|Year : 2019 | Volume
| Issue : 3 | Page : 65-73
Rheumatic and musculoskeletal adverse events with immune checkpoint inhibitors: Data from the United States Food and Drug Administration adverse event reporting system
Xerxes N Pundole1, Mayur Sarangdhar2, Maria E Suarez-Almazor1
1 Department of General Internal Medicine, Section of Rheumatology and Clinical Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
2 Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center; Division of Oncology, Cincinnati Children's Hospital Medical Center; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
|Date of Submission||10-May-2019|
|Date of Acceptance||20-Jun-2019|
|Date of Web Publication||29-Jul-2019|
Dr. Maria E Suarez-Almazor
Department of General Internal Medicine, Section of Rheumatology and Clinical Immunology, Unit 1465, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
Source of Support: None, Conflict of Interest: None
Background: Despite their efficacy, immune checkpoint inhibitors (ICIs) can cause significant immune-related adverse events (irAEs). Rheumatic and musculoskeletal irAEs can be serious and adversely affect the quality of life. The full spectrum of irAEs is still emerging, and to represent and better understand their scope, we evaluated the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database. Methods: We used AERSMine, an open-access web application to mine FAERS data across 11,919,342 patients from 2011 (first quarter) to 2018 (fourth quarter). Measures of disproportionality were calculated using well-established pharmacovigilance metrics, proportional reporting ratios, and safety signals (information component), in patients receiving ICI. Results: We analyzed 63,979 cancer patients for reports of ICI-associated AEs. Eighty-two percent of these reports were in relation with anti-PD-1 inhibitors. Rates of rheumatic and musculoskeletal AEs were higher in men and in patients >65 years of age. Several statistically significant AEs were identified, most in relation with PD-1 inhibitors. AEs with the highest number of reports included arthralgia (n = 1062), followed by myalgia (n = 532), myositis (n = 438), arthritis (n = 403), and rhabdomyolysis (n = 230). Novel AEs affecting the skeleton included compression fractures, fractures at various skeletal sites (rib, thoracic vertebral, and humerus), osteonecrosis of the jaw, osteitis, and osteomyelitis. Conclusion: A wide spectrum of rheumatic and musculoskeletal AE signals were detected within the FAERS data which may signify the emerging trends of irAEs post approval of ICI. Additional research to explore mechanisms and identify optimal management strategies of these AEs is warranted.
Keywords: Food and Drug Administration Adverse Event Reporting System, immune checkpoint inhibitor, immune-related adverse events, safety signals
|How to cite this article:|
Pundole XN, Sarangdhar M, Suarez-Almazor ME. Rheumatic and musculoskeletal adverse events with immune checkpoint inhibitors: Data from the United States Food and Drug Administration adverse event reporting system. J Immunother Precis Oncol 2019;2:65-73
|How to cite this URL:|
Pundole XN, Sarangdhar M, Suarez-Almazor ME. Rheumatic and musculoskeletal adverse events with immune checkpoint inhibitors: Data from the United States Food and Drug Administration adverse event reporting system. J Immunother Precis Oncol [serial online] 2019 [cited 2019 Sep 19];2:65-73. Available from: http://www.jipoonline.org/text.asp?2019/2/3/65/263653
| Introduction|| |
Biologic agents targeting immune checkpoints, including cytotoxic T-lymphocyte-associated protein-4 (CTLA-4), programmed cell death protein-1 (PD-1), and programmed cell death ligand-1 (PD-L1), represent a major advance in cancer treatment., Even though immune checkpoint inhibitors (ICIs) have shown survival benefits in many types of cancer, there are consequences related to the resulting unrestrained activation of the immune system, and a broad spectrum of immune-related adverse events (irAEs) has emerged with continuing use in practice. The most commonly occurring irAEs affect the skin, colon, endocrine system, and lungs. However, irAEs can affect any organ system, including the rheumatic and musculoskeletal systems. A systematic review described the types of rheumatic and musculoskeletal irAEs observed following ICI therapy  and highlighted a wide variety of irAEs including arthralgia, arthritis, inflammatory myopathies, and vasculitis among others. However, due to the emerging nature of these irAEs, there have been a sparse number of irAE reports in recent literature.
