PROBABILITY OF SUCCESS WITH LAPAROSCOPIC VERSUS HYSTEROSCOPIC STERILIZATION

Purpose: Female sterilization is the second most common method of contraception used by US women.  Hysteroscopic sterilization (HS) is a relatively new approach that is becoming more popular than laparoscopic sterilization (LS) due to presumed greater convenience, lower cost, and less morbidity.  However, due to an inconvenient series of procedures required to ensure success, HS has higher rates of failed procedures and non-compliance with essential follow-up; many women who fail HS undergo LS.  Current published assessments of the success of HS do not adequately address these issues.

Method: We constructed a Markov model to estimate the probability of sterilization via 3 strategies: LS, HS in the operating room, and HS in the office setting. Cohorts were followed for 1 year.  Procedure and follow-up testing probabilities were estimated from published sources.  Additional outcome data came from a case series being prepared for publication. We assumed that HS success was identical whether or not women completed follow-up testing, that 20% of women who failed LS would accept HS, that a second HS had similar success regardless of operating room or office location, and that there was no third HS attempt.  Women in HS strategies who ultimately received LS were counted as an HS success, biasing against the LS strategy.

Result: In the base case analysis, the probability of being sterilized is 99.1% with LS, 96.6% for HS in the office, and 91.8% for HS in the operating room.  In sensitivity analyses, despite the bias against it, LS was favored; the lowest LS success rate was 98.3% and the highest rates for HS were 97.5% (office), and 93.4% (operating room).

Conclusion: In our analysis, HS was at least 0.8% less likely to be successful than LS.  With approximately 345,000 women in the United States undergoing LS or HS annually, this could mean ≥2,760 women request but do not achieve sterilization annually if HS is performed.  Subsequent work will incorporate newer data, updated pregnancy rates, and the differing costs and utilities between procedures in a formal probabilistic cost-effectiveness analysis.