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Background Consensus on resectability criteria for colorectal cancer liver metastases (CRLM) is lacking, resulting in differences in therapeutic strategies. This study evaluated variability of resectability assessments and local treatment plans for patients with initially unresectable CRLM by the liver expert panel from the randomised phase III CAIRO5 study. Methods The liver panel, comprising surgeons and radiologists, evaluated resectability by predefined criteria at baseline and 2-monthly thereafter. If surgeons judged CRLM as resectable, detailed local treatment plans were provided. The panel chair determined the conclusion of resectability status and local treatment advice, and forwarded it to local surgeons. Results A total of 1149 panel evaluations of 496 patients were included. Intersurgeon disagreement was observed in 50% of evaluations and was lower at baseline than follow-up (36% vs. 60%, p < 0.001). Among surgeons in general, votes for resectable CRLM at baseline and follow-up ranged between 0–12% and 27–62%, and for permanently unresectable CRLM between 3–40% and 6–47%, respectively. Surgeons proposed different local treatment plans in 77% of patients. The most pronounced intersurgeon differences concerned the advice to proceed with hemihepatectomy versus parenchymal-preserving approaches. Eighty-four percent of patients judged by the panel as having resectable CRLM indeed received local treatment. Local surgeons followed the technical plan proposed by the panel in 40% of patients. Conclusion Considerable variability exists among expert liver surgeons in assessing resectability and local treatment planning of initially unresectable CRLM. This stresses the value of panel-based decisions, and the need for consensus guidelines on resectability criteria and technical approach to prevent unwarranted variability in clinical practice.

PurposeReturning patient-reported outcomes to patients might aid patients in detecting symptoms and might facilitate early intervention. This descriptive study evaluates the use of an individual feedback report on patient-reported outcomes for colorectal cancer patients and aims to assess differences in patient, tumor, and treatment characteristics and cohort retention between patients who opt and do not opt for the feedback report.MethodsPatients with colorectal cancer participating in the nationwide Prospective Dutch ColoRectal Cancer Cohort, who filled in questionnaires digitally between June 2018 and January 2019, were included. Participants were given the option to receive a feedback report at baseline, 3, 6, and 12 months. The usefulness, content, and layout of the feedback report were evaluated. Differences in patient, tumor, and treatment characteristics, patient-reported outcomes, and cohort retention at subsequent questionnaires between participants who did and did not opt for feedback were assessed.ResultsA total of 484 participants were included of whom 293 (61%) opted for feedback. The feedback report was considered useful by 92%. No differences in patient, tumor, and treatment characteristics, and patient-reported outcomes were found between participants who did and did not opt for feedback. The response rate was higher among patients who opted for feedback compared to patients who did not opt for feedback at T3 (84 vs 74%), but not at T6 and T12.ConclusionThe feedback report was used by 6 out of 10 patients. The feedback report was considered valuable and associated with a higher subsequent response rate.

Contains fulltext : 292736.pdf (Publisher’s version ) (Open Access) A Trial within Cohorts (TwiCs) study design is a trial design that uses the infrastructure of an observational cohort study to initiate a randomized trial. Upon cohort enrollment, the participants provide consent for being randomized in future studies without being informed. Once a new treatment is available, eligible cohort participants are randomly assigned to the treatment or standard of care. Patients randomized to the treatment arm are offered the new treatment, which they can choose to refuse. Patients who refuse will receive standard of care instead. Patients randomized to the standard of care arm receive no information about the trial and continue receiving standard of care as part of the cohort study. Standard cohort measures are used for outcome comparisons. The TwiCs study design aims to overcome some issues encountered in standard Randomized Controlled Trials (RCTs). An example of an issue in standard RCTs is the slow patient accrual. A TwiCs study aims to improve this by selecting patients using a cohort and only offering the intervention to patients in the intervention arm. In oncology, the TwiCs study design has gained increasing interest during the last decade. Despite its potential advantages over RCTs, the TwiCs study design has several methodological challenges that need careful consideration when planning a TwiCs study. In this article, we focus on these challenges and reflect on them using experiences from TwiCs studies initiated in oncology. Important methodological challenges that are discussed are the timing of randomization, the issue of non-compliance (refusal) after randomization in the intervention arm, and the definition of the intention-to-treat effect in a TwiCs study and how this effect is related to its counterpart in standard RCTs.

Purpose This individual participant data meta-analysis (IPD-MA) assesses exercise effects on self-reported cognitive functioning (CF) and investigates whether effects differ by patient-, intervention-, and exercise-related characteristics. Methods IPD from 16 exercise RCTs, including 1987 patients across multiple types of non-metastatic cancer, was pooled. A one-stage IPD-MA using linear mixed-effect models was performed to assess exercise effects on self-reported CF (z-score) and to identify whether the effect was moderated by sociodemographic, clinical, intervention- and exercise-related characteristics, or fatigue, depression, anxiety, and self-reported CF levels at start of the intervention (i.e., baseline). Models were adjusted for baseline CF and included a random intercept at study level to account for clustering of patients within studies. A sensitivity analysis was performed in patients who reported cognitive problems at baseline. Results Minimal significant beneficial exercise effects on self-reported CF (β=−0.09 [−0.16; −0.02]) were observed, with slightly larger effects when the intervention was delivered post-treatment (n=745, β=−0.13 [−0.24; −0.02]), and no significant effect during cancer treatment (n=1,162, β=−0.08 [−0.18; 0.02]). Larger effects were observed in interventions of 12 weeks or shorter (β=−0.14 [−0.25; −0.04]) or 24 weeks or longer (β=−0.18 [−0.32; −0.02]), whereas no effects were observed in interventions of 12–24 weeks (β=0.01 [−0.13; 0.15]). Exercise interventions were most beneficial when provided to patients without anxiety symptoms (β=−0.10 [−0.19; −0.02]) or after completion of treatment in patients with cognitive problems (β=−0.19 [−0.31; −0.06]). No other significant moderators were identified. Conclusions This cross-cancer IPD meta-analysis observed small beneficial exercise effects on self-reported CF when the intervention was delivered post-treatment, especially in patients who reported cognitive problems at baseline. Implications for Cancer Survivors This study provides some evidence to support the prescription of exercise to improve cognitive functioning. Sufficiently powered trials are warranted to make more definitive recommendations and include these in the exercise guidelines for cancer survivors.

Purpose: The quality of life and survival of patients with advanced gastroesophageal cancer can be improved. Positive effects of exercise and nutritional interventions on quality of life and potential effects on cancer outcomes are found in gastroesophageal cancer in the curative setting, as well as in other cancer types. We therefore systematically reviewed the current literature on the effect of exercise and nutritional interventions on various outcomes in patients with advanced gastroesophageal cancer. Methods: We searched on the 11th of June 2021 in Pubmed, Embase and the Cochrane library for publications of randomized trials and observational studies on exercise and nutritional interventions (either combined or as separate intervention) in patients with advanced gastroesophageal cancer. The outcomes of interest were overall survival, progression free survival, quality of life, chemotherapy toxicity, and chemotherapy adherence. Results: We screened 1,764 records for eligibility and included one study in our analysis. The other 1,763 were excluded for various reasons, most frequently an incorrect study population (e.g. both curable and incurable patients) or an incorrect intervention. One retrospective cohort study of 40 patients with advanced gastric cancer who received first line chemotherapy was included. It was stated that ‘no significant differences in terms of overall and progression free survival were reported between the two groups of patients.’ No absolute numbers were provided. Conclusion: Our systematic review did not identify any high quality studies on exercise and nutritional interventions in advanced gastroesophageal cancer. We deem a randomized clinical trial on this topic to be highly needed.

