Vaginal native tissue repair versus transvaginal mesh repair for apical prolapse: how utilizing different methods of analysis affects the estimated trade-off between reoperation for mesh exposure/erosion and reoperation for recurrent prolapse.
INTRODUCTION AND HYPOTHESIS: Informed decision-making about optimal surgical repair of apical prolapse with vaginal native tissue (NT) versus transvaginal mesh (TVM) requires understanding the balance between the potential "harm" of mesh-related complications and the potential "benefit" of reducing prolapse recurrence. Synthesis of data from observational studies is required and the current literature shows that the average follow-up for NT repair is significantly longer than for TVM repair. We examined this harm/benefit balance. We hypothesized that using different methods of analysis to incorporate follow-up time would affect the balance of outcomes. METHODS: We used a Markov state transition model to estimate the cumulative 24-month probabilities of reoperation for mesh exposure/erosion or for recurrent prolapse after either NT or TVM repair. We used four different analytic approaches to estimate probability distributions ranging from simple pooled proportions to a random effects meta-analysis using study-specific events per patient-time. RESULTS: As variability in follow-up time was accounted for better, the balance of outcomes became more uncertain. For TVM repair, the incremental ratio of number of operations for mesh exposure/erosion per single reoperation for recurrent prolapse prevented increased progressively from 1.4 to over 100 with more rigorous analysis methods. The most rigorous analysis showed a 70% probability that TVM would result in more operations for recurrent prolapse repair than NT. CONCLUSIONS: Based on the best available evidence, there is considerable uncertainty about the harm/benefit trade-off between NT and TVM for apical prolapse repair. Future studies should incorporate time-to-event analyses, with greater standardization of reporting, in order to better inform decision-making.
Dieter, AA; Willis-Gray, MG; Weidner, AC; Visco, AG; Myers, ER
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