Association of Medicaid expansion and insurance status, cancer stage, treatment and mortality among patients with cervical cancer

Effect of Medicaid expansion on cancer treatment and survival among Medicaid beneficiaries and the uninsured

BACKGROUND

The Affordable Care Act expanded Medicaid coverage for people with low income in the United States. Expanded insurance coverage could promote more timely access to cancer treatment, which could improve overall survival (OS), yet the long-term effects of Medicaid expansion (ME) remain unknown. We evaluated whether ME was associated with improved timely treatment initiation (TTI) and 3-year OS among patients with breast, cervical, colon, and lung cancers who were affected by the policy.

METHODS

Medicaid-insured or uninsured patients aged 40-64 with stage I-III breast, cervical, colon, or non-small cell lung cancer within the National Cancer Database (NCDB). A difference-in-differences (DID) approach was used to compare changes in TTI (within 60 days) and 3-year OS between patients in ME states versus nonexpansion (NE) states before (2010-2013) and after (2015-2018) ME. Adjusted DID estimates for TTI and 3-year OS were calculated using multivariable linear regression and Cox proportional hazards regression models, respectively.

RESULTS

ME was associated with a relative increase in TTI within 60 days for breast (DID = 4.6; p < 0.001), cervical (DID = 5.0 p = 0.013), and colon (DID = 4.0, p = 0.008), but not lung cancer (p = 0.505). In Cox regression analysis, ME was associated with improved 3-year OS for breast (DID hazard ratio [HR] = 0.82, p = 0.009), cervical (DID-HR = 0.81, p = 0.048), and lung (DID-HR = 0.87, p = 0.003). Changes in 3-year OS for colon cancer were not statistically different between ME and NE states (DID-HR, 0.77; p = 0.075).

CONCLUSIONS

Findings suggest that expanded insurance coverage can improve treatment and survival outcomes among low income and uninsured patients with cancer. As the debate surrounding ME continues nationwide, our findings serve as valuable insights to inform the development of policies aimed at fostering accessible and affordable healthcare for all.

Accounting for Medicaid expansion and regional policy and programs to advance equity in cancer prevention in the United States

BACKGROUND

Many studies compare state-level outcomes to estimate changes attributable to Medicaid expansion. However, it is imperative to conduct more granular, demographic-level analyses to inform current efforts on cancer prevention among low-income adults. Therefore, the authors compared the volume of patients with cancer and disease stage at diagnosis in Ohio, which expanded its Medicaid coverage in 2014, with those in Georgia, a nonexpansion state, by cancer site and health insurance status.

METHODS

The authors used state cancer registries from 2010 to 2017 to identify adults younger than 64 years who had incident female breast cancer, cervical cancer, or colorectal cancer. Multivariable Poisson regression was conducted by cancer type, health insurance, and state to examine the risk of late-stage disease, adjusting for individual-level and area-level covariates. A difference-in-differences framework was then used to estimate the differences in risks of late-stage diagnosis in Ohio versus Georgia.

RESULTS

In Ohio, the largest increase in all three cancer types was observed in the Medicaid group after Medicaid expansion. In addition, significantly reduced risks of late-stage disease were observed among patients with breast cancer on Medicaid in Ohio by approximately 7% and among patients with colorectal cancer on Medicaid in Ohio and Georgia after expansion by approximately 6%. Notably, the authors observed significantly reduced risks of late-stage diagnosis among all patients with colorectal cancer in Georgia after expansion.

CONCLUSIONS

More early stage cancers in the Medicaid-insured and/or uninsured groups after expansion suggest that the reduced cancer burden in these vulnerable population subgroups may be attributed to Medicaid expansion. Heterogeneous risks of late-stage disease by cancer type highlight the need for comprehensive evaluation frameworks, including local cancer prevention efforts and federal health policy reforms.