BACKGROUND: Despite the widely acknowledged benefit of exercise for patients with cancer, little evidence on the optimal timing of exercise on adverse effects of cancer treatment is available. OBJECTIVES: The aim of this study was to determine whether an exercise intervention initiated during chemotherapy is superior to an intervention initiated after chemotherapy for improving long-term cardiorespiratory fitness (peak oxygen uptake [VO 2peak]). METHODS: In this prospective, randomized clinical trial, patients scheduled to receive curative chemotherapy were randomized to a 24-week exercise intervention, initiated either during chemotherapy (group A) or afterward (group B). The primary endpoint was VO 2peak 1 year postintervention. Secondary endpoints were VO 2peak postintervention, muscle strength, health-related quality of life (HRQoL), fatigue, physical activity, and self-efficacy. Between-group differences were calculated using intention-to-treat linear mixed-models analyses. RESULTS: A total of 266 patients with breast (n = 139), testicular (n = 95), and colon cancer (n = 30) as well as lymphoma (n = 2) were included. VO 2peak immediately postintervention and 1 year postintervention did not differ between the 2 groups. Immediately postchemotherapy, patients in group A exhibited significantly lower decreases in VO 2peak (3.1 mL/kg/min; 95% CI: 2.2-4.0 mL/kg/min), HRQoL, and muscle strength and reported less fatigue and more physical activity than those in group B. CONCLUSIONS: Exercise can be safely performed during chemotherapy and prevents fatigue and decreases in VO 2peak, muscle strength, and HRQoL, in addition to hastening the return of function after chemotherapy. Also, if exercise cannot be performed during chemotherapy, a program afterward can enable patients to regain the same level of function, measured 1 year after completion of the intervention. (Optimal Timing of Physical Activity in Cancer Treatment [ACT]; NCT01642680).

Background: Higher levels of physical activity are associated with a lower risk of cardiovascular disease in the general population. Whether the same holds for women who underwent treatment for breast cancer is unclear.Objectives: The aim of this study was to evaluate the association between physical activity in a typical week in the past 12 months and cardiac dysfunction in breast cancer survivors.Methods: We used data from a cohort of breast cancer survivors who were treated at ages 40 to 50 years (N = 559). The association between physical activity and global longitudinal strain (GLS) and left ventricular ejection fraction (LVEF) was evaluated using both linear and modified Poisson regression analyses adjusted for relevant confounders.Results: In total, 559 breast cancer survivors were included, with median age of 55.5 years and a median time since treatment of 10.2 years. GLS was less favorable in inactive survivors (-17.1%) than in moderately inactive (-18.4%), moderately active (-18.2%), and active survivors (-18.5%), with an adjusted significant difference for active versus inactive survivors (β = -1.31; 95% CI: -2.55 to -0.06)). Moderately active (n = 57/130) and active survivors (n = 87/124) had significantly lower risks of abnormal GLS (defined as >-18%) compared with inactive survivors (n = 17/26) (RR: 0.65 [95% CI: 0.45-0.94] and RR: 0.61 [95% CI: 0.43-0.87], respectively). LVEF, in normal ranges in all activity categories, was not associated with physical activity.Conclusions: In long-term breast cancer survivors, higher physical activity levels were associated with improved GLS but not LVEF, with the relatively largest benefit for doing any activity versus none. This finding suggests that increasing physical activity may contribute to cardiovascular health benefits, especially in inactive survivors.

Background: Higher levels of physical activity are associated with a lower risk of cardiovascular disease in the general population. Whether the same holds for women who underwent treatment for breast cancer is unclear. Objectives: The aim of this study was to evaluate the association between physical activity in a typical week in the past 12 months and cardiac dysfunction in breast cancer survivors. Methods: We used data from a cohort of breast cancer survivors who were treated at ages 40 to 50 years (N = 559). The association between physical activity and global longitudinal strain (GLS) and left ventricular ejection fraction (LVEF) was evaluated using both linear and modified Poisson regression analyses adjusted for relevant confounders. Results: In total, 559 breast cancer survivors were included, with median age of 55.5 years and a median time since treatment of 10.2 years. GLS was less favorable in inactive survivors (-17.1%) than in moderately inactive (-18.4%), moderately active (-18.2%), and active survivors (-18.5%), with an adjusted significant difference for active versus inactive survivors (β = -1.31; 95% CI: -2.55 to -0.06)). Moderately active (n = 57/130) and active survivors (n = 87/124) had significantly lower risks of abnormal GLS (defined as >-18%) compared with inactive survivors (n = 17/26) (RR: 0.65 [95% CI: 0.45-0.94] and RR: 0.61 [95% CI: 0.43-0.87], respectively). LVEF, in normal ranges in all activity categories, was not associated with physical activity. Conclusions: In long-term breast cancer survivors, higher physical activity levels were associated with improved GLS but not LVEF, with the relatively largest benefit for doing any activity versus none. This finding suggests that increasing physical activity may contribute to cardiovascular health benefits, especially in inactive survivors.

Supplemental digital content is available in the text., Purpose The randomized controlled OptiTrain trial showed beneficial effects on fatigue after a 16-wk exercise intervention in patients with breast cancer undergoing adjuvant chemotherapy. We hypothesize that exercise alters systemic inflammation and that this partially mediates the beneficial effects of exercise on fatigue. Methods Two hundred and forty women scheduled for chemotherapy were randomized to 16 wk of resistance and high-intensity interval training (RT-HIIT), moderate-intensity aerobic and high-intensity interval training (AT-HIIT), or usual care (UC). In the current mechanistic analyses, we included all participants with >60% attendance and a random selection of controls (RT-HIIT = 30, AT-HIIT = 27, UC = 29). Fatigue (Piper Fatigue Scale) and 92 markers (e.g., interleukin-6 [IL-6] and tumor necrosis factor α [TNF-α]) were assessed at baseline and postintervention. Mediation analyses were conducted to explore whether changes in inflammation markers mediated the effect of exercise on fatigue. Results Overall, chemotherapy led to an increase in inflammation. The increases in IL-6 (pleiotropic cytokine) and CD8a (T-cell surface glycoprotein) were however significantly less pronounced after RT-HIIT compared with UC (−0.47, 95% confidence interval = −0.87 to −0.07, and −0.28, 95% confidence interval = −0.57 to 0.004, respectively). Changes in IL-6 and CD8a significantly mediated the exercise effects on both general and physical fatigue by 32.0% and 27.7%, and 31.2% and 26.4%, respectively. No significant between-group differences in inflammatory markers at 16 wk were found between AT-HIIT and UC. Conclusions This study is the first showing that supervised RT-HIIT partially counteracted the increase in inflammation during chemotherapy, i.e., IL-6 and soluble CD8a, which resulted in lower fatigue levels postintervention. Exercise, including both resistance and high-intensity aerobic training, might be put forward as an effective treatment to reduce chemotherapy-induced inflammation and subsequent fatigue.

Additional file 2: Appendix II. Add-on measurements.

Additional file 1: Appendix I. Organizational aspects of the trial.

Additional file 1.

Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treatments in daily practice. Since 2013, the Prospective Dutch Colorectal Cancer (PLCRC) cohort, linked to the Netherlands Cancer Registry, serves as an infrastructure for scientific research collecting additional patient-reported outcomes (PRO) and biospecimens. Here we report on cohort developments and investigate to what extent PLCRC reflects the “real-world”. Clinical and demographic characteristics of PLCRC participants were compared with the general Dutch CRC population (n = 74,692, Dutch-ref). To study representativeness, standardized differences between PLCRC and Dutch-ref were calculated, and logistic regression models were evaluated on their ability to distinguish cohort participants from the Dutch-ref (AU-ROC 0.5 = preferred, implying participation independent of patient characteristics). Stratified analyses by stage and time-period (2013–2016 and 2017–Aug 2019) were performed to study the evolution towards RWD. In August 2019, 5744 patients were enrolled. Enrollment increased steeply, from 129 participants (1 hospital) in 2013 to 2136 (50 of 75 Dutch hospitals) in 2018. Low AU-ROC (0.65, 95% CI: 0.64–0.65) indicates limited ability to distinguish cohort participants from the Dutch-ref. Characteristics that remained imbalanced in the period 2017–Aug’19 compared with the Dutch-ref were age (65.0 years in PLCRC, 69.3 in the Dutch-ref) and tumor stage (40% stage-III in PLCRC, 30% in the Dutch-ref). PLCRC approaches to represent the Dutch CRC population and will ultimately meet the current demand for high-quality RWD. Efforts are ongoing to improve multidisciplinary recruitment which will further enhance PLCRC’s representativeness and its contribution to a learning healthcare system.

