In-Hospital Mortality and Post-Surgical Complications Among Cancer Patients with Metabolic Syndrome

Background Metabolic syndrome (MetS) is an important etiologic and prognostic factor for cancer, but few studies have assessed hospitalization outcomes among patients with both conditions. Methods Data was obtained from the Healthcare Cost and Utilization project Nationwide Inpatient Sample (HCUP-NIS). Study variables were assessed using ICD-9 codes on adults aged 40 years and over admitted to a US hospital between 2007 and 2011 with primary diagnosis of either breast, colorectal, or prostate cancer. We examined in-hospital mortality, post-surgical complications, and discharge disposition among cancer patients with MetS and compared with non-MetS patients. Results Hospitalized breast (OR: 0.31, 95% CI: 0.20–0.46), colorectal (OR: 0.41, 95% CI: 0.35–0.49), and prostate (OR: 0.28, 95% CI: 0.16–0.49) cancer patients with MetS had significantly reduced odds of in-hospital mortality. The odds of post-surgical complications among breast (OR: 1.20, 95% CI: 1.03–1.39) and prostate (OR: 1.22, 95% CI: 1.09–1.37) cancer patients with MetS were higher, but lower by 7% among colorectal cancer patients with MetS. Additionally, breast (OR: 1.21, 95% CI: 1.11–1.32) and colorectal (OR: 1.06, 95% CI: 1.01–1.11) cancer patients with MetS had significantly higher odds for discharge to a skilled nursing facility compared with those without MetS, but this was not statistically significant among prostate cancer patients. Conclusions Adverse health outcomes were significantly higher among hospitalized patients with a primary diagnosis of cancer and MetS. Future studies are needed to identify clinical strategies for detecting and managing patients with MetS to reduce the likelihood of poor inpatient outcomes

Demographic, Presentation, and Treatment Factors and Racial Disparities in Ovarian Cancer Hospitalization Outcomes

BACKGROUND: This study examines whether racial disparities in hospitalization outcomes persist between African-American and White women with ovarian cancer after matching on demographic, presentation, and treatment factors. METHODS: Using data from the Nationwide Inpatient Sample database, 5,164 African-American ovarian cancer patients were sequentially matched with White patients on demographic (e.g., age, income), presentation (e.g., stage, comorbidities), and treatment (e.g., surgery, radiation) factors. Racial differences in-hospital length of stay, post-operative complications, and in-hospital mortality were evaluated using conditional logistic regression models. RESULTS: White ovarian cancer patients had relatively higher odds of post-operative complications when matched on demographics (OR 1.35, 95% CI 1.05, 1.74), and presentation (OR 1.28, 95% CI 1.00, 1.65) but not when additionally matched on treatment (OR 1.03, 95% CI 0.78, 1.35). African-American patients had longer in-hospital length of stay (6.96 ± 7.21 days) compared with White patients when matched on demographics (6.37 ± 7.07 days), presentation (6.48 ± 7.16 days), and treatment (6.53 ± 7.59 days). Compared with African-American patients, White patients experienced lower odds of in-hospital mortality when matched on demographics (OR 0.78, 95% CI 0.66, 0.92), but this disparity was no longer significant when additionally matched on presentation (OR 0.88, 95% CI 0.75, 1.04) and treatment (OR 0.95, 95% CI 0.81, 1.12). CONCLUSION: Racial disparities in ovarian cancer hospitalization outcomes persisted after adjusting for demographic and presentation factors; however these differences were eliminated after additionally accounting for treatment factors. More studies are needed to determine the factors driving racial differences in ovarian cancer treatment in otherwise similar patient populations

Post-traumatic stress symptoms in cancer survivors: relationship to the impact of cancer scale and other associated risk factors

PURPOSE: The purpose of this study was to determine the prevalence of post-traumatic stress symptoms in a sample of cancer survivors and to investigate their association with the impact of cancer, depressive symptoms, and social support. METHODS: We administered a survey to participants in a cancer survivor registry. It included: Post-Traumatic Stress Disorder Checklist-Civilian version (PCL-C), Impact of Cancer Scale (IOC) v.2, and measures of social support, income, and long-term effects of cancer. We performed multivariate analyses to estimate associations between PCL-C and other variables. PCL-C score was examined as a continuous dependent variable and categorically. RESULTS: Responses were available from 162 cancer survivors. Mean age was 51 years (standard deviation (SD) 16); mean time since diagnosis was 11 years (SD 10). Mean PCL-C score was 27 (SD 9, range 17–64); 29% of the sample scored 30 and above, 13% scored 38 and above, 7% scored 44 and above. Linear regression indicated that PCL-C scores were significantly associated with the IOC negative impact summary scale (NIS) (p <0.001), depressive symptoms (p = 0.003), less social support (p = 0.02), and lower income (p = 0.03). NIS subscale analyses showed that two subscales, life interference (LI) and worry (W), were significantly correlated with PCL-C score (LI: p <0.001; W: p = 0.02). CONCLUSIONS: In this study, the IOC NIS was associated with endorsement of PTSD symptoms. Assessing survivors for PTSD symptoms with the PCL-C could detect those individuals in need of psychosocial support. The IOC may be useful for identifying target areas for interventions to reduce these symptoms among cancer survivors

Depression and Anxiety Disorders among Hospitalized Women with Breast Cancer.

To document the prevalence of depression and anxiety disorders, and their associations with mortality among hospitalized breast cancer patients.We examined the associations between breast cancer diagnosis and the diagnoses of anxiety or depression among 4,164 hospitalized breast cancer cases matched with 4,164 non-breast cancer controls using 2006-2009 inpatient data obtained from the Nationwide Inpatient Sample database. Conditional logistic regression models were used to compute odds ratios (ORs) and 95% confidence intervals (CI) for the associations between breast cancer diagnosis and diagnoses of anxiety or depression. We also used binary logistic regression models to examine the association between diagnoses of depression or anxiety, and in-hospital mortality among breast cancer patients.We observed that breast cancer cases were less likely to have a diagnosis of depression (OR=0.63, 95% CI: 0.52-0.77), and less likely to have a diagnosis of anxiety (OR=0.68, 95% CI: 0.52-0.90) compared with controls. This association remained after controlling for race/ethnicity, residential income, insurance and residential region. Breast cancer patients with a depression diagnosis also had lower mortality (OR=0.69, 95% CI: 0.52-0.89) compared with those without a depression diagnosis, but there was no significant difference in mortality among those with and without anxiety diagnoses.Diagnoses of depression and anxiety in breast cancer patients were less prevalent than expected based on our analysis of hospitalized breast cancer patients and matched non-breast cancer controls identified in the NIS dataset using ICD-9 diagnostic codes. Results suggest that under-diagnosis of mental health problems may be common among hospitalized women with a primary diagnosis of breast cancer. Future work may fruitfully explore reasons for, and consequences of, inappropriate identification of the mental health needs of breast cancer patients