Treatment Patterns and Survival Outcomes in Patients With Breast Cancer on Medicaid, Pre- and Post-Expansion

Authors:
Siran M. Koroukian Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH
Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH
Center for Community Health Integration, School of Medicine, Case Western Reserve University, Cleveland, OH

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Weichuan Dong Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH

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Jeffrey M. Albert Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH

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Uriel Kim Center for Community Health Integration, School of Medicine, Case Western Reserve University, Cleveland, OH

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Kirsten Eom Public Health Research Institute, The MetroHealth System and Case Western Reserve University, Cleveland, OH

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Johnie Rose Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH
Center for Community Health Integration, School of Medicine, Case Western Reserve University, Cleveland, OH

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Cynthia Owusu Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH
Department of Internal Medicine, University Hospitals of Cleveland, School of Medicine, Case Western Reserve University, Cleveland, OH

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Kristine M. Zanotti Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH
Department of Obstetrics and Gynecology, Gynecologic Oncology, University Hospitals of Cleveland, School of Medicine, Case Western Reserve University, Cleveland, OH

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Gregory Cooper Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH
Department of Internal Medicine, University Hospitals of Cleveland, School of Medicine, Case Western Reserve University, Cleveland, OH

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Jennifer Tsui Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA

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Background: The objective of this study was to evaluate the impact of Medicaid expansion on breast cancer treatment and survival among Medicaid-insured women in Ohio, accounting for the timing of enrollment in Medicaid relative to their cancer diagnosis and post-expansion heterogeneous Medicaid eligibility criteria, thus addressing important limitations in previous studies. Methods: Using 2011–2017 Ohio Cancer Incidence Surveillance System data linked with Medicaid claims data, we identified women aged 18 to 64 years diagnosed with local-stage or regional-stage breast cancer (n=876 and n=1,957 pre-expansion and post-expansion, respectively). We accounted for women’s timing of enrollment in Medicaid relative to their cancer diagnosis, and flagged women post-expansion as Affordable Care Act (ACA) versus non-ACA, based on their income eligibility threshold. Study outcomes included standard treatment based on cancer stage and receipt of lumpectomy, mastectomy, chemotherapy, radiation, hormonal treatment, and/or treatment for HER2-positive tumors; time to treatment initiation (TTI); and overall survival. We conducted multivariable robust Poisson and Cox proportional hazards regression analysis to evaluate the independent associations between Medicaid expansion and our outcomes of interest, adjusting for patient-level and area-level characteristics. Results: Receipt of standard treatment increased from 52.6% pre-expansion to 61.0% post-expansion (63.0% and 59.9% post-expansion in the ACA and non-ACA groups, respectively). Adjusting for potential confounders, including timing of enrollment in Medicaid, being diagnosed in the post-expansion period was associated with a higher probability of receiving standard treatment (adjusted risk ratio, 1.14 [95% CI, 1.06–1.22]) and shorter TTI (adjusted hazard ratio, 1.14 [95% CI, 1.04–1.24]), but not with survival benefits (adjusted hazard ratio, 1.00 [0.80–1.26]). Conclusions: Medicaid expansion in Ohio was associated with improvements in receipt of standard treatment of breast cancer and shorter TTI but not with improved survival outcomes. Future studies should elucidate the mechanisms at play.

Background

Medicaid expansion under the Affordable Care Act (ACA) is one of the most transformative health policy initiatives in the past decade,1 raising the income eligibility threshold from 90% to 138% of the federal poverty level and allowing childless adults with low incomes to enroll in Medicaid. In addition, thanks to the extensive outreach efforts of the ACA, known as the “welcome mat,”2 Medicaid expansion provided people who may have been eligible for Medicaid even before expansion the opportunity to join the program.

Breast cancer is the second most common cancer in women, claiming >40,000 lives annually.3 Prior studies comparing breast cancer treatment patterns and outcomes before and after Medicaid expansion have yielded mixed results.4 However, most studies have used the National Cancer Database5,6 or state cancer registry data,710 both of which lack detailed data on the enrollment history of patients with cancer in Medicaid before and after cancer diagnosis. Conversely, linked cancer registry and Medicaid files offer the benefit of conducting a detailed examination of cancer outcomes across Medicaid eligibility categories, including among those who enroll in Medicaid through the Breast and Cervical Cancer Prevention and Treatment Program.1117 The linked cancer registry and Medicaid files also allowed us to examine the heterogeneous composition of Medicaid enrollees17 and to study cancer outcomes in the context of individuals’ timing of enrollment in Medicaid relative to cancer diagnosis.14,15,1721 Indeed, patients with cancer who enrolled in Medicaid several months prior to their cancer diagnosis (or the “stably enrolled”) experience better outcomes than those enrolling in Medicaid just as they are diagnosed with cancer (or the “emergently enrolled”).17