© 2017 Springer Science+Business Media, LLC, part of Springer Nature Purpose: Exercise has been shown to reduce fatigue during cancer treatment. Hypothesized mechanisms include inflammatory pathways. Therefore, we investigated effects of exercise on markers of inflammation in breast cancer patients during adjuvant chemotherapy. Methods: We pooled data from two randomized controlled exercise intervention trials with breast cancer patients during adjuvant chemotherapy (n = 130), which had previously shown beneficial effects of exercise on fatigue. Exercise comprised a 12-week resistance training (BEATE study) or an 18-week combined resistance and aerobic training (PACT study). Serum IL-6, IL-1ra, and the IL-6/IL-1ra ratio were quantified at baseline, mid-intervention, post-intervention, and 6–9 months post-baseline. Results: Mixed effect models showed significant increases in IL-6 and IL-6/IL-1ra ratio during chemotherapy and decreases afterwards. Differences between exercise and control group were not significant at any time point. Changes in total cancer-related fatigue were significantly correlated with changes in IL-6/IL-1ra ratio (partial correlation r = 0.23) and IL-6 (r = 0.21), and changes in physical cancer-related fatigue with changes in IL-6/IL-1ra ratio (r = 0.21). Conclusions: Changes in fatigue were slightly correlated with changes in inflammatory markers, and there was a strong inflammatory response to adjuvant chemotherapy. The supervised exercise training did not counteract this increase in inflammation, suggesting that beneficial effects of exercise on fatigue during adjuvant chemotherapy for breast cancer are not essentially mediated by IL-6, IL-1ra, or the IL-6/IL-1ra ratio.

Background Observational studies suggest that loss of skeletal muscle mass (SMM) is associated with chemotherapy‐related toxicity, poor quality of life, and poor survival in metastatic colorectal cancer (mCRC) patients. Little is known about the evolution of SMM during palliative systemic therapy. We investigated changes in SMM during various consecutive palliative systemic treatment regimens using repeated abdominal computed tomography scans of mCRC patients who participated in the randomized phase 3 CAIRO3 study. Methods In the CAIRO3 study, mCRC patients with stable disease or better after 6 cycles of first‐line treatment with capecitabine + oxaliplatin + bevacizumab (CAPOX‐B) were randomized between maintenance treatment with capecitabine + bevacizumab (CAP‐B) or observation. Upon first disease progression, in both groups, CAPOX‐B or other treatment was reintroduced until the second disease progression, which was the primary study endpoint. We analysed 1355 computed tomography scans of 450 (81%) CAIRO3 patients (64 ± 9.0 years, CAP‐B n = 223; observation n = 227) for SMM at four time points (i.e. prior to the start of pre‐randomization initial treatment, at randomization, and at first and at second disease progression) using the Slice‐o‐matic software and single slice evaluation at the lumbar 3 level. By using accepted and widely used formulas, whole body SMM was calculated. A linear mixed effects model, adjusted for relevant confounders, was used to assess SMM changes for the total group and within and between study arms. Results During 6 cycles of initial treatment with CAPOX‐B prior to randomization, SMM decreased significantly in all patients [CAP‐B arm: −0.53 kg (95% CI −1.12; −0.07) and observation arm: −0.85 kg (−1.45; −0.25)]. After randomization, SMM recovered during CAP‐B treatment by 1.32 kg (0.73; 1.90) and observation by 1.20 kg (0.63; 1.78) (median time from randomization to first disease progression 8.6 and 4.1 months for CAP‐B arm and observation arm, respectively). After first progression and during reintroduction treatment with CAPOX‐B or other treatment, SMM again decreased significantly and comparable in both arms, CAP‐B: −2.71 kg (−3.37; −2.03), and observation: −2.01 kg (−2.64; −1.41) (median time from first progression until second progression CAP‐B arm: 4.7 months and observation arm: 6.6 months). Conclusions This longitudinal study provides a unique insight in SMM changes in mCRC patients during palliative systemic treatment regimens, including observation. Our data show that muscle loss is reversible and may be influenced by the intensity of systemic regimens. Although studies have shown prognostic capacity for SMM, the effects of subsequent changes in SMM are unknown and may be clues for new future therapeutic interventions.

Background: The higher risk of death resulting from excess adiposity may be attenuated by physical activity (PA). However, the theoretical number of deaths reduced by eliminating physical inactivity compared with overall and abdominal obesity remains unclear. Objective: We examined whether overall and abdominal adiposity modified the association between PA and all-cause mortality and estimated the population attributable fraction (PAF) and the years of life gained for these exposures. Design: This was a cohort study in 334,161 European men and women. The mean follow-up time was 12.4 y, corresponding to 4,154,915 person-years. Height, weight, and waist circumference (WC) were measured in the clinic. PA was assessed with a validated self-report instrument. The combined associations between PA, BMI, and WC with mortality were examined with Cox proportional hazards models, stratified by center and age group, and adjusted for sex, education, smoking, and alcohol intake. Center-specific PAF associated with inactivity, body mass index (BMI; in kg/m2) (>30), and WC (≥102 cm for men, ≥88 cm for women) were calculated and combined in random-effects meta-analysis. Life-tables analyses were used to estimate gains in life expectancy for the exposures. Results: Significant interactions (PA × BMI and PA × WC) were observed, so HRs were estimated within BMI and WC strata. The hazards of all-cause mortality were reduced by 16–30% in moderately inactive individuals compared with those categorized as inactive in different strata of BMI and WC. Avoiding all inactivity would theoretically reduce all-cause mortality by 7.35% (95% CI: 5.88%, 8.83%). Corresponding estimates for avoiding obesity (BMI >30) were 3.66% (95% CI: 2.30%, 5.01%). The estimates for avoiding high WC were similar to those for physical inactivity. Conclusion: The greatest reductions in mortality risk were observed between the 2 lowest activity groups across levels of general and abdominal adiposity, which suggests that efforts to encourage even small increases in activity in inactive individuals may be beneficial to public health.

The cohort multiple randomized controlled trial (cmRCT) design in exercise-oncology: First experiences

BACKGROUND: The higher risk of death resulting from excess adiposity may be attenuated by physical activity (PA). However, the theoretical number of deaths reduced by eliminating physical inactivity compared with overall and abdominal obesity remains unclear.OBJECTIVE: We examined whether overall and abdominal adiposity modified the association between PA and all-cause mortality and estimated the population attributable fraction (PAF) and the years of life gained for these exposures.DESIGN: This was a cohort study in 334,161 European men and women. The mean follow-up time was 12.4 y, corresponding to 4,154,915 person-years. Height, weight, and waist circumference (WC) were measured in the clinic. PA was assessed with a validated self-report instrument. The combined associations between PA, BMI, and WC with mortality were examined with Cox proportional hazards models, stratified by center and age group, and adjusted for sex, education, smoking, and alcohol intake. Center-specific PAF associated with inactivity, body mass index (BMI; in kg/m(2)) (>30), and WC (≥102 cm for men, ≥88 cm for women) were calculated and combined in random-effects meta-analysis. Life-tables analyses were used to estimate gains in life expectancy for the exposures.RESULTS: Significant interactions (PA × BMI and PA × WC) were observed, so HRs were estimated within BMI and WC strata. The hazards of all-cause mortality were reduced by 16-30% in moderately inactive individuals compared with those categorized as inactive in different strata of BMI and WC. Avoiding all inactivity would theoretically reduce all-cause mortality by 7.35% (95% CI: 5.88%, 8.83%). Corresponding estimates for avoiding obesity (BMI >30) were 3.66% (95% CI: 2.30%, 5.01%). The estimates for avoiding high WC were similar to those for physical inactivity.CONCLUSION: The greatest reductions in mortality risk were observed between the 2 lowest activity groups across levels of general and abdominal adiposity, which suggests that efforts to encourage even small increases in activity in inactive individuals may be beneficial to public health.