PLAIN LANGUAGE SUMMARY

This study looked at how Medicaid expansion affected cancer diagnosis and treatment in two states, Ohio and Georgia. The researchers found that, after Ohio expanded their Medicaid program, there were more patients with cancer among low-income adults on Medicaid. The study also found that, among people on Medicaid, there were lower rates of advanced cancer at the time of diagnosis for breast cancer and colon cancer in Ohio and for colon cancer in Georgia. These findings suggest that Medicaid expansion may be effective in reducing the cancer burden among low-income adults.

A health equity framework to support the next generation of cancer population simulation models

Over the past 2 decades, population simulation modeling has evolved as an effective public health tool for surveillance of cancer trends and estimation of the impact of screening and treatment strategies on incidence and mortality, including documentation of persistent cancer inequities. The goal of this research was to provide a framework to support the next generation of cancer population simulation models to identify leverage points in the cancer control continuum to accelerate achievement of equity in cancer care for minoritized populations. In our framework, systemic racism is conceptualized as the root cause of inequity and an upstream influence acting on subsequent downstream events, which ultimately exert physiological effects on cancer incidence and mortality and competing comorbidities. To date, most simulation models investigating racial inequity have used individual-level race variables. Individual-level race is a proxy for exposure to systemic racism, not a biological construct. However, single-level race variables are suboptimal proxies for the multilevel systems, policies, and practices that perpetuate inequity. We recommend that future models designed to capture relationships between systemic racism and cancer outcomes replace or extend single-level race variables with multilevel measures that capture structural, interpersonal, and internalized racism. Models should investigate actionable levers, such as changes in health care, education, and economic structures and policies to increase equity and reductions in health-care-based interpersonal racism. This integrated approach could support novel research approaches, make explicit the effects of different structures and policies, highlight data gaps in interactions between model components mirroring how factors act in the real world, inform how we collect data to model cancer equity, and generate results that could inform policy.

Establishment of prediction models to predict survival among patients with cervical cancer based on socioeconomic factors: a retrospective cohort study based on the SEER Database

OBJECTIVE

To construct and validate predictive models based on socioeconomic factors for predicting overall survival (OS) in cervical cancer and compare them with the American Joint Council on Cancer (AJCC) staging system.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

We extracted data from 5954 patients who were diagnosed with cervical cancer between 2007 and 2011 from the Surveillance, Epidemiology, and End Results Database. This database holds data related to cancer incidence from 18 population-based cancer registries in the USA.

OUTCOME MEASURES

1-year and 5-year OS.

RESULTS

Of the total 5954 patients, 5820 patients had 1-year mortality and 5460 patients had 5-year mortality. Lower local education level [Hazard ratios (HR): 1.15, 95% confidence interval (CI): 1.04 to 1.27, p= 0.005] and being widowed (HR 1.28, 95% CI 1.06 to 1.55, p=0.009) were associated with a worse OS for patients with cervical cancer. Having insurance (HR 0.75, 95% CI 0.62 to 0.90, p=0.002), earning a local median annual income of ≥US$56 270 (HR 0.83, 95% CI 0.75 to 0.92, p<0.001) and being married (HR 0.79, 95% CI 0.69 to 0.89, p<0.001) were related to better OS in patients with cervical cancer. The predictive models based on socioeconomic factors and the AJCC staging system had a favourable performance for predicting OS in cervical cancer compared with the AJCC staging system alone.

CONCLUSION

Our proposed predictive models exhibit superior predictive performance, which may highlight the potential clinical application of incorporating socioeconomic factors in predicting OS in cervical cancer.

In pursuit of equity in cancer care: moving beyond the Affordable Care Act

Although Medicaid Expansion under the Patient Protection and Affordable Care Act (ACA) has been associated with many improvements for patients with cancer, Snyder et al. provide evidence demonstrating the persistence of racial disparities in cancer. This Editorial describes why insurance coverage alone does not ensure access to health care, highlights various manifestations of structural racism that constitute barriers to access beyond the direct costs of care, and calls for not just equality, but equity, in cancer care.