(A) real-world study on the risk of interstitial lung diseases following COVID-19 vaccination

다국어 초록 (Multilingual Abstract)

Introduction & objective: The Coronavirus disease 2019 (COVID-19) vaccination is scheduled for regular immunization program in a worldwide. The World Health Organization (WHO) recently released high-priority use group have a significant risk of severe disease and mortality, as well as vaccination is more beneficial in the high- priority use group compared to delayed vaccination. It remains unknown whether COVID-19 vaccination-associated interstitial lung diseases (ILD) have distinct characteristics. Therefore, this study aims to evaluate the risk of ILD following COVID-19 vaccination using a real-world data. Method: This study conducted both a descriptive study using the global scale pharmacovigilance data, VigiBase, and an association study using linked database from the Korea Disease Control and Prevention Agency (KDCA)'s COVID-19 vaccination database and the National Health Insurance Service (NHIS)'s claims data referred to as K-COV-N database. The descriptive study was analyzed on adverse event (AE) following immunization from December 13, 2020 to January 26, 2023. To evaluate signal of ILD following COVID-19 vaccination, this study applied a case/non-case approach matched by age and sex in a 1:10 ratio. All other vaccines served as the reference group compared to COVID-19 vaccines. The association study conducted both modified self-controlled case series (SCCS) and case-control studies between February 26, 2021 to December 31, 2022. The SCCS included only cases, and ILD defined as the patients hospitalized or visited emergency room for ILD. The risk period for modified SCCS was 1 to 7 days, and incidence rate ratio (IRR) of ILD following COVID-19 vaccination was calculated using conditional Poisson regression. For case-control study, the patients with ILD from SCCS were used as the cases, and during study period, individuals hospitalized or visited emergency room for other than ILD were selected as controls. The incidence density sampling exact 1:5 matching was performed by age, sex, and admission date (±1 day). Exposure was defined as COVID-19 vaccination before index date. Conditional logistic regression was used to estimate the risk for ILD following COVID-19 vaccination. Result: In the descriptive study, among 1,233,969 vaccine-related reports, there were 679 reports of ILD. Of these, Tozinameran accounted for 376 cases (55.4%), Vaxzevria for 129 cases (19.0%), followed by Elasomeran for the next highest with 78 cases (11.5%). The reporting odds ratio (ROR) for ILD following COVID-19 vaccination compared to all other vaccines, was 0.86 (95% confidence interval (CI) 0.64–1.15). In the association study, among patients hospitalized or visited emergency room for ILD during the study period, there were 23,867 study participants. The IRR for ILD following COVID-19 vaccination in the modified SCCS was 1.00 (95% CI 0.91‒1.09). The results of the case-control study showed that the OR, adjusted for history of hospitalization for ILD, comedication, Charlson comorbidity, for ILD following COVID-19 vaccination compared to non-vaccinated individuals, was 0.82 (95% CI 0.73‒0.92). The significantly increased risk of ILD occurrence was observed for individuals with a history of chronic obstructive pulmonary disease. Conclusion: This study applied various data sources and pharmacoepidemiologic methodologies to evaluate the risk of ILD following COVID-19 vaccination. It was found that ILD following COVID-19 vaccination was not detected in the pharmacovigilance database compared to all other vaccines. The increased IRR and adjusted OR for ILD following COVID-19 vaccination was not observed. However, the risk of ILD following COVID-19 vaccination increased in patients with a history of respiratory disease. The results of this study contribute to the deep understanding and long-term safety management of COVID-19 vaccines.

국문 초록 (Abstract)

