Identification of NHLRC1 as a Novel AKT Activator from a Lung Cancer Epigenome-Wide Association Study (EWAS).

Changes in DNA methylation identified by epigenome-wide association studies (EWAS) have been recently linked to increased lung cancer risk. However, the cellular effects of these differentially methylated positions (DMPs) are often unclear. Therefore, we investigated top differentially methylated positions identified from an EWAS study. This included a putative regulatory region of NHLRC1. Hypomethylation of this gene was recently linked with decreased survival rates in lung cancer patients. HumanMethylation450 BeadChip array (450K) analysis was performed on 66 lung cancer case-control pairs from the European Prospective Investigation into Cancer and Nutrition Heidelberg lung cancer EWAS (EPIC HD) cohort. DMPs identified in these pre-diagnostic blood samples were then investigated for differential DNA methylation in lung tumor versus adjacent normal lung tissue from The Cancer Genome Atlas (TCGA) and replicated in two independent lung tumor versus adjacent normal tissue replication sets with MassARRAY. The EPIC HD top hypermethylated DMP cg06646708 was found to be a hypomethylated region in multiple data sets of lung tumor versus adjacent normal tissue. Hypomethylation within this region caused increased mRNA transcription of the closest gene NHLRC1 in lung tumors. In functional assays, we demonstrate attenuated proliferation, viability, migration, and invasion upon NHLRC1 knock-down in lung cancer cells. Furthermore, diminished AKT phosphorylation at serine 473 causing expression of pro-apoptotic AKT-repressed genes was detected in these knock-down experiments. In conclusion, this study demonstrates the powerful potential for discovery of novel functional mechanisms in oncogenesis based on EWAS DNA methylation data. NHLRC1 holds promise as a new prognostic biomarker for lung cancer survival and prognosis, as well as a target for novel treatment strategies in lung cancer patients.

Air quality in an air ventilated fitness center reopening for pilot study during COVID-19 pandemic lockdown.

During COVID-19 lockdowns less people were able to fulfill the WHO recommendations on physical activity. Also, fitness centers were associated to SARS-CoV-2 superspreader events. However, the risk of infection can be strongly reduced by outdoor air ventilation. To investigate whether a reopening of fitness centers can be justified, CO 2 concentration was measured during four days in a fitness center. Except for one room, the observed CO 2 concentrations were mainly under 800 ppm, which stands for high air quality. The strong decrease of CO 2 concentration during the 15 min evacuations following each hour of workout, speaks for the functionality of the ventilation system. In particular, the number of people present in the studio has a strong impact on the estimated CO 2 value. In a linear mixed model, an additional CO 2 concentration of 2.24 ppm (95 % confidence interval [2.04, 2.43]) was estimated for this setting with a total volume of 4065 m 3 in the fitness center and a possible air change rate per hour up to 10. This means, that for 45 visitors, 100 ppm can be added to the predicted concentration. To summarize, a combination of ventilation, restriction of the number of visitors and surveying the CO 2 concentration allowing for further restrictions in case of need, seems to be an adequate means to reduce the risk of SARS-CoV-2 infection in fitness centers.

Postdiagnosis weight change is associated with poorer survival in breast cancer survivors: A prospective population-based patient cohort study.

More women are surviving after breast cancer due to early detection and modern treatment strategies. Body weight also influences survival. We aimed to characterize associations between postdiagnosis weight change and prognosis in postmenopausal long-term breast cancer survivors. We used data from a prospective population-based patient cohort study (MARIE) conducted in two geographical regions of Germany. Breast cancer patients diagnosed 50 to 74 years of age with an incident invasive breast cancer or in situ tumor were recruited from 2002 to 2005 and followed up until June 2015. Baseline weight was ascertained at an in-person interview at recruitment and follow-up weight was ascertained by telephone interview in 2009. Delayed entry Cox proportional hazards regression was used to assess associations between relative weight change and all-cause mortality, breast cancer mortality, and recurrence-free survival. In total, 2216 patients were included. Compared to weight maintenance (within 5%), weight loss >10% increased risk of all-cause mortality (HR 2.50, 95% CI 1.61, 3.88), breast cancer mortality (HR 3.07, 95% CI 1.69, 5.60) and less so of recurrence-free survival (HR 1.43, 95% CI 0.87, 2.36). Large weight gain of >10% also increased all-cause mortality (HR 1.64, 95% CI 1.02, 2.62) and breast cancer mortality (HR 2.25, 95% CI 1.25, 4.04). Weight maintenance for up to 5 years in long-term breast cancer survivors may help improve survival and prognosis. Postdiagnosis fluctuations in body weight of greater than 10% may lead to increased mortality. Survivors should be recommended to avoid large deviations in body weight from diagnosis onwards to maintain health and prolong life.

Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score.

BACKGROUND: Nutrition and lifestyle have been long established as risk factors for colorectal cancer (CRC). Modifiable lifestyle behaviours bear potential to minimize long-term CRC risk; however, translation of lifestyle information into individualized CRC risk assessment has not been implemented. Lifestyle-based risk models may aid the identification of high-risk individuals, guide referral to screening and motivate behaviour change. We therefore developed and validated a lifestyle-based CRC risk prediction algorithm in an asymptomatic European population. METHODS: The model was based on data from 255,482 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study aged 19 to 70 years who were free of cancer at study baseline (1992-2000) and were followed up to 31 September 2010. The model was validated in a sample comprising 74,403 participants selected among five EPIC centres. Over a median follow-up time of 15 years, there were 3645 and 981 colorectal cancer cases in the derivation and validation samples, respectively. Variable selection algorithms in Cox proportional hazard regression and random survival forest (RSF) were used to identify the best predictors among plausible predictor variables. Measures of discrimination and calibration were calculated in derivation and validation samples. To facilitate model communication, a nomogram and a web-based application were developed. RESULTS: The final selection model included age, waist circumference, height, smoking, alcohol consumption, physical activity, vegetables, dairy products, processed meat, and sugar and confectionary. The risk score demonstrated good discrimination overall and in sex-specific models. Harrell's C-index was 0.710 in the derivation cohort and 0.714 in the validation cohort. The model was well calibrated and showed strong agreement between predicted and observed risk. Random survival forest analysis suggested high model robustness. Beyond age, lifestyle data led to improved model performance overall (continuous net reclassification improvement = 0.307 (95% CI 0.264-0.352)), and especially for young individuals below 45 years (continuous net reclassification improvement = 0.364 (95% CI 0.084-0.575)). CONCLUSIONS: LiFeCRC score based on age and lifestyle data accurately identifies individuals at risk for incident colorectal cancer in European populations and could contribute to improved prevention through motivating lifestyle change at an individual level.

Theoretical potential for endometrial cancer prevention through primary risk factor modification: Estimates from the EPIC cohort.

Endometrial cancer (EC) incidence rates vary ~10-fold worldwide, in part due to variation in EC risk factor profiles. Using an EC risk model previously developed in the European EPIC cohort, we evaluated the prevention potential of modified EC risk factor patterns and whether differences in EC incidence between a European population and low-risk countries can be explained by differences in these patterns. Predicted EC incidence rates were estimated over 10 years of follow-up for the cohort before and after modifying risk factor profiles. Risk factors considered were: body mass index (BMI, kg/m2 ), use of postmenopausal hormone therapy (HT) and oral contraceptives (OC) (potentially modifiable); and, parity, ages at first birth, menarche and menopause (environmentally conditioned, but not readily modifiable). Modeled alterations in BMI (to all ≤23 kg/m2 ) and HT use (to all non-HT users) profiles resulted in a 30% reduction in predicted EC incidence rates; individually, longer duration of OC use (to all ≥10 years) resulted in a 42.5% reduction. Modeled changes in not readily modifiable exposures (i.e., those not contributing to prevention potential) resulted in ≤24.6% reduction in predicted EC incidence. Women in the lowest decile of a risk score based on the evaluated exposures had risk similar to a low risk countries; however, this was driven by relatively long use of OCs (median = 23 years). Our findings support avoidance of overweight BMI and of HT use as prevention strategies for EC in a European population; OC use must be considered in the context of benefits and risks.

