Interstitial lung disease with antibody–drug conjugates: a real-world pharmacovigilance study based on the FAERS database during the period 2014

Abstract

Background:

Antibody–drug conjugates (ADCs) combine the targeted nature of monoclonal antibodies with the potent efficacy of small-molecule cytotoxic drugs. However, they also carry unique safety risks, including lung toxicity.

Objective:

To conduct a systematic review and analysis of ADC-related interstitial lung disease (ILD) incidence, characteristics, and risk factors to optimize safe and effective clinical use.

Design:

ADC-related ILD reports from the FDA Adverse Event Reporting System (FAERS) database between January 2014 and March 2023 were analyzed.

Methods:

ADC-related ILD reports were retrieved from the FAERS database. Statistical analyses were conducted using reporting odds ratio (ROR) and information components (ICs). The lower limit of the 95% confidence interval (CI) was set for ROR (ROR025) >1 or IC (IC025) >0, and statistical significance was determined based on a minimum of three reports.

Results:

The study analyzed the statistical data on ADC-induced ILDs (1277 cases). Trastuzumab deruxtecan was reported to be the most frequent (38.4%). Among the 33 preferred terms (PTs) in standardized MedDRA queries (SMQ) = “Interstitial lung disease,” the three most common were as follows: ILD (40.6%), pneumonitis (27.9%), and acute respiratory distress syndrome (ARDS) (7.6%). Trastuzumab deruxtecan showed the strongest association with ILD (PT) and pneumonitis, whereas ARDS was associated with four different drugs. The median time to onset of ADC-related ILDs was 51 days (interquartile range (IQR), 16–196), with ARDS having the earliest median time to onset at 15 days (IQR, 6–52). The onsets of pneumonitis, ILD, lung infiltration, and pulmonary toxicity were similar. More than 26% of ADC-related ILD cases result in death, with ARDS having the highest mortality rate of 65.0%.

Conclusion:

ADCs are associated with an increased risk of pulmonary adverse events, such as ILDs, with significant differences between drugs and varying mortality rates for different adverse events, necessitating distinct monitoring and appropriate management.

Plain language summary

A study on the risk of lung diseases associated with antibody-drug conjugates (ADCs) cancer treatment

Why was this study important? Antibody drug conjugates (ADCs) represent a new drug for cancer treatment, using a “targeting device” (antibody) to locate the cancer cells and “powerful medicine” (chemotherapy drug) to destroy them. However, this method can sometimes cause lung injuries. Understanding how common these lung problems are, what they look like, and who is most susceptible is crucial for ensuring patient safety and effective treatment. What did researchers do? They examined reports related to ADC-induced lung problems in a U.S. system that records drug side effects (which we’ll call the FDA Adverse Event Reporting System) from January 2014 to March 2023. What were the findings? Among the 1,277 cases of lung problems caused by ADCs, Trastuzumab deruxtecan, an ADC drug, was the most common. These lung problems mainly involved three conditions: inflammation in the lungs (pneumonia), hardening and disease of lung tissue (interstitial lung disease), and sudden respiratory distress (acute respiratory distress syndrome). Among them, acute respiratory distress syndrome had the highest mortality rate. What does this mean? Using ADCs for cancer treatment may pose a risk of lung problems, with varying degrees of risk and severity depending on the specific drug. Therefore, it is necessary to closely monitor and manage patients when using these treatments.

Keywords

antibody–drug conjugate FAERS database interstitial lung disease pharmacovigilance analysis real-world study

Introduction

Antibody–drug conjugates (ADCs) synergistically harness the strength of targeted selective antibodies and potent cytotoxic drugs, thereby yielding robust antitumor efficacy. This innovative amalgamation effectively curtails the off-target side effects inherent to small-molecule cytotoxic drugs while preserving their tumor-suppressing attributes.¹ The intricate molecular blueprint and mode of operation underlying ADC drug evolution combine the formidable tumor cell eradication of conventional chemotherapy with the precision accuracy of antibody-based drugs.² These attributes have attracted increasing interest in recent years.