서론 및 목적: 코로나19 백신이 전 세계적으로 주기적인 백신접종 프로그램으로 계획되고 있다. 국제보건기구(WHO)는 우선순위가 높은 그룹(high-priority use group)에서 높은 중증과 사망 위험을 갖는 것으로 제안하였으며, 백신접종을 연기하는 것보다 접종 받는 것이 더 이익이 될 수 있다고 한다. 현재 코로나19 백신접종과 간질성폐질환 발생 보고되었으며, 인과관계가 명확하게 알려져 있지 않다. 따라서, 본 연구는 실사용자료를 이용하여 코로나19 백신 접종 이후 발생하는 간질성폐질환의 위험을 평가하고자 한다.
방법: 본 연구는 global scale 약물감시 자료인 VigiBase를 이용한 descriptive 연구와 질병관리청 코로나19 백신접종 자료와 국민건강보험공단 청구자료를 연계한 K-COV-N 자료를 이용한 association 연구를 수행하였다. Descriptive 연구는 2020년 12월 13일~2023년 1월 26일 동안 백신접종 이후 발생하는 이상반응 보고 건을 대상으로 하였다. 본 연구는 코로나19 백신 접종 후 발생하는 간질성폐질환의 실마리정보 평가를 위하여 연령과 성별을 1:10으로 매칭하여 case/non-case 연구를 적용하였다.
그 외 모든 백신을 비교그룹으로 하여 코로나19 백신과 비교하였다.
Association 연구는 2021년 2월26일~2022년 12월 31일 동안의 자료를 이용하여 자기-대조 환자군 연구와 환자-대조군 연구를 수행하였다. 자기-대조 환자군 연구는 환자군만 연구 대상자로 이용하며, 본 연구에서는 간질성폐질환으로 인한 입원 및 응급실 방문한 환자로 정의하였다. 국내 코로나19 백신 특성을 고려하여 확장된(modified) 자기-대조 환자군 연구를 적용하였다. 확장된 자기-대조 환자군 연구의 위험구간은 14일을 적용하였으며, conditional Poisson regression을 이용하여 코로나19 백신 접종 후 발생하는 간질성폐질환의 발생률비율(incidence rate ratio)을 산출하였다.
환자-대조군 연구는 자기-대조 환자군 연구의 환자군으로 이용하였으며, 같은 기간 동안 간질성폐질환이 아닌 입원 또는 응급실 방문 환자를 대조군으로 선정하였다. 연령, 성별, 입원 일자(±1일)를 이용하여 발생밀도 추출 1:5 정확 매칭하였다. 노출은 간질성폐질환 발생 이전 코로나19 백신 접종으로 정의하였다. 조건부 로지스틱 회귀분석을 이용하여 코로나19 백신 접종 후 발생하는 간질성폐질환의 오즈비를 산출하였다.
결과: Descriptive 연구 결과, 백신 관련 보고서 1,233,969건 중, 간질성폐질환 보고는 679건이었다. 간질성폐질환 보고 건 중 Tozinameran (376건, 55.4%), Vaxzevria (129건, 19.0%), 그 다음 Elasomeran (78건, 11.5%)이 보고되었다. 코로나19 백신은 그 외 모든 백신과 비교하여 보고오즈비는 0.86 (95% 신뢰구간 0.64‒1.15)이었다. Association 연구 결과, 연구기간 동안 간질성폐질환으로 인한 입원 및 응급실 방문한 환자 중 연구 대상자는 23,867명이었다. 확장된 자기-대조 환자군 연구 결과 대조구간과 비교하여 위험구간에서 코로나19 백신 접종 후 간질성폐질환 발생 발생률비는 1.00 (95% 신뢰구간 0.91‒1.09)이었다. 환자-대조군 연구 결과는 코로나19 백신 접종 후 간질성폐질환 발생 오즈비는 미접종자와 비교하여 0.82 (95% 신뢰구간 0.73‒0.92)이었다. 여성이거나 고령의 만성폐쇄성폐질환으로 입원 과거력이 있는 환자는 유의하게 증가된 위험도를 나타났다 [여성 1.47 (95% 신뢰구간 1.02‒2.13), 1.73 (95% 신뢰구간 1.09‒2.75)]
결론: 본 연구에서 코로나19 백신접종 후 발생하는 간질성폐질환의 발생 위험도를 평가하기 위하여 다양한 자료원과 약물역학적 방법론을 적용하였다. 연구 결과, 코로나19 백신 접종으로 인한 간질성폐질환은 그 외 모든 백신과 비교하여 실마리정보 탐지되지 않았으며, 코로나19 백신 접종 이후 간질성폐질환 발생률비와 오즈비는 유의하지 않은 값을 산출하였다.
다만, 과거 호흡기 질환력이 있는 환자는 증가하는 간질성폐질환 발생위험도가 산출되어, 주의 깊은 모니터링이 요구된다. 본 연구 결과는 이후 장기간 코로나19 백신 안전성과 깊은 이해에 기여하여 코로나19 백신 안전성 관리에 증거를 제공할 수 있다.