Validation of two US breast cancer risk prediction models in German women.

PURPOSE: There are no models for German women that predict absolute risk of invasive breast cancer (BC), i.e., the probability of developing BC over a prespecified time period, given a woman's age and characteristics, while accounting for competing risks. We thus validated two absolute BC risk models (BCRAT, BCRmod) developed for US women in German women. BCRAT uses a woman's medical, reproductive, and BC family history; BCRmod adds modifiable risk factors (body mass index, hormone replacement therapy and alcohol use). METHODS: We assessed model calibration by comparing observed BC numbers (O) to expected numbers (E) computed from BCRmod/BCRAT for German women enrolled in the prospective European Prospective Investigation into Cancer and Nutrition (EPIC), and after updating the models with German BC incidence/competing mortality rates. We also compared 1-year BC risk predicted for all German women using the German Health Interview and Examination Survey for Adults (DEGS) with overall German BC incidence. Discriminatory performance was quantified by the area under the receiver operator characteristics curve (AUC). RESULTS: Among 22,098 EPIC-Germany women aged 40+ years, 745 BCs occurred (median follow-up: 11.9 years). Both models had good calibration for total follow-up, EBCRmod/O = 1.08 (95% confidence interval: 0.95-1.21), and EBCRAT/O = 0.99(0.87-1.11), and over 5 years. Compared to German BC incidence rates, both models somewhat overestimated 1-year risk for women aged 55+ and 70+ years. For total follow-up, AUCBCRmod = 0.61(0.58-0.63) and AUCBCRAT = 0.58(0.56-0.61), with similar values for 5-year follow-up. CONCLUSION: US BC risk models showed adequate calibration in German women. Discriminatory performance was comparable to that in US women. These models thus could be applied for risk prediction in German women.

Prognostic associations of circulating phytoestrogens and biomarker changes in long-term survivors of postmenopausal breast cancer.

Lignans are associated with improved postmenopausal breast cancer (BC) survival, but whether these associations, particularly with enterolactone (major lignan metabolite), persist over time is unclear. Little is known about other phytoestrogens on prognosis in long-term survivors. The study examines associations of prognosis with 1) circulating postdiagnosis enterolactone, 2) eight circulating phytoestrogen metabolites, and 3) changes in enterolactone and genistein. In a German cohort of 2,105 postmenopausal BC patients with blood samples collected at recruitment 2002-2005 (baseline) and re-interview in 2009 (follow-up), delay-entry Cox proportional hazards regression was used. Landmark analysis showed that circulating enterolactone (log2) associations with 5-year survival changed over time, with strongest hazard ratios of 0.89 (95% CI, 0.80-0.99) at blood draw (BD) and 0.86 (0.77-0.97) at 2 years post-BD for BC mortality, and 0.87 (0.80-0.95) at BD and 0.84 (0.76-0.92) at 3 years post-BD for all-cause mortality, which attenuated thereafter. In long-term survivors, increasing concentrations of genistein (1.17, 1.01-1.36), resveratrol (1.19, 1.02-1.40), and luteolin (1.96, 1.07-3.58) measured in follow-up blood samples were associated with poorer subsequent prognosis. Neither enterolactone at follow-up nor changes in enterolactone/genistein were associated with prognosis. Large long-term longitudinal studies with multiple phytoestrogen measurements are required to understand long-term effects of phytoestrogens after BC.

Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data.