Background: Disability-adjusted life-years (DALYs) are an indicator of mortality, morbidity, and disability. We calculated DALYs for cancer in middle-aged and older adults participating in the Consortium on Health and Ageing Network of Cohorts in Europe and the United States (CHANCES) consortium. Methods: A total of 90 199 participants from five European cohorts with 10 455 incident cancers and 4399 deaths were included in this study. DALYs were calculated as the sum of the years of life lost because of premature mortality (YLLs) and the years lost because of disability (YLDs). Population-attributable fractions (PAFs) were also estimated for five cancer risk factors, ie, smoking, adiposity, physical inactivity, alcohol intake, and type II diabetes. Results: After a median follow-up of 12 years, the total number of DALYs lost from cancer was 34 474 (382 per 1000 individuals) with a similar distribution by sex. Lung cancer was responsible for the largest number of lost DALYs (22.9%), followed by colorectal (15.3%), prostate (10.2%), and breast cancer (8.7%). Mortality (81.6% of DALYs) predominated over disability. Ever cigarette smoking was the risk factor responsible for the greatest total cancer burden (24.0%, 95% confidence interval [CI] = 22.2% to 26.0%), followed by physical inactivity (4.9%, 95% CI = 0.8% to 8.1%) and adiposity (1.8%, 95% CI = 0.2% to 2.8%). Conclusions: DALYs lost from cancer were substantial in this large European sample of middle-aged and older adults. Even if the burden of disease because of cancer is predominantly caused by mortality, some cancers have sizeable consequences for disability. Smoking remained the predominant risk factor for total cancer burden.

General obesity, as reflected by BMI, is an established risk factor for esophageal adenocarcinoma (EAC), a suspected risk factor for gastric cardia adenocarcinoma (GCC) and appears unrelated to gastric non-cardia adenocarcinoma (GNCC). How abdominal obesity, as commonly measured by waist circumference (WC), relates to these cancers remains largely unexplored. Using measured anthropometric data from 391,456 individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC) study and 11 years of follow-up, we comprehensively assessed the association of anthropometric measures with risk of EAC, GCC and GNCC using multivariable proportional hazards regression. One hundred twenty-four incident EAC, 193 GCC and 224 GNCC were accrued. After mutual adjustment, BMI was unrelated to EAC, while WC showed a strong positive association (highest vs. lowest quintile HR=1.19; 95% CI, 0.63-2.22 and HR=3.76; 1.72-8.22, respectively). Hip circumference (HC) was inversely related to EAC after controlling for WC, while WC remained positively associated (HR=0.35; 0.18-0.68, and HR=4.10; 1.94-8.63, respectively). BMI was not associated with GCC or GNCC. WC was related to higher risks of GCC after adjustment for BMI and more strongly after adjustment for HC (highest vs. lowest quintile HR=1.91; 1.09-3.37, and HR=2.23; 1.28-3.90, respectively). Our study demonstrates that abdominal, rather than general, obesity is an indisputable risk factor for EAC and also provides evidence for a protective effect of gluteofemoral (subcutaneous) adipose tissue in EAC. Our study further shows that general obesity is not a risk factor for GCC and GNCC, while the role of abdominal obesity in GCC needs further investigation. What’s new? While mainly general obesity, as measured by body mass index, has been investigated in relation to gastric and esophageal cancer, the effect of a large waist on these cancer sites is unknown. In this article, the authors report results of extensive analysis of measured anthropometry, including measures of general (BMI) and abdominal obesity (waist circumference), collected by the European Prospective Investigation into Cancer and Nutrition (EPIC). They show that general obesity is not a risk factor for esophageal and gastric cancer, while waist circumference strongly increases risk of esophageal cancer and may potentially be related to gastric cardia cancer.

Background: Neopterin may be relevant for colorectal cancer (CRC) development, as a biomarker of cellular immune activity exerting pleiotropic effects on cellular ageing, oxidative stress, and inflammation. So far, the association between prediagnostic neopterin and colon and rectal cancer risk has not been evaluated in human populations. Methods: A nested case-control study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort using data on plasma concentrations of total neopterin (T-N, sum of neopterin and 7,8-dihydroneopterin) in 830 incident CRC case patients (561 colon and 269 rectal) matched within risk sets to 830 control participants. A subsequent replication study used data from the Hordaland Health Study, where 173 CRC case patients have been diagnosed among 6594 healthy participants over 12 years of follow-up. Results: After multivariable adjustment for a priori chosen CRC risk factors, a “U-shaped” association of T-N with CRC was revealed. Compared with the second quintile of the T-N distribution, the relative risks for the first, third, fourth, and fifth quintiles were 2.37 (95% CI = 1.66 to 3.39), 1.24 (95% CI = 0.87 to 1.77), 1.55 (95% CI = 1.08 to 2.22), and 2.31 (95% CI = 1.63 to 3.27), respectively. Replication of these associations within the Hordaland Health Study yielded similar results. No differences have been observed when the associations were explored by colon and rectal cancer site (two-sided P-difference = .87) and after excluding case patients diagnosed within the first four follow-up years. Conclusions: These novel findings provide evidence of the role of both suppressed and activated cell-mediated immunity as reflected by prediagnostic T-N concentrations in the development of CRC.

Objective: To quantify the independent associations between objectively measured physical activity (PA), cardiorespiratory fitness (CRF), and anthropometry in European men and women. Methods: 2,056 volunteers from 12 centers across Europe were fitted with a heart rate and movement sensor at 2 visits 4 months apart for a total of 8 days. CRF (ml/kg/min) was estimated from an 8 minute ramped step test. A cross-sectional analysis of the independent associations between objectively measured PA (m/s(2)/d), moderate and vigorous physical activity (MVPA) (% time/d), sedentary time (% time/d), CRF, and anthropometry using sex stratified multiple linear regression was performed. Results: In mutually adjusted models, CRF, PA, and MVPA were inversely associated with all anthropometric markers in women. In men, CRF, PA, and MVPA were inversely associated with BMI, whereas only CRF was significantly associated with the other anthropometric markers. Sedentary time was positively associated with all anthropometric markers, however, after adjustment for CRF significant in women only. Conclusion: CRF, PA, MVPA, and sedentary time are differently associated with anthropometric markers in men and women. CRF appears to attenuate associations between PA, MVPA, and sedentary time. These observations may have implications for prevention of obesity.

Long-term weight gain (i.e., weight gain since age 20) has been related to higher risk of postmenopausal breast cancer, but a lower risk of premenopausal breast cancer. The effect of weight change in middle adulthood is unclear. We investigated the association between weight change in middle adulthood (i.e., women aged 40-50 years) and the risk of breast cancer before and after the age of 50. We included female participants of the European Prospective Investigation into Cancer and Nutrition cohort, with information on anthropometric measures at recruitment and after a median follow-up of 4.3 years. Annual weight change was categorized using quintiles taking quintile 2 and 3 as the reference category (-0.44 to 0.36 kg/year). Multivariable Cox proportional hazards regression analysis was used to examine the association. 205,723 women were included and 4,663 incident breast cancer cases were diagnosed during a median follow-up of 7.5 years (from second weight assessment onward). High weight gain (Q5: 0.83-4.98 kg/year) was related to a slightly, but significantly higher breast cancer risk (HRQ5_versus_Q2/3: 1.09, 95% CI: 1.01-1.18). The association was more pronounced for breast cancer diagnosed before or at age 50 (HRQ5_versus_Q2/3: 1.37, 95% CI: 1.02-1.85). Weight loss was not associated with breast cancer risk. There was no evidence for heterogeneity by hormone receptor status. In conclusion, high weight gain in middle adulthood increases the risk of breast cancer. The association seems to be more pronounced for breast cancer diagnosed before or at age 50. Our results illustrate the importance of avoiding weight gain in middle adulthood.

