326 research outputs found
Brain and salivary gland tumors and mobile phone use : evaluating the evidence from various epidemiological study designs
No full textMobile phones (MPs) are the most relevant source of radiofrequency electromagnetic field (RF-EMF) exposure to the brain and the salivary gland. Whether this exposure implies a cancer risk has been addressed in several case-control and few cohort studies. A meta-analysis of these studies does not show increased risks for meningioma, pituitary, and salivary gland tumors. For glioma and acoustic neuroma, the results are heterogeneous, with few case-control studies reporting substantially increased risks. However, these elevated risks are not coherent with observed incidence time trends, which are considered informative for this specific topic owing to the steep increase in MP use, the availability of virtually complete cancer registry data from many countries, and the limited number of known competing environmental risk factors. In conclusion, epidemiological studies do not suggest increased brain or salivary gland tumor risk with MP use, although some uncertainty remains regarding long latency periods (>15 years), rare brain tumor subtypes, and MP usage during childhood
Risk of breast cancer in men in relation to weight change: A national case‐control study in England and Wales
No full textBreast cancer is uncommon in men and knowledge about its causation limited. Obesity is a risk factor but there has been no investigation of whether weight change is an independent risk factor, as it is in women. In a national case‐control study, 1998 men with breast cancer incident in England and Wales during 2005 to 2017 and 1597 male controls were interviewed about risk factors for breast cancer including anthropometric factors at several ages. Relative risks of breast cancer in relation to changes in body mass index (BMI) and waist/height ratios at these ages were obtained by logistic regression modelling. There were significant trends of increasing breast cancer risk with increase in BMI from age 20 to 40 (odds ratio [OR] 1.11 [95% confidence interval (CI) 1.05‐1.17] per 2 kg/m(2) increase in BMI; P < .001), and from age 40 to 60 (OR 1.12 [1.04‐1.20]; P = .003), and with increase in self‐reported adiposity compared to peers at age 11 to BMI compared with peers at age 20 (OR 1.19 [1.09‐1.30]; P < .001). Increase in waist/height ratio from age 20 to 5 years before diagnosis was also highly significantly associated with risk (OR 1.13 [1.08‐1.19]; P < .001). The associations with increases in BMI and waist/height ratio were significant independently of each other and of BMI or waist/height ratio at the start of the period of change analysed, and effects were similar for invasive and in situ tumours separately. Increases in BMI and abdominal obesity are each risk factors for breast cancer in men, independently of obesity per se. These associations might relate to increasing oestrogen levels with weight gain, but this needs investigation
Comparative performance of lung cancer risk models to define lung screening eligibility in the United Kingdom.
No full textBACKGROUND: The National Health Service England (NHS) classifies individuals as eligible for lung cancer screening using two risk prediction models, PLCOm2012 and Liverpool Lung Project-v2 (LLPv2). However, no study has compared the performance of lung cancer risk models in the UK. METHODS: We analysed current and former smokers aged 40-80 years in the UK Biobank (N = 217,199), EPIC-UK (N = 30,813), and Generations Study (N = 25,777). We quantified model calibration (ratio of expected to observed cases, E/O) and discrimination (AUC). RESULTS: Risk discrimination in UK Biobank was best for the Lung Cancer Death Risk Assessment Tool (LCDRAT, AUC = 0.82, 95% CI = 0.81-0.84), followed by the LCRAT (AUC = 0.81, 95% CI = 0.79-0.82) and the Bach model (AUC = 0.80, 95% CI = 0.79-0.81). Results were similar in EPIC-UK and the Generations Study. All models overestimated risk in all cohorts, with E/O in UK Biobank ranging from 1.20 for LLPv3 (95% CI = 1.14-1.27) to 2.16 for LLPv2 (95% CI = 2.05-2.28). Overestimation increased with area-level socioeconomic status. In the combined cohorts, USPSTF 2013 criteria classified 50.7% of future cases as screening eligible. The LCDRAT and LCRAT identified 60.9%, followed by PLCOm2012 (58.3%), Bach (58.0%), LLPv3 (56.6%), and LLPv2 (53.7%). CONCLUSION: In UK cohorts, the ability of risk prediction models to classify future lung cancer cases as eligible for screening was best for LCDRAT/LCRAT, very good for PLCOm2012, and lowest for LLPv2. Our results highlight the importance of validating prediction tools in specific countries
Maternal breast cancer risk in relation to birthweight and gestation of her offspring
