Optimal Cutoffs of Obesity Measures in Relation to Cancer Risk in Postmenopausal Women in the Women's Health Initiative Study

Moonseong Heo, Geoffrey C. Kabat, Howard Strickler, Juan Lin, Lifang Hou, Marcia L. Stefanick, Garnet L. Anderson, Thomas E. Rohan

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Background: Obesity is a risk factor for several cancers in postmenopausal women. We attempted to determine cutoffs of adiposity measures in relation to risk of obesity-related cancers among postmenopausal women and to examine the effects of hormone therapy (HT) use on the cutoffs, neither of which has been broadly studied. Methods: We used data from the Women's Health Initiative cohort (n=144,701) and applied Cox-proportional hazards regressions to each combination of 17 cancer types and 6 anthropometric measures (weight, body mass index [BMI], weight to height ratio, waist circumference, waist to hip ratio [WHR], and waist to height ratio). Interactions between the anthropometric measures and HT use were also examined. Cutoffs were determined by applying a grid search followed by a two-fold cross validation method. Survival ROC analysis of 5- and 10-year incidence followed. Results: Breast, colorectal, colon, endometrium, kidney, and all cancers combined were significantly positively associated with all six anthropometric measures, whereas lung cancer among ever smokers was significantly inversely associated with all measures except WHR. The derived cutoffs of each obesity measure varied across cancers (e.g., BMI cutoffs for breast and endometrium cancers were 30kg/m2 and 34kg/m2, respectively), and also depended on HT use. The Youden indices of the cutoffs for predicting 5- and 10-year cancer incidence were higher among HT never users. Conclusion: Using a panel of different anthropometric measures, we derived optimal cut-offs categorizing populations into high- and low-risk groups, which differed by cancer type and HT use. Although the discrimination abilities of these risk categories were generally poor, the results of this study could serve as a starting point from which to determine adiposity cutoffs for inclusion in risk prediction models for specific cancer types.

Original languageEnglish (US)
Pages (from-to)218-227
Number of pages10
JournalJournal of Women's Health
Volume24
Issue number3
DOIs
StatePublished - Mar 1 2015

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Women's Health
Obesity
Hormones
Neoplasms
Waist-Hip Ratio
Adiposity
Body Mass Index
Therapeutics
Weights and Measures
Kidney Neoplasms
Incidence
Waist Circumference
Endometrial Neoplasms
Survival Analysis
Endometrium
ROC Curve
Lung Neoplasms
Colon
Breast
Breast Neoplasms

ASJC Scopus subject areas

  • Medicine(all)

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Optimal Cutoffs of Obesity Measures in Relation to Cancer Risk in Postmenopausal Women in the Women's Health Initiative Study. / Heo, Moonseong; Kabat, Geoffrey C.; Strickler, Howard; Lin, Juan; Hou, Lifang; Stefanick, Marcia L.; Anderson, Garnet L.; Rohan, Thomas E.

In: Journal of Women's Health, Vol. 24, No. 3, 01.03.2015, p. 218-227.

Research output: Contribution to journalArticle

Heo, Moonseong ; Kabat, Geoffrey C. ; Strickler, Howard ; Lin, Juan ; Hou, Lifang ; Stefanick, Marcia L. ; Anderson, Garnet L. ; Rohan, Thomas E. / Optimal Cutoffs of Obesity Measures in Relation to Cancer Risk in Postmenopausal Women in the Women's Health Initiative Study. In: Journal of Women's Health. 2015 ; Vol. 24, No. 3. pp. 218-227.
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AB - Background: Obesity is a risk factor for several cancers in postmenopausal women. We attempted to determine cutoffs of adiposity measures in relation to risk of obesity-related cancers among postmenopausal women and to examine the effects of hormone therapy (HT) use on the cutoffs, neither of which has been broadly studied. Methods: We used data from the Women's Health Initiative cohort (n=144,701) and applied Cox-proportional hazards regressions to each combination of 17 cancer types and 6 anthropometric measures (weight, body mass index [BMI], weight to height ratio, waist circumference, waist to hip ratio [WHR], and waist to height ratio). Interactions between the anthropometric measures and HT use were also examined. Cutoffs were determined by applying a grid search followed by a two-fold cross validation method. Survival ROC analysis of 5- and 10-year incidence followed. Results: Breast, colorectal, colon, endometrium, kidney, and all cancers combined were significantly positively associated with all six anthropometric measures, whereas lung cancer among ever smokers was significantly inversely associated with all measures except WHR. The derived cutoffs of each obesity measure varied across cancers (e.g., BMI cutoffs for breast and endometrium cancers were 30kg/m2 and 34kg/m2, respectively), and also depended on HT use. The Youden indices of the cutoffs for predicting 5- and 10-year cancer incidence were higher among HT never users. Conclusion: Using a panel of different anthropometric measures, we derived optimal cut-offs categorizing populations into high- and low-risk groups, which differed by cancer type and HT use. Although the discrimination abilities of these risk categories were generally poor, the results of this study could serve as a starting point from which to determine adiposity cutoffs for inclusion in risk prediction models for specific cancer types.

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