As randomized trials in the USA and Europe have convincingly demonstrated efficacy of lung cancer screening by computed tomography (CT), European countries are discussing the introduction of screening programs. To maintain acceptable cost-benefit and clinical benefit-to-harm ratios, screening should be offered to individuals at sufficiently elevated risk of having lung cancer. Using federal-wide survey and lung cancer incidence data (2008-2013), we examined the performance of four well-established risk models from the USA (PLCOM2012, LCRAT, Bach) and the UK (LLP2008) in the German population, comparing with standard eligibility criteria based on age limits, minimal pack years of smoking (or combination of total duration with average intensity) and maximum years since smoking cessation. The eligibility criterion recommended by the United States Preventive Services Taskforce (USPSTF) would select about 3.2 million individuals, a group equal in size to the upper fifth of ever smokers age 50-79 at highest risk, and to 11% of all adults aged 50-79. According to PLCOM2012, the model showing best concordance between numbers of lung cancer cases predicted and reported in registries, persons with 5-year risk ≥ 1.7% included about half of all lung cancer incidence in the full German population. Compared to eligibility criteria (e.g. USPSTF), risk models elected individuals in higher age groups, including ex-smokers with longer average quitting times. Further studies should address how in Germany these shifts may affect expected benefits of CT screening in terms of life-years gained versus the potential harm of age-specific increasing risk of over-diagnosis.

Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals: a systematic literature review and external validation in the EPIC and UK Biobank prospective cohort studies.

OBJECTIVE: To systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts. DESIGN: Models were identified through an update of a published systematic review and validated in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted probability). RESULTS: The systematic review and its update identified 16 models from 8 publications (8 colorectal, 5 colon and 3 rectal). The number of participants included in each model validation ranged from 41 587 to 396 515, and the number of cases ranged from 115 to 1781. Eligible and ineligible participants across the models were largely comparable. Calibration of the models, where assessable, was very good and further improved by recalibration. The C-statistics of the models were largely similar between validation cohorts with the highest values achieved being 0.70 (95% CI 0.68 to 0.72) in the UK Biobank and 0.71 (95% CI 0.67 to 0.74) in EPIC. CONCLUSION: Several of these non-invasive models exhibited good calibration and discrimination within both external validation populations and are therefore potentially suitable candidates for the facilitation of risk stratification in population-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained.

Pre- to postdiagnosis leisure-time physical activity and prognosis in postmenopausal breast cancer survivors.

BACKGROUND: Physical activity (PA) before and after breast cancer diagnosis has been reported to be associated with lower mortality. However, whether changes in the activity after diagnosis impact prognosis is unclear and has not received much attention. This study aimed to examine pre- to postdiagnosis leisure-time PA and breast cancer prognosis. METHODS: We used data from the MARIE study, a prospective population-based patient cohort study of 3813 postmenopausal breast cancer patients, aged 50-74 at diagnosis, recruited from 2002 to 2005, re-interviewed in 2009, and followed up until June 2015. Prediagnosis PA was assessed at recruitment; postdiagnosis PA was assessed at re-interview in 2009. To examine pre- to postdiagnosis change in PA, women were categorized by pre- and postdiagnosis PA using a cut-off of 7.5 MET-h/week for meeting PA recommendations and combined into four groups: insufficiently active, increasingly active, decreasingly active, and sufficiently active. Cox regression models with delayed entry were used to assess associations between pre- to postdiagnosis patterns of PA and overall mortality (OM), breast cancer mortality (BCM), and recurrence-free survival (RFS). Additional analyses of pre- and postdiagnosis PA (no activity (reference), low activity, sufficient activity) with cancer outcomes, such as using a time-dependent model, were performed. In total, 2042 patients were included in the analyses. RESULTS: There were 206 deaths (114 from breast cancer) after a median follow-up time of 6.0 years after the 2009 interview. Compared to insufficiently active women, increasingly active women were at lower risk of OM, BCM, and RFS (HR (95%CI) of 0.50 (0.31-0.82), 0.54 (0.30-1.00), 0.58 (0.40-0.84), respectively). In sufficiently active women, associations for OM (0.75 (0.48-1.15)), BCM (0.61 (0.33-1.13)), and RFS 0.80 (0.57-1.14)) were similar to increasingly active women but attenuated, and decreasingly active women were not at lower risk for OM (0.91 (0.61-1.36)), BCM (0.80 (0.45-1.42)), and RFS (1.04 (0.76-1.43)). In time-dependent analyses, sufficient activity vs. no activity was associated with better OM (0.73 (0.57-0.93)), BCM (0.64 (0.46-0.89)), and RFS (0.82 (0.68-0.99)). Low activity was not significantly associated with prognosis. CONCLUSION: Our data support benefits for breast cancer prognosis in being physically active pre- and postdiagnosis particularly for women who were insufficiently active prediagnosis.

