Long-term survival of endometrioid endometrial cancer patients

Gottwald, Leszek; Pluta, Piotr; Piekarski, Janusz; Spych, Michał; Hendzel, Katarzyna; Topczewska-Tylinska, Katarzyna; Nejc, Dariusz; Bibik, Robert; Korczyński, Jerzy; Ciałkowska-Rysz, Aleksandra

doi:10.5114/aoms.2010.19305

Cited by 60 publications

(53 citation statements)

References 32 publications

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“…In general, patients with tumors of non-endometrioid subtypes have a worse prognosis than those with tumors of endometrioid subtypes [12,20]. In this study, patients with non-endometrioid subtype (71.5%) were lived shorter than those with endometrioid type (93.4%) (p<0.05).…”

Section: Discussionmentioning

confidence: 61%

“…Over the past few decades, several studies have demonstrated the prognostic importance of different parameters [6][7][8][9][10][11][12]. In this study, 5-years survival of patients was 89%.…”

Section: Discussionmentioning

confidence: 62%

“…Bristow et al [8] and Ferlay et al [19], demonstrated that EC survival decreases in older patients. However, Karateke et al [9], Gottwald et al [12], and Bajracharya and Juan [6], found age at diagnosis was not signifi cant predictor of survival for EC.…”

Section: Discussionmentioning

confidence: 99%

“…The previous study confi rmed that in these data on survival. Gottwald et al [12], found that the 5-year survival for EC was 87%. Ayhan et al [17], reported that the 5-year overall survival rate of entire group was 86% [17].…”

Section: Discussionmentioning

confidence: 99%

“…The overall 5-year survival for all stages is 86%; patients; when diagnosed at a local or regional stage, the 5-year survival rate is 97% and 67% respectively, while distant stage survival decreases to 16% [7]. In order to improve survival of EC patients, clinic-pathological prognostic factors have been studied previously [5][6][7][8][9][10][11][12]. Unfortunately, the importance of predictive factors for the prognosis of patients with EC has not yet been fully established.…”

Section: Introductionmentioning

confidence: 99%

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Survival Determinants in Endometrial Cancer Patients: 5-Years Experience

Pınar¹

2017

Arch Nursing Pract Care

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Aim: The aim of the study was to explore fi ve years survival in women with endometrial cancer. Material and methods:A retrospective review of 146 patients with endometrial cancer treated at Baskent University Hospital Gyne-oncologic Clinic in Ankara, Turkey between 2010 and 2015 was performed. Demographic and clinic-pathological data were compared with survival. Results:The median age of the patients was 61.4 y±5.3 years (36-82). The overall 5-years survival was 89%. Multivariate Cox regression model revealed that the FIGO stage, grade, age, histological type, myometrial invasion, and lymph node involvement were all predictive factors on survival (p<0.05). However, the menopausal status, age at menopause, parity, BMI, comorbidities, ECOG performance score, therapy modality, HR status, and family history were not associated with survival (p>0.05). Conclusion:The results of our study, several clinic-pathological prognostic factors of EC have been identifi ed on survival. These results provided signifi cant evidence that early foresight of EC survival. Further prospective randomized studies are necessary to clarify the role of these factors.

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Section: Discussionmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 62%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Survival Determinants in Endometrial Cancer Patients: 5-Years Experience

Pınar¹

2017

Arch Nursing Pract Care

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Development and Validation of a Serum Metabolomic Signature for Endometrial Cancer Screening in Postmenopausal Women