Adiposity is a risk factor for colon cancer, but underlying mechanisms are not well understood. We evaluated the extent to which 11 biomarkers with inflammatory and metabolic actions mediate the association of adiposity measures, waist circumference (WC) and body mass index (BMI), with colon cancer in men and women. We analyzed data from a prospective nested case-control study among 662 incident colon cancer cases matched within risk sets to 662 controls. Relative risks (RRs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression. The percent effect change and corresponding CIs were estimated after adjusting for biomarkers shown to be associated with colon cancer risk. After multivariable adjustment, WC was associated with colon cancer risk in men (top vs. bottom tertile RR 1.68, 95% CI 1.06-2.65; p(trend)=0.02) and in women (RR 1.67, 95% CI 1.09-2.56; p(trend)=0.03). BMI was associated with risk only in men. The association of WC with colon cancer was accounted mostly for by three biomarkers, high-density lipoprotein cholesterol, non-high-molecular-weight adiponectin and soluble leptin receptor, which in combination explained 46% (95% CI 37-57%) of the association in men and 50% (95% CI 40-65%) of the association in women. Similar results were observed for the associations with BMI in men. These data suggest that alterations in levels of these metabolic biomarkers may represent a primary mechanism of action in the relation of adiposity with colon cancer. Further studies are warranted to determine whether altering their concentrations may reduce colon cancer risk. What’s new? Adiposity is a well-established risk factor for colon cancer. However, the mechanisms that underlie this relationship still aren’t well understood. In this study, the authors evaluated a panel of inflammatory and metabolic biomarkers for their impact on colon-cancer risk. They found that serum levels of high-density lipoprotein cholesterol, non-high-molecular-weight adiponectin, and soluble leptin receptor had the greatest impact on the association between adiposity and colon cancer. These biomarkers may thus lead to promising strategies for the targeted prevention of colon cancer.

Background: A moderate association exists between body mass index (BMI) and colorectal cancer. Less is known about the effect of weight change. Objective: We investigated the relation between BMI and weight change and subsequent colon and rectal cancer risk. Design: This was studied among 328,781 participants in the prospective European Prospective Investigation into Cancer Physical Activity, Nutrition, Alcohol, Cessation of Smoking, Eating study (mean age: 50 y). Body weight was assessed at recruitment and on average 5 y later. Self-reported weight change (kg/y) was categorized in sex-specific quintiles, with quintiles 2 and 3 combined as the reference category (men: -0.6 to 0.3 kg/y; women: -0.4 to 0.4 kg/y). In the subsequent years, participants were followed for the occurrence of colon and rectal cancer (median period: 6.8 y). Multivariable Cox proportional hazards regression analyses were used to study the association. Results: A total of 1261 incident colon cancer and 747 rectal cancer cases were identified. ME at recruitment was statistically significantly associated with colon cancer risk in men (HR: 1.04; 95% CI: 1.02, 1.07). Moderate weight gain (quintile 4) in men increased risk further (HR: 1.32; 95% CI: 1.04, 1.68), but this relation did not show a clear trend. In women, BMI or weight gain was not related to subsequent risk of colon cancer. No statistically significant associations for weight loss and colon cancer or for BMI and weight changes and rectal cancer were found. Conclusions: BMI attained at adulthood was associated with colon cancer risk. Subsequent weight gain or loss was not related to colon or rectal cancer risk in men or women.

Aim: Weight change during adult life may reflect metabolic changes and influence colorectal cancer (CRC) development, but such role is not well established. We aimed to explore the association between adult weight change (from age 20 to 50) and CRC risk. In particular, we investigated differences according to colon and rectal cancer, sex and measures of attained adiposity. Methods: We included 201,696 participants from six participating countries in the European Prospective Investigation into Cancer and Nutrition (1992-2010). During a mean follow-up of 11.2 years 2384 (1194 in men and 1190 in women) incident CRC cases occurred. Cox proportional hazard models adjusted for body mass index at age 20 and lifestyle factors at study recruitment were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: After multivariable adjustment, each kg of weight gained annually from age 20 to 50 was associated with a 60% higher risk of colon cancer (95% CI 1.20-2.09), but not rectal cancer (HR 1.13, 95% CI 0.79-1.62, P-interaction = 0.04). The higher risk of colon cancer was restricted to people with high attained waist circumference at age 50 (HR 1.82, 95% CI 1.14-2.91, P-interaction = 0.02). Results were not different in men and women (P-interaction = 0.81). Conclusion(s): Adult weight gain, as reflected by attained abdominal obesity at age 50, increases colon cancer risk in both men and women. These data underline the importance of weight management and metabolic health maintenance in early adult life years for colon cancer prevention. (C) 2013 Elsevier Ltd. All rights reserved.

Background: The effect of the macronutrient composition of the usual diet on long term weight maintenance remains controversial. Methods: 373,803 subjects aged 25-70 years were recruited in 10 European countries (1992-2000) in the PANACEA project of the EPIC cohort. Diet was assessed at baseline using country-specific validated questionnaires and weight and height were measured at baseline and self-reported at follow-up in most centers. The association between weight change after 5 years of follow-up and the iso-energetic replacement of 5% of energy from one macronutrient by 5% of energy from another macronutrient was assessed using multivariate linear mixed-models. The risk of becoming overweight or obese after 5 years was investigated using multivariate Poisson regressions stratified according to initial Body Mass Index. Results: A higher proportion of energy from fat at the expense of carbohydrates was not significantly associated with weight change after 5 years. However, a higher proportion of energy from protein at the expense of fat was positively associated with weight gain. A higher proportion of energy from protein at the expense of carbohydrates was also positively associated with weight gain, especially when carbohydrates were rich in fibre. The association between percentage of energy from protein and weight change was slightly stronger in overweight participants, former smokers, participants >= 60 years old, participants underreporting their energy intake and participants with a prudent dietary pattern. Compared to diets with no more than 14% of energy from protein, diets with more than 22% of energy from protein were associated with a 23-24% higher risk of becoming overweight or obese in normal weight and overweight subjects at baseline. Conclusion: Our results show that participants consuming an amount of protein above the protein intake recommended by the American Diabetes Association may experience a higher risk of becoming overweight or obese during adult life.

We prospectively investigated dietary flavonoid intake and esophageal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. The study included 477,312 adult subjects from 10 European countries. At baseline, country-specific validated dietary questionnaires were used. During a mean follow-up of 11 years (1992-2010), there were 341 incident esophageal cancer cases, of which 142 were esophageal adenocarcinoma (EAC), 176 were esophageal squamous cell carcinoma (ESCC), and 23 were other types of esophageal cancer. In crude models, a doubling in total dietary flavonoid intake was inversely associated with esophageal cancer risk (hazard ratio (HR) (log(2))=0.87, 95% confidence interval (CI): 0.78, 0.98) but not in multi-variable models (HR (log(2))=0.97, 95% CI: 0.86, 1.10). After covariate adjustment, no statistically significant association was found between any flavonoid subclass and esophageal cancer, EAC, or ESCC. However, among current smokers, flavonols were statistically significantly associated with a reduced esophageal cancer risk (HR (log(2)) = 0.72, 95% CI: 0.56, 0.94), whereas total flavonoids, flavanols, and flavan-3-ol monomers tended to be inversely associated with esophageal cancer risk. No associations were found in either never or former smokers. These findings suggest that dietary flavonoid intake was not associated with overall esophageal cancer, EAC, or ESCC risk, although total flavonoids and some flavonoid subclasses, particularly flavonols, may reduce the esophageal cancer risk among current smokers.