In 2000, the United States Food and Drug Administration (FDA) marked a significant milestone by approving ADC drugs for treating acute myeloid leukemia.³ By July 2023, 14 ADCs had been approved for therapeutic use,^4
–7 effectively targeting various hematological tumors and solid malignancies such as breast cancer and gastric cancer. Noteworthy members include: brentuximab vedotin, ado-trastuzumab emtansine, polatuzumab vedotin-piiq, enfortumab vedotin, tisotumab vedotin-tftv, gemtuzumab ozogamicin, inotuzumab ozogamicin, trastuzumab deruxtecan, sacituzumab govitecan, loncastuximab tesirine, disitamab vedotin, mirvetuximab soravtansine, and cetuximab saratolacan.

While administering ADC drugs, the associated concerns include hematological toxicity,⁸ cardiotoxicity,⁹ pulmonary toxicity,¹⁰ hepatotoxicity,¹¹ and ocular toxicity,¹² all of which have received significant attention. Drug-related lung toxicity, notably interstitial lung disease (ILD), has emerged as a concern in the ADC clinical trials. Notable instances include the T-DM1, DS-8201, and DESTINY-Lung01 trials, in which cases of ILD have been documented, even leading to fatalities.^13
–15 Data from 169 clinical trials involving 22,492 patients were collated for a meta-analysis of adverse events linked to ADC treatment. The study revealed that the incidence of adverse events in the respiratory system surpassed 20%, and the top five causes of death related to ADC treatment were associated with the respiratory system, notably ILD.¹⁶

Furthermore, an increasing number of cases of ADC-associated pulmonary toxicities have emerged in clinical practice and clinical trials. Notably, the potential risks associated with this paradigm shift have not been thoroughly assessed in prior research endeavors. In light of this, a pharmacovigilance study was undertaken utilizing the Adverse Event Reporting System Database of the US Food and Drug Administration (FAERS), with the intent of meticulously uncovering potential lung toxicities attributed to ADCs.

Therefore, the objective of this study was to comprehensively outline the lung toxicities associated with ADCs, both in their entirety and within specific drug classes. This study has aimed to provide substantial insights to guide optimal treatment regimens in clinical practice.

Materials and methods

Data sources

We analyzed the FAERS database to investigate pulmonary toxicity associated with ADCs and explore potential differences in lung toxicities between various ADCs. The FAERS is a publicly accessible safety report database provided by patients, healthcare professionals, and pharmaceutical companies. Adverse reactions reported in the FAERS database were coded based on PT codes from the Medical Dictionary for Regulatory Activities (MedDRA), with different PTs grouped into standardized MedDRA queries (SMQs). The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)¹⁷ statement (Table S1).

Data extraction

To identify pulmonary adverse reactions, we extracted Preferred Terms from MedDRA (version 24.1, International Council for Harmonisation of Technical equirements for Pharmaceuticals for Human Use (ICH)) associated with the System Organ Class (SMQ) “Interstitial lung disease.” In the FAERS database, we used the following ADCs (brentuximab vedotin; ado-trastuzumab emtansine; polatuzumab vedotin-piiq; enfortumab vedotin; tisotumab vedotin-tftv; gemtuzumab ozogamicin; inotuzumab ozogamicin; trastuzumab deruxteca; sacituzumab govitecan; loncastuximab tesirine; disitamab vedotin; mirvetuximab soravtansine; cetuximab saratolacan) as keywords to retrieve reports between January 1, 2014, and March 31, 2023.

Data deduplication

Data deduplication was conducted on the extracted data (Figure 1), which depicts the deduplication process. Duplicate entries and reports representing the same case were excluded. Only the latest version of each case or report was retained to ensure that duplicates did not influence the analyses. Drug–event combinations considering immune checkpoint inhibitors (ICIs) and adverse events (AEs) were established. Subsequently, only AE cases or reports where the drug’s role was labeled as “suspected” were included for further analysis.

Figure 1.

Flowchart of report selection.

Statistical analysis

We utilized the reporting odds ratio (ROR) and IC techniques to detect signals of adverse drug events. The ROR measures the relative frequency of AEs under drug exposure, whereas the IC integrates the prevalence of drug use with the frequency of AEs to offer a comprehensive assessment considering factors such as drug exposure and the reporting of AEs. A drug is considered to have a statistically significant association with its related AEs if it has at least three records of AEs and if either the lower limit of its 95% CI for the ROR (ROR025) exceeds 1 or the lower limit of its 95% CI for the IC (IC025) is above 0, as shown in Table 1.

