relationship. Consequently, these associations necessitate further examination through advanced analytical methodologies and large-scale clinical trials. Furthermore, our real-world study was constrained to a single-center retrospective analysis based on medical records with a limited sample size, which, by its nature, cannot replace the evidence strength of well-designed prospective studies. This limitation precluded us from including certain risk factors such as concomitant medication use and from systematically assessing for DIAIH, potentially underestimating its true incidence. Lastly, it is essential to note that the clinical data employed in this study primarily derive from hospitalized patients, suggesting that the actual incidence of adverse effects may be higher than reported. Despite limitations related to sample size, we contend that our findings are informative and contribute significantly to understanding clinical outcomes and underlying diseases associated with these therapeutic agents.

Conclusions

The findings of this study underscore the critical importance of monitoring pirfenidone and nintedanib due to their associated risks of liver injury. Our analysis of the FAERS database, along with real-world cases of AEs, highlights the necessity for cautious clinical application of these medications. In administering pirfenidone, particular attention should be directed towards patients with a BMI of 23.9 kg/m² or lower, those presenting with four or more comorbidities, individuals with a history of liver disease, and those who have a history of alcohol consumption. It is imperative to closely monitor their hepatic function and overall clinical condition.

Acknowledgments

The authors would like to thank all reviewers for their valuable comments.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-104/rc

Data Sharing Statement: Available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-104/dss

Peer Review File: Available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-104/prf

