Effects of risk factors for ovarian cancer in women with and without endometriosis

Phung, Minh Tung; Muthukumar, Aruna; Trabert, Britton; Webb, Penelope M.; Jordan, Susan J.; Terry, Kathryn L.; Cramer, Daniel W.; Titus, Linda; Risch, Harvey A.; Doherty, Jennifer A.; Harris, Holly R.; Goodman, Marc T.; Modugno, Francesmary; Moysich, Kirsten B.; Jensen, Allan; Kjær, Susanne K.; Anton‐Culver, Hoda; Ziogas, Argyrios; Berchuck, Andrew; Khoja, Lilah; Wu, Anna H.; Pike, Malcolm C.; Pearce, Celeste Leigh; Lee, Alice W.

doi:10.1016/j.fertnstert.2022.07.019

Cited by 7 publications

(1 citation statement)

References 37 publications

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“…Through a systematic review of previous study, Younis et al found that 70% of patients diagnosed with EAOC were over the age of 50, and a tumor size larger than 9 cm was identified as a risk factor for EAOC (Younis and Izhaki 2023 ). Phung et al ( 2022 ) revealed that EAOC patients might have a higher BMI compared to patients with OEM. Chao et al ( 2022 ) discovered that the significance of CA125 and CA19-9 in diagnosing EAOC.…”

Section: Discussionmentioning

confidence: 99%

Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively

Xu,

Nie,

Zhang

et al. 2024

J Cancer Res Clin Oncol

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Purpose The preoperative diagnosis of endometriosis associated ovarian cancer (EAOC) remains challenging for lack of effective diagnostic biomarker. We aimed to study clinical characteristics and develop a nomogram for diagnosing EAOC before surgery. Methods A total of 87 patients with EAOC and 348 patients with ovarian endometrioma (OEM) were enrolled in our study. Least absolute shrinkage and selection operator (LASSO) regression and Logistic regression were utilized to select variables and construct the prediction model. The performance of the model was assessed using receiver operating characteristic (ROC) analyses and calibration plots, while decision curve analyses (DCAs) were conducted to assess clinical value. Bootstrap resampling was used to evaluated the stability of the model in the derivation set. Results The EAOC patients were older compared to the OEM patients (46.41 ± 9.62 vs. 36.49 ± 8.09 year, P < 0.001) and proportion of postmenopausal women was higher in EAOC group than in the OEM group (34.5 vs. 1.5%, P < 0.001). Our prediction model, which included age at diagnosis, tumor size, cancer antigen (CA) 19–9 and risk of ovarian malignancy algorithm (ROMA), demonstrated an area under the curve (AUC) of 0.858 (95% confidence interval (CI): 0.795–0.920) in the derivation set (N = 304) and an AUC of 0.870 (95% CI: 0.779–0.961) in the validation set (N = 131). The model fitted both the derivation (Hosmer–Lemeshow test (HL) chi-square = 12.600, P = 0.247) and the validation (HL chi-square = 8.210, P = 0.608) sets well. Conclusion Compared to patients with OEM, those with EAOC exhibited distinct clinical characteristics. Our four-variable prediction model demonstrated excellent performance in both the derivation and validation sets, suggesting its potential to assist with preoperative diagnosis of EAOC.

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Section: Discussionmentioning

confidence: 99%

Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively

Xu,

Nie,

Zhang

et al. 2024

J Cancer Res Clin Oncol

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Global epidemiology of epithelial ovarian cancer

Webb,

Jordan

2024

Nat Rev Clin Oncol

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Ovarialkarzinom: Wirkung der Risikofaktoren bei Frauen mit und ohne Endometriose

2023

Geburtshilfe Frauenheilkd

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Zahlreiche Faktoren erhöhen bzw. senken die Wahrscheinlichkeit, an einem Ovarialkarzinom zu erkranken. Die Endometriose gilt ebenfalls als Risikofaktor: Sie verdoppelt beispielsweise das Risiko für ein endometrioides oder niedriggradiges seröses Ovarialkarzinom. Ein Forscherteam ging nun der Frage nach, ob sich Frauen mit und ohne Endometriose im Hinblick auf den Zusammenhang zwischen 10 etablierten Faktoren und dem Tumorrisiko unterscheiden.

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Effects of risk factors for ovarian cancer in women with and without endometriosis

Cited by 7 publications

References 37 publications

Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively

Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively

Global epidemiology of epithelial ovarian cancer

Ovarialkarzinom: Wirkung der Risikofaktoren bei Frauen mit und ohne Endometriose

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