Table 1.

Disproportionality analysis based on a two-by-two contingency table.

Drug	Target adverse events	Other adverse events	Total
Target drug	a (N_observed)	b	N_drug = a + b
Other drugs	c	d	c + d
Total	N_event = a + c	b + d	N_total = a + b + c + d
ROR = (N_observed + 0.5)/(N_expected + 0.5); IC = log2[(N_observed + 0.5)/(N_expected + 0.5)]; N_expected = N_drug * N_event/N_total;

N_expected, the number of records expected for the selected drug-adverse event combination; N_observed, the observed number of records for the selected drug-adverse event combination; N_drug, the total number of records for the selected drug; N_event, the total number of total records for the selected adverse event; N_total, the total number of records in the database.

Drug classification criteria

As of July 2023, 14 ADCs have been approved for tumor treatment. Belantamab mafodotin, which was withdrawn from the market on November 22, 2022, and drugs with insufficient data (disitamab vedotin, mirvetuximab soravtansine, and cetuximab saratolacan) were excluded from this study. Currently, approximately 6–8 cell toxins used in clinical trials or marketed ADC drugs are of natural origin. These include DNA synthesis inhibitors (e.g., carboplatin and adriamycin), topoisomerase inhibitors, RNA polymerase 2 inhibitors (e.g., camptothecin derivatives and alpha-amanitin), which can be summarized as nucleic acid synthesis inhibitors, and microtubule protein inhibitors (e.g., auristatin-based olisthocins and derivatives of maytansine) as another class.

The remaining 10 drugs included in this study are divided into two groups based on the mechanism of action of the payload. Group 1 included drugs with microtubule inhibitors as payloads (e.g., brentuximab vedotin, ado-trastuzumab emtansine, polatuzumab vedotin-piiq, enfortumab vedotin, and tisotumab vedotin-tftv), and Group 2 included drugs with nucleic acid synthesis inhibitors as payloads (e.g., gemtuzumab ozogamicin; inotuzumab ozogamicin; trastuzumab deruxtecan; sacituzumab govitecan; loncastuximab tesirine).

Descriptive analysis

We conducted a descriptive analysis focusing on clinical characteristics, including patient sex, age group, report origin country (referring to the country where the AEs were reported, not the patient’s nationality), outcome, treatment indication, and report type. Specifically, we defined the time of onset of ILD related to anticancer drugs (ADCs) as the time elapsed from the start of treatment to the onset of the event.

Results

Descriptive analysis of ADC-related ILD cases

Between the first quarters of 2014 and 2023, 13,703,053 reports were extracted from the FAERS database and screened to obtain 11,892,405 reports. Among these, 86,161 reports were related to ADCs. Ultimately, we obtained 1277 reports on ILD (Figure 1). This allowed us to compile statistical data regarding ADC-related ILD over the past 9 years (Table 2).

Table 2.

Characteristics of reports with ADC-related ILD (SMQ) events sourced from the FAERS database (January 1, 2014–March 31, 2023).

