Can differences in IVF success rates between centres be explained by patient characteristics and sample size?
BACKGROUND: Pregnancy rates cannot be used reliably for comparison of IVF clinic performance because of differences in patients between clinics. We investigate if differences in pregnancy chance between IVF centres remain after adjustment for patient mix. METHODS: We prospectively collected IVF and ICSI treatment data from 11 out of 13 IVF centres in the Netherlands, between 2002 and 2004. Adjustment for sampling variation was made using a random effects model. A prognostic index for subfertility-related factors was used to adjust for differences in patient mix. The remaining variability between centres was split into random variation and true differences. RESULTS: The crude 1-year ongoing pregnancy chance per centre differed by nearly a factor 3 between centres, with hazard ratios (HRs) of 0.48 (95% CI: 0.34-0.69) to 1.34 (95% CI: 1.18-1.51) compared with the mean 1-year ongoing pregnancy chance of all centres. After accounting for sampling variation, the difference shrank since HRs became 0.66 (95% CI: 0.51-0.85) to 1.28 (95% CI: 1.13-1.44). After adjustment for patient mix, the difference narrowed somewhat further to HRs of 0.74 (95% CI: 0.57-0.94) to 1.33 (95% CI: 1.20-1.48) and 17 of the variation between centres could be explained by patient mix. The 1-year cumulative ongoing pregnancy rate in the two most extreme centres was 36% and 55%. CONCLUSION: SOnly a minor part of the differences in pregnancy chance between IVF centres is explained by patient mix. Further research is needed to elucidate the causes of the remaining differences.
|Keywords||Differences in clinics, IVF, League tables, Success rates|
|Persistent URL||dx.doi.org/10.1093/humrep/dep358, hdl.handle.net/1765/27859|
|Note||Free full text at PubMed|
Lintsen, A.M.E., Braat, D.D.M., Habbema, J.D.F., Kremer, J.A.M., & Eijkemans, M.J.C.. (2010). Can differences in IVF success rates between centres be explained by patient characteristics and sample size?. Human Reproduction, 25(1), 110–117. doi:10.1093/humrep/dep358