The prognosis of pancreatic cancer (PaC) strongly varies across different stages and age groups, which has unfortunately not been well recorded in the literature. This international population-based study aimed to provide tumor-node-metastasis (TNM) stage- and age-specific survival estimates and trends in resected and overall (resected and unresected) PaC in the early twenty-first century. Using data from the US Surveillance, Epidemiology, and End Results-18 Program and the national cancer registries of the Netherlands, Belgium, Norway, and Slovenia, short-term and long-term overall survival results stratified by TNM stage and age in resected and overall primary PaC, irrespective of being microscopically confirmed or not, in 2003–2014 were computed using the Kaplan-Meier method. The temporal survival trends over three predefined periods (2003–2005, 2006–2008, and 2009–2011) were further examined using the log-rank test. In total, data for 125,183 patients were analyzed. Overall, age-stratified 3-year survival was 20–34% (< 60 years), 14–25% (60–69 years), and 9–13% (≥ 70 years) in stages I–II PaC; and 2–5% (< 60 years), 1–2% (60–69 years), and < 1–1% (≥ 70 years) in stages III–IV cancer. Patients who underwent operation had higher 3-year survival in each stage and age group (stages I–II: 23–39% (< 60 years), 16–31% (60–69 years), and 17–30% (≥ 70 years); stages III–IV: 5–19% (< 70 years) and 2–14% (≥ 70 years)). Perioperative survival also decreased with advancing stage and older age (stages I–II: 98–100% (< 60 years), 97–99% (60–69 years), and 94–99% (≥ 70 years); stages III–IV: 94–99% (< 70 years) and 81–96% (≥ 70 years)). Between 2003 and 2005 and 2009–2011, for overall PaC, both short-term and long-term survival improvements were observed in all countries except Belgium; for resected disease, short-term improvements were present only in the USA and Slovenia, but long-term improvements were observed in all countries except Slovenia, with stage-specific variations. Our large international study provides TNM stage- and age-specific population-based survival in overall and resected PaC that will facilitate clinical counseling. While the survival expectations for patients with resected PaC are substantially higher than the widely available and known dismal survival predictions for overall patients, conclusions on the benefits of resection cannot be made from this observational study. Patients with advanced-stage disease and/or older age should undergo careful risk assessment before treatment. Limited but inspiring improvement in survival is observed.

Preclinical studies have demonstrated that propranolol inhibits several pathways involved in breast cancer progression and metastasis. We investigated whether breast cancer patients who used propranolol, or other non-selective beta-blockers, had reduced breast cancer-specific or all-cause mortality in eight European cohorts. Incident breast cancer patients were identified from eight cancer registries and compiled through the European Cancer Pharmacoepidemiology Network. Propranolol and non-selective beta-blocker use was ascertained for each patient. Breast cancer-specific and all-cause mortality were available for five and eight cohorts, respectively. Cox regression models were used to calculate hazard ratios (HR) and 95% confidence intervals (CIs) for cancer-specific and all-cause mortality by propranolol and non-selective beta-blocker use. HRs were pooled across cohorts using meta-analysis techniques. Dose–response analyses by number of prescriptions were also performed. Analyses were repeated investigating propranolol use before cancer diagnosis. The combined study population included 55,252 and 133,251 breast cancer patients in the analysis of breast cancer-specific and all-cause mortality respectively. Overall, there was no association between propranolol use after diagnosis of breast cancer and breast cancer-specific or all-cause mortality (fully adjusted HR = 0.94, 95% CI, 0.77, 1.16 and HR = 1.09, 95% CI, 0.93, 1.28, respectively). There was little evidence of a dose–response relationship. There was also no association between propranolol use before breast cancer diagnosis and breast cancer-specific or all-cause mortality (fully adjusted HR = 1.03, 95% CI, 0.86, 1.22 and HR = 1.02, 95% CI, 0.94, 1.10, respectively). Similar null associations were observed for non-selective beta-blockers. In this large pooled analysis of breast cancer patients, use of propranolol or non-selective beta-blockers was not associated with improved survival.