Clinical characteristics	Group 1	Group 2	Total
Clinical characteristics	(n = 681)	(n = 596)	(n = 1277)
Age
Median (Min, Max)	61 (4, 87)	60 (5, 90)	60 (4, 90)
<18 years (%)	23 (3.4)	12 (2.0)	35 (2.7)
18–65 years (%)	259 (38.0)	152 (25.5)	419 (32.8)
⩾65 years (%)	169 (24.8)	105 (17.6)	247 (19.3)
Missing (%)	230 (33.8)	327 (54.9)	576 (45.1)
Gender (%)
Male	220 (32.3)	91 (15.3)	311 (24.4)
Female	352 (51.7)	356 (59.7)	708 (55.4)
Missing	109 (16.0)	149 (25.0)	258 (20.2)
Indications (%)
Breast cancer	172 (25.3)	320 (53.7)	492 (38.5)
Lymphoma	346 (50.8)	7 (1.2)	353 (27.6)
Hematologic malignancies	7 (1.0)	52 (8.9)	59 (4.6)
Bladder cancer	47 (6.9)	5 (0.5)	52 (4.1)
Gastric carcinoma	0	37 (6.2)	37 (2.9)
Other	18 (2.6)	32 (5.4)	50 (3.9)
Missing	91 (13.4)	143 (24)	234 (18.3)
Reported countries (%)
United States	192 (28.2)	346 (58.0)	538 (42.1)
Japan	131 (19.2)	79 (13.3)	210 (16.4)
France	47 (6.9)	35 (5.9)	82 (6.4)
Great Britain (UK)	24 (3.5)	12 (2.0)	36 (2.8)
Germany	21 (3.1)	12 (2.0)	33 (2.6)
Other country	149 (21.9)	99 (16.6)	248 (19.4)
Missing	117 (17.2)	13 (2.2)	130 (10.2)
Reported year (%)
2014	40 (5.9)	7 (1.2)	47 (3.7)
2015	53 (7.8)	2 (0.3)	55 (4.3)
2016	58 (8.5)	7 (1.2)	65 (5.1)
2017	36 (5.3)	4 (0.7)	40 (3.1)
2018	43 (6.3)	3 (0.5)	46 (3.6)
2019	57 (8.4)	8 (1.3)	65 (5.1)
2020	75 (11.0)	21 (3.5)	96 (7.5)
2021	94 (13.8)	115 (19.3)	209 (16.4)
2022	117 (17.2)	224 (37.6)	341 (26.7)
2023 Q1	108 (15.9)	205 (34.4)	313 (24.5)
Type of reporter (%)
Health professional	446 (65.5)	290 (48.7)	736 (57.6)
Non-health professional	64 (9.4)	13 (2.2)	77 (6.0)
Missing	171 (25.1)	293 (49.2)	464 (36.3)

Group 1: Using microtubule inhibitors as their payloads (Brentuximab vedotin, Ado-trastuzumab emtansine, Polatuzumab vedotin-piiq, Enfortumab vedotin, Tisotumab vedotin-tftv, a total of five drugs).

Group 2: Using nucleic acid synthesis inhibitors as their payloads (gemtuzumab ozogamicin, inotuzumab ozogamicin, trastuzumab deruxtecan, sacituzumab govitecan, loncastuximab tesirine, a total of five drugs).

ADC, antibody–drug conjugates; FAERS, FDA adverse event reporting system; ILD, interstitial lung disease; SMQ, standardized MedDRA queries.

Among all of the ADCs reports, we found 1277 cases of ILD, accounting for 1.49% of all AEs. The age distribution of patients ranged from 4 to 90 years old, with a median age of 60 years. We divided the patients into three age groups and found that the number of patients aged between 18 and 65 years (N = 419, 32.8%) was the highest. The proportion of females (N = 708, 55.4%) was higher than that of males (N = 311, 24.4%).

Breast cancer (38.5%, 492/1277), lymphomas (27.6%, 353/1277), hematological malignancies (4.6%, 59/1277), and bladder cancer (4.1%, 52/1277) accounted for the majority of ADC-treated tumors. From a geographical perspective, the United States had the highest number of cases (538, 42.1%) and the highest proportion of professional healthcare personnel in the reporting population (736, 57.6%).

Disproportionality analysis of ADCs drug-related ILD

We conducted a disproportionality analysis of reports of ILD, including PTs with at least three cases, and found that the incidence and association of ILD with different ADC drugs were not identical (Figure 2). The frequency of ILD reports for ADCs was significantly higher when compared to the entire database (Table 3), with a ROR (ROR 025, ROR 975) of 5.38 (5.08, 5.68), and an IC (IC025, IC975) of 2.43 (2.33, 2.49).

Figure 2.

The number of cases of ILD with different ADCs.

Table 3.

Disproportionality analysis results associated with different ADCs.

