BACKGROUND: The aim of tubal testing is to identify women with bilateral tubal pathology in a timely manner, so they can be treated with IVF or tubal surgery. At present, it is unclear for which women early tubal testing is indicated, and in whom it can be deferred. METHODS: Data on 3716 women who underwent tubal patency testing as a part of their routine fertility workup were used to relate elements in their medical history to the presence of tubal pathology. With multivariable logistic regression, we constructed two diagnostic models. One in which tubal disease was defined as occlusion and/or severe adhesions of at least one tube, whereas in a second model, tubal disease was defined as the presence of bilateral abnormalities. RESULTS: Both models discriminated moderately well between women with and women without tubal disease with an area under the receiver-operating characteristic curve (AUC) of 0.65 (95% CI: 0.63-0.68) for any tubal pathology and 0.68 (95% CI: 0.65-0.71) for bilateral tubal pathology, respectively. However, the models could make an almost perfect distinction between women with a high and a low probability of tubal pathology. A decision rule in the form of a simple diagnostic score chart was developed for application of the models in clinical practice. CONCLUSIONS: In conclusion, the present study provides two easy to use decision rules that can accurately express a woman's probability of (severe) tubal pathology at the couple's first consultation. They could be used to select women for tubal testing more efficiently.
BACKGROUND: The aim of tubal testing is to identify women with bilateral tubal pathology in a timely manner, so they can be treated with IVF or tubal surgery. At present, it is unclear for which women early tubal testing is indicated, and in whom it can be deferred. METHODS: Data on 3716 women who underwent tubal patency testing as a part of their routine fertility workup were used to relate elements in their medical history to the presence of tubal pathology. With multivariable logistic regression, we constructed two diagnostic models. One in which tubal disease was defined as occlusion and/or severe adhesions of at least one tube, whereas in a second model, tubal disease was defined as the presence of bilateral abnormalities. RESULTS: Both models discriminated moderately well between women with and women without tubal disease with an area under the receiver-operating characteristic curve (AUC) of 0.65 (95% CI: 0.63-0.68) for any tubal pathology and 0.68 (95% CI: 0.65-0.71) for bilateral tubal pathology, respectively. However, the models could make an almost perfect distinction between women with a high and a low probability of tubal pathology. A decision rule in the form of a simple diagnostic score chart was developed for application of the models in clinical practice. CONCLUSIONS: In conclusion, the present study provides two easy to use decision rules that can accurately express a woman's probability of (severe) tubal pathology at the couple's first consultation. They could be used to select women for tubal testing more efficiently.