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The vast majority of head and neck cancers (HNCs) are sporadic squamous cell carcinomas, smoking and heavy drinking being the main risk factors. However, little is known about the possible role of family history and the importance of inherited factors versus shared environment. We used Swedish population-based registries to study the family history of HNC. In order to estimate the risk for family members to get the same cancer, and the risk for cancer-specific death in patients with a family history of HNC compared with patients without a family history, multivariate Cox proportional hazards analyses were performed. A 1.43-fold increased risk for developing HNC in the first-degree relatives (FDRs) of HNC patients [hazard ratio (HR), 1.43; 95% CI, 1.28-1.61] was found, when compared with relatives of healthy controls. In spouses of patients with HNC, the risk for developing any HNC was moderately increased (HR, 1.25; 95% CI, 1.01-1.53), compared with spouses of healthy controls. In addition, a 1.34-fold increased risk for death of HNC was found in HNC patients with a family history of HNC (HR, 1.34; 95% CI, (1.03-1.73) compared with HNC patients without a family history. We found an increased risk for HNC in relatives and spouses of HNC patients, when compared with family members of healthy controls. This suggests that in addition to inherited factors, shared environmental factors have a significant role in the development of the cancer. Family history of HNC was associated with worse survival in a newly diagnosed HNC patient.

The long-term mortality remains unknown in women diagnosed with breast cancer in situ (BCIS). Here we assessed the cause-specific mortality in BCIS patients. This population-based cohort study included 12 243 women diagnosed with BCIS in Sweden between 1980 and 2011. Patients were followed until death, emigration, or 31 December 2013, whichever came first. The 30-year cumulative incidence of breast cancer-specific mortality was 6.3%, which is considerably lower than 49.7% observed for other-cause mortality. Women diagnosed with BCIS were more likely to die from breast cancer (standardize mortality ratio [SMR], 3.85; 95%CI, 3.47-4.27) but less likely to die from cardiovascular disease (SMR, 0.88; 95% CI, 0.82-0.95) than women in the general population. Specifically, the SMRs for breast cancer-specific mortality decreased over time from 5.17 (95%CI, 3.95-6.81) among BCIS diagnosed during 1980-1989 to 3.03 (95%CI, 2.35-3.91) among those diagnosed during 2000-2011. Furthermore, higher risk of death from other causes was seen among those with older age at BCIS diagnosis, lower levels of education, nulliparity, higher Charlson Comorbidity Index, and being hospitalized before BCIS diagnosis; whereas lower risk of death from breast cancer was seen among BCIS diagnosed in the later time period and those with younger age at first birth. We conclude that most women diagnosed with BCIS die from causes other than breast cancer, which highlights the need for actions not only to reduce non-breast cancer mortality but also to identify patient where extensive curative BCIS treatment is not adding to survival. This article is protected by copyright. All rights reserved.

Proliferation-related gene signatures have been proposed to aid breast cancer management by providing reproducible prognostic and predictive information on a patient-by-patient basis. It is unclear however, whether a less demanding assessment of cell division rate (as determined in clinical setting by expression of Ki67) can function in place of gene profiling. We investigated agreement between literature-, distribution-based, as well as signature-derived values for Ki67, relative to the genomic grade index (GGI), 70-gene signature, p53 signature, recurrence score (RS), and the molecular subtype models of Sorlie, Hu, and Parker in representative sets of 253 and 159 breast cancers with a median follow-up of 13 and 14.5 years, respectively. The relevance for breast cancer specific survival was also addressed in uni- and bivariate Cox models. Taking both cohorts into account, our broad approach identified ROC optimized Ki67 cutoffs in the range of 8–28%. With optimum signature-reproducing cutoffs, similarity in classification of individual tumors was higher for binary signatures (72–85%), than multi-level signatures (67–73%). Consistent with strong agreement, no prognostic superiority was noted for either Ki67 or the binary GGI, 70-gene and p53 signatures in the Uppsala dataset by bivariate analyses. In contrast, Ki67-independent prognostic capacity could be demonstrated for RS and molecular subtypes according to Sorlie, Hu and Parker in both datasets. Our results show that the added prognostic value of binary proliferation-related gene signatures is limited for Ki67-assessed breast cancers. More complex, multi-level descriptions have a greater potential in short- and long-term prognostication for biologically relevant breast cancer subgroups.