A systematic methodological review of non-randomised interventional studies of elective ventral hernia repair: clear definitions and a standardised minimum dataset are needed.

BACKGROUND

Ventral hernias (VHs) often recur after surgical repair and subsequent attempts at repair are especially challenging. Rigorous research to reduce recurrence is required but such studies must be well-designed and report representative and comprehensive outcomes.

OBJECTIVE

We aimed to assesses methodological quality of non-randomised interventional studies of VH repair by systematic review.

METHODS

We searched the indexed literature for non-randomised studies of interventions for VH repair, January 1995 to December 2017 inclusive. Each prospective study was coupled with a corresponding retrospective study using pre-specified criteria to provide matched, comparable groups. We applied a bespoke methodological tool for hernia trials by combining relevant items from existing published tools. Study introduction and rationale, design, participant inclusion criteria, reported outcomes, and statistical methods were assessed.

RESULTS

Fifty studies (17,608 patients) were identified: 25 prospective and 25 retrospective. Overall, prospective studies scored marginally higher than retrospective studies for methodological quality, median score 17 (IQR: 14-18) versus 15 (IQR 12-18), respectively. For the sub-categories investigated, prospective studies achieved higher median scores for their, 'introduction', 'study design' and 'participants'. Surprisingly, no study stated that a protocol had been written in advance. Only 18 (36%) studies defined a primary outcome, and only 2 studies (4%) described a power calculation. No study referenced a standardised definition for VH recurrence and detection methods for recurrence varied widely. Methodological quality did not improve with publication year or increasing journal impact factor.

CONCLUSION

Currently, non-randomised interventional studies of VH repair are methodologically poor. Clear outcome definitions and a standardised minimum dataset are needed.