CA19-9 and apolipoprotein-A2 isoforms as detection markers for pancreatic cancer: a prospective evaluation.

Recently, we identified unique processing patterns of apolipoprotein A2 (ApoA2) in patients with pancreatic cancer. Our study provides a first prospective evaluation of an ApoA2 isoform ("ApoA2-ATQ/AT"), alone and in combination with carbohydrate antigen 19-9 (CA19-9), as an early detection biomarker for pancreatic cancer. We performed ELISA measurements of CA19-9 and ApoA2-ATQ/AT in 156 patients with pancreatic cancer and 217 matched controls within the European EPIC cohort, using plasma samples collected up to 60 months prior to diagnosis. The detection discrimination statistics were calculated for risk scores by strata of lag-time. For CA19-9, in univariate marker analyses, C-statistics to distinguish future pancreatic cancer patients from cancer-free individuals were 0.80 for plasma taken ≤6 months before diagnosis, and 0.71 for >6-18 months; for ApoA2-ATQ/AT, C-statistics were 0.62, and 0.65, respectively. Joint models based on ApoA2-ATQ/AT plus CA19-9 significantly improved discrimination within >6-18 months (C = 0.74 vs. 0.71 for CA19-9 alone, p = 0.022) and ≤ 18 months (C = 0.75 vs. 0.74, p = 0.022). At 98% specificity, and for lag times of ≤6, >6-18 or ≤ 18 months, sensitivities were 57%, 36% and 43% for CA19-9 combined with ApoA2-ATQ/AT, respectively, vs. 50%, 29% and 36% for CA19-9 alone. Compared to CA19-9 alone, the combination of CA19-9 and ApoA2-ATQ/AT may improve detection of pancreatic cancer up to 18 months prior to diagnosis under usual care, and may provide a useful first measure for pancreatic cancer detection prior to imaging.

Adherence to the World Cancer Research Fund/American Institute for Cancer Research cancer prevention recommendations and risk of in situ breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

BACKGROUND: Even though in situ breast cancer (BCIS) accounts for a large proportion of the breast cancers diagnosed, few studies have investigated potential risk factors for BCIS. Their results suggest that some established risk factors for invasive breast cancer have a similar impact on BCIS risk, but large population-based studies on lifestyle factors and BCIS risk are lacking. Thus, we investigated the association between lifestyle and BCIS risk within the European Prospective Investigation into Cancer and Nutrition cohort. METHODS: Lifestyle was operationalized by a score reflecting the adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations. The recommendations utilized in these analyses were the ones pertinent to healthy body weight, physical activity, consumption of plant-based foods, energy-dense foods, red and processed meat, and sugary drinks and alcohol, as well as the recommendation on breastfeeding. Cox proportional hazards regression was used to assess the association between lifestyle score and BCIS risk. The results were presented as hazard ratios (HR) and corresponding 95% confidence intervals (CI). RESULTS: After an overall median follow-up time of 14.9 years, 1277 BCIS cases were diagnosed. Greater adherence to the WCRF/AICR cancer prevention recommendations was not associated with BCIS risk (HR = 0.98, 95% CI 0.93-1.03; per one unit of increase; multivariable model). An inverse association between the lifestyle score and BCIS risk was observed in study centers, where participants were recruited mainly via mammographic screening and attended additional screening throughout follow-up (HR = 0.85, 95% CI 0.73-0.99), but not in the remaining ones (HR = 0.99, 95% CI 0.94-1.05). CONCLUSIONS: While we did not observe an overall association between lifestyle and BCIS risk, our results indicate that lifestyle is associated with BCIS risk among women recruited via screening programs and with regular screening participation. This suggests that a true inverse association between lifestyle habits and BCIS risk in the overall cohort may have been masked by a lack of information on screening attendance. The potential inverse association between lifestyle and BCIS risk in our analyses is consistent with the inverse associations between lifestyle scores and breast cancer risk reported from previous studies.

Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts.