From a policy standpoint, there have been several competing forces at play in the period following Medicaid expansion, potentially shaping cancer care and outcomes. On the one hand, Medicaid expansion likely improved receipt of standard treatment, shortened time to treatment initiation (TTI), and improved survival given the increased access to care and use of high-value care by Medicaid enrollees post-expansion.6,22 On the other hand, the projected shortage of oncologists and radiation oncologists,23 especially following implementation of the ACA,24 may have exacerbated wait times and lengthened TTI.

The net effect of these competing forces remains unknown. In this study, we evaluate the effect of Medicaid expansion on receipt of standard treatment, TTI, and survival, hypothesizing that (1) compared patients with cancer who were emergently enrolled, the stably enrolled would have a higher probability of receiving standard treatment and shorter TTI because they may have had a greater opportunity to connect to providers when enrolled in Medicaid for longer periods of time; (2) given their higher income, patients in the ACA group post-expansion may have a greater probability than their non-ACA counterparts to receive standard treatment and shorter TTI; and (3) overall survival may have improved post-expansion, with patients with breast cancer in the ACA group experiencing more favorable survival outcomes than their post-expansion non-ACA counterparts.

Methods

This study was approved by the Ohio Department of Health, Ohio Department of Medicaid, and the Case Western Reserve University Institutional Review Board (#20191777).

Data Sources

Consistent with our previous studies,1316 we linked the Ohio Cancer Incidence Surveillance System (OCISS) and Ohio Medicaid enrollment data using a deterministic linkage algorithm based on patients’ social security numbers, first and last names, and dates of birth.

With an estimated completeness of 98%,25 the OCISS captures incident cancer cases diagnosed among residents of Ohio, except in situ cancers of the cervix uteri and squamous and basal cell carcinoma of the skin. In addition to patient identifiers, the OCISS includes the address of residence at the time of cancer diagnosis, cancer anatomic site, the date of cancer diagnosis, cancer stage, first-course treatment modalities and the relevant dates of treatment initiation, and the date and cause of death, if applicable. Patients’ addresses were geocoded and linked with data at the census tract level from the 2013–2017 American Community Survey and the county level from the Health Resources and Services Administration to identify patients residing in Health Professional Shortage Areas (HPSAs).

From Medicaid enrollment files, we constructed the patient’s history of enrollment in Medicaid relative to their date of cancer diagnosis. We leveraged Medicaid claims data to identify comorbid conditions and treatment with trastuzumab (HER2 inhibitor targeted therapy) in patients with HER2-positive tumors. All other treatment modalities were identified from the OCISS, given that procedure codes in claims data were incomplete.

Study Population

Our study population included women aged 18 to 64 years at the time of diagnosis who were residents of Ohio, diagnosed with incident local-stage or regional-stage breast cancer in May 2011 through December 2017, and insured by Medicaid around the time of diagnosis. We excluded women who joined Medicaid through the Ohio Breast and Cervical Cancer Early Detection Program or with missing data on treatment modalities (n=2,833; see Figure S1 in the supplementary materials, available online with this article). We did not account for pregnancy status in our inclusion/exclusion criteria.

Variables of Interest

We examined the following outcomes:

  1. (1) Receipt of stage-appropriate standard treatment corresponding to our study period,26 as follows: For all patients, we required mastectomy or lumpectomy followed by radiation. For those diagnosed with regional-stage disease, we also required chemotherapy. Regardless of stage at diagnosis, we required patients with positive hormone receptors to receive hormonal treatment (Supplementary Table S1). Last, for patients with regional-stage disease with HER2-positive tumors, we required that they receive trastuzumab. These criteria are more stringent than those used elsewhere, in which definitive treatment was defined as surgery or neoadjuvant systemic therapy followed by surgery.27
  2. (2) TTI as a measure of receipt of timely treatment,27 defined as the time elapsed between the date of diagnosis and the first instance of the first treatment modality.
  3. (3) Survival, defined as the time elapsed between the date of diagnosis and the date of death from any cause. Patients without a date of death were censored at December 31, 2018.

