Objective To analyse biopsies of large loop excision of the transformation zone of the cervix; to identify factors associated with negative histology; and to develop predictive models in order to reduce the number of negative loop excisions.
Design Retrospective analysis of patient notes and audit database.
Setting Colposcopy clinic of a large district general hospital in North Staffordshire.
Population Four hundred and fifty-two women who underwent a large loop excision of the transformation zone (LLETZ) procedure for suspected cervical intraepithelial neoplasia.
Methods Women who underwent a LLETZ procedure were placed in two different groups, one positive for cervical intra epithelial neoplasia and the other negative for cervical intra epithelial neoplasia. Information was obtained on a number of clinical and colposcopic variables. Analysis was undertaken to determine if there were any differences between the two groups. These factors were then identified and three predictive models generated. Receiver-operator characteristic curves were used to assess and test these models.
Main outcomes measures To identify factors associated with negative histology on a LLETZ specimen. To predict how to reduce the number of negative LLETZ specimens.
Results Four hundred and fifty-two women underwent a LLETZ procedure, 88 were negative (19%) and 364 were positive (81%). In women who were treated at their first visit, 56/316 (18%) had negative histology. There were significant associations between negative histology in the LLETZ and negative or low grade cytological atypia, negative colposcopic findings and years of age > 50 in both bivariate analysis and stepwise logistic regression. In the predictive models, the sensitivity ranged between 72% and 80%, the specificity 59%–72%, and the area under the receiver-operator characteristic was 0.75–0.77. If we had used the predictor models and managed women with negative or low grade cervical atypia and negative colposcopy findings conservatively, we would have reduced the negative biopsy rate from 19% to 14%, but five cases of high grade disease and 25 cases of low grade disease would have been missed. If we had also included women aged > 50 years in this model, the negative biopsy rate would have dropped from 19% to 15%, with only one case of high grade disease and 11 cases of low grade disease missed. All these women would require continued cytological and colposcopic surveillance. Importantly, no cases of invasion would have been missed.
Conclusion Using a predictive model can reduce the number of negative LLETZ specimens, but at the expense of continued cytological and colposcopic surveillance and cannot be recommended in normal practice. This raises the question whether current standards for negative histology in LLETZ specimens are set unrealistically high.