Pre-operative Prolapse Phenotype is Predictive of Surgical Outcome with Minimally Invasive Sacrocolpopexy

Abstract

The gold standard treatment for advanced pelvic organ prolapse is sacrocolpopexy. However, the pre-operative features of prolapse that predict optimal outcomes are unknown. We aimed to develop a clinical prediction model that uses pre-operative scores on the Pelvic Organ Prolapse Quantification examination to predict outcomes after minimally invasive sacrocolpopexy for stages 2, 3, and 4 uterovaginal prolapse and vaginal vault prolapse. A two-institution database of pre- and post-operative variables from 881 cases of minimally invasive sacrocolpopexy was analyzed. Data from patients were analyzed in four groups: stage 2 uterovaginal prolapse, stage 3-4 uterovaginal prolapse, stage 2 vaginal vault prolapse, and stage 3-4 vaginal vault prolapse. Unsupervised machine learning was used to identify clusters and investigate associations between clusters and outcome. The K-means clustering analysis was performed with pre-operative Pelvic Organ Prolapse Quantification points and stratified by prior hysterectomy status. The "optimal" surgical outcome was defined as post-operative Pelvic Organ Prolapse Quantification stage <2. Demographic variables were compared by cluster with Student's t-test and Chi-squared tests. Odds ratios were calculated to determine whether clusters could predict the outcome. Age at surgery, body mass index, and prior prolapse surgery were used for adjusted odds ratios. Five statistically distinct prolapse clusters (phenotypes C, A, A>P, P, and P>A) were found. These phenotypes reflected the predominant region of prolapse (apical, anterior, or posterior) and whether or not support was preserved in the non-predominant region. Phenotype A (anterior compartment prolapse predominant, posterior support preserved) was found in all four groups of patients and was considered the reference in analysis. In 111 patients with stage 2 uterovaginal prolapse, phenotypes A and A>P (greater anterior prolapse than posterior prolapse) were found, and patients with phenotype A were more likely than those with phenotype A>P to have an optimal surgical outcome. In 401 patients with stage 3-4 uterovaginal prolapse, phenotypes C (apical compartment predominant, prolapse in all compartments), A, and A>P were found, and patients with phenotype A>P were more likely than those with phenotype A to have ideal surgical outcome. In 72 patients with stage 2 vaginal vault prolapse, phenotypes A, A>P, and P (posterior compartment predominant, anterior support preserved) were found, and those with phenotype A>P were less likely to have an ideal outcome than patients with phenotype A. In 297 patients with stage 3-4 vaginal vault prolapse, phenotypes C, A, and P>A (prolapse greater in posterior compartment than in anterior) were found, but there were no significant differences in rate of ideal outcome between phenotypes. Five anatomic phenotypes based on pre-operative Pelvic Organ Prolapse Quantification scores were present in patients with stages 2 and 3-4 uterovaginal prolapse and vaginal vault prolapse. These phenotypes are predictive of surgical outcome after minimally invasive sacrocolpopexy. Further work needs to confirm the presence and predictive nature of these phenotypes. Additionally, whether the phenotypes represent a progression of prolapse or discrete prolapse presentations resulting from different anatomic and life course risk profiles is unknown. These phenotypes may be useful in surgical counseling and planning.