Marike S. Lombaers

The impact of the patient macroenvironment on molecular subgroups in endometrial cancer

Abstract More than half of endometrial cancer diagnoses can be attributed to obesity. A purely molecular classification in endometrial cancer hampers further understanding of the impact of patient macroenvironment as a major risk factor. The relationship between patient factors, such as age, body mass index (BMI), comorbidity, and ethnicity, and molecular subgroups was studied in a publicly available data set ( N  = 225) and two multicenter European cohorts ( N  = 223; N  = 946). Age at diagnosis was highest in the TP53 ‐mutated subgroup, and differed significantly between molecular subgroups. Patients with obesity were younger at diagnosis compared to their lean counterparts across all molecular subgroups (61.9 vs. 66.2 years; p  < .01). Survival was worst in the TP53 ‐mutated subgroup but improved with increasing BMI, which resulted in nonsignificant differences from other subgroups when BMI was >35. These data underscore that patient factors remain important, and their integration with molecular factors needs to be better understood to ultimately improve treatment and prevention strategies in endometrial cancer.

Implementation of a Personalized Risk Model for Lymph Node Metastasis in Endometrial Carcinoma: Healthcare Providers' Perspectives on Use, Barriers, and Facilitators

ABSTRACT Background The ENDORISK model estimates the risk of lymph node metastases (LNM) in endometrial carcinoma (EC) patients using preoperative clinical variables and biomarkers. This qualitative study investigated healthcare providers' (HCP) perspectives on the use of the model and barriers and facilitators for clinical implementation. Methods Eight focus group interviews were performed among HCPs. A semi‐structured interview guide was used based on the Grol and Wensing implementation model. Results Focus groups included gynecologists, residents of gynecology, pathologists, radiation oncologists, and a nurse specialist ( n  = 41). ENDORISK was deemed supportive for counseling of patients and shared decision‐making for optimal surgical and adjuvant treatment. Barriers for implementation were difficulty in explaining the model and risk percentages to patients, differences in preoperative diagnostic tools used per hospital, and use of the model with the sentinel node procedure. Facilitators were a clear guideline for using the model with a predefined risk cutoff and making the model easily understandable for patients. A 10% risk cutoff was considered clinically relevant for lymph node assessment. Conclusion HCP found ENDORISK use in clinical practice supportive for patient counseling. Future implementation should focus on a user‐friendly interface, a cohesive guideline, and training to aid efficient use and counseling of patients.

ENDORISK-2: A personalized Bayesian network for preoperative risk stratification in endometrial cancer, integrating molecular classification and preoperative myometrial invasion assessment

ENDORISK is a Bayesian network that can assist in preoperative risk estimation of lymph node metastasis (LNM) risk in endometrial cancer (EC) with consistent performance in external validations. To reflect state of the art care, ENDORISK was optimized by integrating molecular classification and preoperative assessment of myometrial invasion (MI). Variables for POLE, MSI, and preoperative assessment of MI, either by expert transvaginal ultrasound or pelvic magnetic resonance imaging (MRI), were added to develop ENDORISK-2. The p53 biomarker, part of the molecular classification, was already included in ENDORISK. External validation of ENDORISK-2 for LNM prediction was performed in two independent cohorts from: Brno (CZ), (n = 581) and Tübingen (DE), (n = 247). ENDORISK-2 yielded AUCs of 0·85 (95 % CI 0·80-0·90) (CZ) and 0·86 (95 % CI 0·77-0·96) (DE) for predicting LNM. In patients with low-grade histology, 83 % (CZ) and 89 % (DE) were estimated having less than 10 % risk of LNM, with false negative rates (FNR) of 4·3 % (CZ) and 2·2 % (DE). The previously defined set of minimally required variables, i.e.: preoperative tumor grade, three of the four immunohistochemical (IHC) markers, and one clinical marker, could be interchanged with the new variables, with comparable validation metrics, including AUC values of 0·79-0·87 for LNM prediction. Incorporation of molecular data and preoperative MI improved the flexibility of ENDORISK with comparable diagnostic accuracy for estimating LNM as when based on low-cost immunohistochemical biomarkers. In addition, the high diagnostic accuracy in patients with low-grade EC demonstrates how ENDORISK-2 could aid clinicians in identifying patients in whom surgical lymph node assessment may safely be omitted. These results underline its power for clinical use in both high and low resource countries.