A B S T R A C T PurposeTo examine the impact of marital status on stage at diagnosis, use of definitive therapy, and cancer-specific mortality among each of the 10 leading causes of cancer-related death in the United States. Methods ResultsMarried patients were less likely to present with metastatic disease (adjusted odds ratio [OR], 0.83; 95% CI, 0.82 to 0.84; P Ͻ .001), more likely to receive definitive therapy (adjusted OR, 1.53; 95% CI, 1.51 to 1.56; P Ͻ .001), and less likely to die as a result of their cancer after adjusting for demographics, stage, and treatment (adjusted hazard ratio, 0.80; 95% CI, 0.79 to 0.81; P Ͻ .001) than unmarried patients. These associations remained significant when each individual cancer was analyzed (P Ͻ .05 for all end points for each malignancy). The benefit associated with marriage was greater in males than females for all outcome measures analyzed (P Ͻ .001 in all cases). For prostate, breast, colorectal, esophageal, and head/neck cancers, the survival benefit associated with marriage was larger than the published survival benefit of chemotherapy. ConclusionEven after adjusting for known confounders, unmarried patients are at significantly higher risk of presentation with metastatic cancer, undertreatment, and death resulting from their cancer. This study highlights the potentially significant impact that social support can have on cancer detection, treatment, and survival.

The marginal likelihood is commonly used for comparing different evolutionary models in Bayesian phylogenetics and is the central quantity used in computing Bayes Factors for comparing model fit. A popular method for estimating marginal likelihoods, the harmonic mean (HM) method, can be easily computed from the output of a Markov chain Monte Carlo analysis but often greatly overestimates the marginal likelihood. The thermodynamic integration (TI) method is much more accurate than the HM method but requires more computation. In this paper, we introduce a new method, steppingstone sampling (SS), which uses importance sampling to estimate each ratio in a series (the "stepping stones") bridging the posterior and prior distributions. We compare the performance of the SS approach to the TI and HM methods in simulation and using real data. We conclude that the greatly increased accuracy of the SS and TI methods argues for their use instead of the HM method, despite the extra computation needed.

Background-Tyrosine kinase inhibitors (TKIs) have advanced cancer treatment. Sunitinib, a recently-approved, multi-targeted TKI, prolongs survival for patients with metastatic renal cell carcinoma (RCC) and gastrointestinal stromal tumor (GIST), but concerns about cardiac safety have arisen with this agent.