Is time-to-treatment associated with higher mortality in Korean elderly lung cancer patients?

What is the relationship between the local population change and cancer incidence in patients with dyslipidemia: Evidence of the impact of local extinction in Korea

BACKGROUND

Changes in the local population are intricately linked to healthcare infrastructure, which subsequently impacts the healthcare sector. A decreasing local population can result in lagging health infrastructure, potentially leading to adverse health outcomes as patients may be at risk of not receiving optimal care and treatment. While some studies have explored the relationship between chronic diseases and local population decline, evidence regarding cancer is insufficient. In this study, we focused on how deteriorating management of chronic diseases such as dyslipidemia could influence the risk of cancer. We investigated the relationship between changes in the local population and cancer incidence among patients with dyslipidemia.

METHODS

This cohort study was conducted using claims data. Data from adult patients with dyslipidemia from the National Health Insurance Service-National Sample Cohort conducted between 2002 and 2015 were included. Population changes in each region were obtained from the Korean Statistical Information Service and were used to link each individual's regional code. Cancer risk was the dependent variable, and Cox proportional hazards regression was used to estimate the target associations.

RESULTS

Data from 336,883 patients with dyslipidemia were analyzed. Individuals who resided in areas with a decreasing population had a higher risk of cancer than those living in areas with an increasing population (decrease: hazard ratio (HR) = 1.06, 95% CI = 1.03-1.10; normal: HR = 1.05, 95% CI = 1.02-1.09). Participants living in regions with a low number of hospitals had a higher risk of cancer than those in regions with a higher number of hospitals (HR = 1.20, 95% CI = 1.12-1.29).

CONCLUSION

Patients in regions where the population has declined are at a higher risk of cancer, highlighting the importance of managing medical problems caused by regional extinction. This could provide evidence for and useful insights into official policies on population decline and cancer risk.

Does Multidisciplinary Team Management Improve Clinical Outcomes in NSCLC? A Systematic Review With Meta-Analysis

Introduction

The implementation of multidisciplinary teams (MDTs) has been found to be effective for improving outcomes in oncology. Nevertheless, there is still a dearth of robust literature on patients with NSCLC. The aim of this study was to conduct a systematic review regarding the impact of MDTs on patient with NSCLC outcomes.

Methods

Databases were systematically searched up to February 2023. Two reviewers independently performed study selection and data extraction. Risk of bias was evaluated using the Newcastle-Ottawa and certainty of evidence by the Grading of Recommendations Assessment, Development and Evaluation approach. Overall survival was the primary outcome. Secondary outcomes included mortality, length of survival, progression-free survival, time from diagnosis to treatment, complete staging, treatment received, and adherence to guidelines. A meta-analysis with a random-effect model was performed. Statistical analysis was performed with the R 3.6.2 package.

Results

A total of 22 studies were included in the systematic review. Ten outcomes were identified, favoring the MDT group over the non-MDT group. Pooled analysis revealed that patients managed by MDTs had better overall survival (three studies; 38,037 participants; hazard ratio 0.60, 95% confidence interval [CI]: 0.49-0.75, I2 = 78%), shorter treatment time compared with patients in the non-MDT group (six studies; 15,235 participants; mean difference = 12.20 d, 95% CI: 10.76-13.63, I2 = 63%), and higher proportion of complete staging (four studies; 14,925 participants; risk ratio = 1.36, 95% CI: 1.17-1.57, I2 = 89%).

Conclusions

This meta-analysis revealed that MDT-based patient care was associated with longer overall survival and better quality-of-care-related outcomes.

The effect of fragmented cancer care and change in nurse staffing grade on cancer patient mortality

BACKGROUND

Continuity of patient care ensures timely and appropriate care and is associated with better patient outcomes among cancer patients. However, the impact of nurse staffing grade changes on patient outcomes remains unknown.

AIMS

This retrospective cohort study aimed to evaluate the effect of fragmented care and changes in nurse staffing grade on the survival of colorectal cancer patients who underwent surgery.

METHODS

This study included 2228 newly diagnosed colorectal cancer patients. Fragmented care was defined as the receipt of treatment in multiple hospitals and was divided into three categories based on changes in nurse staffing grade. Five-year survival rates were used to evaluate the effect of fragmented care and nurse staffing grade on outcomes of cancer patients. Survival analysis was performed by adjusting for covariates using the Cox proportional hazards model for 5-year mortality.

RESULTS

Approximately 18.5% of patients died within 5 years; the mortality rate during cancer treatment was higher in patients who received fragmented care, especially in those transferred to hospitals with fewer nurses. Patients who received fragmented care had shorter survival times, and those transferred to hospitals with fewer nurses had higher risks of 5-year mortality (hazard ratio: 1.625; 95% CI: [1.095, 2.412]). Transfers to hospitals with fewer nurses were associated with increased mortality rates in low-income patients, hospitals located in metropolitan and rural areas, and high-severity groups.

LINKING EVIDENCE TO ACTION

Receipt of fragmented care and change in nurse staffing grade due to patients' transfer to different hospitals were associated with increased mortality rates in cancer patients, thus underlining the importance of ensuring continuity and quality of care. Patients from rural areas, from low-income families, and with high disease severity may have better outcomes if they receive treatment in well-staffed hospitals.

