Methodological Remarks Regarding the Meta Analysis on Possible Associations of Maternal Factors During Pregnancy With the Risk of Childhood Acute Lymphoblastic Leukemia
To the Editor: We read with great interest the recent metaanalysis by Yan et al.[1] on the associations of maternal factors during pregnancy and the risk of childhood acute lymphoblastic leukemia (ALL) Yet, certain methodological shortcomings, overlooked in this meta analysis, need to be addressed. Exclusion of overlapping studies, namely, studies that have been performed on the same population during time intervals overlapping each other, is a prerequisite in the quantitative synthesis of studies included in a meta analysis, as to avoid introducing replicate datasets in the synthesized scientific evidence.[2] The authors stated that the issue of overlap was addressed by retaining only the largest or themost recent study; nevertheless, in the forest plots provided by Yan et al. several publications springing from the same population during coinciding time periods were included as independent studies. Most strikingly, in the forest plot for birth order (Fig. 2) the AusALL study, a case control study conducted during 2003 2007[3] was represented by five studies [Bailey et al. (2011) Milne et al. (2009) Milne et al. (2010) Milne et al. (2012) and Milne et al. (2013) along with twoGreek studies [Diamantaras et al. (2013) and Lariou et al. (2013) reporting on the same study population of the Nationwide Registry of Childhood Hematological Malignancies (NARECHEM) during the period 1999 2003;[4] likewise, in both included Californian studies [Ma et al. (2005) and Oksuzyan et al. (2013) the Californian Cancer Registrywas the source of cases and the study periods coincided.[5] Similarly, in the forest plot examining maternal age (Supplementary Fig. S2) six studies (Bartley et al. (2005) Chang et al. (2006) Kwan et al. (2005) Kwan et al. (2009) Ma et al. (2005a) and Ma et al. (2005b) overlapped completely with the study by Oksuzyan et al.[5] three Greek studies (Diamantaras et al. (2013) Lariou et al. (2013) and Petridou et al. (2005) were based on overlapping populations during the same time period and five studies [Bailey et al. (2010) Bailey et al. (2011) Milne et al. (2009) Milne et al. (2013) and Reid et al. (2011) were actually different publications of the Aus ALL study for the period 2003 2007.[3] Moreover, as studies published up to 2014 were included, it is indirectly inferred that the end of search date, not disclosed in the paper, was 2014. If this is indeed the case, multiple potentially eligible studies were not included; not even, a large US multicenter study by Johnson et al. comprising over 4,000 childhood ALL cases, [6] published back in 2009. In conclusion, repeated inclusion of the same study populations via multiple publications as well as non identification of eligible studies during the search and selection of studies process, may have considerably distorted the pooled effect estimates in the recent meta analysis addressing exposures, as maternal age, birth order, and maternal education in association with childhood ALL. An elaborate strategy employing snowball procedures seems required in this context, as the respective variables are often used in multivariate models, aiming to investigate other exposures.
Pediatric blood cancer