Drug group	Agent	N (%)	ROR	ROR025	ROR975	IC	IC025	IC975
Group 1	Brentuximabvedotin	346 (24.7%)	4.95	4.45	5.51	2.31	2.13	2.44
	Ado-trastuzumab emtansine	230 (16.4%)	3.44	3.02	3.92	1.78	1.57	1.94
	Polatuzumab vedotin-piiq	95 (6.8%)	2.73	2.23	3.34	1.45	1.11	1.70
	Enfortumab vedotin	68 (4.9%)	4.57	3.60	5.81	2.19	1.79	2.48
	Tisotumab vedotin-tftv	1 (0.1%)	—	—	—	—	—	—
Group 2	Gemtuzumab ozogamicin	42 (3.0%)	3.20	2.36	4.34	1.68	1.17	2.04
	Inotuzumab ozogamicin	35 (2.5%)	2.36	1.69	3.29	1.24	0.68	1.64
	Trastuzumab deruxtecan	538 (38.4%)	27.86	3.60	30.43	4.80	4.66	4.90
	Sacituzumab govitecan	43 (3.1%)	2.18	25.51	2.94	1.13	0.62	1.49
	Loncastuximab tesirine	4 (0.3%)	3.92	1.46	10.53	1.97	0.21	3.05
Total		1277	5.38	5.08	5.69	2.43	2.33	2.49

ADC, antibody–drug conjugates; ILD, interstitial lung disease; ROR, reporting odds ratio.

Group 1 had more ILD reports (Group 1 = 740, 57.9% vs Group 2 = 622, 48.7%), among which brentuximab vedotin (N = 346, 24.7%) had the most ILD in Group 1, whereas in Group 2, trastuzumab deruxtecan (N = 538, 38.4%) had the most ILD reports among all ADC drugs. Furthermore, trastuzumab deruxtecan showed the strongest signal for ILD (SMQ) (IC025/ROR025 = 4.66/3.60), followed by brentuximab vedotin (IC025/ROR025 = 2.13/4.45) and enfortumab vedotin (IC025/ROR025 = 1.79/3.60). As fewer than three cases of ILD were reported for tisotumab vedotin-tftv, it was not included in the discussion.

Spectrum of pulmonary AEs based on PTs for ADCs

As the AE names in the FAERS database are recorded in the form of PT, the same AEs may have multiple similar PTs. To reduce the miss rate, this study first searched for “Interstitial lung disease” events based on SMQ and then conducted a secondary analysis based on all of the included PTs. A total of 34 PTs were retrieved, of which 15 were related to ADCs (IC025 > 0; ROR025 > 1; Table 4). The five most common ILD-related AEs were ILD (N = 550, 40.6%), pneumonitis (N = 378, 27.9%), ARDS (N = 103, 7.6%), pulmonary toxicity (N = 91, 6.7%), and lung infiltration (N = 46, 3.4%). The strongest signal was observed for pneumonitis (IC025/ROR025 = 3.08/10.53), followed by ILD (IC025/ROR025 = 2.87/8.04), pulmonary toxicity (IC025/ROR025 = 2.86/11.37), lung opacity (IC025/ROR025 = 2.78/14.07), and ARDS (IC025/ROR025 = 1.79/5.27). In addition, 9 other PTs were related to ADCs, whereas the remaining 18 PTs did not show clear signals.

Table 4.

Disproportionality analysis for ADC based on specific PTs.

