Social support score in patients with malignant diseases-with sociodemographic and medical characteristics

Causal Effects of the Affordable Care Act (ACA) Implementation on Non-Hodgkin's Lymphoma Survival: A Difference-in-Differences Analysis

INTRODUCTION

Non-Hodgkin's Lymphoma (NHL) accounts for a substantial number of cancer cases in the United States, with a significant prevalence and mortality rate. The implementation of the Affordable Care Act (ACA) has the potential to impact cancer-specific survival among NHL patients by improving access to healthcare services and treatments.

OBJECTIVE

This study aims to assess the impact of the implementation of the ACA on cancer-specific survival among patients diagnosed with NHL.

METHODOLOGY

In this retrospective analysis, we leveraged data from the Surveillance, Epidemiology, and End Results (SEER) registry to assess the impact of the ACA on cancer-specific survival among NHL patients. The study covered the years 2000-2020, divided into pre-ACA (2000-2013) and post-ACA (2017-2020) periods, with a three-year washout (2014-2016). Using a Difference-in-Differences approach, we compared Georgia (a non-expansion state) to New Jersey (an expansion state since 2014). We adjusted for patient demographics, income, metropolitan status, disease stage, and treatment modalities.

RESULTS

Among 74,762 patients, 56.2% were in New Jersey (42,005), while 43.8% were in Georgia (32,757). The pre-ACA period included 32,851 patients (51.7% in Georgia and 56.7% in New Jersey), and 27,447 patients were in the post-ACA period (48.3% in Georgia and 43.4% in New Jersey). The post-ACA period exhibited a 34% survival improvement (OR=0.66, 95% CI 0.58-0.75). ACA implementation was associated with a 16% survival boost among NHL patients in New Jersey (OR=0.84, 95% CI 0.74-0.95). Other factors linked to improved survival included surgery (OR=0.86, 95% CI 0.81-0.91), radiotherapy (OR=0.77, 95% CI 0.72-0.82), and married status (OR=0.67, 95% CI 0.64-0.71).

CONCLUSION

The study underscores the ACA's potential positive impact on cancer-specific survival among NHL patients, emphasizing the importance of healthcare policy interventions in improving patient outcomes.

The Role of Resilience in the Relationship between Sociodemographic, Clinical Characteristics, and Social Support among Breast Cancer Patients in Serbia

BACKGROUND

The management of breast cancer treatments within the limitations of family, social, and professional life is emotionally burdening and negatively affects physical, psychological, and social well-being, reducing the overall quality of life of patients and their families.

METHODS

This cross-sectional descriptive-analytical study was conducted from March to August 2023 at the "Dr. Radivoj Simonović" General Hospital in Sombor. A total of 236 breast cancer patients participated in this study. The research was conducted using the following instruments: a questionnaire on sociodemographic and clinical characteristics of patients, the Berlin Social-Support Scales-for assessing social support-and the Connor-Davidson Resilience Scale-for assessing resilience. This study aimed to determine the predictors and levels of social support and resilience of breast cancer patients. We also wanted to examine whether resilience is a mediator between patients' sociodemographic and clinical characteristics and levels of social support.

RESULTS

The total average value of social support was 3.51 ± 0.63, while on the resilience scale, the respondents achieved a total average score of 52.2 ± 9.63. Perceived and actually received social support of breast cancer patients were positively correlated with resilience [p < 0.01], while no statistically significant correlations were found for the need for support and satisfaction. The sets of predictors can significantly predict their effects on all types of perceived social support (emotional social support: 9%; perceived instrumental social support: 9%) and all types of received social support (actually received emotional social support: 8%; actually received instrumental social support: 7%; actually received informational social support: 8%). There is a potential mediating role of resilience in relation to sociodemographic factors, clinical characteristics, and the need for support.

CONCLUSION

This study confirms that a strong connection exists between social support and resilience. However, the analysis did not confirm the mediating role of resilience between the sociodemographic and clinical characteristics on the one hand and social support on the other.