What do @entity263 XXXX die of?

@entity1 @entity712 @entity263 @entity417 @entity1494 @entity5 @entity204
BACKGROUND: A recent rise in the incidence of @entity263 and a more favorable outcome have increased the proportions of other causes of @entity204 in affected @entity1 . Extending the survival of @entity263 @entity1 thus requires knowledge of all causes of @entity204 . METHODS: Data on the population, @entity5 , and causes of @entity204 were gathered from the nationwide Swedish Family- @entity5 Database. A Cox regression model, @entity263 @entity1 with all other @entity1 , was applied. Hazard ratios ( @entity712 ) were calculated both for the underlying cause and for dying with a specific cause listed among multiple causes of @entity204 . FINDINGS: Among 686,500 observed deaths, 62,500 were @entity263 @entity1 . For underlying causes other than @entity263 , the highest cause-specific HRs were found for external causes ( @entity712 , 1.24; 95% confidence interval [CI], 1.16-1.31), diseases of the pulmonary circulation ( @entity712 , 1.22; 95% CI, 1.09-1.37), and @entity712 ( @entity712 , 1.18; 95% CI, 1.11-1.24). For specific multiple causes, the highest HRs were found for @entity417 ( @entity712 , 2.28; 95% CI, 2.14-2.42), diseases of the pulmonary circulation ( @entity712 , 1.61; 95% CI, 1.55-1.68), and @entity1494 ( @entity712 , 1.90; 95% CI, 1.84-1.96). INTERPRETATIONS: @entity263 @entity1 have a higher risk for dying from various causes other than @entity263 , including external causes and @entity712 . Mechanisms have been proposed linking these elevated risks to both @entity5 and treatment. More attention should be paid to comorbidities in @entity1 with @entity263 . The present study fulfills a gap in the knowledge of @entity204 causes in @entity263 @entity1 .
