Background: Endometrial cancer risk stratification may help target interventions, screening, or prophylactic hysterectomy to mitigate the rising burden of this cancer. However, existing prediction models have been developed in select cohorts and have not considered genetic factors. Methods: We developed endometrial cancer risk prediction models using data on postmenopausal white women aged 45-85 years from 19 case-control studies in the Epidemiology of Endometrial Cancer Consortium. Relative risk estimates for predictors were combined with age-specific endometrial cancer incidence rates and estimates for the underlying risk factor distribution. We externally validated the models in three cohorts: Nurses' Health Study (NHS), Nurses' Health Study II (NHS II) and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Results: Area under the receiver operating characteristic curves for the epidemiologic model ranged from 0.64 (95% CI: 0.62, 0.67) to 0.69 (95% CI: 0.66, 0.72). Improvements in discrimination from the addition of genetic factors were modest (no change in AUC in NHS,; PLCO: 0.64 to 0.66). The epidemiologic model was well calibrated in NHS II (overall E/O = 1.09; 95% CI: 0.98, 1.22) and PLCO (overall E/O = 1.04; 95% CI: 0.95, 1.13) but poorly calibrated in NHS (overall E/O = 0.55; 95% CI: 0.51, 0.59). Conclusion: Using data from the largest, most heterogeneous study population to date, prediction models based on epidemiologic factors alone successfully identified women at high risk of endometrial cancer. Genetic factors offered limited improvements in discrimination. Further work is needed to refine this tool for clinical or public health practice and expand these models to multiethnic populations.

Risk prediction models for endometrial cancer: development and validation in an international consortium / J. Shi, P. Kraft, B. Rosner, Y. Benavente, A. Black, A.L. Brinton, C. Chen, M.A. Clarke, L.S. Cook, L. Costas, L. Dal Maso, J.L. Freudenheim, J. Frias-Gomez, M.G. Friedenreich, M. Garcia-Closas, M.T. Goodman, L. Johnson, C. La Vecchia, F. Levi, J. Lissowska, L. Lu, S.E. Mccann, K.B. Moysich, E. Negri, K. O' Connell, F. Parazzini, S. Petruzella, J. Polesel, J. Ponte, T.R. Rebbeck, P. Reynolds, F. Ricceri, H. Risch, C. Sacerdote, V.W. Setiawan, X.-. Shu, A.B. Spurdle, B. Trabert, P.M. Webb, N. Wentzensen, L.R. Wilkens, W.H. Xu, H.P. Yang, H. Yu, M. Du, I. De Vivo. - In: JOURNAL OF THE NATIONAL CANCER INSTITUTE. - ISSN 0027-8874. - 2023:(2023), pp. djad014.1-djad014.32. [Epub ahead of print] [10.1093/jnci/djad014]

Risk prediction models for endometrial cancer: development and validation in an international consortium

C. La Vecchia;E. Negri;F. Parazzini;
2023

Abstract

Background: Endometrial cancer risk stratification may help target interventions, screening, or prophylactic hysterectomy to mitigate the rising burden of this cancer. However, existing prediction models have been developed in select cohorts and have not considered genetic factors. Methods: We developed endometrial cancer risk prediction models using data on postmenopausal white women aged 45-85 years from 19 case-control studies in the Epidemiology of Endometrial Cancer Consortium. Relative risk estimates for predictors were combined with age-specific endometrial cancer incidence rates and estimates for the underlying risk factor distribution. We externally validated the models in three cohorts: Nurses' Health Study (NHS), Nurses' Health Study II (NHS II) and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Results: Area under the receiver operating characteristic curves for the epidemiologic model ranged from 0.64 (95% CI: 0.62, 0.67) to 0.69 (95% CI: 0.66, 0.72). Improvements in discrimination from the addition of genetic factors were modest (no change in AUC in NHS,; PLCO: 0.64 to 0.66). The epidemiologic model was well calibrated in NHS II (overall E/O = 1.09; 95% CI: 0.98, 1.22) and PLCO (overall E/O = 1.04; 95% CI: 0.95, 1.13) but poorly calibrated in NHS (overall E/O = 0.55; 95% CI: 0.51, 0.59). Conclusion: Using data from the largest, most heterogeneous study population to date, prediction models based on epidemiologic factors alone successfully identified women at high risk of endometrial cancer. Genetic factors offered limited improvements in discrimination. Further work is needed to refine this tool for clinical or public health practice and expand these models to multiethnic populations.
endometrium; cancer risk; endometrial cancer; prediction model;
Settore MED/01 - Statistica Medica
Settore MED/06 - Oncologia Medica
Settore MED/40 - Ginecologia e Ostetricia
Settore MED/42 - Igiene Generale e Applicata
2023
23-gen-2023
Article (author)
File in questo prodotto:
File Dimensione Formato  
Risk prediction endometrial_Shi.pdf

accesso aperto

Tipologia: Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione 1.16 MB
Formato Adobe PDF
1.16 MB Adobe PDF Visualizza/Apri
Risk enodmetrial Ca.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 1.32 MB
Formato Adobe PDF
1.32 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/951937
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact