Is an Increased Risk of Developing Guillain–Barré Syndrome Associated with Seasonal Influenza Vaccination? A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Selection and Characteristics of Studies
3.2. iTIV Vaccination and GBS Risk
3.3. Estimate of GBS Risk in Specific Subgroups
3.4. Influenza and GBS Risk
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Study, Year [Ref.]; Country; Study Period | Study Design | Participants | iTIV1 (%) | GBS2 Assessment | Time Window (Days) | Effect Size (95% CI3) | Quality |
---|---|---|---|---|---|---|---|
Hurwitz 1981 [11]; USA; 1978–1979 | C4 | F9: 44%; Age: 0–95 y10; 544 pts11 | 100 | Committee12 | ≤56 | cRR13:1.4 (0.7–2.7) | N14 |
Kaplan 1982 [12]; USA; 1979–1981 | C | F: 43%; Age: 15–74 y; 778 pts | 100 | Neurologists | ≤56 | cRR:0.6 (0.29–1.31) S1979–198021cRR:1.4 (0.8–2.5) S1980–1981 | N |
Lasky 1998 [32]; USA; 1992–1994 | C | F: 38%; Age: ≥18 y; 273 pts | 100 | ICD-9: 357.015 | ≤42 | aRR13:2.0 (<1.0–4.3) S1992–1993aRR:1.5 (0.8–2.9) S1993–1994 | Y14 |
Liu 2003 [33]; China; ? | C-C5 | F: 49%; Age: 1–14 y; 51 pts and 51 controls | 10016 | Selection criteria17 | Any time | OR18:3.13 (0.27–82.33) | N |
Hughes 2006 [13]; UK; 1992–2000 | SCCS6 | F: 47%; Age: 0+; 228 pts | 100 | ICD-9: 357.0 | ≤42 | aRR:0.99 (0.32–3.12) | Y |
Juurlink 2006 [34]; Canada; 1992–2004 | SCCS | F: ?19; Age: ≥18 y; 685 pts | 100 | ICD-9: 357.0 | ≤49 | aRR:1.45 (1.05–1.99) | Y |
Tam 2007 [4]; UK; 1990–2001 | C-C | F: ?; Age: 0+ y; 553 pts and 5445 controls | 100 | ICD-9: 357.0 | ≤60 | aOR18:0.16 (0.02–1.25) | Y |
Stowe 2009 [14]; UK; 1990–2005 | SCCS | F: 43%; Age: 0+ y; 690 pts | 100 | ICD-9: 357.0 | ≤30≤180 | aRR20:0.58 (0.18–1.86)aRR:0.80 (0.51–1.27) | Y |
Burwen 2010 [15]; USA; 2000–2002 | SCRI7 | F: 60%; Age: 0+ y; 164 pts | 100 | BCC: 1,222 | ≤42 | IRR20:0.86 (0.52–1.41) S2000–2001IRR:1.21 (0.79–1.86) S2001–2002 | Y |
Grimaldi-Bensouda 2011 [16] France; 2007–2010 | C-C | F: 39%; Age: 3–80 y; 145 pts and 1080 controls | 100 | BCC: 1,2,3 | ≤42≤180 | aOR:1.3 (0.41–4.12)cOR4:0.74 (0.46–1.19)23 | Y |
Ho 2012 [35]; Taiwan; 2008–2009 | C | F: 52%; Age: ≥65 y; 41,986 vaccinated and 51,063 unvaccinated | 100 | ICD-9: 357.0 | ≤365 | aOR:1.64 (0.77–3.49) | Y |
Tokars 2012 [36]; USA; 2009-2010 | SCRI | F: 58%; Age: 2–88 y; 78 pts | >51,3 | BCC: 1,2,3 | ≤42 | RR:1.5 (0.8–3.0)24 | Y |
Wise 2012 [17]; USA; 2009–10 | C | F: 48%; Age: 0+ y; 411 pts | >53 | BCC: 1,2,3 | ≤42 | aRR:1.43 (0.94–1.89) | Y |
Greene 2012 [18]; USA; 2009–2010 | SCRI | F: 63%; Age: 2–83 y; 14 pts | 100 | BCC: 1,2,3 | ≤42 | RR:1.0 (0.3–3.5) | Y |
Crawford 2012 [19]; Australia; 2010–2011 | SCCS | F: 48%; Age: 7–95 y; 54 pts | 100 | BCC: 1,2,3,4 | ≤42 | IRR:0.69 (0.08–5.64) | Y |
Baxter 2013 [20]; USA; 1995–2006 | Cc8 | F: 41%; Age: 5–87 y; 451 pts | 100 | BCC: 1,2,3 | ≤42 | aOR:1.11 (0.39–3.08) | Y |
≤70 | aOR:0.99 (0.33–2.70) | ||||||