목차 (Table of Contents)

• Ⅰ. Introduction 1
• Ⅱ. Objectives 3
• Ⅲ. Methods 4
• 1. Descriptive study 4
• 1.1. Data Source 4
• 1.2. Variables 5
• 1.3. Statistical analysis 7
• 2. Association study 12
• 2.1. Data source 12
• 2.2. Self-controlled case series study 13
• 2.2.1. Study population 13
• 2.2.2. Study design 14
• 2.2.3. Modified self-controlled case series study 16
• 2.2.4. Time-varying confounder 19
• 2.2.5. Statistical analysis 22
• 2.3. Ca se-control study 24
• 2.3.1. Study population 24
• 2.3.2. Definition of case and control 25
• 2.3.3. Exposure and covariates 26
• 2.3.4. Statistical analysis 28
• Ⅳ. Results 29
• 1. Descriptive study 29
• 2. Association study 47
• 2.1. Self-controlled case series study 47
• 2.2. Case-control study 61
• Ⅴ. Discussion 71
• Ⅵ. Conclusion 79
• References 80
• Appendix 87
• 국문초록 106

참고문헌 (Reference)

1. Interstitial lung diseases, Wijsenbeek M, Suzuki A, Maher TM, 400(10354):769-86, , 2022

2. Drug induced interstitial lung disease, Haeckel T, Märkl B, Behr W, Foerg W, Schwaiblmair M, Berghaus T., 6:63, , 2012

3. Drug-induced interstitial lung disease, Spagnolo P Bonniaud P, Rossi G, Sverzellati N, Cottin V., 60(4), , 2022

4. COVID- 19 mRNA vaccine-induced pneumonitis, Arai M., Tago O, Inoshima I, Hirasawa Y, Matsuzaki S, Kamiya H, 61(1):81-6, , 2022

5. COVID-19 vaccine induced interstitial lung disease, Yoshifuji A, Murata S, Uwamino Y et al, Suda S, Masuzawa Y, Ishioka K, 28(1):95-8, , 2022

6. Influenza vaccine-induced interstitial lung disease, Katayama N, Inuzuka K, Watanabe S, Waseda Y, Takato H, Kasahara K et al, 41(2):474-7, , 2013

7. Drug-induced interstitial lung disease: a systematic review, Weatherley N, Hayton C et al, Swift AJ, Skeoch S, Oldroyd A, Johns C, 7(10):356, , 2018

8. Self-controlled case series studies: a modelling guide with R, Farrington P, Weldeselassie YG, Whitaker H, CRC Press, , 2018

9. COVID-19 vaccine-related interstitial lung disease: a case study, Kim J-H, Park JY, Hwang YI, et al, Kim HI, Park S, Lee IJ, 77(1):102-4, , 2022

10. Case–non-case studies: principle, methods, bias and interpretation, Faillie J-L., 74(2):225-32, , 2019

11. A case of severe interstitial lung disease after COVID-19 vaccination, Iwashina K, Yoshioka R, Kono A, Hawk P, Suzuki M, et al, Inoue D, 114(11):805-6, , 2021

12. Graphical depiction of longitudinal study designs in health care databases, Rassen JA, Arlett P et al, Rothman KJ, Happe L, Brown JS, Schneeweiss S, 170(6):398-406, , 2019

13. COVID-19 vaccine in patients with exacerbation of idiopathic pulmonary fibrosis, Comes A, Sgalla G, Richeldi L., Lerede M, Magrì T, 206(2):219-21, , 2022

14. Vaccine-induced interstitial lung disease: a rare reaction to COVID-19 vaccination, Farrand E., DeDent AM, 77(1):9-10, , 2022

15. 40 Drug-induced interstitial lung disease: mechanisms and best diagnostic approaches, Matsuno O., 13(1):1-9, , 2012

16. COVID-19 Vaccine-Associated Pneumonitis in the Republic of Korea: A Nationwide Multicenter Survey, Park MS, Jeong SH, Lee HL et al, Kim SY, Yoo H, Park S-W, 38(14), , 2023

17. COVID‐19 mRNA vaccine‐related interstitial lung disease: Two case reports and literature review, So C, Ishida A, Hashimoto M et al, Hirakawa R, Kusaba Y, Izumi S, 10(4):e0938, , 2022

18. COVID- 19 vaccination and non–COVID-19 mortality risk—seven integrated health care organizations, Huang R, Glenn SC, Sy LS, Ryan DS, Morrissette K, et al, Xu S, United States Morbidity and Mortality Weekly Report70(43):1520, , 2020