The mechanisms of rheumatic and musculoskeletal irAEs in patients receiving ICI therapy are poorly understood. Most evidence suggest a T-cell-mediated pathway. During therapy with ICI, there is an enhanced T helper 1 (Th1) and T helper 17 (Th17) response and increased production of pro-inflammatory cytokines (interleukin [IL] IL-1, IL-6, IL-8, IL-12, and IL-17; tumor necrosis factor-α [TNF-α]; and interferon-γ [IFN-γ])., This pro-inflammatory state and the Th17 pathway have been implicated in the development of autoimmune diseases ,, and ICI-induced colitis. In addition, the IL-6–Th17 pathway may play a role in the pathogenesis of arthritis irAE. A few studies have shown that patients who developed arthritis following ICI therapy responded well to the IL-6 receptor antibody, tocilizumab.,,
It is conceivable that triggering of a preclinical disease state, with the use of ICI therapy, may result in patients presenting with irAEs. A retrospective review was reported on six patients with rheumatoid arthritis. Of these, three patients had anti-cyclic citrullinated peptide (anti-CCP) antibodies evaluated prior to immunotherapy, and the anti-CCP antibodies were detected in two of the three patients. These patients developed rheumatoid arthritis shortly after the initiation of ICI therapy, and this could suggest a prerheumatoid arthritis status, as reported by the authors, which when triggered by ICI therapy could result in clinical disease.
The role of B-cells is ill defined in the pathogenesis of irAEs; however, some reports of patients with autoantibodies such as rheumatoid factor, antinuclear antibodies, or anti-Sjögren's-syndrome-related antigen A or anti-Sjögren's-syndrome-related antigen B antibodies suggest a B-cell-mediated mechanism for the development of irAEs., From a genetic standpoint, single-nucleotide polymorphisms in the CTLA-4 and PD-1 genes have been linked to various autoimmune and inflammatory conditions including rheumatoid arthritis, ankylosing spondylitis, and systemic lupus erythematosus.,,, The functional consequences of these identified single-nucleotide polymorphisms are not completely understood, but could play a role in the pathogenesis of irAEs.
In the last few decades, the treatment landscape in oncology has been evolving at a rapid pace. As more patients are being treated with immunotherapy, new AEs are emerging. As such, timely and accurate identification of such AEs is crucial. The United Sates Food and Drug Administration maintains an Adverse Event Reporting System (FAERS), which contains millions of records of detailed drug exposure and clinical outcomes. Harnessing information from such a large database could detect novel irAEs and identify areas that necessitate further research. In this analysis of the FAERS, we aimed to identify and describe rheumatologic and musculoskeletal irAEs following treatment with ICI therapy.
| Methods|| |
The FAERS database contains AEs filed with the FDA since the first quarter (Q1) of 2004, and reports are released on a quarterly basis. Each file contains demographic information, type of reactions, suspect and concomitant drugs, and indications for use. This study was performed on publically available anonymized patient data; therefore, ethics committee approval was not required. We used AERSMine, an open-access web-based data mining tool, to analyze FAERS data from 2011 (Q1) up to 2018 (Q4) in patients with any cancer indication. The AERSMine is a comprehensive data mining framework to analyze the FAERS, which effectively mines millions of patient reports through systematic normalization, unification and ontological aggregation of drugs, clinical indications, and AEs.
