Effect of psychological nursing intervention on the quality of life of breast cancer patients based on meta-analysis
We thank Dr. Feng and others for their comments on systematic review and meta-analysis of the efficiency and safety of psychological intervention nursing on the quality of life of breast cancer patients published in Gland Surgery (1). In this paper, the literature search chapter supplements Scopus, Web of Science and Cochrane Library and other electronic databases. Looking carefully at Fig. 2 and Fig. 3, it is found that allocation concealment is mentioned in five documents, so this part is explained again.
In a meta-analysis, the heterogeneity among studies has to be analyzed and its possible source has to be explored in detail, which are essential. Meta-regression analysis (MRA) is an extension of subgroup analysis (SGA) by combining the effects of different factors (2,3). If there are more than 10 studies included, the MRA and SGA are necessary to be performed (4). However, there are less than 10 studies in which each observation index is included in this paper, failing to satisfying the basic requirement on number of studies of MRA and SGA, so heterogeneity results are not performed with the MRA and SGA further. We hope you can understand this point. The heterogeneity of this paper may come from the fact that the sample size of the study is generally small, the nursing methods implemented by different research centers are different, and the follow-up time of patients included in the literature is relatively short. At the end of the discussion chapter, the heterogeneous sources of this paper are supplemented clearly, hoping it can meet the related requirement.
In a meta-analysis, the publication bias can be determined by many different methods, such as the funnel plot method, safety loss method, Begg rank correlation method, and Egger regression method (5). In this paper, the funnel circles are found to be distributed near the midline symmetrically, which meant high accuracy and no publication bias of the enrolled studies. However, due to the relatively small space of the included literature, the reasons for possible bias are added in the discussion part. There may be potential selection bias, loss of visit bias, information bias, confounding bias, and recall bias in this paper. Please check the revised manuscript.
Acknowledgments
Funding: None.
Footnote
Provenance and Peer Review: This article was commissioned by the Editorial Office, Gland Surgery. The article did not undergo external peer review.
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-2022-04/coif). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
References
- Li H, Li J, Wang X, et al. Systematic review and meta-analysis of the efficacy and safety of psychological intervention nursing on the quality of life of breast cancer patients. Gland Surg 2022;11:882-91. [Crossref] [PubMed]
- Leeflang MM. Systematic reviews and meta-analyses of diagnostic test accuracy. Clin Microbiol Infect 2014;20:105-13. [Crossref] [PubMed]
- Sousa MR, Ribeiro AL. Systematic review and meta-analysis of diagnostic and prognostic studies: a tutorial. Arq Bras Cardiol 2009;92:229-45. [Crossref] [PubMed]
- Ma X, Nie L, Cole SR, et al. Statistical methods for multivariate meta-analysis of diagnostic tests: An overview and tutorial. Stat Methods Med Res 2016;25:1596-619. [Crossref] [PubMed]
- Lin L, Chu H. Quantifying publication bias in meta-analysis. Biometrics 2018;74:785-94. [Crossref] [PubMed]