Background: Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. Methods: We used lifestyle and nutritional data from 53 degrees 758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining >= 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). Results: Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model’s discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of >= 200 points were 9% and 96%, respectively. Conclusion: The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

Background: Fruit and vegetable consumption might prevent weight gain through their low energy density and high dietary fiber content. Objective: We assessed the association between the baseline consumption of fruit and vegetables and weight change in participants from 10 European countries participating in the European Prospective Investigation into Cancer and Nutrition study. Design: Diet was assessed at baseline in 373,803 participants by using country-specific validated questionnaires. Weight was measured at baseline and self-reported at follow-up in most centers. Associations between baseline fruit and vegetable intakes (per 100 g/d) and weight change (g/y) after a mean follow-up of 5 y were assessed by using linear mixed-models, with age, sex, total energy intake, and other potential confounders controlled for. Results: After exclusion of subjects with chronic diseases at baseline and subjects who were likely to misreport energy intakes, baseline fruit and vegetable intakes were not associated with weight change overall. However, baseline fruit and vegetable intakes were inversely associated with weight change in men and women who quit smoking during follow-up. We observed weak positive associations between vegetable intake and weight change in women who were overweight, were former smokers, or had high prudent dietary pattern scores and weak inverse associations between fruit intake and weight change in women who were >50 y of age, were of normal weight, were never smokers, or had low prudent dietary pattern scores. Conclusions: In this large study, higher baseline fruit and vegetable intakes, while maintaining total energy intakes constant, did not substantially influence midterm weight change overall but could help to reduce risk of weight gain in persons who stop smoking. The interactions observed in women deserve additional attention. Am J Clin Nutr 2012;95:184-93.

Purpose. We assessed the association between smoking cessation and prospective weight change in the European population of the European Prospective Investigation into Cancer and Nutrition-Physical Activity, Nutrition, Alcohol, Cessation of smoking. Eating out of home And obesity (EPIC-PANACEA) project. Methods. The study involved more than 300,000 healthy volunteers, recruited between 1992 and 2000 in 9 European countries, who provided data on anthropometry and smoking habits at baseline and after a follow-up of 5 years on average. Adjusted mixed-effects linear regression models were used to obtain sex-specific summary estimates of the association between the change in smoking status and the annual change in weight. Results. Smoking cessation tends to be followed by weight gain; when compared to stable smokers, annual weight gain was higher in men (0.44 kg (95%CI: 0.36; 0.52)) and women (0.46 kg (95%CI: 0.41; 0.52)) who stopped smoking during follow-up. When smokers who stopped smoking at least 1 year before recruitment were compared to never smokers, no major differences in annual weight gain were observed. The excess weight gain following smoking cessation appears to mainly occur in the first years following the cessation. Conclusions. When considering the benefits of smoking cessation, such findings strengthen the need for promoting cessation offering information on weight gain control and support to weight-concerned smokers in order to remove a barrier to quitting. (C) 2011 Elsevier Inc. All rights reserved.

Background: The evidence that individual dietary and lifestyle factors influence a person’s weight and waist circumference is well established; however their combined impact is less well documented. Therefore, we investigated the combined effect of physical activity, nutrition and smoking status on prospective gain in body weight and waist circumference. Methods: We used data of the prospective EPIC-PANACEA study. Between 1992 and 2000, 325,537 participants (94,445 men and 231,092 women, aged between 25-70) were recruited from nine European countries. Participants were categorised into two groups (positive or negative health behaviours) for each of the following being physically active, adherent to a healthy (Mediterranean not including alcohol) diet, and never-smoking for a total score ranging from zero to three. Anthropometric measures were taken at baseline and were mainly self-reported after a medium follow-up time of 5 years. Results: Mixed-effects linear regression models adjusted for age, educational level, alcohol consumption, baseline body mass index and follow-up time showed that men and women who reported to be physically active, never-smoking and adherent to the Mediterranean diet gained over a 5-year period 537 (95% CI -706, -368) and 200 (-478, -87) gram less weight and 0.95 (-1.27, -0.639) and 0.99 (-1.29, -0.69) cm less waist circumference, respectively, compared to participants with zero healthy behaviours. Conclusion: The combination of positive health behaviours was associated with significantly lower weight and waist circumference gain.

Background: In 2007 the World Cancer Research Fund (WCRF) and the American Institute of Cancer Research (AICR) issued 8 recommendations (plus 2 special recommendations) on diet, physical activity, and weight management for cancer prevention on the basis of the most comprehensive collection of available evidence. Objective: We aimed to investigate whether concordance with the WCRF/AICR recommendations was related to cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Design: The present study included 386,355 EPIC participants from 9 European countries. At recruitment, dietary, anthropometric, and lifestyle information was collected. A score was constructed based on the WCRF/AICR recommendations on weight management, physical activity, foods and drinks that promote weight gain, plant foods, animal foods, alcoholic drinks, and breastfeeding for women; the score range was 0-6 for men and 0-7 for women. Higher scores indicated greater concordance with WCRF/AICR recommendations. The association between the score and cancer risk was estimated by using multivariable Cox regression models. Results: Concordance with the score was significantly associated with decreased risk of cancer. A 1-point increment in the score was associated with a risk reduction of 5% (95% Cl: 3%, 7%) for total cancer, 12% (95% CI: 9%, 16%) for colorectal cancer, and 16% (95% CI: 9%, 22%) for stomach cancer. Significant associations were also observed for cancers of the breast, endometrium, lung, kidney, upper aerodigestive tract, liver, and esophagus but not for prostate, ovarian, pancreatic, and bladder cancers. Conclusion: Adherence to the WCRF/AICR recommendations for cancer prevention may lower the risk of developing most types of cancer. Am J Clin Nutr 2012;96:150-63.

Objective: We investigated the association between the proportion of long-chain n-3 polyunsaturated fatty acids (PUFA) in plasma phospholipids from blood samples drawn at enrollment and subsequent change in body weight. Sex, age, and BMI were considered as potential effect modifiers. Method: A total of 1,998 women and men participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) were followed for a median of 4.9 years. The associations between the proportion of plasma phospholipid long-chain n-3 PUFA and change in weight were investigated using mixed-effect linear regression. Results: The proportion of long-chain n-3 PUFA was not associated with change in weight. Among all participants, the 1-year weight change was -0.7 g per 1% point higher long-chain n-3 PUFA level (95% confidence interval: -20.7 to 19.3). The results when stratified by sex, age, or BMI groups were not systematically different. Conclusion: The results of this study suggest that the proportion of long-chain n-3 PUFA in plasma phospholipids is not associated with subsequent change in body weight within the range of exposure in the general population.

Body fatness has been associated with increased risk of a number of hormone-dependent cancers. Recent studies suggest that body mass index (BMI) may be related to meningiomas, which are more common in women than men, and for which estrogens are believed to play a role. Using data from a large European propective cohort, 203 incident cases of meningioma and 340 cases of glioma were included in the analysis for measures of body fat, height, and physical activity among 380,775 participants. All analyses were conducted using Cox proportional hazards model and controlling for age, sex, country, and education. A 71% increase in risk of meningioma was observed among men and women in the top quartile of waist circumference (HR = 1.71, 95% CI = 1.08-2.73, P-trend = 0.01). A positive association was also observed for BMI and meningioma (HR = 1.48, 95% CI = 0.98-2.23, for BMI >= 30 compared with a BMI of 20-24.9, P-trend = 0.05). An association with height and meningioma was also suggestive (HR = 1.24, 95% 0.96-1.51, for each 10 cm increase). In contrast, no associations were observed for height and different measures of body fat and risk of glioma. Physical activity was not related to either type of brain tumors. Results from this study support an increase in risk of meningioma with higher body fatness among both men and women. No association was observed between anthropometric measures and risk of glioma. Cancer Prev Res; 4(9); 1385-92. (C) 2011 AACR.

