| Literature DB >> 35429819 |
Mario Habek1, Dominik Piskač2, Tereza Gabelić3, Barbara Barun3, Ivan Adamec3, Magdalena Krbot Skorić4.
Abstract
OBJECTIVE: To determine the influence of immunoglobulins (Ig) level on the rate of infections in people with multiple sclerosis (pwMS) treated with ocrelizumab.Entities:
Keywords: COVID-19; Hypogammaglobulinemia; infections; multiple sclerosis; ocrelizumab
Mesh:
Substances:
Year: 2022 PMID: 35429819 PMCID: PMC8994678 DOI: 10.1016/j.msard.2022.103798
Source DB: PubMed Journal: Mult Scler Relat Disord ISSN: 2211-0348 Impact factor: 4.808
Demographic characteristics of the cohort (N=109).
| Age | 44.6±9.5 |
| Sex (females) | 75 (68.8%) |
| MS phenotype | |
| RRMS | 73 (67%) |
| PPMS | 36 (33%) |
| Disease duration (years) | 8.5±5.8 |
| EDSS | 3.5 (0-7.0) |
| Number of relapses in the previous year | 1 (0-3) |
| Number of active lesions in the most recent MRI (N=100) | 1 (0-20) |
| Previous DMTs | |
| Treatment naïve | 34 (31.2%) |
| 1 previous DMT | 58 (53.2%) |
| 2previous DMTs | 13 (11.9%) |
| ≥3previous DMTs | 4 (3.7%) |
| Previous DMTs* | |
| 1st line injectables | 51 (46.4%) |
| 1st line orals | 21 (19.1%) |
| Azathioprine | 1 (0.9%) |
| Fingolimod | 9 (8.2%) |
| Natalizumab | 1 (0.9%) |
| Alemtuzumab | 2 (1.8%) |
| Rituximab | 1 (0.9%) |
| Duration of previous therapies (months) | 64.3±47.9 |
| Number of ocrelizumab cycles | |
| 2 | 3 (2.8%) |
| 3 | 8 (7.3%) |
| 4 | 19 (17.4%) |
| 5 | 42 (38.5%) |
| 6 | 29 (26.6%) |
| 7 | 5 (4.6%) |
| 8 | 3 (2.8%) |
Fig. 1Proportion of pwMS with levels of IgM and IgG below lower level of normal.
Fig. 2Absolute levels of IgM and IgG before each new cycle of the ocrelizumab.
Rate and characteristics of infections in the studied cohort (N=109).
| Number of pwMS having any infection | 64 (58.7%) |
| Median number of infections per pwMS | 1 (0-4) |
| Number of infections per pwMS (distribution) | |
| 0 | 45 (41.3%) |
| 1 | 37 (33.9%) |
| 2 | 19 (17.4%) |
| 3 | 7 (6.4%) |
| 4 | 1(0.9%) |
| Type of infection (number of events) | |
| Respiratory | 39 |
| Urinary | 40 |
| Skin | 14 |
| Gastrointestinal | 3 |
| Other | 4 |
| Duration of infections | 10 (2-42) |
| Number of episodes requiring specific treatment | 69 |
| Number of episodes requiring hospitalization | 9 |
| Number of pwMS with COVID-19 | 35 (32.1%) |
| Number of pwMS with COVID-19 requiring treatment (antibiotics, steroids, remdesivir, antibodies) | 14 (40%) |
| Number of pwMS with COVID-19 requiring hospitalization | 7 (20%) |
| Number of pwMS who received COVID-19 vaccine | 68 (62.4%) |
| 1 dose | 3 (2.8%) |
| 2 doses | 41 (37.6%) |
| 3 doses | 24 (22.0%) |
| Number of pwMS with COVID-19 after vaccination | 11 of 19 (57.9%) |
Fig. 3Kaplan-Meier survival curve showing survival probability for a) the first infection, b) infection requiring hospitalization and c) COVID-19.
Results of the univariable and multivariable Cox hazard models for predicting any infection, infection requiring hospitalization and COVID-19 in pwMS treated with ocrelizumab.
| Univariable COX hazard model | Multivariable Cox hazard model | |||||
|---|---|---|---|---|---|---|
| HR | 95% C.I. for HR | p value | HR | 95% C.I. for HR | p value | |
| Age | 0.998 | 0.973-1.024 | 0.881 | |||
| Sex | 2.561 | 1.382-4.774 | 0.003 | |||
| Disease duration | 1.01 | 0.968-1.055 | 0.633 | |||
| EDSS | 0.962 | 0.822-1.127 | 0.635 | |||
| MS phenotype | 0.832 | 0.479-1.445 | 0.514 | |||
| Δ IgM | 0.841 | 0.387-1.829 | 0.663 | |||
| Δ IgG | 0.83 | 0.649-1.063 | 0.14 | |||
| Age | 1.099 | 1.030-1.173 | 0.004 | 1.086 | 1.018-1.159 | 0.013 |
| Sex | 0.641 | 0.169-2.431 | 0.513 | |||
| Disease duration | 0.216 | 0.963-1.180 | 0.216 | |||
| EDSS | 0.953 | 0.626-1.452 | 0.824 | |||
| MS phenotype | 1.913 | 0.478-7.655 | 0.359 | |||
| Δ IgM | 11.321 | 1.836-69.824 | 0.009 | 9.216 | 1.124-75.558 | 0.039 |
| Δ IgG | 1.452 | 0.896-2.355 | 0.13 | |||
| COVID-19 | ||||||
| Age | 1.005 | 0.965-1.047 | 0.802 | |||
| Sex | 1.33 | 0.583-3.033 | 0.498 | |||
| Disease duration | 1.09 | 1.025-1.158 | 0.006 | 1.075 | 1.002-1.154 | 0.045 |
| EDSS | 1.211 | 0.976-1.503 | 0.082 | |||
| MS phenotype | 1.071 | 0.454-2.527 | 0.875 | |||
| Δ IgM | 2.369 | 1.014-5.534 | 0.046 | 1.426 | 0.576-3.531 | 0.443 |
| Δ IgG | 0.938 | 0.687-1.280 | 0.686 | |||
adjusted to possible COVID-19 exposure (from March 2020) and number of COVID-19 vaccines received