PT	a	b	c	d	N (%)	ROR	ROR025	ROR975	IC	IC025	IC975
Pneumonitis	378	92,907	15,461	37,349,077	378 (27.9)	9.51	10.53	8.58	3.25	3.08	3.37
Interstitial lung disease	550	92,767	26,918	37,337,620	550 (40.6)	8.04	8.75	7.38	3.01	2.87	3.11
Pulmonary toxicity	91	93,174	3698	37,360,840	91 (6.7)	9.24	11.37	7.5	3.21	2.86	3.46
Lung opacity	36	93,218	1159	37,363,379	36 (2.7)	10.1	14.07	7.25	3.34	2.78	3.73
Acute respiratory distress syndrome	103	93,148	9300	37,355,238	103 (7.6)	4.34	5.28	3.58	2.12	1.79	2.35
Radiation pneumonitis	22	93,231	1427	37,363,111	22 (1.6)	5.55	8.45	3.64	2.47	1.76	2.97
Lung infiltration	46	93,208	4023	37,360,515	46 (3.4)	4.43	5.92	3.31	2.15	1.66	2.5
Immune-mediated lung disease	9	93,244	461	37,364,077	9 (0.7)	5.34	10.32	2.76	2.42	1.28	3.18
Organizing pneumonia	27	93,227	2874	37,361,664	27 (2.0)	3.61	5.27	2.47	1.85	1.21	2.3
Eosinophilic pneumonia acute	7	93,245	416	37,364,122	7 (0.5)	4.87	10.29	2.31	2.29	0.98	3.14
Diffuse alveolar damage	7	93,245	595	37,363,943	7 (0.5)	3.74	7.88	1.78	1.9	0.6	2.76
Sarcoidosis	17	93,235	2705	37,361,833	17 (1.3)	2.42	3.9	1.5	1.28	0.46	1.84
Pulmonary alveolar hemorrhage	17	93,235	3045	37,361,493	17 (1.3)	2.18	3.51	1.35	1.12	0.31	1.69
Restrictive pulmonary disease	6	93,246	648	37,363,890	6 (0.4)	3.07	6.86	1.37	1.62	0.2	2.53
Pulmonary fibrosis	40	93,215	10,101	37,354,437	40 (2.9)	1.57	2.14	1.15	0.65	0.13	1.03

ADC, antibody–drug conjugates; PT, preferred terms; ROR, reporting odds ratio.

Regarding the individual drugs, there were differences in the frequency and association of adverse reactions with different ADCs (Figure 3). Among these, trastuzumab deruxtecan (IC025 = 5.75) had the strongest correlation with ILD, followed by enfortumab vedotin (IC025 = 1.92), adotrastuzumab emtansine (IC025 = 1.75), and brentuximab vedotin (IC025 = 1.27). Trastuzumab deruxtecan (IC025 = 4.90) had the strongest correlation with pneumonitis, followed by adotrastuzumab emtansine (IC025 = 2.27) and brentuximab vedotin (IC025 = 2.81). Four drugs were associated with ARDS: gemtuzumab ozogamicin (IC025 = 2.76), brentuximab vedotin (IC025 = 2.18), inotuzumab ozogamicin (IC025 = 1.43), and trastuzumab deruxtecan (IC025 = 0.44). In addition, signals were detected in four drugs for pulmonary toxicity and lung infiltration, and in three drugs for lung opacity (Figure 3). However, because the fatality risk and incidence rates for these three AEs (pulmonary toxicity and lung infiltration, lung infiltration, and lung opacity) were relatively low, we did not further investigate them.

Figure 3.

The risk assessment of different pulmonary toxicities (PTs) in patients treated with different ADCs based on IC025.

Time to onset analysis of ADC-related ILD and other pulmonary AEs

We observed that more than 50% of ADC-related ILDs occurred within the first 2 months after initiating ADC treatment (Figure 4(a)), with a median onset time of 51 days (IQR 16–196) (Figure 4(b)).

Figure 4.

Time to onset for ADC-related ILD. (a) The proportion of onset time of ADC-related ILD. (b) Median (interquartile range) time to onset of pulmonary AEs (PTs) detected as significant signals.

Based on the PTs, we analyzed the time to onset of AEs with significant signals and found that ARDS had the earliest onset time, with a median time (IQR) of 15 (6–52) days, whereas lung opacity had the latest onset time at 160 (76–215) days. The onset times of pneumonitis, ILD, lung infiltration, and pulmonary toxicity were similar (Figure 4(b)).

Outcome of AEs

More than 26% of patients with ADC-related pulmonary AEs died. Although these AEs may not be the direct cause of death, when comparing the differences between fatal and nonfatal cases may provide clinical clues for improving patient outcomes. In the prognostic analysis, patients with ARDS had the highest mortality rate at 65.0% (67/103), whereas those with lung opacity had the lowest mortality rate at 16.7% (6/36).

The most common AE, ILD, had a fatality rate of 25.8% (142/550), which was similar to that of the other three adverse events (Figure 5). This suggests that, despite the differences between these AEs, their impacts on patient outcomes may be similar.