Independent Variables

The main independent variable was a composite of Medicaid expansion and income eligibility threshold. Specifically, this 3-level variable included the following categories: pre-expansion for women diagnosed with breast cancer prior to 2014, post-expansion non-ACA for those diagnosed with breast cancer in 2014 or later and with an income eligibility threshold that would have qualified them for Medicaid regardless of expansion, and post-expansion ACA for women diagnosed in 2014 or later and with a higher income eligibility threshold. Identification of women in the latter 2 categories was based on the Medicaid Information Technology System Aid Categories, which incorporate the Modified Adjusted Gross Income levels. The pre-expansion category was used as the reference in our multivariable regression analyses. In a separate model, we also created a 2-level variable to analyze our outcomes of interest before and after Medicaid expansion, without accounting for income eligibility thresholds.

With regard to the timing of enrollment in Medicaid, consistent with our previous study,17 we considered women as stably enrolled if they enrolled in Medicaid at least 3 months prior to the diagnosis and remained continuously enrolled for 4 months postdiagnosis, and as emergently enrolled if they enrolled in Medicaid in the 3 months before or after cancer diagnosis.

Demographic variables included age at diagnosis, categorized as age <50, 50–54, 55–59, and 60–64 years; race/ethnicity, grouped as non-Hispanic Black, non-Hispanic White, and all other; and marital status, dichotomized as married versus not. Using the enrollment files, we identified women in the disability eligibility categories (henceforth referred to as “disabled”), and using claims data for services spanning from cancer diagnosis to 120 days postdiagnosis, we flagged the chronic conditions with which the patients presented based on Elixhauser’s list.28,29 We grouped these conditions as follows: no comorbidities, physical conditions only, mental health conditions and/or substance abuse disorders only, and physical conditions co-occurring with mental conditions and/or substance abuse disorders.

Area-level variables from the American Community Survey included median household income, educational attainment (percentage of adults with high school diploma), and percent uninsured at the census tract level, which we grouped in quartiles; HPSA (counties not HPSA, part HPSA, and whole HPSA); and county rurality to identify counties as Appalachian, non-Appalachian/non-Metropolitan, and non-Appalachian/Metropolitan.

Analytic Approach

In addition to detailed descriptive analysis, we conducted multivariable robust Poisson regression analysis for receipt of standard treatment and Cox proportional hazards models for TTI and survival. The robust Poisson regression model, which provides a robust standard error estimate and estimated covariate effects interpretable as risk ratios (RRs) is appropriate for a binary outcome as noted in the literature.30 Note that this is a loglinear model; that is, the log-transformed probability of the outcome (receipt of standard treatment) is modeled as a linear function of the covariates listed in Table 1. The proportional hazard assumption for each Cox model covariate was assessed using a score test.31 If the proportional hazard assumption was found to be violated for a given covariate, we used a stratified Cox model—in this case, by receipt of standard treatment.

Table 1.

Patient Characteristics of Study Population

Table 1.

Using these models, we conducted an analysis using a 3-level independent variable described earlier (pre-expansion, post-expansion ACA group, and post-expansion non-ACA group), which also accounted for the eligibility category post-expansion. We conducted an additional analysis to compare outcomes between pre-expansion and post-expansion periods. In both analyses, the pre-expansion group was used as the reference category.

All analyses were performed using R version 4.3.2 (R Foundation for Statistical Computing).

Results

Table 1 presents the characteristics of our study population. The number of patients in the post-expansion period was 2.2 times greater than in the pre-expansion period. However, only 35% (n=683) of those in the post-expansion period enrolled in Medicaid via the new ACA eligibility criteria under the ACA, whereas the remaining 65% (n=1,274) may have been eligible for Medicaid prior to the expansion. The lowest percentage of emergently enrolled women was in the non-ACA post-expansion group, at 13.1% (n=167), compared with 23.7% (n=208) in the pre-expansion group and 34.4% (n=235) in the ACA group. In addition, although the number of disabled women remain relatively unchanged from pre-expansion to post-expansion, their percentage dropped from 45.3% to 22.3%, with >98% of women in the post-expansion period represented in the non-ACA group.

Outcomes Between Pre-Expansion and Post-Expansion Periods

Figure 1 shows the effect of Medicaid expansion on our outcomes of interest after adjusting for patient demographics, timing of enrollment in Medicaid, tumor characteristics, and area-level attributes. Medicaid expansion was associated with a higher probability of receiving standard treatment (adjusted RR [aRR], 1.14 [95% CI, 1.06–1.22]) and shorter TTI (adjusted hazard ratio [aHR], 1.14 [95% CI, 1.04–1.24]) but not with improved overall survival (aHR, 1.00 [95% CI, 0.80–1.26]).

Figure 1.
Figure 1.

Effect of Medicaid expansion on receipt of standard treatment, time to treatment initiation, and survival among Medicaid beneficiaries diagnosed with local or regional breast cancer. All 3 models were adjusted by individual-level and area-level characteristics from Table 1.

