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Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification.

ABSTRACT: Endometrial cancer (EC) is the most common gynaecologic malignancy in developed countries. The main challenge in EC management is to correctly estimate the risk of metastases at diagnosis and the risk to develop recurrences in the future. Risk stratification determines the need for surgical staging and adjuvant treatment. Detection of occult, microscopic metastases upstages patients, provides important prognostic information and guides adjuvant treatment. The molecular classification subdivides EC into four prognostic subgroups: POLE ultramutated; mismatch repair deficient (MMRd); nonspecific molecular profile (NSMP); and TP53 mutated (p53abn). How surgical staging should be adjusted based on preoperative molecular profiling is currently unknown. Moreover, little is known whether and how other known prognostic biomarkers affect prognosis prediction independent of or in addition to these molecular subgroups. This review summarizes the factors incorporated in surgical staging (i.e., peritoneal washing, lymph node dissection, omentectomy and peritoneal biopsies), and its impact on prognosis and adjuvant treatment decisions in an era of molecular classification of EC. Moreover, the relation between FIGO stage and molecular classification is evaluated including the current gaps in knowledge and future perspectives.

SUBMITTER: Kasius JC

PROVIDER: S-EPMC8616052 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification.

Kasius Jenneke C JC Pijnenborg Johanna M A JMA Lindemann Kristina K Forsse David D van Zwol Judith J Kristensen Gunnar B GB Krakstad Camilla C Werner Henrica M J HMJ Amant Frédéric F

Cancers 20211122 22

Endometrial cancer (EC) is the most common gynaecologic malignancy in developed countries. The main challenge in EC management is to correctly estimate the risk of metastases at diagnosis and the risk to develop recurrences in the future. Risk stratification determines the need for surgical staging and adjuvant treatment. Detection of occult, microscopic metastases upstages patients, provides important prognostic information and guides adjuvant treatment. The molecular classification subdivides ...[more]

PMID: 34831000

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Project description:ObjectivesAccurate pre-operative prediction of risk stratification using a non-invasive imaging tool is clinically important for planning optimal treatment strategies, particularly in early-stage endometrial cancer (EC). This study aimed to investigate the utility of apparent diffusion coefficient (ADC) histogram analysis in evaluating the pathological characteristics and risk stratification in patients with Stage I EC.MethodsBetween October 2009 and December 2014, a total of 108 patients with surgically proven Stage I EC (endometrioid type = 91; non-endometrioid type = 17) excluding stage ≥II that underwent preoperative 3T-diffusion-weighted imaging without administration of contrast medium were enrolled in this retrospective study. Risk stratification was divided into four risk categories based on the ESMO-ESGO-ESTRO Guidelines: low, intermediate, high-intermediate, and high risk. The ADC histogram parameters (minimum, mean [ADCmean], 10th-90th percentile, and maximum [ADCmax]) of the tumor were generated using an in-house software. The ADC histogram parameters were compared between patients with endometrioid type and non-endometrioid type, between Stage IA and IB, between histological grades, and evaluated for differentiating non-high risk group from high risk group. Inter-reader agreement for tumor ADC measurements was also evaluated. Statistical analyses were performed using the Student's t-test, Mann-Whitney U test, receiver operating characteristics (ROC) analysis, or intraclass correlation coefﬁcient (ICC).ResultsIn differentiating endometrioid type from non-endometrioid type EC, all ADC histogram parameters were statistically significant (p < 0.05). In differentiating histological grades, 90th percentile ADC and ADCmax showed significantly higher values in tumor Grade III than in tumor Grade I-II (p < 0.05). In differentiating superficial myometrial invasion from deep myometrial invasion, all ADC histogram parameters were statistically significant (p < 0.05), except ADCmax. In differentiating non-high risk group from high risk group, ADCmean, 75th-90th percentile ADC, and ADCmax were statistically significant (p < 0.05). For predicting the high risk group, the area under the ROC curve of ADCmax was 0.628 and the highest among other histogram parameters. All histogram parameters revealed moderate to good inter-reader reliability (ICC = 0.581‒0.769).ConclusionThe ADC histogram analysis as reproducible tool may be useful for evaluating the pathological characteristics and risk stratification in patients with early-stage EC.Advances in knowledgeADC histogram analysis may be useful for evaluating risk stratification in early-stage endometrial cancer patients.

Dataset Information

Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification.

Publications

Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification.

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