Pancreatic cancer (PaC) remains extremely lethal worldwide even after resection. PaC resection rates are low, making prognostic studies in resected PaC difficult. This large international population-based study aimed at exploring factors associated with survival in patients with resected TNM stage I–II PaC receiving chemotherapy and at developing and internationally validating a survival-predicting model. Data of stage I–II PaC patients resected and receiving chemotherapy in 2003–2014 were obtained from the national cancer registries of Belgium, the Netherlands, Slovenia, and Norway, and the US Surveillance, Epidemiology, and End Results (SEER)-18 Program. Multivariable Cox proportional hazards models were constructed to investigate the associations of patient and tumor characteristics with overall survival, and analysis was performed in each country respectively without pooling. Prognostic factors remaining after backward selection in SEER-18 were used to build a nomogram, which was subjected to bootstrap internal validation and external validation using the European datasets. A total of 11,837 resected PaC patients were analyzed, with median survival time of 18–23 months and 3-year survival rates of 21–31%. In the main analysis, patient age, tumor T stage, N stage, and differentiation were associated with survival across most countries, with country-specific association patterns and strengths. However, tumor location was mostly not significantly associated with survival. Resection margin, hospital type, tumor size, positive and harvested lymph node number, lymph node ratio, and comorbidity number were associated with survival in certain countries where the information was available. A median survival time- and 1-, 2-, 3-, and 5-year survival probability-predictive nomogram incorporating the backward-selected variables in the main analysis was established. It fits each European national cohort similarly well. Calibration curves showed very good agreement between nomogram-prediction and actual observation. The concordance index of the nomogram (0.60) was significantly higher than that of the T and N stage-based model (0.56) for predicting survival. In these large international population-based cohorts, patients with resected PaC receiving chemotherapy have distinct characteristics independently associated with survival, with country-specific patterns and strengths. A robust benchmark population-based survival-predicting model is established and internationally validated. Like previous models predicting survival in resected PaC, our nomogram performs modestly.

Overdiagnosis of invasive breast cancer (BC) is a contentious issue. The aim of this paper is to estimate the overdiagnosis rate of invasive BC in an organised BC screening program and to evaluate the impact of age and follow-up time. The micro-simulation model SiMRiSc was calibrated and validated for BC screening in Flanders, where women are screened biennially from age 50 to 69. Overdiagnosis rate was defined as the number of invasive BC that would not have been diagnosed in the absence of screening per 100,000 screened women during the screening period plus follow-up time (which was set at 5 years and varied from 2 to 15 years). Overdiagnosis rate was calculated overall and stratified by age. The overall overdiagnosis rate for women screened biennially from 50 to 69 was 20.1 (95%CI: 16.9-23.2) per 100,000 women screened at 5-year follow-up from stopping screening. Overdiagnosis at 5-year follow-up time was 12.9 (95%CI: 4.6-21.1) and 74.2 (95%CI: 50.9-97.5) per 100,000 women screened for women who started screening at age 50 and 68, respectively. At 2- and 15-year follow-up time, overdiagnosis rate was 98.5 (95%CI: 75.8-121.3) and 13.4 (95%CI: 4.9-21.9), respectively, for women starting at age 50, and 297.0 (95%CI: 264.5-329.4) and 34.2 (95%CI: 17.5-50.8), respectively, for those starting at age 68. Sufficient follow-up time (≥10 years) after screening stops is key to obtaining unbiased estimates of overdiagnosis. Overdiagnosis of invasive BC is a larger problem in older compared to younger women.

Background: Socio-economic position is associated with cancer incidence, but the direction and magnitude of this relationship differs across cancer types, geographical regions, and socio-economic parameters. In this nationwide cohort study, we evaluated the association between different individual-level socio-economic and -demographic factors, cancer incidence, and stage at diagnosis in Belgium. Methods: The 2001 census was linked to the nationwide Belgian Cancer Registry for cancer diagnoses between 2004 and 2013. Socio-economic parameters included education level, household composition, and housing conditions. Incidence rate ratios were assessed through Poisson regression models. Stage-specific analyses were conducted through logistic regression models. Results: Deprived groups showed higher risks for lung cancer and head and neck cancers, whereas an inverse relation was observed for malignant melanoma and female breast cancer. Typically, associations were more pronounced in men than in women. A lower socio-economic position was associated with reduced chances of being diagnosed with known or early stage at diagnosis; the strongest disparities were found for male lung cancer and female breast cancer. Conclusions: This study identified population groups at increased risk of cancer and unknown or advanced stage at diagnosis in Belgium. Further investigation is needed to build a comprehensive picture of socio-economic inequality in cancer incidence.

Background: Socioeconomic status (SES) is an important factor in cancer survival; however, results are heterogeneous and linked to characteristics of the study population and health care system. This population-based cohort study evaluates the association between individual-level socioeconomic and demographic factors and cancer survival for the first time in Belgium. Methods: From the Belgian Cancer Registry, we identified 109,591 patients diagnosed between 2006 and 2013 with one of eight common cancer types. Information on treatment, socioeconomic parameters, and vital status were retrieved from multiple data sources and linked using a unique personal identification number. The outcome was 5-year observed survival. Associations between survival and socioeconomic and demographic factors were assessed using multivariable Cox proportional–hazard regression models. Results: Lower income, unemployment, and living alone were all associated with worse cancer survival. These associations were most pronounced for certain lifestyle-related cancer types (e.g., head and neck cancers) and those with good to moderate prognosis (e.g., colorectal and female breast cancer). Conclusions: These results indicate that, despite a comprehensive and nationwide health insurance program in which equity in rights and access to health care are pursued, SES is associated with disparities in cancer survival in Belgium. Impact: This population-based study with individual-level socioeconomic information of more than 100,000 patients with cancer identifies patient groups that may be at highest risk for socioeconomic disparities in cancer survival. Reasons behind the observed disparities are multiple and complex and should be further examined. Health policy interventions should consider the observed deprivation gap to plan targeted actions.