The amount of preoperative endometrial tissue surface in relation to final endometrial cancer classification.

OBJECTIVE: To evaluate whether the amount of preoperative endometrial tissue surface is related to the degree of concordance with final low- and high-grade endometrial cancer (EC). In addition, to determine whether discordance is influenced by sampling method and impacts outcome. METHODS: A retrospective cohort study within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC). Surface of preoperative endometrial tissue samples was digitally calculated using ImageJ. Tumor samples were classified into low-grade (grade 1-2 endometrioid EC (EEC)) and high-grade (grade 3 EEC + non-endometroid EC). RESULTS: The study cohort included 573 tumor samples. Overall concordance between pre- and postoperative diagnosis was 60.0%, and 88.8% when classified into low- and high-grade EC. Upgrading (preoperative low-grade, postoperative high-grade EC) was found in 7.8% and downgrading (preoperative high-grade, postoperative low-grade EC) in 26.7%. The median endometrial tissue surface was significantly lower in concordant diagnoses when compared to discordant diagnoses, respectively 18.7 mm2 and 23.5 mm2 (P = 0.022). Sampling method did not influence the concordance in tumor classification. Patients with preoperative high-grade and postoperative low-grade showed significant lower DSS compared to patients with concordant low-grade EC (P = 0.039). CONCLUSION: The amount of preoperative endometrial tissue surface was inversely related to the degree of concordance with final tumor low- and high-grade. Obtaining higher amount of preoperative endometrial tissue surface does not increase the concordance between pre- and postoperative low- and high-grade diagnosis in EC. Awareness of clinically relevant down- and upgrading is crucial to reduce subsequent over- or undertreatment with impact on outcome.

Predicting the likelihood of successful medical treatment of early pregnancy loss: development and internal validation of a clinical prediction model.

STUDY QUESTION: What are clinical predictors for successful medical treatment in case of early pregnancy loss (EPL)? SUMMARY ANSWER: Use of mifepristone, BMI, number of previous uterine aspirations and the presence of minor clinical symptoms (slight vaginal bleeding or some abdominal cramps) at treatment start are predictors for successful medical treatment in case of EPL. WHAT IS KNOWN ALREADY: Success rates of medical treatment for EPL vary strongly, between but also within different treatment regimens. Up until now, although some predictors have been identified, no clinical prediction model has been developed yet. STUDY DESIGN, SIZE, DURATION: Secondary analysis of a multicentre randomized controlled trial in 17 Dutch hospitals, executed between 28 June 2018 and 8 January 2020. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women with a non-viable pregnancy between 6 and 14 weeks of gestational age, who opted for medical treatment after a minimum of 1 week of unsuccessful expectant management. Potential predictors for successful medical treatment of EPL were chosen based on literature and expert opinions. We internally validated the prediction model using bootstrapping techniques. MAIN RESULTS AND THE ROLE OF CHANCE: 237 out of 344 women had a successful medical EPL treatment (68.9%). The model includes the following variables: use of mifepristone, BMI, number of previous uterine aspirations and the presence of minor clinical symptoms (slight vaginal bleeding or some abdominal cramps) at treatment start. The model shows a moderate capacity to discriminate between success and failure of treatment, with an AUC of 67.6% (95% CI = 64.9-70.3%). The model had a good fit comparing predicted to observed probabilities of success but might underestimate treatment success in women with a predicted probability of success of ∼70%. LIMITATIONS, REASONS FOR CAUTION: The vast majority (90.4%) of women were Caucasian, potentially leading to less optimal model performance in a non-Caucasian population. Limitations of our model are that we have not yet been able to externally validate its performance and clinical impact, and the moderate accuracy of the prediction model of 0.67. WIDER IMPLICATIONS OF THE FINDINGS: We developed a prediction model, aimed to improve and personalize counselling for medical treatment of EPL by providing a woman with her individual chance of complete evacuation. STUDY FUNDING/COMPETING INTEREST(S): The Triple M Trial, upon which this secondary analysis was performed, was funded by the Healthcare Insurers Innovation Foundation (project number 3080 B15-191). TRIAL REGISTRATION NUMBER: Clinicaltrials.gov: NCT03212352.

Immunohistochemical biomarkers are prognostic relevant in addition to the ESMO-ESGO-ESTRO risk classification in endometrial cancer.

OBJECTIVE: Pre-operative immunohistochemical (IHC) biomarkers are not incorporated in endometrial cancer (EC) risk classification. We aim to investigate the added prognostic relevance of IHC biomarkers to the ESMO-ESGO-ESTRO risk classification and lymph node (LN) status in EC. METHODS: Retrospective multicenter study within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), analyzing pre-operative IHC expression of p53, L1 cell-adhesion molecule (L1CAM), estrogen receptor (ER) and progesterone receptor (PR), and relate to ESMO-ESGO-ESTRO risk groups, LN status and outcome. RESULTS: A total of 763 EC patients were included with a median follow-up of 5.5-years. Abnormal IHC expression was present for p53 in 112 (14.7%), L1CAM in 79 (10.4%), ER- in 76 (10.0%), and PR- in 138 (18.1%) patients. Abnormal expression of p53/L1CAM/ER/PR was significantly related with higher risk classification groups, and combined associated with the worst outcome within the 'high and advanced/metastatic' risk group. In multivariate analysis p53-abn, ER/PR- and ESMO-ESGO-ESTRO 'high and advanced/metastatic' were independently associated with reduced disease-specific survival (DSS). Patients with abnormal IHC expression and lymph node metastasis (LNM) had the worst outcome. Patients with LNM and normal IHC expression had comparable outcome with patients without LNM and abnormal IHC expression. CONCLUSION: The use of pre-operative IHC biomarkers has important prognostic relevance in addition to the ESMO-ESGO-ESTRO risk classification and in addition to LN status. For daily clinical practice, p53/L1CAM/ER/PR expression could serve as indicator for surgical staging and refine selective adjuvant treatment by incorporation into the ESMO-ESGO-ESTRO risk classification.