Abbreviations: aHR, adjusted hazard ratio; aRR, adjusted risk ratio.

Citation: Journal of the National Comprehensive Cancer Network 22, 3; 10.6004/jnccn.2023.7104

Outcomes Accounting for Eligibility Category in the Post-Expansion Period

Table 2 presents more detailed findings from the multivariable models for receipt of standard treatment, TTI, and survival.

Table 2.

Multivariable Regression Analysis of Associations of Individual- and Area-Level Characteristics With Receipt of Standard Treatment, TTI, and Survival

Table 2.

With regard to receipt of standard treatment, we noted a 14% higher probability of receiving the standard treatment in each of the post-expansion ACA and non-ACA groups compared with women in the pre-expansion group (aRR, 1.14 [95% CI, 1.03–1.25] and 1.14 [95% CI, 1.05–1.23], respectively). Age, race/ethnicity, marital status, being disabled, emergently enrolled in Medicaid, and having multiple chronic conditions were not associated with receipt of standard treatment; however, women with regional-stage cancer at diagnosis (aRR, 0.71 [95% CI, 0.66–0.76]), positive HER2 receptor status (aRR, 0.70 [95% CI, 0.64–0.76]), and positive hormonal receptor status (aRR, 0.77 [95% CI, 0.72–0.83]) had a lower probability of receiving standard treatment than their counterparts with local-stage disease, negative HER2 receptor status, and negative hormonal status, respectively.

Table 2 also shows the factors associated with TTI from cancer diagnosis. Compared with women diagnosed in the pre-expansion period, those in the ACA and non-ACA groups diagnosed in the post-expansion period had a shorter TTI (aHR, 1.24 [95% CI, 1.11–1.39] and 1.10 [95% CI, 1.01–1.20], respectively). Other factors associated with shorter TTI included being non-Hispanic White versus non-Hispanic Black (aHR, 1.11 [95% CI, 1.01–1.22]) and being married versus nonmarried (aHR, 1.18 [95% CI, 1.08–1.29]). Compared with women with tumors with negative hormonal status, those with positive hormonal status had significantly longer TTI (aHR, 0.87 [95% CI, 0.80–0.95]).

Relative to survival outcomes, we note a greater percentage of patients who were censored in the post-expansion period compared with the pre-expansion period (90.6% [1,774/1,957] vs 77.3% [677/876]) due to the shorter follow-up period post-expansion. We observed no survival advantage in the post-expansion period, neither in the ACA nor the non-ACA group (aHR, 1.14 [95% CI, 0.79–1.64] and 0.97 [95% CI, 0.76–1.24], respectively). As expected, however, our results showed greater hazards of death in women diagnosed with regional-stage cancer compared with those diagnosed with localized disease (aHR, 2.31 [95% CI, 1.87–2.86]), among those who were disabled (aHR, 1.77 [95% CI, 1.39–2.26]), and among those with physical comorbid conditions only (aHR, 1.47 [95% CI, 1.08–1.99]) and physical comorbid conditions co-occurring with mental conditions and/or substance abuse disorders (aHR, 1.77 [95% CI, 1.31–2.38]) compared with those with no comorbid conditions.

Discussion

Our findings showed that Medicaid expansion was associated with increased receipt of standard treatment and shorter TTI but not with improved survival.

Thanks to the data granularity in the linked cancer registry and the Medicaid files, our study is among the few to examine these outcomes while accounting for individuals’ timing of enrollment in Medicaid relative to cancer diagnosis as well as by eligibility category in the post-expansion period. In addition, we were able to gain insight into the comorbidity burden borne by various subgroups of the Medicaid population, and learned that the highest percentage of women with no comorbid conditions were in the ACA group. Conversely, the highest percentage of women with physical and/or psychiatric conditions and/or substance abuse disorders was among women in the non-ACA post-expansion group (35.1%). Similarly, in the post-expansion period, patients with breast cancer who were disabled were almost exclusively represented in the non-ACA group.