19. 25 A potential competition bias in the detection of safety signals from spontaneous reporting databases, Didailler M, Pariente A, Fourrier‐Reglat A, Avillach P, Miremont‐Salamé G, Haramburu F, et al, 19(11):1166-71, , 2010

20. Increased odds of death for patients with interstitial lung disease and COVID-19: a case–control study, Fredenburgh LE, Putman RK, Menon AA, Esposito AJ, El- Chemaly SY, et al, Ghosh AJ, 202(12):1710-3, , 2020

21. Response to: Multisystem inflammatory syndrome following COVID-19 vaccination: ignored and underdiagnosed, Kono A Hawke P, Yoshioka R., 115(10):698-, , 2022

22. Exacerbation of connective tissue diseaseassociated interstitial lung disease due to influenza vaccination, Okusaki T, Fukuhara K., 33:101463, , 2021

23. COVID-19 mRNA Vaccines and Interstitial Lung Disease Exacerbation: Causation or Just a Temporal Association?, Ehteshami-Afshar S, Raj R., 206(7):919-, , 2022

24. Vaccination against COVID-19: insight from arterial and venous thrombosis occurrence using data from VigiBase, Lillo-Le Louet A., Chocron R, Sanchez O, Yue Q-Y, Smadja DM, 58(1), , 2021

25. Primer: administrative health databases in observational studies of drug effects—advantages and disadvantages, Garbe E., Suissa S, 3(12):725-32, , 2007

26. Risk factors for mortality and mortality rates in interstitial lung disease patients in the intensive care unit, Danoff SK, Brower RG, Harden CT, Huapaya JA, Wilfong EM, 27(150), , 2018

27. Utilization of positive and negative controls to examine comorbid associations in observational database studies, St Louis M, Desai JR, Hyde CL, Bonato V, Kabadi S, Loomis AK et al, 55(3):244, , 2017

28. Functional status is a confounder of the association of influenza vaccine and risk of all cause mortality in seniors, Neuzil KM, Reid RJ, Nelson JC, Benson P, Jackson LA, Psaty BM et al, 35(2):345- 52, , 2006

29. Outcome of hospitalization for COVID-19 in patients with interstitial lung disease. An international multicenter study, Harrison EM, Quint JK, Agnew S, et al, Docherty AB, Adamali H, Drake TM, 202(12):1656-65, , 2020

30. Data resource profile: the national health information database of the National Health Insurance Service in South Korea, Cheol Seong S, Heon Park J, Khang Y-H, Lee H, et al, Kim Y-Y, Kang H-J, 46(3):799-800, , 2017

31. Detection algorithms and attentive points of safety signal using spontaneous reporting systems as a clinical data source, Teramachi H., Tachi T, Noguchi Y, 22(6):bbab347, , 2021

32. Patient-centered outcomes research in interstitial lung disease: an official American Thoracic Society research statement, Danoff SK, Suzuki A, Wijsenbeek MS, et al, Russell A-M, Ryerson CJ, Aronson KI, 204(2):e3-e23, , 2021

33. Trends and seasonal variation of hospitalization and mortality of interstitial lung disease in the United States from 2006 to 2016, Ho ATN, Charbek E., Shmelev A, Respiratory Research21:1-9, , 2020

34. Benefits and strengths of the disproportionality analysis for identification of adverse drug reactions in a pharmacovigilance database, Montastruc J-L, Sommet A, Lapeyre-Mestre M., Bagheri H, 72(6):905, , 2011

35. Association of influenza vaccination with SARS-CoV-2 infection and associated hospitalization and mortality among patients aged 66 years or older, Campitelli MA, Hosseini-Moghaddam SM He S, Kwong JC, Calzavara A, JAMA Network Open5(9):e2233730-e, , 2022

36. Healthcare resource utilization and related costs in chronic fibrosing interstitial lung diseases with a progressive phenotype: a US claims database analysis, Patnaik P, Olson AL, Bohn RL, Singer D et al, Hartmann N, Garry EM, Advances in Therapy39(4):1794-809, , 2022

37. A modified self‐controlled case series method for eventdependent exposures and high event‐related mortality, with application to COVID‐ 19 vaccine safety, Baricault B, Drouin J et al, Jabagi MJ, Ghebremichael‐Weldeselassie Y, Bertrand M, Botton J, 41(10):1735-50, , 2022