Is Fragmented Cancer Care Associated With Medical Expenditure? Nationwide Evidence From Patients With Lung Cancer Using National Insurance Claim Data

Objectives: We aimed to investigate the association between fragmented cancer care in the early phase after cancer diagnosis and patient outcomes using national insurance claim data. Methods: We identified National Health Insurance beneficiaries diagnosed with lung cancer in South Korea from 2010 to 2014. We included 1,364 lung cancer patients with reduced immortal time bias and heterogeneity. We performed multiple regression analysis using a generalized estimate equation with a gamma distribution for medical expenditures. Results: Among the 1,364 patients with lung cancer, 12.8% had fragmented cancer care. Healthcare costs were higher in fragmented cancer care for both during diagnosis to 365 days and diagnosis to 1,825 days. Linear regression results showed that fragmented cancer care was associated with 1.162 times higher costs during the period from diagnosis to 365 days and 1.163 times the cost for the period from diagnosis to 1,825 days. Conclusion: We found fragmented cancer care is associated with higher medical expenditure. Future health policy should consider the limitation of patients' free will when opting for fragmented cancer care, as there are currently no control mechanisms.

A long waiting time from diagnosis to treatment decreases the survival of non-small cell lung cancer patients with stage IA1: A retrospective study

Objective

The prognostic effect of delayed treatment on stage IA1 non-small cell lung cancer (NSCLC) patients is still unclear. This study aimed to explore the association between the waiting time before treatment and the prognosis in stage IA1 NSCLC patients.

Methods

Eligible patients diagnosed with pathological stage IA1 NSCLC were included in this study. The clinical endpoints were overall survival (OS) and cancer-specific survival (CSS). The Kaplan-Meier method, the Log-rank test, univariable, and multivariable Cox regression analyses were used in this study. Propensity score matching was used to reduce the bias of data distribution.

Results

There were eligible 957 patients in the study. The length of waiting time before treatment stratified the survival in patients [<3 months vs. ≥3-months, unadjusted hazard ratio (HR) = 0.481, P = 0.007; <2 months vs. ≥2-months, unadjusted HR = 0.564, P = 0.006; <1 month vs. ≥1-month, unadjusted HR = 0.537, P = 0.001]. The 5-year CSS rates were 95.0% and 77.0% in patients of waiting time within 3 months and over 3 months, respectively. After adjusting for other confounders, the waiting time was identified as an independent prognostic factor.

Conclusions

A long waiting time before treatment may decrease the survival of stage IA1 NSCLC patients. We propose that the waiting time for those patients preferably is less than one month and should not exceed two months.

Healthcare vulnerability disparities in pancreatic cancer treatment and mortality using the Korean National Sample Cohort: a retrospective cohort study

Background

The gap in treatment and health outcomes after diagnosis of pancreatic cancer is a major public health concern. We aimed to investigate the differences in the health outcomes and treatment of pancreatic cancer patients in healthcare vulnerable and non-vulnerable areas.

Methods

This retrospective cohort study evaluated data from the Korea National Health Insurance Corporation-National Sample Cohort from 2002 to 2019. The position value for relative comparison index was used to define healthcare vulnerable areas. Cox proportional hazard regression was used to estimate the risk of mortality in pancreatic cancer patients according to healthcare vulnerable areas, and multiple logistic regression was used to estimate the difference in treatment.

Results

Among 1,975 patients, 279 (14.1%) and 1,696 (85.9%) lived in the healthcare vulnerable and non-vulnerable areas, respectively. Compared with the non-vulnerable area, pancreatic cancer patients in the vulnerable area had a higher risk of death at 3 months (hazard ratio [HR]: 1.33, 95% confidence interval [CI] = 1.06–1.67) and 6 months (HR: 1.23, 95% CI = 1.03–1.48). In addition, patients with pancreatic cancer in the vulnerable area were less likely to receive treatment than patients in the non-vulnerable area (odds ratio [OR]: 0.70, 95% CI = 0.52–0.94). This trend was further emphasized for chemotherapy (OR: 0.68, 95% CI = 0.48–0.95).

Conclusion

Patients with pancreatic cancer belonging to medically disadvantaged areas receive less treatment and have a higher risk of death. This may be a result of the late diagnosis of pancreatic cancer among these patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10027-2.

Association of institutional transition of cancer care with mortality in elderly patients with lung cancer: a retrospective cohort study using national claim data

Background

Although survival based outcomes of lung cancer patients have been well developed, institutional transition of cancer care, that is, when patients transfer from primary visiting hospitals to other hospitals, and mortality have not yet been explored using a large-scale representative population-based sample.

Methods

Data from the Korean National Elderly Sampled Cohort survey were used to identify patients with lung cancer who were diagnosed during 2005–2013 and followed up with for at least 1 year after diagnosis (3738 patients with lung cancer aged over 60 years). First, the authors examined the distribution of the study population by mortality, and Kaplan-Meier survival curves/log-rank test were used to compare mortality based on institutional transition of cancer care. Survival analysis using the Cox proportional hazard model was conducted after controlling for all other variables.

Results

Results showed that 1-year mortality was higher in patients who underwent institutional transition of cancer care during 30 days after diagnosis (44.2% vs. 39.7%, p = .027); however, this was not associated with 5-year mortality. The Cox proportional hazard model showed that patients who underwent institutional transition of cancer care during 30 days after diagnosis exhibited statistically significant associations with high mortality for 1 year and 5 years (1-year mortality, Hazard ratio [HR]: 1.279, p = .001; 5-year mortality, HR: 1.158, p = .002).

Conclusion

This study found that institutional transition of cancer care was associated with higher mortality among elderly patients with lung cancer. Future consideration should also be given to the limitation of patients’ choice when opting for institutional transition of care since there are currently no control mechanisms in this regard. Results of this study merit health policymakers’ attention.