Associations of insulin resistance and inflammatory biomarkers with endometrial cancer survival: The Alberta endometrial cancer cohort study

Morielli, Andria R.; Kokts-Porietis, Renée L; Benham, Jamie L; McNeil, Jessica; Cook, Linda S.; Courneya, Kerry S.; Friedenreich, Christine M.

doi:10.1002/cam4.4584

Cancer Medicine

2022

DOI: 10.1002/cam4.4584

|View full text |Cite

Associations of insulin resistance and inflammatory biomarkers with endometrial cancer survival: The Alberta endometrial cancer cohort study

Andria R. Morielli

Renée L Kokts-Porietis

Jamie L Benham

et al.

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

2023

Publication Types

Select...

Article5

Relationship

Self Cite1

Independent4

Authors

Journals

Cited by 8 publications

(4 citation statements)

References 45 publications

(118 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Given the well-established relationship between metabolic disorders, IR, and EC, 9,10 the TyG index is deemed to an indicator of EC incidence and development. However, studies looking at the TyG index have focused mainly on cardiovascular diseases, gastrointestinal cancers, breast cancer, prostate cancer, and lung cancer; [11][12][13][14][15] few clinical studies have assessed the TyG index in the context of endometrial malignancy.…”

mentioning

confidence: 99%

Triglyceride‐glucose index (TyG index) and endometrial carcinoma risk: A retrospective cohort study

Shi

Guo

Zheng³

et al. 2023

Intl J Gynecology & Obste

View full text Add to dashboard Cite

ObjectiveWe analyzed the association between the triglyceride‐glucose index (TyG index) and incident endometrial carcinogenesis, aiming to determine whether the TyG index is a promising predictive biomarker for endometrial carcinoma (EC).MethodsIn this retrospective cohort study, multiple logistic regression analysis was performed to evaluate the relationship between TyG index and EC incidence and progression. The receiver operating characteristic (ROC) curve was used to calculate the area under the curve (AUC), as well as the cut‐off value of the TyG index for EC incidence.ResultsThe TyG index was significantly higher in patients with EC or endometrial atypical hyperplasia (EAH) than in those with normal endometrium (P < 0.001). A continuous rise was observed in the incidence of EC and EAH among the tertiles of the TyG index (P < 0.001). The multiple logistic regression analysis revealed that the TyG index was associated with EC and EAH risk after adjusting for potential confounding factors (EAH: odds ratio [OR] 2.54, 95% confidence interval [CI] 1.33–4.85, P = 0.005; EC: OR 2.65, 95% CI 1.60–4.41, P < 0.001). Moreover, high TyG index was positively associated with advanced pathological stage (OR 2.14, 95% CI 1.32–3.47, P = 0.002) and poorer differentiation (OR 2.53, 95% CI 1.36–4.72, P = 0.004).ConclusionThe TyG index might be a promising biomarker for endometrial carcinogenesis. Subjects with a higher TyG index should be aware of the risk of EC incidence and progression.

show abstract

mentioning

confidence: 99%

Triglyceride‐glucose index (TyG index) and endometrial carcinoma risk: A retrospective cohort study

Shi

Guo

Zheng³

et al. 2023

Intl J Gynecology & Obste

View full text Add to dashboard Cite

show abstract

“…For instance, a combination of age, cancer histologic grade, socioeconomic factors, and other clinical prognostic factors have been investigated in endometrial cancer survival studies within the framework of the CPH model. [12][13][14][15] Until the advent of radiomics, image biomarkers have been insufficiently studied as potential survival predictors for endometrial cancer. Radiomics is a rapidly expanding field of research in oncology.…”

mentioning

confidence: 99%

“…Based on the CPH model, it is possible to evaluate a single covariate's and/or the combination joint covariates effects on the survival time estimation. For instance, a combination of age, cancer histologic grade, socioeconomic factors, and other clinical prognostic factors have been investigated in endometrial cancer survival studies within the framework of the CPH model 12–15 …”

mentioning

confidence: 99%

See 1 more Smart Citation

An Integrated Clinical‐MR Radiomics Model to Estimate Survival Time in Patients With Endometrial Cancer

Marcus

Russell

et al. 2022

Magnetic Resonance Imaging

View full text Add to dashboard Cite

Background Determination of survival time in women with endometrial cancer using clinical features remains imprecise. Features from MRI may improve the survival estimation allowing improved treatment planning. Purpose To identify clinical features and imaging signatures on T2‐weighted MRI that can be used in an integrated model to estimate survival time for endometrial cancer subjects. Study Type Retrospective. Population Four hundred thirteen patients with endometrial cancer as training (N = 330, 66.41 ± 11.42 years) and validation (N = 83, 67.60 ± 11.89 years) data and an independent set of 82 subjects as testing data (63.26 ± 12.38 years). Field Strength/Sequence 1.5‐T and 3‐T scanners with sagittal T2‐weighted spin echo sequence. Assessment Tumor regions were manually segmented on T2‐weighted images. Features were extracted from segmented masks, and clinical variables including age, cancer histologic grade and risk score were included in a Cox proportional hazards (CPH) model. A group least absolute shrinkage and selection operator method was implemented to determine the model from the training and validation datasets. Statistical Tests A likelihood‐ratio test and decision curve analysis were applied to compare the models. Concordance index (CI) and area under the receiver operating characteristic curves (AUCs) were calculated to assess the model. Results Three radiomic features (two image intensity and volume features) and two clinical variables (age and cancer grade) were selected as predictors in the integrated model. The CI was 0.797 for the clinical model (includes clinical variables only) and 0.818 for the integrated model using training and validation datasets, the associated mean AUC value was 0.805 and 0.853. Using the testing dataset, the CI was 0.792 and 0.882, significantly different and the mean AUC was 0.624 and 0.727 for the clinical model and integrated model, respectively. Data Conclusion The proposed CPH model with radiomic signatures may serve as a tool to improve estimated survival time in women with endometrial cancer. Evidence Level 4 Technical Efficacy Stage 2

show abstract