Objectives: Disease flares in the post-coronavirus disease 2019 (COVID-19) vaccination period represent a prominent concern, though risk factors are poorly understood. We studied these flares among patients with idiopathic inflammatory myopathies (IIMs) and other autoimmune rheumatic diseases (AIRDs). Methods: The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with >7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models. Results: Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7-235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P < 0.001) were associated with disparity between self-reported and IS-denoted flares. Conclusion: A diagnosis of IIMs confers an equal risk of flares in the post-COVID-19 vaccination period to AIRDs, with active disease, female gender and comorbidities conferring a higher risk. Disparity between patient- and physician-reported outcomes represents a future avenue for exploration.
Flares in IIMs and the timeline following COVID-19 vaccination: a combined analysis of the COVAD-1 and -2 surveys / Naveen, R.; Sen, P.; Griger, Z.; Day, J.; Joshi, M.; Nune, A.; Nikiphorou, E.; Saha, S.; Tan, A. L.; Shinjo, S. K.; Ziade, N.; Velikova, T.; Milchert, M.; Jagtap, K.; Parodis, I.; Gracia-Ramos, A. E.; Cavagna, L.; Kuwana, M.; Knitza, J.; Chen, Y. M.; Makol, A.; Agarwal, V.; Patel, A.; Pauling, J. D.; Wincup, C.; Barman, B.; Zamora Tehozol, E. A.; Rojas Serrano, J.; Garcia-De La Torre, I.; Colunga-Pedraza, I. J.; Merayo-Chalico, J.; Chibuzo, O. C.; Katchamart, W.; Akarawatcharangura Goo, P.; Shumnalieva, R.; Hoff, L. S.; El Kibbi, L.; Halabi, H.; Vaidya, B.; Shaharir, S. S.; Hasan, A. T. M. T.; Dey, D.; Toro Gutierrez, C. E.; Caballero-Uribe, C. V.; Lilleker, J. B.; Salim, B.; Gheita, T.; Chatterjee, T.; Distler, O.; Saavedra, M. A.; Chinoy, H.; Agarwal, V.; Aggarwal, R.; Gupta, L.; Kardes, S.; Andreoli, L.; Lini, D.; Screiber, K.; Vince, M. N.; Singh, Y. P.; Ranjan, R.; Jain, A.; Pandya, S. C.; Pilania, R. K.; Sharma, A.; Manesh Manoj, M.; Gupta, V.; Kavadichanda, C. G.; Patro, P. S.; Ajmani, S.; Phatak, S.; Goswami, R. P.; Chowdhury, A. C.; Mathew, A. J.; Shenoy, P.; Asranna, A.; Bommakanti, K. T.; Shukla, A.; Pande, A. R.; Chandwar, K.; Ghodke, A.; Boro, H.; Fazal, Z. Z.; Cansu, D. U.; Ylldlrlm, R.; Gasparyan, A. Y.; Del Papa, N.; Sambataro, G.; Fabiola, A.; Govoni, M.; Parisi, S.; Bocci, E. B.; Sebastiani, G. D.; Fusaro, E.; Sebastiani, M.; Quartuccio, L.; Franceschini, F.; Sainaghi, P. P.; Orsolini, G.; De Angelis, R.; Danielli, M. G.; Venerito, V.; Grignaschi, S.; Giollo, A.; Alluno, A.; Ioannone, F.; Fornaro, M.; Traboco, L. S.; Wibowo, S. A. K.; Loarce-Martos, J.; Prieto-Gonzalez, S.; Gonzalez, R. A.; Yoshida, A.; Nakashima, R.; Sato, S.; Kimura, N.; Kaneko, Y.; Gono, T.; Tomaras, S.; Proft, F. N.; Holzer, M. -T.; Gromova, M. A.; Aharonov, O.; Griger, Z.; Hmamouchi, I.; El Bouchti, I.; Baba, Z.; Giannini, M.; Maurier, F.; Campagne, J.; Meyer, A.; Langguth, D.; Limaye, V.; Needham, M.; Srivastav, N.; Hudson, M.; Landon-Cardinal, O.; Zuleta, W. G. R.; Arbelaez, A.; Cajas, J.; Silva, J. A. P.; Fonseca, J. E.; Zimba, O.; Bohdana, D.; Ima-Edomwonyi, U.; Dedeke, I.; Airenakho, E.; Madu, N. H.; Yerima, A.; Olaosebikan, H.; Becky, A.; Koussougbo, O. D.; Palalane, E.; So, H.; Ugarte-Gil, M. F.; Chinchay, L.; Bernaola, J. P.; Pimentel, V.; Fathi, H. M.; Mohammed, R. H. A.; Harifi, G.; Fuentes-Silva, Y.; Cabriza, K.; Losanto, J.; Colaman, N.; Cachafeiro-Vilar, A.; Bautista, G. G.; Ho, E. J. G.; Gonzalez, R.; Nunez, L. S.; Cristian Vergara, M.; Baez, J. T.; Alonzo, H.; Pastelin, C. B. S.; Salinas, R. G.; Obiols, A. Q.; Chavez, N.; Ordonez, A. B.; Llerena, G. A. R.; Sierra-Zorita, R.; Arrieta, D.; Hidalgo, E. R.; Saenz, R.; Idania Escalante, M.; Calapaqui, W.; Quezada, I.; Arredondo, G.. - In: RHEUMATOLOGY. - ISSN 1462-0324. - 63:1(2024), pp. 127-139. [10.1093/rheumatology/kead180]
Flares in IIMs and the timeline following COVID-19 vaccination: a combined analysis of the COVAD-1 and -2 surveys
Sebastiani M.;
2024-01-01
Abstract
Objectives: Disease flares in the post-coronavirus disease 2019 (COVID-19) vaccination period represent a prominent concern, though risk factors are poorly understood. We studied these flares among patients with idiopathic inflammatory myopathies (IIMs) and other autoimmune rheumatic diseases (AIRDs). Methods: The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with >7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models. Results: Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7-235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P < 0.001) were associated with disparity between self-reported and IS-denoted flares. Conclusion: A diagnosis of IIMs confers an equal risk of flares in the post-COVID-19 vaccination period to AIRDs, with active disease, female gender and comorbidities conferring a higher risk. Disparity between patient- and physician-reported outcomes represents a future avenue for exploration.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.