We used the AERSMine to identify all rheumatological and musculoskeletal AEs [Supplementary Appendix A shows all high-level group terms evaluated] reported with six ICIs, ipilimumab (CTLA-4 inhibitor); nivolumab or pembrolizumab (PD-1 inhibitors); and durvalumab, atezolizumab, or avelumab (PD-L1 inhibitors). Combination therapies of these ICIs were also evaluated. Any reports of musculoskeletal or rheumatologic AE diagnosis such as arthritis, rheumatoid arthritis, myalgia, and myositis were included in the analysis. Nonspecific terms such as back pain, bone pain, and others or events with <5 reports combined in relation with any of the ICIs were considered statistically underpowered and not evaluated. To limit confounding, we limited the analysis to patients with a cancer diagnosis and calculated the rates and measures of disproportionality  (proportional reporting ratios [PRRs] and safety signals [information components (IC)]) within this group of patients. The PRR is a test statistic providing the degree of disproportionate reporting of an AE for an agent compared to the same AE for all other products. The PRR is based on the assumption of independence, i.e., there is no association between the agent of interest and the AE. When disproportionate reporting is identified, there may in fact be an association between the agent of interest and the AE, suggesting further exploration of a relationship between the agent of interest and the AE. The 95% confidence interval (CI) of a PRR is interpreted in the same way as a 95% CI of a relative risk. If the PRR is >1 and the 95% CI does not include 1, then there is a disproportion detected, such that the agent of interest and the AE are more frequently reported compared to all the other agents and the same AE. If the PRR is <1 and the 95% CI does not include 1, then there is a disproportion detected, such that the agent of interest and the AE are less frequently reported compared to all the other agents and the same AE. If the 95% CI of the PRR contains 1, then disproportionate reporting is not detected.[Additional file 4]
We also calculated quantitative safety signals by measuring the disproportionality between the observed and the expected reporting frequency of a drug–AE pair (IC), or drug–drug–AE triplet (Ω). This method is based on the Bayesian statistics and neural network architecture and methods. Generally, an IC = 0 represents no change in risk compared to baseline, whereas IC >0 represents an increased risk based on the disproportionality that the observed number of AE drug events is higher than expected. The higher the IC score, the more the combination stands out from the background and represents a suspected association. A positive score indicates a potential safety concern requiring further review, whereas IC < 0 does not represent a safety signal. Frequencies of co-reporting of the included AEs and exploration of known co-existing AEs were evaluated.
| Results|| |
The FAERS data from 2011 (Q1) to 2018 (Q4) included 63,979 patients with a cancer diagnosis and a concomitant AE associated with therapy with an ICI. Our analysis showed that 4496 AEs correlated with the use of an ICI (ipilimumab, nivolumab, pembrolizumab, durvalumab, atezolizumab, or avelumab); select clinically important AEs are shown in [Table 1], [Table 2], [Table 3], [Table 4]. AEs with the highest number of reports included arthralgia (n = 1062), followed by myalgia (n = 532), myositis (n = 438), arthritis (n = 403), and rhabdomyolysis (n = 230).
|Table 1: Frequency of proportional reporting ratios and safety signals of rheumatologic and musculoskeletal adverse events within records where anti-PD-1 ICI monotherapies were listed as suspect or concomitant drugs in the FAERS database|
Click here to view
|Table 2: Frequency of proportional reporting ratios and safety signals of rheumatologic and musculoskeletal adverse events within records where anti-PD-L1 ICI monotherapies were listed as suspect or concomitant drugs in the FAERS database|
Click here to view
|Table 3: Frequency of proportional reporting ratios and safety signals of rheumatologic and musculoskeletal adverse events within records where anti-CTLA-4 ICI inhibitor monotherapy was listed as suspect or concomitant drugs in the FAERS database|
Click here to view
|Table 4: Frequency of proportional reporting ratios and safety signals of rheumatologic and musculoskeletal adverse events within records where a combination of ICI therapies were listed as suspect or concomitant drugs in the FAERS database|
Click here to view
In general, the frequency of reports for rheumatic and musculoskeletal AEs is greater in patients on PD-1 inhibitors (nivolumab or pembrolizumab). [Table 1], [Table 2], [Table 3] show the number of reports, PRRs, and safety signals identified in relation with anti-PD-1, anti-PD-L1, and anti-CTLA-4 monotherapy, respectively. Statistically significant increased PRRs for AEs associated with ICI therapy are presented according to agent class as follows:
- Nivolumab: arthritis (n = 198; PRR, 1.19; IC, 0.25), arthralgia (n = 513; PRR, 1.17; IC, 0.22), rheumatoid arthritis (n = 140; PRR, 1.49; IC, 0.57), psoriatic arthropathy (n = 47; PRR, 1.96; IC, 0.97), myalgia (n = 261; PRR, 1.18; IC, 0.24), myositis (n = 217; PRR, 1.20; IC, 0.26), compression fracture (n = 14; PRR, 2.11; IC, 1.08), rib fracture (n = 31; PRR, 1.87; IC, 0.90), humerus fracture (n = 12; PRR, 2.23; IC, 1.16), osteonecrosis of the jaw (n = 35; PRR, 1.72; IC, 0.79), and osteomyelitis (n = 21; PRR, 1.75; IC, 0.81)
- Pembrolizumab: arthralgia (n = 265; PRR, 1.17; IC, 0.22), arthropathy (n = 19; PRR, 1.93; IC, 0.95), polymyalgia rheumatica (n = 46; PRR, 2.69; IC, 1.43), immune-mediated necrotizing myositis (n = 6; PRR, 3.50; IC, 1.81), Sjögren's syndrome (n = 29; PRR, 1.61; IC, 0.69), sarcoidosis (n = 37; PRR, 1.96; IC, 0.97), cutaneous sarcoidosis (n = 10; PRR, 2.75; IC, 1.46), pulmonary sarcoidosis (n = 20; PRR, 3.22; IC, 1.69), systemic scleroderma (n = 5; PRR, 3.34; IC, 1.74), thoracic vertebral fracture (n = 10; PRR, 2.92; IC, 1.55), and spinal compression fracture (n = 23; PRR, 2.19; IC, 1.13).