Galeotti 2013 [37]; Italy; 2010–2011 | C-C | F: 42%; Age: ≥18 y; 140 pts and 308 controls | 100 | BCC: 1,2,3 | ≤42 | aOR:3.8 (1.3–10.5) | Y |
≤365 | aOR:1.6 (0.9–2.7) | ||||||
Kwong 2013 [38]; Canada; 1993–2011 | SCCS | F: 46%; Age: 0+ y; 330 pts | 100 | ICD-9: 357.0 | ≤42 | IRR:1.52 (1.17–1.99) | Y |
McCarthy 2013 [39]; USA; 2009–2011 | SCRI | F: ?; Age: 0–80 y; 1021 pts | ? | ICD-9: 357.0 | ≤42 | aRR:1.57 (0.61–4.05) S2009–2010aRR:1.00 (0.45–2.23) S2010-2011 | Y |
Kawai 2014 [21]; USA; 2012–2013 | SCRI | F: 44%; Age: 0+ y; 116 pts | 100 | ICD-9: 357.0 | ≤42 | aRR:0.5 (0.3–0.9) | Y |
Chang 2019 [22]; Taiwan; 2007–2015 | C-C | F: 38%; Age: ≥50 y; 182 pts and 910 controls | 100 | ICD-9: 357.0 | ≤42≤90 | OR:1.46 (0.56–3.78)OR:1.26 (0.67–2.38) | Y |
Chen 2019 [40]; China; 2011–2015 | C-C | F: 38%; Age: 0+ y; 1056 pts and 4312 controls | 10016 | BCC: 1,2,3 | ≤42 | aOR:1.03 (0.73–1.45) | Y |
Critical Variable | High-Quality Studies | All Studies | |||
---|---|---|---|---|---|
Study Records | ES1 (95% CI2) | Study Records | ES (95% CI) | ||
Time window | shorter3 | 17 | 1.19 (0.99–1.44) | 18 | 1.20 (1.00–1.44) |
longer4 | 7 | 1.08 (0.77–1.52) | 12 | 1.12 (0.89–1.42) | |
Age (years) | ≥65 | 5 | 1.11 (0.88–1.39) | 5 | 1.11 (0.88–1.39) |
Study (type) | C-C | 4 | 0.97 (0.62–1.53) | 6 | 1.05 (0.74–1.48) |
C | 4 | 1.56 (1.16–2.09) | 7 | 1.39 (1.10–1.75) | |
SCCS | 5 | 1.25 (0.94–1.65) | 5 | 1.25 (0.94–1.65) | |
SCRI | 7 | 0.98 (0.72–1.34) | 7 | 0.98 (0.72–1.34) | |
Geographic region | North America | 13 | 1.24 (1.02–1.50) | 16 | 1.22 (1.02–1.45) |
Europe | 5 | 0.90 (0.58–1.40) | 5 | 0.90 (0.58–1.40) | |
Influenza season | 2009–2010 | 4 | 1.43 (1.03–1.97) | 4 | 1.43 (1.03–1.97) |
2010–2011 | 3 | 1.35 (0.88–2.07) | 3 | 1.35 (0.88–2.07) |
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Petráš, M.; Králová Lesná, I.; Dáňová, J.; Čelko, A.M. Is an Increased Risk of Developing Guillain–Barré Syndrome Associated with Seasonal Influenza Vaccination? A Systematic Review and Meta-Analysis. Vaccines 2020, 8, 150. https://doi.org/10.3390/vaccines8020150
Petráš M, Králová Lesná I, Dáňová J, Čelko AM. Is an Increased Risk of Developing Guillain–Barré Syndrome Associated with Seasonal Influenza Vaccination? A Systematic Review and Meta-Analysis. Vaccines. 2020; 8(2):150. https://doi.org/10.3390/vaccines8020150
Chicago/Turabian StylePetráš, Marek, Ivana Králová Lesná, Jana Dáňová, and Alexander M. Čelko. 2020. "Is an Increased Risk of Developing Guillain–Barré Syndrome Associated with Seasonal Influenza Vaccination? A Systematic Review and Meta-Analysis" Vaccines 8, no. 2: 150. https://doi.org/10.3390/vaccines8020150
APA StylePetráš, M., Králová Lesná, I., Dáňová, J., & Čelko, A. M. (2020). Is an Increased Risk of Developing Guillain–Barré Syndrome Associated with Seasonal Influenza Vaccination? A Systematic Review and Meta-Analysis. Vaccines, 8(2), 150. https://doi.org/10.3390/vaccines8020150