No full textAbstract Background Parity and age at first pregnancy are well-established risk factors for breast cancer, but the effects of other characteristics of pregnancies are uncertain and the literature is inconsistent. Methods In a cohort of 83,451 parous women from the general population of the UK, which collected detailed information on each pregnancy and a wide range of potential confounders, we investigated the associations of length of gestation and birthweight of offspring in a woman’s pregnancies with her breast cancer risk, adjusting for a full range of non-reproductive as well as reproductive risk factors unlike in previous large studies. Results Gestation of the first-born offspring was significantly inversely related to the risk of pre-menopausal breast cancer (p trend = 0.03; hazard ratio (HR) for 26–31 compared with 40–41 weeks, the baseline group, = 2.38, 95% confidence interval (CI) 1.26–4.49), and was borderline significantly related to risk of breast cancer overall (p trend = 0.05). Risk was significantly raised in mothers of high birthweight first-born (HR for breast cancer overall = 1.53, 95% CI 1.06–2.21 for ≥ 4500 g compared with 3000–3499 g, the baseline group). For gestation and birthweight of most recent birth, there were no clear effects. Analyses without adjustment for confounders (other than age) gave similar results. Conclusions Our data add to evidence that short gestation pregnancies may increase the risk of breast cancer, at least pre-menopausally, perhaps by hormonal stimulation and breast proliferation early in pregnancy without the opportunity for the differentiation that occurs in late pregnancy. High birthweight first pregnancies may increase breast cancer risk, possibly through the association of birthweight with oestrogen and insulin-like growth factor 1 levels
Family history and risk of breast cancer: an analysis accounting for family structure
No full textPURPOSE: Family history is an important risk factor for breast cancer incidence, but the parameters conventionally used to categorize it are based solely on numbers and/or ages of breast cancer cases in the family and take no account of the size and age-structure of the woman's family. METHODS: Using data from the Generations Study, a cohort of over 113,000 women from the general UK population, we analyzed breast cancer risk in relation to first-degree family history using a family history score (FHS) that takes account of the expected number of family cases based on the family's age-structure and national cancer incidence rates. RESULTS: Breast cancer risk increased significantly (P trend < 0.0001) with greater FHS. There was a 3.5-fold (95% CI 2.56-4.79) range of risk between the lowest and highest FHS groups, whereas women who had two or more relatives with breast cancer, the strongest conventional familial risk factor, had a 2.5-fold (95% CI 1.83-3.47) increase in risk. Using likelihood ratio tests, the best model for determining breast cancer risk due to family history was that combining FHS and age of relative at diagnosis. CONCLUSIONS: A family history score based on expected as well as observed breast cancers in a family can give greater risk discrimination on breast cancer incidence than conventional parameters based solely on cases in affected relatives. Our modeling suggests that a yet stronger predictor of risk might be a combination of this score and age at diagnosis in relatives
Smoking and risk of breast cancer in the Generations Study cohort
No full textAbstract Background Plausible biological reasons exist regarding why smoking could affect breast cancer risk, but epidemiological evidence is inconsistent. Methods We used serial questionnaire information from the Generations Study cohort (United Kingdom) to estimate HRs for breast cancer in relation to smoking adjusted for potentially confounding factors, including alcohol intake. Results Among 102,927 women recruited 2003–2013, with an average of 7.7 years of follow-up, 1815 developed invasive breast cancer. The HR (reference group was never smokers) was 1.14 (95% CI 1.03–1.25; P = 0.010) for ever smokers, 1.24 (95% CI 1.08–1.43; P = 0.002) for starting smoking at ages < 17 years, and 1.23 (1.07–1.41; P = 0.004) for starting smoking 1–4 years after menarche. Breast cancer risk was not statistically associated with interval from initiation of smoking to first birth (P-trend = 0.97). Women with a family history of breast cancer (ever smoker vs never smoker HR 1.35; 95% CI 1.12–1.62; P = 0.002) had a significantly larger HR in relation to ever smokers (P for interaction = 0.039) than women without (ever smoker vs never smoker HR 1.07; 95% CI 0.96–1.20; P = 0.22). The interaction was prominent for age at starting smoking (P = 0.003) and starting smoking relative to age at menarche (P = 0.0001). Conclusions Smoking was associated with a modest but significantly increased risk of breast cancer, particularly among women who started smoking at adolescent or peri-menarcheal ages. The relative risk of breast cancer associated with smoking was greater for women with a family history of the disease
Breast cancer risk in relation to history of preeclampsia and hyperemesis gravidarum: Prospective analysis in the Generations Study