- Durvalumab: autoimmune arthritis (n = 5; PRR, 4.62; IC, 2.21) and fibula fracture (n = 2; Prr, 12.14; Ic, 3.6)
- Atezolizumab: ankle fracture (n = 3; PRR, 4.57; IC, 2.19) and osteonecrosis of the jaw (n = 8; PRR, 2.24; IC, 1.16)
- Avelumab: sarcoidosis (n = 6; PRR, 6.45; IC, 2.69).
- Ipilimumab: sarcoidosis (n = 20; PRR, 1.66; IC, 0.73), temporal arteritis (n = 11; PRR, 2.59; IC, 1.37), and osteitis (n = 4; PRR, 3.25; IC, 1.7).
Combination immune checkpoint inhibitor regimens
[Table 4] illustrates the PRRs and safety signals of rheumatologic and musculoskeletal AEs in relation with combination ICI therapies.
- Nivolumab + ipilimumab: arthritis (n = 73; PRR, 1.51; Ω, 0.59), autoimmune arthritis (n = 12; PRR, 2.17; Ω, 1.12), seronegative arthritis (n = 8; PRR, 2.89; Ω, 1.53), rhabdomyolysis (n = 44; PRR, 1.59; Ω, 0.67), Sjögren's syndrome (n = 16; PRR, 1.59; Ω, 0.66), and temporal arteritis (n = 4; PRR, 1.07; Ω, 0.10)
- Pembrolizumab + ipilimumab: arthritis (n = 8; PRR, 4.57; Ω, 2.19), autoimmune arthritis (n = 3; PRR, 4.70; Ω, 3.91), rhabdomyolysis (n = 5; PRR, 2.08; Ω, 2.32), Sjögren's syndrome (n = 5; PRR, 13.7; Ω, 3.78), temporal arteritis (n = 3; PRR, 22.27; Ω, 4.48), sarcoidosis (n = 4; PRR, 10.46; Ω, 3.39), cutaneous sarcoidosis (n = 1; PRR, 13.54; Ω, 3.76), pulmonary sarcoidosis (n = 1; PRR, 7.94; Ω, 2.98), and osteonecrosis (n = 4, PRR, 40.02; Ω, 5.32)
- Nivolumab + pembrolizumab: Sjögren's syndrome (n = 2; PRR, 20.31; Ω, 4.34), hip fracture (n = 1; PRR, 19.84; Ω, 4.31), and pelvic fracture (n = 1; PRR, 121.86; Ω, 6.93).
In addition to the increased PRRs mentioned above, safety signals using IC were identified for several AEs in relation with ICI monotherapy and combination ICI therapies [Table 1], [Table 2], [Table 3], [Table 4]. Rates of rheumatic and musculoskeletal AEs were higher in men and in the elderly population (>65 years). Heat maps of age- and sex-specific PRRs or safety signals (IC) did not reveal any clear patterns [Supplementary Figure 1] and [Supplementary Figure 2].[Additional file 2][Additional file 3]
We evaluated co-reporting of the included AEs. In general, co-reporting of the included AEs is <20%, with the frequency of most co-reports being <5%. For example, of the reports with arthralgia, 15% co-reported myalgia, 7% pain in extremity, 5% back pain, 5% muscular weakness, and 5% musculoskeletal pain. Of the myalgia reports, 30% co-reported arthralgia, 5% pain in extremity, 9% muscular weakness, and 5% myositis. Of the myositis reports, 16% co-reported myasthenia gravis, 11% rhabdomyolysis, 6% myalgia, and 5% muscular weakness. Of the arthritis reports, 13% co-reported arthralgia. Of the rhabdomyolysis reports, 22% co-reported myositis, 10% myasthenia gravis, and 5% muscular weakness. Detailed co-reporting is presented in [Supplementary Table 1].[Additional file 1]
| Discussion|| |
This comprehensive analysis of the FAERS database highlighted several important findings associated with the use of ICI. Arthralgia, myalgia, myositis, arthritis, and rhabdomyolysis were the most commonly reported rheumatic and musculoskeletal AEs following ICI therapy. This is consistent with the findings of prior systematic reviews. The most frequently reported irAEs include arthralgia (1%–43%), arthritis (1%–7%), myalgia (2%–21%), myositis (0.4%–6%), polymyalgia rheumatica (0.2%–2.1%), and sicca symptoms (1.2%–24.2%).,,, The true incidence of rheumatic and musculoskeletal irAEs is unknown, and this is partially attributable to the underrecognition and underreporting of these irAEs. Our study identified 438 reports of myositis and 403 reports of arthritis. These numbers are greater than previous reports in systematic reviews and observational studies ,,,,, and may represent a potential trend of increased recognition of and long-term risk of AEs with ICI therapy.
In addition, we identified several other AEs which are included in the broad spectrum of joint and muscle disorders, but were classified with other terminologies, namely, rheumatoid arthritis, polyarthritis, autoimmune arthritis, arthropathy, psoriatic arthropathy, rhabdomyolysis, myopathy, polymyositis, dermatomyositis, necrotizing myositis, and polymyalgia rheumatica. Other reported rheumatic AEs included sarcoidosis, temporal arteritis, and Sjögren's syndrome.
We found several safety signals and increased PRRs in relation with anti-PD-1 inhibitors, nivolumab and pembrolizumab. This was considerably greater than the signals identified with anti-PD-L1 inhibitors (durvalumab, atezolizumab, and avelumab) and the anti-CTLA-4 inhibitor ipilimumab monotherapy. Combination ICI therapy showed similar AE phenotypes, however, the PRRs and safety signals were greater in patients receiving monotherapy with anti-PD-1 inhibitors or anti-CTLA-4 inhibitor. These results need to be interpreted with caution as there were fewer reports of AEs in relation with combination therapy than with monotherapy. Nevertheless, such AEs need to be monitored as the use of combination therapy is growing with increased approval for many types of malignancies.
Of importance, we found several reports of skeletal AEs, especially fractures, seldom reported before. Several safety signals for different types of fracture were detected in relation with all the investigated ICIs. To the best of our knowledge, there has only been one case series of six patients with skeletal events during immune checkpoint blockade, of which three experienced new osteoporotic fractures and another three had the development of focal bone-resorptive lesions. From a mechanistic standpoint, pro-inflammatory disease states have a direct effect on bone metabolism. Therapy with ICIs promotes a pro-inflammatory state, where activated T-cells secrete cytokines such as TNF-α, IL-1, IL-4, IL-6, IL-17, and IFN-γ, which promote antitumor effects. These cytokines have also been shown to have unfavorable effects on bone metabolism by increasing bone-resorbing osteoclast activity over that of bone-building osteoblast activity.,,, Furthermore, patients receiving ICIs can develop irAEs which are often treated with glucocorticoids. It is well established that glucocorticoids can have deleterious effects on bone metabolism,,, and thus may further increase bone loss in the setting of ICI therapy. The direct and indirect effects of ICI on skeletal remodeling need further investigation.
Other nonspecific AEs and those with overall reports of <5 reports in relation with ICIs were also reported in the FAERS, but were not included in this study analysis. This suggests that other low-frequency rheumatic and musculoskeletal AEs may occur following ICI therapy, but may not be attributed or documented as a specific disease.
Our findings could have potential limitations based on the nature of the FAERS data. Particularly, the FAERS data represent pharmacovigilance actions and as such do not inform on the true risk in clinical practice. Events are reported spontaneously to the FAERS and do not require validation from healthcare professionals, and a causal relationship between the therapy and AEs cannot be demonstrated. FAERS data are nonetheless useful in describing the spectrum of possible AEs and in comparing the rates, demographics, and associated conditions. It is possible that some of these AEs were flares of preexisting autoimmune diseases, as reported in a systematic review of the literature. However, this cannot be determined in the FAERS data.