et al. 2020

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IMPORTANCE Endometrial carcinoma (EC) is the most commonly diagnosed gynecologic cancer. Its early detection is advisable because 20% of women have advanced disease at the time of diagnosis. OBJECTIVE To clinically validate a metabolomics-based classification algorithm as a screening test for EC. DESIGN, SETTING, AND PARTICIPANTS This diagnostic study enrolled 2 cohorts. A multicenter prospective cohort, with 50 cases (postmenopausal women with EC; International Federation of Gynecology and Obstetrics stage I-III and grade G1-G3) and 70 controls (no EC but matched on age, years from menopause, tobacco use, and comorbidities), was used to train multiple classification models. The accuracy of each trained model was then used as a statistical weight to produce an ensemble machine learning algorithm for testing, which was validated with a subsequent prospective cohort of 1430 postmenopausal women. The study was conducted at the San Giovanni di Dio e Ruggi d'Aragona University Hospital of Salerno (Italy) and Lega Italiana per la Lotta contro i Tumori clinic in Avellino (Italy). Data collection was conducted from January 2018 to February 2019, and analysis was conducted from January to March 2019. MAIN OUTCOMES AND MEASURES The presence or absence of EC based on evaluation of the blood metabolome. Metabolites were extracted from dried blood samples from all participants and analyzed by gas chromatography-mass spectrometry. A confusion matrix was used to summarize test results. Performance indices included sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and accuracy. Confirmation or exclusion of EC in women with a positive test result was by means of hysteroscopy. Participants with negative results were followed up 1 year after enrollment to investigate the appearance of EC signs. RESULTS The study population consisted of 1550 postmenopausal women. The mean (SD) age was 68.2 (11.7) years for participants with no EC in the training cohort, 69.4 (13.8) years for women with EC in the training cohort, and 59.7 (7.7) years for women in the validation cohort. Application of the ensemble machine learning to the validation cohort resulted in 16 true-positives, 2 false-positives, and 0 false-negatives, and it correctly classified more than 99% of samples. Disease prevalence was 1.12% (16 of 1430). CONCLUSIONS AND RELEVANCE In this study, dried blood metabolomic profile was used to assess the presence or absence of EC in postmenopausal women not receiving hormonal therapy with greater than 99% accuracy.

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A 7‐lncRNA signature predict prognosis of Uterine corpus endometrial carcinoma

Ouyang¹,

Li³

et al. 2019

J of Cellular Biochemistry

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Current research indicate that long noncoding RNAs (lncRNAs) are associated with the progression of various cancers and can be used as prognostic biomarkers. This study aims to construct a prognostic lncRNA signature for the risk assessment of Uterine corpus endometrial carcinoma (UCEC). The RNA‐Seq expression profile and corresponding clinical data of UCEC patients obtained from The Cancer Genome Atlas database. First, some prognosis‐related lncRNAs were obtained by univariate Cox analysis. The minimum absolute contraction and selection operator (LASSO) regression and the Cox proportional hazard regression method were used to further identify the lncRNA prognostic model. Finally, seven lncRNAs (AC110491.1, AL451137.1, AC005381.1, AC103563.2, AC007422.2, AC108025.2, and MIR7‐3HG) were identified as potential prognostic factors. According to the model constructed by the above analysis, the risk score of each UCEC patient was calculated, and the patients were classified into high and low‐risk groups. The low‐risk group had significant survival benefits. Moreover, we constructed a nomogram that incorporated independent prognostic factors (age, tumor stage, tumor grade, and risk score). The c‐index value for evaluating the predictive nomogram model was 0.801. The area under the curve was 0.797 (3‐year survival). The calibration curve also showed that there was a satisfactory agreement between the predicted and observed values in the probability of 1‐, 3‐, and 5‐year overall survival. On the basis of the coexpression relationship, we established a coexpression network of lncRNA‐messenger RNA (mRNA) of the 7‐lncRNA. The Kyoto Encyclopedia of Genes and Genomes analysis of the coexpressing mRNAs showed that the main pathways related to the 7‐lncRNA signature were neuroactive ligand‐receptor interaction, serotonergic synapse, and gastric cancer pathway. Therefore, our study revealed that the 7‐lncRNA could be used to predict the prognosis of UCEC and for postoperative treatment and follow‐up.

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Long-term survival of endometrioid endometrial cancer patients

Cited by 60 publications

References 32 publications

Survival Determinants in Endometrial Cancer Patients: 5-Years Experience

Survival Determinants in Endometrial Cancer Patients: 5-Years Experience

Development and Validation of a Serum Metabolomic Signature for Endometrial Cancer Screening in Postmenopausal Women

A 7‐lncRNA signature predict prognosis of Uterine corpus endometrial carcinoma

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