No full textPreeclampsia and hyperemesis gravidarum are pregnancy complications associated with altered sex hormone levels. Previous studies suggest preeclampsia may be associated with a decreased risk of subsequent breast cancer and hyperemesis with an increased risk, but the evidence remains unclear. We used data from the Generations Study, a large prospective study of women in the United Kingdom, to estimate relative risks of breast cancer in relation to a history of preeclampsia and hyperemesis using Cox regression adjusting for known breast cancer risk factors. During 7.5 years average follow-up of 82,053 parous women, 1,969 were diagnosed with invasive or in situ breast cancer. Women who had experienced preeclampsia during pregnancy had a significantly decreased risk of premenopausal breast cancer (hazard ratio (HR) =0.67, 95% confidence interval (CI): 0.49-0.90) and of HER2-enriched tumours (HR = 0.33, 95% CI: 0.12-0.91), but there was no association with overall (HR = 0.90, 95% CI: 0.80-1.02) or postmenopausal (HR = 0.97, 95% CI: 0.85-1.12) breast cancer risk. Risk reductions among premenopausal women were strongest within 20 years since the last pregnancy with preeclampsia. Hyperemesis was associated with a significantly increased risk of HER2-enriched tumours (HR = 1.76, 95% CI: 1.07-2.87), but not with other intrinsic subtypes or breast cancer risk overall. These results provide evidence that preeclampsia is associated with a decreased risk of premenopausal and HER2-enriched breast cancer and that hyperemesis, although not associated with breast cancer risk overall, may be associated with raised risk of HER2-enriched tumours
Domestic light at night and breast cancer risk: a prospective analysis of 105 000 UK women in the Generations Study
No full textBackground: Circadian disruption caused by exposure to light at night (LAN) has been proposed as a risk factor for breast cancer and a reason for secular increases in incidence. Studies to date have largely been ecological or case-control in design and findings have been mixed. Methods: We investigated the relationship between LAN and breast cancer risk in the UK Generations Study. Bedroom light levels and sleeping patterns at age 20 and at study recruitment were obtained by questionnaire. Analyses were conducted on 105 866 participants with no prior history of breast cancer. During an average of 6.1 years of follow-up, 1775 cases of breast cancer were diagnosed. Cox proportional hazard models were used to calculate hazard ratios (HRs), adjusting for potential confounding factors. Results: There was no association between LAN level and breast cancer risk overall (highest compared with lowest LAN level at recruitment: HR=1.01, 95% confidence interval (CI): 0.88–1.15), or for invasive (HR=0.98, 95% CI: 0.85–1.13) or in situ (HR=0.96, 95% CI: 0.83–1.11) breast cancer, or oestrogen-receptor (ER) positive (HR=0.98, 95% CI: 0.84–1.14); or negative (HR=1.16, 95% CI: 0.82–1.65) tumours separately. The findings did not differ by menopausal status. Adjusting for sleep duration, sleeping at unusual times (non-peak sleep) and history of night work did not affect the results. Night waking with exposure to light, occurring around age 20, was associated with a reduced risk of premenopausal breast cancer (HR for breast cancer overall=0.74, 95% CI: 0.55–0.99; HR for ER-positive breast cancer=0.69, 95% CI: 0.49–0.97). Conclusions: In this prospective cohort analysis of LAN, there was no evidence that LAN exposure increased the risk of subsequent breast cancer, although the suggestion of a lower breast cancer risk in pre-menopausal women with a history of night waking in their twenties may warrant further investigation
Night shift work and risk of breast cancer in women: the Generations Study cohort
No full textBACKGROUND: It is plausible that night shift work could affect breast cancer risk, possibly by melatonin suppression or circadian clock disruption, but epidemiological evidence is inconclusive. METHODS: Using serial questionnaires from the Generations Study cohort, we estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for breast cancer in relation to being a night shift worker within the last 10 years, adjusted for potential confounders. RESULTS: Among 102,869 women recruited in 2003-2014, median follow-up 9.5 years, 2059 developed invasive breast cancer. The HR in relation to night shift work was 1.00 (95%CI: 0.86-1.15). There was a significant trend with average hours of night work per week (P = 0.035), but no significantly raised risks for hours worked per night, nights worked per week, average hours worked per week, cumulative years of employment, cumulative hours, time since cessation, type of occupation, age starting night shift work, or age starting in relation to first pregnancy. CONCLUSIONS: The lack of overall association, and no association with all but one measure of dose, duration, and intensity in our data, does not support an increased risk of breast cancer from night shift work in women
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