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.
- Klíčová slova
- Concordant, Diagnosis, Discordant, Endometrial carcinoma, Endometrial sampling, Pathology,
- MeSH
- biopsie metody MeSH
- endometrium patologie MeSH
- endometroidní karcinom * chirurgie patologie MeSH
- lidé MeSH
- nádory endometria * patologie MeSH
- retrospektivní studie MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
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.
- Klíčová slova
- Biomarker, Endometrial carcinoma, Immunohistochemistry, Lymph node metastasis, Outcome,
- MeSH
- analýza přežití MeSH
- kohortové studie MeSH
- lidé MeSH
- lymfatické metastázy MeSH
- molekula buněčné adheze nervové L1 metabolismus MeSH
- nádorové biomarkery metabolismus MeSH
- nádory endometria diagnóza mortalita patologie MeSH
- prediktivní hodnota testů MeSH
- prognóza MeSH
- retrospektivní studie MeSH
- rizikové faktory MeSH
- senioři MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- Geografické názvy
- Evropa MeSH
- Názvy látek
- molekula buněčné adheze nervové L1 MeSH
- nádorové biomarkery MeSH
BACKGROUND: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. METHODS AND FINDINGS: Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte count; imaging results on lymphadenopathy; and cervical cytology. In the MoMaTEC cohort, the area under the curve (AUC) was 0.82 (95% confidence interval [CI] 0.76-0.88) for LNM and 0.82 (95% CI 0.77-0.87) for 5-year DSS. In the PIPENDO cohort, the AUC for 5-year DSS was 0.84 (95% CI 0.78-0.90). The network was well-calibrated. In the MoMaTEC cohort, 249 patients (55.8%) were classified with <5% risk of LNM, with a false-negative rate of 1.6%. A limitation of the study is the use of imputation to correct for missing predictor variables in the development cohort and the retrospective study design. CONCLUSIONS: In this study, we illustrated how BNs can be used for individualizing clinical decision-making in oncology by incorporating easily accessible and multimodal biomarkers. The network shows the complex interactions underlying the carcinogenetic process of endometrial cancer by its graphical representation. A prospective feasibility study will be needed prior to implementation in the clinic.
- MeSH
- Bayesova věta MeSH
- hodnocení rizik MeSH
- lidé středního věku MeSH
- lidé MeSH
- lymfatické metastázy MeSH
- nádorové biomarkery metabolismus MeSH
- nádory endometria patologie MeSH
- prospektivní studie MeSH
- receptory pro estrogeny metabolismus MeSH
- receptory progesteronu MeSH
- retrospektivní studie MeSH
- senioři MeSH
- stupeň nádoru MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH
- Názvy látek
- nádorové biomarkery MeSH
- receptory pro estrogeny MeSH
- receptory progesteronu MeSH
BACKGROUND: Identification of endometrial carcinoma (EC) patients at high risk of recurrence is lacking. In this study, the prognostic role of hypoxia and angiogenesis was investigated in EC patients. METHODS: Tumour slides from EC patients were stained by immunofluorescence for carbonic anhydrase IX (CAIX) as hypoxic marker and CD34 for assessment of microvessel density (MVD). CAIX expression was determined in epithelial tumour cells, with a cut-off of 1%. MVD was assessed according to the Weidner method. Correlations with disease-specific survival (DSS), disease-free survival (DFS) and distant disease-free survival (DDFS) were calculated using Kaplan-Meier curves and Cox regression analysis. RESULTS: Sixty-three (16.4%) of 385 ECs showed positive CAIX expression with high vascular density. These ECs had a reduced DSS compared to tumours with either hypoxia or high vascular density (log-rank p = 0.002). Multivariable analysis showed that hypoxic tumours with high vascular density had a reduced DSS (hazard ratio [HR] 3.71, p = 0.002), DDFS (HR 2.68, p = 0.009) and a trend for reduced DFS (HR 1.87, p = 0.054). CONCLUSIONS: This study has shown that adverse outcome in hypoxic ECs is seen in the presence of high vascular density, suggesting an important role of angiogenesis in the metastatic process of hypoxic EC. Differential adjuvant treatment might be indicated for these patients.
- MeSH
- dospělí MeSH
- hypoxie buňky MeSH
- karboanhydrasa IX analýza MeSH
- lidé středního věku MeSH
- lidé MeSH
- nádory endometria krevní zásobení mortalita patologie MeSH
- patologická angiogeneze MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- karboanhydrasa IX MeSH