BACKGROUND: Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction. METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention. RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail. CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.

Tumor-associated autoantibodies as early detection markers for ovarian cancer? A prospective evaluation.

Immuno-proteomic screening has identified several tumor-associated autoantibodies (AAb) that may have diagnostic capacity for invasive epithelial ovarian cancer, with AAbs to P53 proteins and cancer-testis antigens (CTAGs) as prominent examples. However, the early detection potential of these AAbs has been insufficiently explored in prospective studies. We performed ELISA measurements of AAbs to CTAG1A, CTAG2, P53 and NUDT11 proteins, for 194 patients with ovarian cancer and 705 matched controls from the European EPIC cohort, using serum samples collected up to 36 months prior to diagnosis under usual care. CA125 was measured using electrochemo-luminiscence. Diagnostic discrimination statistics were calculated by strata of lead-time between blood collection and diagnosis. With lead times ≤6 months, ovarian cancer detection sensitivity at 0.98 specificity (SE98) varied from 0.19 [95% CI 0.08-0.40] for CTAG1A, CTAG2 and NUDT1 to 0.23 [0.10-0.44] for P53 (0.33 [0.11-0.68] for high-grade serous tumors). However, at longer lead-times, the ability of these AAb markers to distinguish future ovarian cancer cases from controls declined rapidly; at lead times >1 year, SE98 estimates were close to zero (all invasive cases, range: 0.01-0.11). Compared to CA125 alone, combined logistic regression scores of AAbs and CA125 did not improve detection sensitivity at equal level of specificity. The added value of these selected AAbs as markers for ovarian cancer beyond CA125 for early detection is therefore limited.

Ovarian cancer early detection by circulating CA125 in the context of anti-CA125 autoantibody levels: Results from the EPIC cohort.

CA125 is the best ovarian cancer early detection marker to date; however, sensitivity is limited and complementary markers are required to improve discrimination between ovarian cancer cases and non-cases. Anti-CA125 autoantibodies are observed in circulation. Our objective was to evaluate whether these antibodies (1) can serve as early detection markers, providing evidence of an immune response to a developing tumor, and (2) modify the discriminatory capacity of CA125 by either masking CA125 levels (resulting in lower discrimination) or acting synergistically to improve discrimination between cases and non-cases. We investigated these objectives using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition cohort (EPIC) including 250 cases diagnosed within 4 years of blood collection and up to four matched controls. Circulating CA125 antigen and antibody levels were quantified using an electrochemiluminescence assay. Adjusted areas under the curve (aAUCs) by 2-year lag-time intervals were calculated using conditional logistic regression calibrated toward the absolute risk estimates from a pre-existing epidemiological risk model as an offset-variable. Anti-CA125 levels alone did not discriminate cases from controls. For cases diagnosed <2 years after blood collection, discrimination by CA125 antigen was suggestively higher with higher anti-CA125 levels (aAUC, highest antibody tertile: 0.84 [0.76-0.92]; lowest tertile: 0.76 [0.67-0.86]; phet = 0.06). We provide the first evidence of potentially synergistic discrimination effects of CA125 and anti-CA125 antibodies in ovarian early detection. If these findings are replicated, evaluating CA125 in the context of its antibody may improve ovarian cancer early detection.

Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination.

Phyto-oestrogens and colorectal cancer risk: a systematic review and dose-response meta-analysis of observational studies.