Figure 5.

Proportions of fatalities for ILD detected as significant signals.

Discussion

ADCs have shown promise in cancer therapy by enabling targeted delivery of drugs to cancer cells, enhancing tumor prognosis, and minimizing the adverse effects typically associated with chemotherapy. Nevertheless, concerns regarding ADC-induced lung toxicity have become increasingly important. This study has used the Food and Drug Administration Adverse Event Reporting System (FAERS) database to examine ADC-related pulmonary toxicity and identify potential risk factors, thereby paving the way for safer utilization of ADCs in the future. Based on the findings of this study, the following observations were made.

Population distribution characteristics of ADC-related ILD

The median age of the patients was 60 years, with the majority aged between 18 and 65 years (N = 419; 32.8%). Female patients (N = 708, 55.4%) outnumbered male patients (N = 311, 24.4%). Among all ADC treatment cases, breast cancer accounted for the largest proportion (38.5%, 492/1277), followed by lymphoma (27.6%, 353/1277). It was further observed that female patients were significantly more affected than male patients, which could be attributed to several factors: (1) ADC drugs are commonly used in the treatment of breast cancer and gynecological tumors, which are more prevalent in women; (2) women have a higher risk of developing autoimmune and chronic diseases, including ILD, possibly due to hormone levels, immune response mechanisms, and genetic polymorphisms; and (3) women may have a higher sensitivity and susceptibility to ADC drugs. The mechanism of action of ADC drugs involves targeted antibody recognition and effective drug release.^18
–21 Women may display differences in immune response and target expression, resulting in a more sensitive reaction to ADC drugs. However, a larger proportion of the elderly population experienced ADC-related ILD, which could be attributed to the following reasons: (1) structural changes in the pulmonary tissue occur in the elderly, including decreased alveolar elasticity, reduced lung compliance, apoptosis, and remodeling of bronchial epithelial cells. These changes may increase the lungs’ sensitivity to ADC drugs, making interstitial pneumonia more likely to occur; (2) elderly individuals have compromised immune system function and reduced pathogen clearance ability, potentially increasing the patient’s susceptibility to pulmonary disease induced by ADC drugs^15,22
–24; (3) older individuals often have multiple comorbidities such as chronic obstructive pulmonary disease, which may elevate the risk of ADC-induced interstitial pneumonia^13,25
–27; (4) metabolic and excretion capacities may be diminished in elderly patients, leading to a prolonged half-life of ADC drugs and drug accumulation in the body, thereby increasing the risk of toxicity.

Correlation between trastuzumab deruxtecan and ILD

This study found a strong correlation between trastuzumab deruximab use and ILD. The pathological and physiological mechanisms underlying interstitial pneumonia caused by trastuzumab deruxtecan may involve multiple mechanisms. First, the anti-HER2 monoclonal antibody component of trastuzumab deruxtecan may bind to certain cell-surface antigens in the lungs, triggering an immune response and leading to pulmonary inflammation and injury.^28,29 Second, the cytotoxic drug components of ADC drugs may directly damage pulmonary tissue, resulting in pulmonary inflammation and scar formation.^30,31 In addition, factors such as underlying lung disease, smoking history, drug interactions, and other variables may affect the occurrence and development of pulmonary toxicity. It is important to note that interstitial pneumonia is a disease that involves inflammation and fibrotic changes in the lung interstitium and alveolar cavity, including the alveolar epithelial cells, capillary endothelial cells, basal membrane, and tissues around the blood and lymphatic vessels. Ultimately, this leads to pulmonary interstitial fibrotic changes, causing a loss of pulmonary alveolar-capillary function. In summary, trastuzumab deruxtecan may cause interstitial pneumonia through multiple mechanisms.

