| 1. |
- Aleksandrova, Krasimira, et al.
(författare)
-
Development and validation of a lifestyle-based model for colorectal cancer risk prediction : the LiFeCRC score
- 2021
-
Ingår i: BMC Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 19:1
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 2. |
- Conti, David, V, et al.
(författare)
-
Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- 2021
-
Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:1, s. 65-75
-
Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction. A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.
|
|
| 3. |
- Perez-Cornago, Aurora, et al.
(författare)
-
Comparison of 2 different approaches to calculate dietary intakes in the Oxford WebQ questionnaire used in UK Biobank
- 2021
-
Konferensbidrag (refereegranskat)abstract
- Introduction: The Oxford WebQ is a web-based 24-hour dietary assessment tool used in UK Biobank and other large-scale prospective studies to assess dietary intake. The food composition table (FCT) used to calculate nutrient intakes, the McCance and Widdowson’s FCT 6th edition (2002), has recently been replaced with the UK Nutrient Databank (2013), as this FCT is, on average, closer in time to when participants completed the questionnaire. Moreover, portion sizes, personalisation of fats used in cooking, food group disaggregation and the underlying code for nutrient calculation were revised and updated. In this study we aim to compare the two versions of obtained nutrient intakes in UK Biobank participants. Methods: A subsample of UK Biobank participants recruited towards the end of the recruitment period and/or those who provided email addresses, completed the Oxford WebQ questionnaire up to 5 times (2009/2012). After excluding participants with extreme energy intakes (men: >20,000 kJ/d, women: 18,000 kJ/d), a total of 210,109 participants, who completed the Oxford WebQ questionnaire at least once, were included. Means and standard deviations of macronutrient and fibre intakes were averaged for all completed WebQ questionnaires for each participant and Spearman correlations and paired t-tests were used to compare the mean nutrient intakes between the two versions.Results: All nutrient intake differences were significantly different from zero after the WebQ update (P<0.001). Compared to the previous version , mean nutrient intakes in this updated version were slightly lower for energy (-144 kJ/d), protein (-1.2 g/d), total fat (-4.5 g/d) and saturated fat (-2.7 g/d), but slightly higher for carbohydrates (+1.8 g/d), total sugars (+5.3 g/d) and fibre (+1.4 g/d). High correlations were found between nutrients calculated using the two versions: energy (r=0.96), protein (r=0.97), total fat (r=0.95), carbohydrates (r=0.95), saturated fat (r=0.91), total sugars (r=0.96), and fibre (r=0.94).Discussion: Absolute differences in nutrient intakes between the two versions were observed, although the ranking of individuals was minimally affected. Future work will assess the heterogeneous differences among individuals caused by the changes made to the WebQ, and this updated version will be available to all studies using the Oxford-WebQ.
|
|
| 4. |
- Piernas, Carmen, et al.
(författare)
-
Describing a new food group classification system for UK biobank : analysis of food groups and sources of macro- and micronutrients in 208,200 participants
- 2021
-
Ingår i: European Journal of Nutrition. - : Springer. - 1436-6207 .- 1436-6215. ; 60:5, s. 2879-2890
-
Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: The UK Biobank study collected detailed dietary data using a web-based self-administered 24 h assessment tool, the Oxford WebQ. We aimed to describe a comprehensive food grouping system for this questionnaire and to report dietary intakes and key sources of selected nutrients by sex and education.METHODS: Participants with at least one valid 24-h questionnaire were included (n = 208,200). Dietary data were grouped based on the presence of nutrients as well as culinary use, processing, and plant/animal origin. For each food group, we calculated the contribution to energy intake, key macronutrients, and micronutrients. We also identified the top contributors to energy intake, free sugars and saturated fat by sex and education.RESULTS: From the 93 food groups, the top five contributors to energy intake (in descending order) were: desserts/cakes/pastries; white bread; white pasta/rice; bananas/other fruit; semi-skimmed milk. Wine, beer, and fruit juices were the top beverage contributors to overall energy intake. Biscuits, and desserts/cakes/pastries were the highest contributors to free sugars, total fat, and saturated fat intakes, but also contributed to the calcium and iron intakes. Top contributors to energy, saturated fat, and free sugars were broadly similar by sex and education category, with small differences in average nutrient intakes across the population.CONCLUSION: This new food classification system will support the growing interest in the associations between food groups and health outcomes and the development of food-based dietary guidelines. Food group variables will be available to all users of the UK Biobank WebQ questionnaire.
|
|