Epidemiological studies suggest that soya consumption as a source of phyto-oestrogens and isoflavones may be associated with a reduced risk of colorectal cancer. However, findings have not yet been synthesised for all groups of phyto-oestrogens. A meta-analysis was conducted to quantify the association between phyto-oestrogens and colorectal cancer risk. Relevant observational studies published up to June 2016 were identified by searching MEDLINE, EMBASE and Cochrane Library databases. Study-specific relative risks (RR) were pooled in both categorical and dose-response meta-analyses. Out of seventeen identified studies, sixteen were included in the meta-analysis. Comparing the highest with the lowest intake category, inverse associations for phyto-oestrogens overall and by subgroup were observed but were statistically significant in case-controls studies and not in cohort studies. The pooled RR in case-control studies were 0·76 (95 % CI 0·69, 0·84), 0·77 (95 % CI 0·69, 0·85) and 0·70 (95 % CI 0·56, 0·89) for phyto-oestrogens, isoflavones and lignans, respectively, whereas the corresponding pooled RR were 0·95 (95 % CI 0·85, 1·06), 0·94 (95 % CI 0·84, 1·05) and 1·00 (95 % CI 0·64, 1·57) in cohort studies. Dose-response analysis yielded an 8 % reduced risk of colorectal neoplasms for every 20 mg/d increase in isoflavones intake in Asians (pooled RR 0·92; 95 % CI 0·86, 0·97). A non-linear inverse association with colorectal cancer risk was found for lignans intake, but no association for circulating enterolactone concentrations was observed. Thus, study heterogeneity precludes a rigorous conclusion regarding an effect of high exposure to isoflavones on risk of colorectal cancer. Current evidence for an association with lignans exposure is limited. Further prospective studies, particularly evaluating lignans, are warranted to clarify the association between different phyto-oestrogens and colorectal cancer risk.

An epidemiological model for prediction of endometrial cancer risk in Europe.

Endometrial cancer (EC) is the fourth most frequent cancer in women in Europe, and as its incidence is increasing, prevention strategies gain further pertinence. Risk prediction models can be a useful tool for identifying women likely to benefit from targeted prevention measures. On the basis of data from 201,811 women (mostly aged 30-65 years) including 855 incident EC cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict EC was developed. A step-wise model selection process was used to select confirmed predictive epidemiologic risk factors. Piece-wise constant hazard rates in 5-year age-intervals were estimated in a cause-specific competing risks model, five-fold-cross-validation was applied for internal validation. Risk factors included in the risk prediction model were body-mass index (BMI), menopausal status, age at menarche and at menopause, oral contraceptive use, overall and by different BMI categories and overall duration of use, parity, age at first full-term pregnancy, duration of menopausal hormone therapy and smoking status (specific for pre, peri- and post-menopausal women). These variables improved the discriminating capacity to predict risk over 5 years from 71% for a model based on age alone to 77% (overall C statistic), and the model was well-calibrated (ratio of expected to observed cases = 0.99). Our model could be used for the identification of women at increased risk of EC in Western Europe. To achieve an EC-risk model with general validity, a large-scale cohort-consortium approach would be needed to assess and adjust for population variation.

Weight cycling and the risk of type 2 diabetes in the EPIC-Germany cohort.

AIMS/HYPOTHESIS: Studies on weight cycling and the risk of type 2 diabetes have revealed inconsistent results, possibly due to differences in the definition of weight fluctuations. Here, we investigated whether weight cycling during adulthood is related to diabetes risk in a large cohort study, using a complementary approach to define patterns of weight development. METHODS: Weight cycling, weight loss and weight gain were defined (1) a priori, using distinct categories, and (2) by functional principal component analysis (FPCA) to capture weight patterns in greater detail. Associations of weight cycling, weight loss and weight gain with the risk of type 2 diabetes were evaluated by Cox regression models. RESULTS: A priori defined weight cycling was associated with increased diabetes risk, compared with stable weight (HR 1.36 [95% CI 1.09, 1.68]). No significant association between FPCA-derived weight cycling and risk of diabetes was observed after adjustment for concurrent weight patterns (HR 1.19 [95% CI 0.89, 1.60]). Subgroup analyses showed that FPCA-derived weight cycling during net weight gain was associated with a higher risk of diabetes (HR 1.68 [95% CI 1.14, 2.48]). A priori defined weight gain (HR 2.08 [95% CI 1.60, 2.70]) was more clearly related to the risk of diabetes than FPCA-derived weight gain (HR 1.20 [95% CI 0.95, 1.51]), while no significant associations were observed for weight loss. CONCLUSIONS/INTERPRETATION: Overall, weight cycling may not be an independent risk factor for type 2 diabetes when accounting for concurrent patterns of weight development. However, weight cycling may pose a stronger risk of diabetes than non-cycling during net weight gain.