Adult Weight Change and Risk of Postmenopausal Breast Cancer

Eliassen, A. Heather; Colditz, Graham A.; Rosner, Bernard; Willett, Walter C.; Hankinson, Susan E.

doi:10.1001/jama.296.2.193

Cited by 556 publications

(385 citation statements)

References 60 publications

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“…To the best of our knowledge, no studies have been one case-control study showed that both adult weight gain before and after menopause were associated with postmenopausal breast cancer risk [13,18,34,35] whereas in one case-control study an increase in risk was only evident for adult weight gain after menopause [17]. None of these studies investigated whether these associations differed by ER/PR status of the tumor.…”

Section: Characteristics Of Studiesmentioning

confidence: 98%

Adult weight gain in relation to breast cancer risk by estrogen and progesterone receptor status: a meta-analysis

Vrieling

Buck

Kaaks

et al. 2010

Breast Cancer Res Treat

144

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Section: Characteristics Of Studiesmentioning

confidence: 98%

Adult weight gain in relation to breast cancer risk by estrogen and progesterone receptor status: a meta-analysis

Vrieling

Buck

Kaaks

et al. 2010

Breast Cancer Res Treat

144

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“…[159][160][161] We and others have demonstrated that losing and maintaining a weight loss of ≥ 5%, either before or after the menopause, reduces post-menopausal breast cancer risk by 25-40% in the general population. [162][163][164] Weight control also appears to be important for reducing the risk of post-menopausal breast cancer among women at moderate risk with a family history with low-penetrance genetic variants (15-30% lifetime risk), 159,160,165 and among high-risk BRCA1/BRCA2 carriers (up to 60-80% lifetime risk). BMI is the only lifestyle factor that is currently incorporated into any risk model.…”

Section: Lifestyle Risk Factorsmentioning

confidence: 99%

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Evans

Astley

Stavrinos³

et al. 2016

Programme Grants Appl Res

117

126

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BackgroundIn the UK, women are invited for 3-yearly mammography screening, through the NHS Breast Screening Programme (NHSBSP), from the ages of 47–50 years to the ages of 69–73 years. Women with family histories of breast cancer can, from the age of 40 years, obtain enhanced surveillance and, in exceptionally high-risk cases, magnetic resonance imaging. However, no NHSBSP risk assessment is undertaken. Risk prediction models are able to categorise women by risk using known risk factors, although accurate individual risk prediction remains elusive. The identification of mammographic breast density (MD) and common genetic risk variants [single nucleotide polymorphisms (SNPs)] has presaged the improved precision of risk models.ObjectivesTo (1) identify the best performing model to assess breast cancer risk in family history clinic (FHC) and population settings; (2) use information from MD/SNPs to improve risk prediction; (3) assess the acceptability and feasibility of offering risk assessment in the NHSBSP; and (4) identify the incremental costs and benefits of risk stratified screening in a preliminary cost-effectiveness analysis.DesignTwo cohort studies assessing breast cancer incidence.SettingHigh-risk FHC and the NHSBSP Greater Manchester, UK.ParticipantsA total of 10,000 women aged 20–79 years [Family History Risk Study (FH-Risk); UK Clinical Research Network identification number (UKCRN-ID) 8611] and 53,000 women from the NHSBSP [aged 46–73 years; Predicting the Risk of Cancer At Screening (PROCAS) study; UKCRN-ID 8080].InterventionsQuestionnaires collected standard risk information, and mammograms were assessed for breast density by a number of techniques. All FH-Risk and 10,000 PROCAS participants participated in deoxyribonucleic acid (DNA) studies. The risk prediction models Manual method, Tyrer–Cuzick (TC), BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) and Gail were used to assess risk, with modelling based on MD and SNPs. A preliminary model-based cost-effectiveness analysis of risk stratified screening was conducted.Main outcome measuresBreast cancer incidence.Data sourcesThe NHSBSP; cancer registration.ResultsA total of 446 women developed incident breast cancers in FH-Risk in 97,958 years of follow-up. All risk models accurately stratified women into risk categories. TC had better risk precision than Gail, and BOADICEA accurately predicted risk in the 6268 single probands. The Manual model was also accurate in the whole cohort. In PROCAS, TC had better risk precision than Gail [area under the curve (AUC) 0.58 vs. 0.54], identifying 547 prospective breast cancers. The addition of SNPs in the FH-Risk case–control study improved risk precision but was not useful inBRCA1(breast cancer 1 gene) families. Risk modelling of SNPs in PROCAS showed an incremental improvement from using SNP18 used in PROCAS to SNP67. MD measured by visual assessment score provided better risk stratification than automatic measures, despite wide intra- and inter-reader variability. Using a MD-adjusted TC model in PROCAS improved risk stratification (AUC = 0.6) and identified significantly higher rates (4.7 per 10,000 vs. 1.3 per 10,000;p < 0.001) of high-stage cancers in women with above-average breast cancer risks. It is not possible to provide estimates of the incremental costs and benefits of risk stratified screening because of lack of data inputs for key parameters in the model-based cost-effectiveness analysis.ConclusionsRisk precision can be improved by using DNA and MD, and can potentially be used to stratify NHSBSP screening. It may also identify those at greater risk of high-stage cancers for enhanced screening. The cost-effectiveness of risk stratified screening is currently associated with extensive uncertainty. Additional research is needed to identify data needed for key inputs into model-based cost-effectiveness analyses to identify the impact on health-care resource use and patient benefits.Future workA pilot of real-time NHSBSP risk prediction to identify women for chemoprevention and enhanced screening is required.FundingThe National Institute for Health Research Programme Grants for Applied Research programme. The DNA saliva collection for SNP analysis for PROCAS was funded by the Genesis Breast Cancer Prevention Appeal.

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“…Diabetes mellitus (OR 1.52, 95% CI 1.30-1.78) [30] and smoking were reported to increase the breast cancer risk [34], but not to a similar extent for all regions [35]. In contrast to reports from developed countries [36,37], a higher body mass index is not associated with premenopausal breast cancer, but is linked to postmenopausal breast cancer in Asian populations [38]. …”

Section: Risk Factorsmentioning

confidence: 99%

Current Status and Future Projections of Breast Cancer in Asia

2015

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Asia is the world's largest continent comprising about 3/5 of the human population. Breast cancer is the most common type of cancer and the second leading cause of cancer-related deaths among women in Asia, accounting for 39% of all breast cancers diagnosed worldwide. The incidence of breast cancer in Asia varies widely across the continent and is still lower than in Western countries, but the proportional contribution of Asia to the global breast cancer rates is increasing rapidly in parallel to the socioeconomic development. However, the mortality-to-incidence ratios are much higher for Asia than for Western countries. Most Asian countries are low- and middle-income countries (LMICs) where breast cancer presents at a younger age and a later stage, and where patients are more likely to die from the disease than those in Western countries. Moreover, diagnostic workup, treatment and palliative services are inadequate in most Asian LMICs. In this review, we present an overview of the breast cancer risk factors and epidemiology, control measures, and cancer care among Asian countries.

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Adult Weight Change and Risk of Postmenopausal Breast Cancer

Cited by 556 publications

References 60 publications

Adult weight gain in relation to breast cancer risk by estrogen and progesterone receptor status: a meta-analysis

Adult weight gain in relation to breast cancer risk by estrogen and progesterone receptor status: a meta-analysis

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Current Status and Future Projections of Breast Cancer in Asia

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