Disease Markers
Volume 2019 (2019), Article ID 4391957, 4 pages
https://doi.org/10.1155/2019/4391957

Letter to the Editor

Response to: Comment on “Sex Differences in the Association between Night Shift Work and the Risk of Cancers: A Meta-Analysis of 57 Articles”

Wen Liu, Zhonghan Zhou, Dahai Dong, Lijiang Sun, and Guiming Zhang

Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China

Correspondence should be addressed to Lijiang Sun; slijiang999@126.com and Guiming Zhang; zhangguiming9@126.com

Received 25 March 2019; Accepted 28 March 2019; Published 7 July 2019

Academic Editor: Fabrizia Bamonti

Copyright © 2019 Wen Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

First of all, I would like to thank Professor Zhenyu Chen for his “Comment on “Sex Differences in the Association between Night Shift Work and the Risk of Cancers: A Meta-Analysis of 57 Articles”” [1]. The answers to the questions raised by Professor Chen are as follows.

In this paper, we conducted searches in strict accordance with PRISMA and the Cochrane handbook. We have indeed given a retrieval strategy in the original article: the search terms were “night shift work” or “rotating shift work” or “night work” or “shift work” and “carcinoma” or “neoplasm” or “tumor” or “cancer”, see Supplementary Search Strategy.

We stated in our article that we tested heterogeneity between studies by statistic with indicating heterogeneity, and if no significant heterogeneity existed, a fixed effects model was adopted, otherwise a random effects model was used. For this question, we recalculated the data (Table 1) with a random effects model and verified that the outcomes in our article were correct [1], so we do not doubt the statistical methods in our study.

Table 1: The data for calculating sex differences in the association between night shift work and cancer risk.