This study has several strengths; specifically, it is unique in being the first to comprehensively evaluate ICI-associated rheumatic and musculoskeletal AEs in a “real-world” setting. We leverage the dynamic large-scale analytical framework, AERSMine, which provides a comprehensive evaluation of the FAERS data through systematic normalization, unification, and ontological aggregation of the ICI therapies; underlying clinical conditions; and AEs. Further, we used established methods for disproportionality analysis to identify safety signals to model an accurate risk of rheumatic and musculoskeletal AEs in patients on ICI therapy.
| Conclusion|| |
A wide spectrum of rheumatic and musculoskeletal safety signals were detected with ICIs. Oncologists and rheumatologists need to be vigilant about these AEs, which could be debilitating, with long-lasting impacts on the quality of life of patients during the survivorship period. The potential impact of rheumatic and musculoskeletal AEs is highly relevant as many patients are now receiving combination ICI therapies, and our results show that several AEs can occur in patients receiving combination therapy. Furthermore, immune checkpoint blockade is increasingly being used as an adjuvant therapy in patients who are otherwise healthy and in whom rheumatic AEs would be detrimental to their function. Post marketing, pharmacovigilance plays an important role in identifying AEs, such as the effects of ICI on the skeleton identified in this analysis. Future studies to explore mechanisms and optimal screening and management strategies of these AEs are warranted.
The supplemental material is available with the article online at jipoonline.org.
Financial support and sponsorship
The authors disclosed no funding related to this article.
Conflicts of interest
Dr. Suarez-Almazor has received consultant fees from Pfizer, AbbVie, and Eli Lilly, unrelated to the submitted work.
| References|| |
Burstein HJ, Krilov L, Aragon-Ching JB,et al
. Clinical cancer advances 2017: Annual report on progress against cancer from the American Society of Clinical Oncology. J Clin Oncol
Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: A common denominator approach to cancer therapy. Cancer Cell
Cappelli LC, Gutierrez AK, Bingham CO 3rd
, et al. Rheumatic and musculoskeletal immune-related adverse events due to immune checkpoint inhibitors: A systematic review of the literature. Arthritis Care Res (Hoboken)
Dulos J, Carven GJ, van Boxtel SJ,et al
. PD-1 blockade augments Th1 and Th17 and suppresses Th2 responses in peripheral blood from patients with prostate and advanced melanoma cancer. J Immunother
von Euw E, Chodon T, Attar N,et al
. CTLA4 blockade increases Th17 cells in patients with metastatic melanoma. J Transl Med
Bailey SR, Nelson MH, Himes RA,et al
. Th17 cells in cancer: The ultimate identity crisis. Front Immunol
Karczewski J, Dobrowolska A, Rychlewska-Hańczewska A, et al. New insights into the role of T cells in pathogenesis of psoriasis and psoriatic arthritis. Autoimmunity
Noack M, Miossec P. Th17 and regulatory T cell balance in autoimmune and inflammatory diseases. Autoimmun Rev
Callahan MK, Yang A, Tandon S, et al. Evaluation of serum IL-17 levels during ipilimumab therapy: Correlation with colitis. J Clin Oncol
Kim ST, Tayar J, Trinh VA,et al
. Successful treatment of arthritis induced by checkpoint inhibitors with tocilizumab: A case series. Ann Rheum Dis
Stroud CR, Hegde A, Cherry C,et al
. Tocilizumab for the management of immune mediated adverse events secondary to PD-1 blockade. J Oncol Pharm Pract
Abdel-Wahab N, Tayar JH, Diab A, et al. Inflammatory arthritis induced by the use of checkpoint inhibitors for immunotherapy of cancer. J Immunother Cancer
Belkhir R, Burel SL, Dunogeant L,et al
