OBJECTIVES-To assess the effect of a prior diagnosis of depression on the diagnosis, treatment, and survival of older women with breast cancer. DESIGN-Retrospective analysis of records from Surveillance, Epidemiology and End Results (SEER) and Medicare claims. SETTING-Registries from seven major cities and five states.PARTICIPANTS-A total of 24,696 women aged 67 to 90 diagnosed with breast cancer between 1993 and 1996 and included in the SEER Medicare linked database were studied.MEASUREMENTS-Information on patient demographics, tumor characteristics, treatment received, and survival were obtained from SEER, and the Medicare inpatient and professional charges for the 2 years before diagnosis were searched for a diagnosis of depression.RESULTS-A total of 1,841 of the 24,696 women (7.5%) had been given a diagnosis of depression sometime in the 2 years before the diagnosis of breast cancer. There was no difference in tumor size or stage at diagnosis between depressed and nondepressed women. Women diagnosed with depression were less likely to receive treatment generally considered definitive (59.7% vs 66.2%, P< .0001), and this difference remained after controlling for age, ethnicity, comorbidity, and SEER site. Also, women with a prior diagnosis of depression had a higher risk of death (hazard ratio =1.42; 95% confidence interval = 1.13-1.79) after controlling for other factors that might affect survival. The higher risk of death associated with a prior diagnosis of depression was also seen in analyses restricted to women who received definitive treatment.CONCLUSION-Women with a recent diagnosis of depression are at greater risk for receiving nondefinitive treatment and experience worse survival after a diagnosis of breast cancer, but differences in treatment do not explain the worse survival. Keywordsdepression; breast cancer; access to care; survival; treatment Depression is associated with impaired recovery from a number of medical illnesses, such as stroke, hip fracture, and myocardial infarction. 1-7 The exact mechanisms whereby depression influences recovery from illness have not been delineated but presumably involve multiple pathways. 8,9Address correspondence to Dr. James S. Goodwin, Sealy Center on Aging, University of Texas Medical Branch, 301 University Blvd., Galveston, Texas 77555. E-mail: jsgoodwi@utmb.edu. Supported by Grants AG 17231 and CA 71773 from the U.S. Public Health Service. The study population consisted of all women in the SEER registries who were diagnosed with incident breast cancer in the years 1993-1996 and who linked with the Medicare data (n =52,010). Because diagnoses of depression in the 2 years before breast cancer diagnosis were assessed with the Medicare claims data, the subjects were limited to women who were aged 67 and older (range 67-90) on January 1 of the year of their breast cancer diagnosis (n =36,833), were enrolled in Medicare parts A and B, and were not members of a health maintenance organization for that same year (n =27,894). Subjects not meeting these cri...
Background Readmissions in patients with chronic obstructive pulmonary disease (COPD) are common and costly. We examined the effect of early follow-up visit with patient’s primary care physician (PCP) or pulmonologist following acute hospitalization on the 30-day risk of an emergency department (ER) visit and readmission. Methods We conducted a retrospective cohort study of fee-for-service Medicare beneficiaries with an identifiable PCP who were hospitalized for COPD between 1996 and 2006. Three or more visits to a PCP in the year prior to the hospitalization established a PCP for a patient. We performed a Cox proportional hazard regression with time-dependent covariates to determine the risk of 30-day ER visit and readmission in patients with or without a follow-up visit to their PCP or pulmonologist. Results Of the 62 746 patients admitted for COPD, 66.9% had a follow-up visit with their PCP or pulmonologist within 30 days of discharge. Factors associated with lower likelihood of outpatient follow-up visit were longer length of hospital stay, prior hospitalization for COPD, older age, black race, lower socioeconomic status, and emergency admission. Those receiving care at nonteaching, for-profit, and smaller-sized hospitals were more likely to have a follow-up visit. In a multivariate, time-dependent analysis, patients who had a follow-up visit had a significantly reduced risk of an ER visit (hazard ratio [HR], 0.86; 95% confidence interval [CI], 0.83–0.90) and readmission (HR, 0.91; 95% CI, 0.87–0.96). Conclusion Continuity with patient’s PCP or pulmonologist after an acute hospitalization may lower rates of ER visits and readmission in patients with COPD.
With up to 15 years of follow-up there were no significant differences in cardiac morbidity after radiation for left- versus right-sided breast cancer.
Most placements in nursing homes are preceded by a hospitalization followed by discharge to a SNF. Discharge to a SNF is associated with a high risk of subsequent long-term care.
The receiver operating characteristic (ROC) curve is a statistical tool for evaluating the accuracy of diagnostic tests. Investigators often compare the validity of two tests based on the estimated areas under the respective ROC curves. However, the traditional way of comparing entire areas under two ROC curves is not sensitive when two ROC curves cross each other. Also, there are some cutpoints on the ROC curves that are not considered in practice because their corresponding sensitivities or specificities are unacceptable. For the purpose of comparing the partial area under the curve (AUC) within a specific range of specificity for two correlated ROC curves, a non-parametric method based on Mann-Whitney U-statistics has been developed. The estimation of AUC along with its estimated variance and covariance is simplified by a method of grouping the observations according to their cutpoint values. The method is used to evaluate alternative logistic regression models that predict whether a subject has incident breast cancer based on information in Medicare claims data.
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