Residual disease after primary surgery for advanced epithelial ovarian cancer: expert elicitation exercise to explore opinions about potential impact of publication bias in a planned systematic review and meta-analysis

Abstract

Objectives We consider expert opinion and its incorporation into a planned meta-analysis as a way of adjusting for anticipated publication bias. We conduct an elicitation exercise among eligible British Gynaecological Cancer Society (BGCS) members with expertise in gynaecology.Design Expert elicitation exercise.Setting BGCS.Participants Members of the BGCS with expertise in gynaecology.Methods Experts were presented with details of a planned prospective systematic review and meta-analysis, assessing overall survival for the extent of excision of residual disease (RD) after primary surgery for advanced epithelial ovarian cancer. Participants were asked views on the likelihood of different studies (varied in the size of the study population and the RD thresholds being compared) not being published. Descriptive statistics were produced and opinions on total number of missing studies by sample size and magnitude of effect size estimated.Results Eighteen expert respondents were included. Responders perceived publication bias to be a possibility for comparisons of RD <1 cm versus RD=0 cm, but more so for comparisons involving higher volume suboptimal RD thresholds. However, experts’ perceived publication bias in comparisons of RD=0 cm versus suboptimal RD thresholds did not translate into many elicited missing studies in Part B of the elicitation exercise. The median number of missing studies estimated by responders for the main comparison of RD<1 cm versus RD=0 cm was 10 (IQR: 5–20), with the number of missing studies influenced by whether the effect size was equivocal. The median number of missing studies estimated for suboptimal RD versus RD=0 cm was lower.Conclusions The results may raise awareness that a degree of scepticism is needed when reviewing studies comparing RD <1 cm versus RD=0 cm. There is also a belief among respondents that comparisons involving RD=0 cm and suboptimal thresholds (>1 cm) are likely to be impacted by publication bias, but this is unlikely to attenuate effect estimates in meta-analyses.