Correlation between gemtuzumab ozogamicin and ARDS

ARDS is primarily related to widespread injury and edema of the alveolar membrane and endothelial cells. Injury and edema may be caused by various factors. In current clinical trials, ARDS was not a common complication of gemtuzumab ozogamicin. However, we found a correlation between gemtuzumab ozogamicin and ARDS, suggesting that gemtuzumab ozogamicin may play a role in the occurrence and development of ARDS. The released cellular toxins of gemtuzumab ozogamicin may damage endothelial and alveolar epithelial cells,^32
–34 leading to increased permeability of the alveolar membrane and exudation of protein-rich fluid into the alveolar cavity, resulting in pulmonary edema. This may lead to an increased shunt in the lungs, causing hypoxemia and triggering ARDS.³⁵ In addition, mylotarg may cause tissue injury and inflammatory responses in the lungs, leading to alveolar collapse and atelectasis, reduced lung volume, and decreased lung compliance, further exacerbating respiratory distress. Future research should explore the mechanism of action of ADC drugs in lung tissue injury to understand how ADC drugs cause damage and inflammatory responses in lung cells.

The onset time and outcomes of ADC-related ILD and other pulmonary AEs

Although the median onset time of ADC-related pulmonary AEs in different treatment regimens was generally similar, mostly concentrated in the first 2 months, the median onset time of ADCs (especially gemtuzumab ozogamicin)-induced ARDS was very short (15 days), and the mortality rate was very high (65.0%). It is worth noting that major observational studies have shown that the in-hospital mortality rate of patients is between 35% and 45%,^36,37 while the data in this study are much higher at 65.0%. This higher average mortality rate may be attributed to prior use of chemotherapy drugs, impaired immune function, advanced age, comorbidities, poor nutritional status, and other factors.

Toxicity mechanisms and adverse reaction variability in ADCs

As modular drugs, ADCs comprise three main components: payload, linker, and antibody, each of which significantly affects their toxicity profiles.³⁸ The payload, typically a small cytotoxic molecule, directly influences the adverse reactions induced by both off- and on-target effects of ADCs.^39,40 The stability of the linker is crucial for the precise delivery of the payload within or near tumor cells, with insufficient or excessive stability potentially leading to adverse effects.^41,42 In addition, the choice of antibody affects the toxicity of ADCs because variations in target expression within non-malignant tissues and accumulation in specific tissues can induce unique toxicities. Furthermore, interactions between the Fc domain of the antibody and immune cells may trigger additional adverse reactions.^43
–45 The combination of these elements contributes to the distinct toxicity profiles of ADCs.

In conclusion, the utilization of ADCs has been associated with an elevated risk of developing ILDs, displaying considerable variations across different drugs and exhibiting diverse mortality rates specific to individual AEs. Consequently, implementing separate monitoring mechanisms and tailored management strategies is imperative.

Limitations

This study has several limitations. Data were obtained from a voluntary reporting system for adverse drug events, that may have been affected by underreporting, misreporting, or incomplete information. Some ADCs have been recently introduced, limiting the available reports and obscuring risks. Although an association between ADCs and ILD was found, the current research design was insufficient for etiological exploration. With improvements to the FAERS database, more detailed analyses are required. Disproportionality analysis, widely used in drug safety assessments, has some limitations. Future plans include adopting more analytical methods to improve the comprehensiveness and accuracy of the research.

Conclusion

This study provides valuable insights into the risks associated with ILD in patients undergoing ADC treatment, including a deeper understanding of clinical case characteristics as well as the varying degrees of heterogeneity and prognostic differences observed among ILD cases attributed to different ADCs. By utilizing this knowledge, we can enhance detection and follow-up measures during drug administration, thereby facilitating earlier identification of potential AEs.

Supplemental Material

sj-docx-1-tar-10.1177_17534666241299935 – Supplemental material for Interstitial lung disease with antibody–drug conjugates: a real-world pharmacovigilance study based on the FAERS database during the period 2014–2023

Supplemental material, sj-docx-1-tar-10.1177_17534666241299935 for Interstitial lung disease with antibody–drug conjugates: a real-world pharmacovigilance study based on the FAERS database during the period 2014–2023 by Jing Shi, Xinya Liu, Li Wu, Yun Jiang, Yuanming Zhang and Yanfeng Wang in Therapeutic Advances in Respiratory Disease

Footnotes

Acknowledgements

The authors would like to thank Mr. Zhou for his technical support and expertise which greatly contributed to the success of this research.

Declarations

ORCID iD

Jing Shi

Supplemental material

Supplemental material for this article is available online.

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