Background: To examine the association of education with body mass index (BMI) and waist circumference (WC) in the European Prospective Investigation into Cancer and Nutrition (EPIC). Method: This study included 141,230 male and 336,637 female EPIC-participants, who were recruited between 1992 and 2000. Education, which was assessed by questionnaire, was classified into four categories; BMI and WC, measured by trained personnel in most participating centers, were modeled as continuous dependent variables. Associations were estimated using multilevel mixed effects linear regression models. Results: Compared with the lowest education level, BMI and WC were significantly lower for all three higher education categories, which was consistent for all countries. Women with university degree had a 2.1 kg/m(2) lower BMI compared with women with lowest education level. For men, a statistically significant, but less pronounced difference was observed (1.3 kg/m(2)). The association between WC and education level was also of greater magnitude for women: compared with the lowest education level, average WC of women was lower by 5.2 cm for women in the highest category. For men the difference was 2.9 cm. Conclusion: In this European cohort, there is an inverse association between higher BMI as well as higher WC and lower education level. Public Health Programs that aim to reduce overweight and obesity should primarily focus on the lower educated population.

Background: Lymphoid neoplasms are a heterogeneous group of cancers that originate in the lymphatic cells of the immune system. Several risk factors have been identified or suggested, but they all account for only a small proportion of the lymphoid neoplasm incidence. It has been hypothesised that regular exercise may modulate the immune system and thereby reduce the risk of developing the disease. Design and methods: The European Investigation into Cancer and Nutrition (EPIC) cohort consists of 521,457 adults, recruited by 23 centres in 10 European countries. The analytical cohort included 343,756 participants, with 778 non-Hodgkin lymphoma (NHL) cases (376 men and 402 women) and 690 B-cell non-Hodgkin lymphoma (B-NHL) cases (326 men and 364 women). Multivariate Cox regression models were used to calculate hazard ratios (HR) for the association between total, recreational, occupational, and household physical activity and NHL and B-NHL risk, as well as the risk for several B-NHL subtypes. Models were stratified by study centre and age at recruitment and adjusted for various potential confounding factors. Results: We found no evidence of any effect of total physical activity on NHL (adjusted p-trend = 0.76 and 0.30 for men and women, respectively) and B-NHL risk (adjusted p-trend = 0.99 and 0.21 for men and women, respectively) for either men or women. Also no robust results were found for B-NHL subtype analyses among men or women. Conclusions: This study provided no consistent evidence for an association between various physical activity measures and the risk of lymphoid neoplasms or any of the B-NHL subtypes. (C) 2010 Elsevier Ltd. All rights reserved.

We examined the associations of measured anthropometric factors, including general and central adiposity and height, with ovarian cancer risk. We also investigated these associations by menopausal status and for specific histological subtypes. Among 226,798 women in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, there were 611 incident cases of primary, malignant, epithelial ovarian cancer diagnosed during a mean 8.9 years of follow-up. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (as), adjusted for potential confounders. Compared to women with body mass index (BMI) < 25 kg/m(2), obesity (BMI >= 30 kg/m(2)) was associated with excess ovarian cancer risk for all women combined (HR = 1.33, 95% Cl = 1.05-1.68; p(trend) = 0.02) and postmenopausal women (HR = 1.59, 95% Cl = 1.20-2.10; p(trend) = 0.001), but the association was weaker for premenopausal women (HR = 1.16, 95% Cl = 0.65-2.06; p(trend) = 0.65). Neither height or weight gain, nor BMI-adjusted measures of fat distribution assessed by waist circumference, waist-hip ratio (WHR) or hip circumference were associated with overall risk. WHR was related to increased risk of mucinous tumors (BMI-adjusted HR per 0.05 unit increment = 1.17, 95% Cl = 1.00-1.38). For all women combined, no other significant associations with risk were observed for specific histological subtypes. This large, prospective study provides evidence that obesity is an important modifiable risk factor for epithelial ovarian cancer, particularly among postmenopausal women.

Lymphomas belong to the few cancer sites with increasing incidence over past decades, and only a few risk factors have been established. We explored the association between education and the incidence of lymphoma in the prospective EPIC study. Within 3,567,410 person-years of follow-up, 1,319 lymphoma cases [1,253 non-Hodgkin lymphomas (NHL) and 66 Hodgkin lymphomas (HL)] were identified. Cox proportional hazard regression was used to examine the association between highest educational level (primary school or less, technical/professional school, secondary school, university) and lymphoma risk. Overall, no consistent associations between educational level and lymphoma risk were observed; however, associations were found for sub-groups of the cohort. We observed a higher risk of B-NHL (HR = 1.31, 95% CI = 1.02-1.68; n = 583) in women with the highest education level (university) but not in men. Concerning sub-classes of B-NHL, a positive association between education and risk of B cell chronic lymphatic leukaemia (BCLL) was observed only in women. In both genders, the risk of diffuse large B cell lymphoma (DLBCL) was significantly lower for subjects with university degree (HR = 0.46, 95% CI = 0.27-0.79) versus lowest educational level. No association was found for HL. We could not confirm an overall consistent association of education and risk of HL or NHL in this large prospective study; although, education was positively related to the incidence of BCLL and B-NHL (in women) but inversely to incidence of DLBCL. Due to limited number of cases in sub-classes and the large number of comparisons, the possibility of chance findings can not be excluded.

Background: Increasing evidence suggests that general obesity [measured by body mass index (BMI)] is positively associated with risk of esophageal adenocarcinoma (EAC). In contrast, previous studies have shown inverse relations with esophageal squamous cell carcinoma (ESCC). However, it is still unclear whether body fat distribution, particularly abdominal obesity, is associated with each type of esophageal cancer. Methods: We applied multivariable adjusted Cox proportional hazards regression to investigate the association between anthropometric measures and risk of EAC and ESCC among 346,554 men and women participating in the European Prospective Investigation into Cancer and Nutrition. All statistical tests were two sided. Results: During 8.9 years of follow-up, we documented 88 incident cases of EAC and 110 cases of ESCC. BMI, waist circumference, and waist-to-hip ratio (WHR) were positively associated with EAC risk [highest versus lowest quintile; relative risk (RR), 2.60; 95% confidence interval (95% CI), 1.23-5.51; P-trend < 0.01; RR, 3.07; 95% CI, 1.35-6.98; P-trend < 0.003; and RR, 2.12; 95% CI, 0.98-4.57; P-trend < 0.004]. In contrast, BMI and waist circumference were inversely related to ESCC risk, whereas WHR showed no association with ESCC. In stratified analyses, BMI and waist circumference were significantly inversely related to ESCC only among smokers but not among nonsmokers. However, when controlled for BMI, we found positive associations for waist circumference and WHR with ESCC, and these associations were observed among smokers and nonsmokers. Conclusion: General and abdominal obesity were associated with higher EAC risk. Further, our study suggests that particularly an abdominal body fat distribution might also be a risk factor for ESCC. (Cancer Epidemiol Biomarkers Prev 2009;18(7):2079-89)

Objective. The present study investigates the cross-sectional relationship between tobacco smoking and body fatness. Methods. This cross-sectional study consisted of 469,543 men and women who participated in the European Prospective Investigation into Cancer and Nutrition (EPIC) study between 1992 and 2000 providing anthropometric measurements and information on smoking. Adjusted multilevel mixed-effects linear regression models were used to assess the association between smoking and body fat mass. Results. The analyses showed that BMI and WC were positively associated with smoking intensity in current smokers but negatively associated with time since quitting in former smokers. When compared to never smokers, average current smokers (17 and 13 cig/day for men and women, respectively) showed a lower BMI. When average former smokers (men and women who had stopped smoking for 16 and 15 years, respectively) were compared to never smokers, higher BMI and WC were observed in men, whereas no significant associations were observed in women. Conclusions. This cross-sectional study suggests that smoking may be associated with body fatness and fat distribution. Although our findings cannot establish cause and effect, they suggest that providing information and support to those who want to stop may help in preventing weight gain and therefore weaken a barrier against stopping smoking. (C) 2009 Elsevier Inc. All rights reserved.

