RESUMEN
This narrative review describes the state of the art in the management of anastomotic leakage in ovarian cancer. Multiple surgical procedures, including bowel resection, are often required to achieve "optimal" cytoreduction in locally advanced ovarian cancer. Intestinal anastomosis is currently the most common way to restore bowel continuity. However, in some patients, a temporary protective stoma is indicated to prevent anastomotic leakage. This is an important issue to improve surgical outcomes and until recently there has been a lack of objective data to clarify the risk factors for anastomotic leakage. This review describes the risk factors for AL associated with surgery and compares the results of recent studies. We also review the current indications for placement of a protective ileostomy and treatment options for conservative management of AL. We present two examples of practical clinical AL risk calculators, in addition to the most assessed AL risk factor. To date, the decision-making processes that lead surgeons to perform a protective ileostomy are quite heterogeneous and based on the personal experience of the surgeon, mainly depending on individual training. Three different management options after colorectal anastomosis in OC are described: conservative management, diversion ileostomy and ghost ileostomy.
RESUMEN
INTRODUCTION: The study aimed to validate the Betella algorithm, focusing on molecular analyses exclusively for endometrial cancer patients, where molecular classification alters risk assessment based on ESGO/ESTRO/ESP 2020 guidelines. MATERIALS AND METHODS: Conducted between March 2021 and March 2023, the retrospective research involved endometrial cancer patients undergoing surgery and comprehensive molecular analyses. These included p53 and mismatch repair proteins immunohistochemistry, as well as DNA sequencing for POLE exonuclease domain. We applied the Betella algorithm to our population and evaluated the proportion of patients in which the molecular analysis changed the risk class attribution. RESULTS: Out of 102 patients, 97 % obtained complete molecular analyses. The cohort exhibited varying molecular classifications: 10.1 % as POLE ultra-mutated, 30.3 % as mismatch repair deficient, 11.1 % as p53 abnormal, and 48.5 % as non-specified molecular classification. Multiple classifiers were present in 3 % of cases. Integrating molecular classification into risk group calculation led to risk group migration in 11.1 % of patients: 7 moved to lower risk classes due to POLE mutations, while 4 shifted to higher risk due to p53 alterations. Applying the Betella algorithm, we can spare the POLE sequencing in 65 cases (65.7 %) and p53 immunochemistry in 17 cases (17.2 %). CONCLUSION: In conclusion, we externally validated the Betella algorithm in our population. The application of this new proposed algorithm enables assignment of the proper risk class and, consequently, the appropriate indication for adjuvant treatment, allowing for the rationalization of the resources that can be allocated otherwise, not only for the benefit of settings with low resources, but of all settings in general.