. Rheumatoid arthritis and polymyalgia rheumatica occurring after immune checkpoint inhibitor treatment. Ann Rheum Dis
Cappelli LC, Gutierrez AK, Baer AN,et al
. Inflammatory arthritis and sicca syndrome induced by nivolumab and ipilimumab. Ann Rheum Dis
Barreto M, Santos E, Ferreira R,et al
. Evidence for CTLA4 as a susceptibility gene for systemic lupus erythematosus. Eur J Hum Genet
Lee YH, Bae SC, Kim JH, et al. Meta-analysis of genetic polymorphisms in programmed cell death 1. Associations with rheumatoid arthritis, ankylosing spondylitis, and type 1 diabetes susceptibility. Z Rheumatol
Lee YH, Woo JH, Choi SJ, et al. Association of programmed cell death 1 polymorphisms and systemic lupus erythematosus: A meta-analysis. Lupus
Li G, Shi F, Liu J, et al. The effect of CTLA-4 A49G polymorphism on rheumatoid arthritis risk: A meta-analysis. Diagn Pathol
Sarangdhar M, Tabar S, Schmidt C,et al
. Data mining differential clinical outcomes associated with drug regimens using adverse event reporting data. Nat Biotechnol
Almenoff JS, Pattishall EN, Gibbs TG,et al
. Novel statistical tools for monitoring the safety of marketed drugs. Clin Pharmacol Ther
Bate A, Lindquist M, Edwards IR,et al
. A Bayesian neural network method for adverse drug reaction signal generation. Eur J Clin Pharmacol
Norén GN, Sundberg R, Bate A, et al. A statistical methodology for drug-drug interaction surveillance. Stat Med
Abdel-Rahman O, Eltobgy M, Oweira H,et al
. Immune-related musculoskeletal toxicities among cancer patients treated with immune checkpoint inhibitors: A systematic review. Immunotherapy
Abdel-Rahman O, Oweira H, Petrausch U,et al
. Immune-related ocular toxicities in solid tumor patients treated with immune checkpoint inhibitors: A systematic review. Expert Rev Anticancer Ther
Baxi S, Yang A, Gennarelli RL,et al
. Immune-related adverse events for anti-PD-1 and anti-PD-L1 drugs: Systematic review and meta-analysis. BMJ
Benfaremo D, Manfredi L, Luchetti MM, et al. Musculoskeletal and rheumatic diseases induced by immune checkpoint inhibitors: A review of the literature. Curr Drug Saf
Shah M, Tayar JH, Abdel-Wahab N, et al. Myositis as an adverse event of immune checkpoint blockade for cancer therapy. Semin Arthritis Rheum
Abdel-Wahab N, Shah M, Suarez-Almazor ME. Adverse events associated with immune checkpoint blockade in patients with cancer: A systematic review of case reports. PLoS One
Pundole X, Abdel-Wahab N, Suarez-Almazor ME. Arthritis risk with immune checkpoint inhibitor therapy for cancer. Curr Opin Rheumatol
Moseley KF, Naidoo J, Bingham CO,et al
. Immune-related adverse events with immune checkpoint inhibitors affecting the skeleton: A seminal case series. J Immunother Cancer
Cauley JA, Barbour KE, Harrison SL,et al
. Inflammatory markers and the risk of hip and vertebral fractures in men: The osteoporotic fractures in men (MrOS). J Bone Miner Res
Pietschmann P, Mechtcheriakova D, Meshcheryakova A, et al. Immunology of osteoporosis: A mini-review. Gerontology
Showalter A, Limaye A, Oyer JL,et al
. Cytokines in immunogenic cell death: Applications for cancer immunotherapy. Cytokine
Weitzmann MN. The role of inflammatory cytokines, the RANKL/OPG axis, and the immunoskeletal interface in physiological bone turnover and osteoporosis. Scientifica (Cairo)
Canalis E. Mechanisms of glucocorticoid action in bone. Curr Osteoporos Rep
Hahn TJ, Halstead LR, Teitelbaum SL, et al. Altered mineral metabolism in glucocorticoid-induced osteopenia. Effect of 25-hydroxyvitamin D administration. J Clin Invest
Van Staa TP, Leufkens HG, Abenhaim L, et al. Use of oral corticosteroids and risk of fractures. J Bone Miner Res
Abdel-Wahab N, Shah M, Lopez-Olivo MA, et al. Use of immune checkpoint inhibitors in the treatment of patients with cancer and preexisting autoimmune disease: A systematic review. Ann Intern Med
[Table 1], [Table 2], [Table 3], [Table 4]