Study
OR
LCI
UCI
Gender

Walasa WM (2018)
0.95
0.57
1.58
Female

Talibov M (2018)
1.03
0.98
1.08
Female

Papantoniou K (2016)
1.21
0.89
1.65
Female

Wang P (2015)
1.34
1.05
1.72
Female

Li WJ (2015)
0.73
0.66
0.82
Female

Datta K (2014)
1.51
0.27
8.52
Female

Rabstein S (2013)
1.01
0.68
1.5
Female

Fritschi L (2013)
1.02
0.71
1.45
Female

Menegaux F (2013)
1.4
1.01
1.92
Female

Grundy A (2013)
2.21
1.14
4.31
Female

Bhatti P (2013)
1.02
0.74
1.42
Female

Hansen J (2012)
2.1
1.3
3.2
Female

Hansen J (2012)
2.1
1
4.5
Female

Lie JS (2011)
1.3
0.9
1.8
Female

Lie JS (2006)
2.21
1.1
4.45
Female

Pesch B (2010)
2.48
0.62
9.99
Female

Hansen J (2001)
1.5
1.3
1.7
Female

Truong (2014)
1.32
1.02
1.72
Female

Kwon P (2015)
0.88
0.69
1.12
Female

Davis S (2001)
1.6
0.8
3.2
Female

Leary ES (2006)
1.04
0.79
1.38
Female

Devore EE (2017)
0.96
0.83
1.11
Female

Knutsson A (2013)
2.02
1.03
3.95
Female

Carter BD (2014)
1.27
1.03
1.56
Female

Poole EM (2010)
0.8
0.51
1.23
Female

Viswanathan AN (2007)
1.47
1.03
2.1
Female

Akerstedt T (2015)
1.77
1.03
3.04
Female

Koppes LLJ (2014)
0.87
0.72
1.05
Female

Natti J (2012)
2.82
1.2
6.65
Female

Schernhammer ES (2006)
1.79
1.06
3.01
Female

Pronk A (2010)
0.8
0.5
1.2
Female

Schernhammer ES (2003)
1.35
1.03
1.77
Female

Vistisen HT (2017)
0.9
0.8
1.01
Female

Schernhammer ES (2013)
1.28
1.07
1.53
Female

Gu FY (2015)
1.08
0.98
1.19
Female

Lahti TA (2008)
1.02
0.94
1.12
Female

Bai YS (2016)
0.9
0.66
1.23
Female

Travis RC (2016)
1
0.92
1.08
Female

Wegrzyn LR (2017)
0.95
0.77
1.17
Female

Wegrzyn LR (2017)
2.15
1.23
3.73
Female

Heckman CJ (2017)
0.79
0.71
0.89
Female

Jorgensen JT (2017)
0.91
0.77
1.08
Female

Talibov M (2018)
1.03
0.98
1.09
Male

Tse LA (2017)
1.76
1.07
2.89
Male

Papantoniou K (2015)
1.38
1.05
1.81
Male

Parent M (2012)
2.02
1.25
3.26
Male

Natti J (2012)
1.78
0.8
4
Male

Lahti TA (2008)
1.1
1.03
1.19
Male

Bai YS (2016)
1.27
1.01
1.59
Male

Akerstedt T (2017)
0.91
0.74
1.12
Male

Dickerman BA (2016)
1
0.7
1.2
Male

Lin YS (2015)
1.43
0.78
2.63
Male

Hammer GP (2015)
0.93
0.73
1.18
Male

Gapstur SM (2014)
1.08
0.95
1.22
Male

Kubo T (2011)
1.79
0.57
5.68
Male

Behrens T (2017)
3.08
1.67
5.69
Male

Kubo T (2006)
3
1.2
7.7
Male

Lin YS (2013)
0.83
0.43
1.6
Male

Yong M (2014)
1.04
0.89
1.21
Male

Abbreviations: OR: odds ratio; LCI: lower confidence interval; UCI: upper confidence interval.

Due to the length of the article, the specific process of binary analysis was not presented. The binary analysis of dose-response relationship was performed before applying a generalized least-squares trend (GLST) model. The original data is shown in Supplementary Table 1. ORs and 95% CIs (the highest dose group compared with the reference dose group) were extracted to conduct binary analysis. The result of binary analysis was statistically significant (OR: 1.26; 95% CI: 1.13-1.40) (Figure 1), indicating that there was a positive association between night shift work and cancer. Therefore, the next step was to explore the dose-response relationship between night shift work and cancer. In addition, there are some meta-analysis articles which also analyzed dose-response relationship between night shift work and different cancer [2–5]. However, they did not mention the step of binary analysis in statistical methods, so we do not think that whether or not to mention binary analysis is the reason for questioning the dose-response relationship in our study.

Figure 1: The outcome of binary analysis.

We have analyzed the cause of publication bias and heterogeneity in our paper. First, as we have discussed in this paper, the contour-enhanced funnel plot and the trim and fill method were used together to analyze the cause of publication bias. The result showed that most of the filled studies were outside the 10% line, which indicated that the previously verified bias might be caused by heterogeneity, not the publication bias. Second, in the process of meta-analysis, a random effects model was used to minimize the influence of heterogeneity. Third, subgroup analyses and metaregression analyses were performed to assess the potential heterogeneity sources. Many subgroups, such as fixed shift, digestive system cancer, hematological system cancer, reproductive system cancer, and lung cancer, could decrease the value of and explain part of the heterogeneity (). As we have pointed out in the discussion, we attribute the remnant heterogeneity to inconsistent definition of work schedules, unclassified occupation based on population, ethnicity, and intrinsic defect of retrospective design; thus, further prospective study in a large-scale population should be performed to explore the relationship between night shift work and cancer. Fourth, leave-one-out analyses indicated a stable positive relationship between night shift work and the risk of cancer when the value of decreases to 29.8%. Therefore, we think that the conclusion of our study is credible and the closest to the truth so far.

In summary, we believe that the final conclusion of the paper after objective analysis is credible.

Conflicts of Interest

The authors declare no competing financial interests.

Supplementary Materials

Supplementary Search Strategy and Supplementary Table 1. (Supplementary Materials)

References

P. Sun, M. Bi, Y. Su, and Z. Chen, “Comment on “Sex differences in the association between night shift work and the risk of cancers: a meta-analysis of 57 articles”,” Disease Markers, vol. 2019, Article ID 9263862, 1 page, 2019.

Y. Gan, L. Li, L. Zhang et al., “Association between shift work and risk of prostate cancer: a systematic review and meta-analysis of observational studies,” Carcinogenesis, vol. 39, no. 2, pp. 87–97, 2018.

D. Rao, H. Yu, Y. Bai, X. Zheng, and L. Xie, “Does night-shift work increase the risk of prostate cancer? A systematic review and meta-analysis,” OncoTargets and Therapy, vol. 8, pp. 2817–2826, 2015.

X. Wang, A. Ji, Y. Zhu et al., “A meta-analysis including dose-response relationship between night shift work and the risk of colorectal cancer,” Oncotarget, vol. 6, no. 28, pp. 25046–25060, 2015.

X. Yuan, C. Zhu, M. Wang, F. Mo, W. Du, and X. Ma, “Night shift work increases the risks of multiple primary cancers in women: a systematic review and meta-analysis of 61 articles,” Cancer Epidemiology Biomarkers & Prevention, vol. 27, no. 1, pp. 25–40, 2018.