Funding: This work was supported by 2022 Special Fund for Hospital Pharmaceutical Research of Guangdong Province Hospital Association (No. YXKY202218), Guangzhou Municipal Science and Technology Bureau Joint Project (No. 2023A03J0370), Guangzhou Municipal Science and Technology Bureau Minsheng Science and Technology Research Plan Project (No. 201803010063).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-104/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of The First Affiliated Hospital of Guangzhou Medical University (approval No. ES-2024-K064-01). For the hospital-based retrospective cohort, the requirement for informed consent was waived by the ethics committee due to the retrospective nature of the study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Moreno-Torres M, Quintás G, Castell JV. The Potential Role of Metabolomics in Drug-Induced Liver Injury (DILI) Assessment. Metabolites 2022;12:564. [Crossref] [PubMed]
2. Li X, Tang J, Mao Y. Incidence and risk factors of drug-induced liver injury. Liver Int 2022;42:1999-2014. [Crossref] [PubMed]
3. Richeldi L, Collard HR, Jones MG. Idiopathic pulmonary fibrosis. Lancet 2017;389:1941-52. [Crossref] [PubMed]
4. Lederer DJ, Martinez FJ. Idiopathic Pulmonary Fibrosis. N Engl J Med 2018;378:1811-23. [Crossref] [PubMed]
5. McCormack PL. Nintedanib: first global approval. Drugs 2015;75:129-39. [Crossref] [PubMed]
6. Lancaster LH, de Andrade JA, Zibrak JD, et al. Pirfenidone safety and adverse event management in idiopathic pulmonary fibrosis. Eur Respir Rev 2017;26:170057. [Crossref] [PubMed]
7. Monteleone G. The management of Familial Pulmonary Fibrosis in different medical settings: Where does that leave us? An Italian nationwide survey. Sarcoidosis Vasc Diffuse Lung Dis 2024;41:e2024047. [Crossref] [PubMed]
8. Chianese M, Screm G, Salton F, et al. Pirfenidone and Nintedanib in Pulmonary Fibrosis: Lights and Shadows. Pharmaceuticals (Basel) 2024;17:709. [Crossref] [PubMed]
9. Chen CH, Lin HC, Wang YH, et al. The safety of nintedanib for the treatment of interstitial lung disease: A systematic review and meta-analysis of randomized controlled trials. PLoS One 2021;16:e0251636. [Crossref] [PubMed]
10. Fournier D, Jouneau S, Bouzillé G, et al. Real-world safety profiles of pirfenidone and nintedanib in idiopathic pulmonary fibrosis patients. Pulm Pharmacol Ther 2022;76:102149. [Crossref] [PubMed]
11. Two new drugs for idiopathic pulmonary fibrosis. Med Lett Drugs Ther 2014;56:123-4.
12. Benesic A, Jalal K, Gerbes AL. Acute Liver Failure During Pirfenidone Treatment Triggered by Co-Medication With Esomeprazole. Hepatology 2019;70:1869-71. [Crossref] [PubMed]
13. Verma N, Kumar P, Mitra S, et al. Drug idiosyncrasy due to pirfenidone presenting as acute liver failure: Case report and mini-review of the literature. Hepatol Commun 2018;2:142-7. [Crossref] [PubMed]
14. Agency MaHPR. Pirfenidone (Esbriet): risk of serious liver injury; updated advice on liver function testing - GOV.UK 2020. Available online: https://www.gov.uk/drug-safety-update/pirfenidone-esbriet-risk-of-serious-liver-injury-updated-advice-on-liver-function-testing
15. Librero Jiménez M, Heredia Carrasco C, Fernández Cano MDC. Severe hepatotoxicity secondary to nintedanib. Rev Esp Enferm Dig 2022;114:244-5. [Crossref] [PubMed]
16. Services DoHaH. Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Available online: https://ctep.cancer.gov/protocolDevelopment/electronic_applications/ctc.htm#ctc_50
17. Danan G, Teschke R. RUCAM in Drug and Herb Induced Liver Injury: The Update. Int J Mol Sci 2015;17:14. [Crossref] [PubMed]
18. Narváez J, Aguilar-Coll M, Roig-Kim M, et al. Efficacy, safety, and tolerability of antifibrotic agents in rheumatoid arthritis-associated interstitial lung disease: A systematic review and meta-analysis. Autoimmun Rev 2025;24:103804. [Crossref] [PubMed]
19. Chaudhuri N, Azuma A, Sroka-Saidi K, et al. Safety and Tolerability of Nintedanib in Patients with Fibrosing Interstitial Lung Diseases: Post-marketing Data. Adv Ther 2024;41:4581-90. [Crossref] [PubMed]
20. Liao KM, Chen CY. Risk of potential hepatotoxicity from pirfenidone or nintedanib in patients with idiopathic pulmonary fibrosis: results of a retrospective analysis of a large insurance database in Taiwan. Front Pharmacol 2024;15:1309712. [Crossref] [PubMed]
21. Sun X, Wang H, Zhan X, et al. Comparison of the safety profiles for pirfenidone and nintedanib: a disproportionality analysis of the US food and drug administration adverse event reporting system. Front Pharmacol 2024;15:1256649. [Crossref] [PubMed]
22. Barešić M, Novak S, Perković D, et al. Real world experience with nintedanib in connective tissue disease-related interstitial lung disease: a retrospective cohort study. Clin Rheumatol 2023;42:2897-903. [Crossref] [PubMed]
23. Mandovra NP, Vaidya PJ, Shah RS, et al. Factors Affecting Best-Tolerated Dose of Pirfenidone in Patients with Fibrosing Interstitial Lung Disease. J Clin Med 2023;12:6513. [Crossref] [PubMed]
24. Raschi E, Fusaroli M, Gatti M, et al. Liver Injury with Nintedanib: A Pharmacovigilance-Pharmacokinetic Appraisal. Pharmaceuticals (Basel) 2022;15:645. [Crossref] [PubMed]
25. He M, Yang T, Zhou J, et al. A real-world study of antifibrotic drugs-related adverse events based on the United States food and drug administration adverse event reporting system and VigiAccess databases. Front Pharmacol 2024;15:1310286. [Crossref] [PubMed]
26. Lucena MI, Andrade RJ, Kaplowitz N, et al. Phenotypic characterization of idiosyncratic drug-induced liver injury: the influence of age and sex. Hepatology 2009;49:2001-9. [Crossref] [PubMed]
27. Chalasani N, Bonkovsky HL, Fontana R, et al. Features and Outcomes of 899 Patients With Drug-Induced Liver Injury: The DILIN Prospective Study. Gastroenterology 2015;148:1340-52.e7. [Crossref] [PubMed]
28. Barratt SL, Mulholland S, Al Jbour K, et al. South-West of England’s Experience of the Safety and Tolerability Pirfenidone and Nintedanib for the Treatment of Idiopathic Pulmonary Fibrosis (IPF). Front Pharmacol 2018;9:1480. [Crossref] [PubMed]
29. Hunt CM, Yuen NA, Stirnadel-Farrant HA, et al. Age-related differences in reporting of drug-associated liver injury: data-mining of WHO Safety Report Database. Regul Toxicol Pharmacol 2014;70:519-26. [Crossref] [PubMed]
30. Ma Z, Li M, Wang Y, et al. Association of BMI with mortality in drug-induced liver injury. Eur J Gastroenterol Hepatol 2024;36:220-8. [Crossref] [PubMed]
31. Hou FQ, Zeng Z, Wang GQ. Hospital admissions for drug-induced liver injury: clinical features, therapy, and outcomes. Cell Biochem Biophys 2012;64:77-83. [Crossref] [PubMed]
32. Yu YC, Mao YM, Chen CW, et al. CSH guidelines for the diagnosis and treatment of drug-induced liver injury. Hepatol Int 2017;11:221-41. [Crossref] [PubMed]
33. Mao YM, Zeng MD, Chen Y, et al. Zhonghua Gan Zang Bing Za Zhi 2009;17:847-51. [Magnesium isoglycyrrhizinate in the treatment of chronic liver diseases: a randomized, double-blind, multi-doses, active drug controlled, multi-center study].
34. Li X, Zhou J, Chen S, et al. Role of bicyclol in preventing chemotherapeutic agent-induced liver injury in patients over 60 years of age with cancer. J Int Med Res 2014;42:906-14. [Crossref] [PubMed]
35. Nathwani RA, Kaplowitz N. Drug hepatotoxicity. Clin Liver Dis 2006;10:207-17. vii. [Crossref] [PubMed]