Association of Ang-2, vWF, and EVLWI with risk of mortality in sepsis patients with concomitant ARDS: A retrospective study

BACKGROUND/PURPOSE

This study aimed to determine the potential effects of angiopoietin-2 (Ang-2), von Willebrand factor (vWF), and extravascular lung water index (EVLWI) on the risk of mortality in sepsis patients with concomitant acute respiratory distress syndrome (ARDS).

METHODS

This retrospective study recruited 41 sepsis patients with concomitant ARDS from January 2015 to June 2018. Data of Ang-2 and vWF levels, EVLWI, and sequential organ failure assessment scores were collected at 0, 24, and 48 h after admission to the hospital.

RESULTS

The length of intensive care unit stay (P = 0.041) and Acute Physiology and Chronic Health Evaluation-2 (APACHE II) score (P = 0.003) were associated with the risk of mortality. Furthermore, increased Ang-2 levels and EVLWI at 24 h and 48 h were associated with an increased risk of mortality. Moreover, the APACHE II score at hospital admission significantly predicted the risk of mortality (area under the curve [AUC], 0.834; 95% confidence interval [CI], 0.665-0.983). Finally, the models containing a combination of Ang-2 level and EVLWI at 24 h (AUC, 0.908; 95% CI, 0.774-0.996) and Ang-2 level and EVLWI at 48 h (AUC, 0.981; 95% CI, 0.817-1.000) had high diagnostic values for predicting risk of mortality.

CONCLUSION

The study findings indicate that Ang-2 levels and EVLWI at 24 h and 48 h after admission are significantly associated with the risk of mortality.

Does Survival Vary for Breast Cancer Patients in the United States? A Study from Six Randomly Selected States

BACKGROUND

Breast cancer is the most common cancer in women. Disparities in some characteristics of breast cancer patients and their survival data for six randomly selected states in the US were examined.

MATERIALS AND METHODS

A probability random sampling method was used to select the records of 2,000 patients from each of six randomly selected states. Demographic and disease characteristics were extracted from the Surveillance Epidemiology and End Results (SEER) database. To evaluate relationships between variables, we employed a Cox Proportional Regression to compare survival times in the different states.

RESULTS

Iowa had the highest mean age of diagnosis at 64.14 years (SE = 0.324) and Georgia had the lowest at 57.97 years (SE = 0.313). New Mexico had the longest mean survival time of 189.09 months (SE = 20.414) and Hawaii the shortest at 119.01 (SE = 5.394) months, a 70.08-month difference (5.84 years). Analysis of stage of diagnosis showed that the highest survival times for Whites and American Indians/Alaska Natives were for stage I cancers. The highest survival times for Blacks varied. Stage IV cancer consistently showed the lowest survival times.

CONCLUSIONS

Differences in breast cancer characteristics across states highlight the need to understand differences between the states that result in variances in breast cancer survival.

Importance of meta-analysis and practical obstacles in oncological and epidemiological studies: statistics very close but also far!

Studies of epidemiological and prognostic factors are very important for oncology practice. There is a rapidly increasing amount of research and resultant knowledge in the scientific literature. This means that health professionals have major challenges in accessing relevant information and they increasingly require best available evidence to make their clinical decisions. Meta-analyses of prognostic and other epidemiological factors are very practical statistical approaches to define clinically important parameters. However, they also feature many obstacles in terms of data collection, standardization of results from multiple centers, bias, and commentary for intepretation. In this paper, the obstacles of meta-analysis are briefly reviewed, and potential problems with this statistical method are discussed.

Black Hispanic and Black non-Hispanic breast cancer survival data analysis with half-normal model application

BACKGROUND

Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model.

MATERIALS AND METHODS

The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End RESULTS cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH.

RESULTS

A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model.

CONCLUSIONS

The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.