To evaluate the association between lifestyle and dietary factors and serum concentrations of androgens in middle-aged healthy men. We conducted a cross-sectional analysis of the association of lifestyle factors with circulating concentrations of androstenedione (A-dione), 3-alpha-androstanediol glucuronide (A-diol-g), testosterone (T), SHBG (sex hormone-binding globulin), and free testosterone (FT) among 636 men in the European Prospective Investigation into Cancer and Nutrition. Compared with the youngest age group (40-49 years), the oldest (70-79 years) had a higher mean concentration of SHBG (by 44%) and lower mean concentrations of A-diol-g (by 29%) FT (19%). Men in the highest BMI group (a parts per thousand yen29.83 kg/m(2)) had a higher mean A-diol-g concentration (by 38%) and lower mean concentration of T (by 20%) SHBG (29%) compared with the lowest (< 24.16 kg/m(2)). Current smokers had higher mean concentrations of T (by 13%), SHBG (14%), and A-dione (15%) compared with never smokers. Physical activity and dietary factors were not associated with androgen concentrations, although men in the highest fifth of alcohol intake had higher mean concentrations of A-dione (by 9%), FT (11%) compared with the lowest. Our results suggest that age, body weight, smoking, and alcohol intake are associated with circulating androgen concentrations in men.

Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI < 18.5 kg/m2) or obese (BMI ≥ 30 kg/m2) categories, while the highest quartile of ABSI separated 18-39% of the individuals within each BMI category, which had 22-55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.

Physical activity has been associated with lower risks of breast and colorectal cancer in epidemiological studies; however, it is unknown if these associations are causal or confounded. In two-sample Mendelian randomisation analyses, using summary genetic data from the UK Biobank and GWA consortia, we found that a one standard deviation increment in average acceleration was associated with lower risks of breast cancer (odds ratio [OR]: 0.51, 95% confidence interval [CI]: 0.27 to 0.98, P-value = 0.04) and colorectal cancer (OR: 0.66, 95% CI: 0.48 to 0.90, P-value = 0.01). We found similar magnitude inverse associations for estrogen positive (ER+ve) breast cancer and for colon cancer. Our results support a potentially causal relationship between higher physical activity levels and lower risks of breast cancer and colorectal cancer. Based on these data, the promotion of physical activity is probably an effective strategy in the primary prevention of these commonly diagnosed cancers.

Additional file 2: Figure S1. Scatter plot of SNP-BMI and SNP-CRC associations. Figure S2. Scatter plot of SNP-BMI and SNP-CRC associations (female specific). Figure S3. Scatter plot of SNP-BMI and SNP-CRC associations (male specific). Figure S4. Scatter plot of SNP-BMI and SNP-colon cancer associations. Figure S5. Scatter plot of SNP-BMI and SNP-proximal colon cancer associations. Figure S6. Scatter plot of SNP-BMI and SNP-distal colon cancer associations. Figure S7. Scatter plot of SNP-BMI and SNP-rectal cancer associations. Figure S8. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of BMI on CRC. Figure S9. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of BMI on CRC (female specific). Figure S10. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of BMI on CRC (male specific). Figure S11. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of BMI on colon cancer. Figure S12. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of BMI on proximal colon cancer. Figure S13. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of BMI on distal colon cancer. Figure S14. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of BMI on rectal cancer. Figure S15. Leave-one-out plot showing the association between BMI and CRC, following SNP-by-SNP removal from the model. Figure S16. Leave-one-out plot showing the association between BMI and CRC (femalespecific), following SNP-by-SNP removal from the model. Figure S17. Leave-one-out plot showing the association between BMI and CRC (malespecific), following SNP-by-SNP removal from the model. Figure S18. Leave-one-out plot showing the association between BMI and colon cancer, following SNP-by-SNP removal from the model. Figure S19. Leave-one-out plot showing the association between BMI and proximal colon cancer, following SNP-by-SNP removal from the model. Figure S20. Leave-one-out plot showing the association between BMI and distal colon cancer, following SNP-by-SNP removal from the model. Figure S21. Leave-one-out plot showing the association between BMI and rectal cancer, following SNP-by-SNP removal from the model. Figure S22. Scatter plot of SNP-WHR and SNP-CRC associations. Figure S23. Scatter plot of SNP-WHR and SNP-CRC associations (female specific). Figure S24. Scatter plot of SNP-WHR and SNP-CRC associations (male specific). Figure S25. Scatter plot of SNP-WHR and SNP-colon cancer associations. Figure S26. Scatter plot of SNP-WHR and SNP-proximal colon cancer associations. Figure S27. Scatter plot of SNP-WHR and SNP-distal colon cancer associations. Figure S28. Scatter plot of SNP-WHR and SNP-rectal cancer associations. Figure S29. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of WHR on CRC. Figure S30. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of WHR on CRC (female specific). Figure S31. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of WHR on CRC (male specific). Figure S32. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of WHR on colon cancer. Figure S33. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of WHR on proximal colon cancer. Figure S34. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of WHR on distal colon cancer. Figure S35. Forest plot showing individual SNP (black) and combined MR estimates (red; Egger and IVW) for the effect of WHR on rectal cancer. Figure S36. Leave-one-out plot showing the association between WHR and CRC, following SNP-by-SNP removal from the model. Figure S37. Leave-one-out plot showing the association between WHR and CRC, following SNP-by-SNP removal from the model (female specific). Figure S38. Leave-one-out plot showing the association between WHR and CRC, following SNP-by-SNP removal from the model (male specific). Figure S39. Leave-one-out plot showing the association between WHR and colon cancer, following SNP-by-SNP removal from the model. Figure S40. Leave-one-out plot showing the association between WHR and proximal colon cancer, following SNP-by-SNP removal from the model. Figure S41. Leave-one-out plot showing the association between WHR and distal colon cancer, following SNP-by-SNP removal from the model. Figure S42. Leave-one-out plot showing the association between WHR and rectal cancer, following SNP-by-SNP removal from the model. Figure S43. Effects of BMI and WHR on circulating metabolite levels (NMR-detected metabolites, 1 of 5), based on two-sample MR (IVW models) in summary GWAS consortia data. Figure S44. Effects of BMI and WHR on circulating metabolite levels (NMR-detected metabolites, 2 of 5), based on two-sample MR (IVW models) in summary GWAS consortia data. Figure S45. Effects of BMI and WHR on circulating metabolite levels (NMR-detected metabolites, 3 of 5), based on two-sample MR (IVW models) in summary GWAS consortia data. Figure S46. Effects of BMI and WHR on circulating metabolite levels (NMR-detected metabolites, 4 of 5), based on two-sample MR (IVW models) in summary GWAS consortia data. Figure S47. Effects of BMI and WHR on circulating metabolite levels (NMR-detected metabolites, 5 of 5), based on two-sample MR (IVW models) in summary GWAS consortia data. Figure S48. Power curves for MR analyses, based on samples sizes for colorectal cancer in the present study (black), Thrift et al., 2015 (blue) and Jarvis et al., 2016 (purple). Upper and lower power curves describe genetic instruments explaining 5% and 0.3% of variance respectively for each study.