Another strength of our study is its comprehensive approach to the analysis of cancer treatment in that it uses data from all treatment modalities to derive a composite measure for receipt of stage-appropriate standard treatment. Our findings are consistent with a recent study,32 which showed increased odds of patients receiving treatment if diagnosed in a state that expanded Medicaid. However, the latter study examined outcomes one treatment modality at a time and combined data from 3 states that adopted Medicaid expansion (Louisiana, Kentucky, and Arkansas), thus masking state-specific variations in outcomes. In addition, Medicaid expansion is seldom the only policy affecting outcomes, given that other local initiatives may also impact outcomes.33

Contrary to our hypothesis, we did not find a significant positive association between being stably enrolled and receipt of standard treatment of breast cancer, suggesting that Medicaid expansion may not have been able to influence referral pathways or quality of oncology care even though it had an impact on preventive screening access. As for the interpretation of why emergently enrolled women had shorter TTI, we speculate that a more advanced stage at diagnosis likely motivates patients to seek care faster than stably enrolled women. Another explanation may be that emergently enrolled women have already established care with a provider, with planned treatment initiation pending insurance arrangements. Interestingly, our findings indicated that Medicaid-insured patients with breast cancer benefited from Medicaid expansion regardless of their income eligibility threshold.

With regard to survival, we censored our data at December 31, 2018, and our data user agreement precluded us from obtaining data for a longer follow-up period. Although a greater percentage of patients were censored in the post-expansion rather than in the pre-expansion period, we do not believe that this difference invalidates our results. Nonetheless, it will be important to reexamine the impact of Medicaid expansion on breast cancer survival outcomes by including data from subsequent years.

Our study has some limitations. First, we were unable to describe the circumstances that led a patient with cancer to seek enrollment in Medicaid. Mixed-methods research is needed to gain a better insight into these findings and to elucidate the mechanisms at play. Second, except for trastuzumab, we identified all treatment modalities from cancer registry data because procedure codes in Medicaid claims data had high rates of missingness. Third, our data capture the 3 years before and 4 years after Medicaid expansion, and these trends may have changed in subsequent years,34 especially given the substantial increase in Medicaid enrollment postpandemic.35 An interrupted time series analysis might be considered as an alternative approach to the analysis. We decided against this approach because we felt the lengths of pre-expansion and post-expansion follow-ups in the present data were not long enough to determine clear trends (particularly for a survival outcome). However, this approach may be of interest in future studies. Fourth, we recognize the fact that certain treatment modalities may have been omitted by patient choice. Although we do not have the means to verify this in our data sources, changes in the representation of childless women with breast cancer in the post-expansion period implies that treatment choices in our study population may not be comparable between the pre-expansion and post-expansion periods given concerns over fertility preservation.36,37 Last, our data are specific to Ohio, and these results may not be generalizable to other states with Medicaid expansion. However, our nuanced and comprehensive analysis could only be reasonably conducted using a single state’s data due to difficulties in accessing and linking cancer registry and Medicaid data from multiple states.

Conclusions

In analyzing treatment and survival data in Ohio patients with breast cancer post–Medicaid expansion, we observed improvements in receipt of standard treatment and TTI but not in overall survival. Given the short follow-up period in our study, future studies should reexamine these outcomes with subsequent years’ data.

Acknowledgments

The authors wish to thank Mr. Long Vu for his review of our analytic approach, and Ms. Roberta Slocumb of Ohio Department of Health for her careful review of an earlier version of the manuscript.

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Submitted February 22, 2023; final revision received October 19, 2023. accepted for publication October 25, 2023. Published online March 19, 2024.

Author contributions: Study concept and design: Koroukian, Albert, Tsui. Data curation: Koroukian, Dong. Formal analysis: Koroukian, Dong, Albert. Funding acquisition: Koroukian, Albert, Owusu, Zanotti, Cooper, Tsui. Investigation: All authors. Methodology: Koroukian, Dong, Albert. Project administration: Koroukian, Dong. Resources: Koroukian. Software: Dong. Supervision: Koroukian, Albert. Validation: Koroukian, Albert. Visualization: Dong, Kim. Writing—original draft: Koroukian, Dong, Albert. Writing—review and editing: All authors.

Disclosures: The authors have disclosed that they have not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.

Funding: This study was supported by the American Cancer Society (132678-RSGI-19-213-01-CPHPS).

Previous presentation: Results were presented in part at the annual meeting of the American Association for Cancer Research Conference on The Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; September 16–19, 2022; Philadelphia, PA.

Supplementary material: Supplementary material associated with this article is available online at https://doi.org/10.6004/jnccn.2023.7104. The supplementary material has been supplied by the author(s) and appears in its originally submitted form. It has not been edited or vetted by JNCCN. All contents and opinions are solely those of the author. Any comments or questions related to the supplementary materials should be directed to the corresponding author.

Correspondence: Siran M. Koroukian, PhD, Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue WG-43, Cleveland, OH 44106-4945. Email: skoroukian@case.edu

Supplementary Materials

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  • Figure 1.

    Effect of Medicaid expansion on receipt of standard treatment, time to treatment initiation, and survival among Medicaid beneficiaries diagnosed with local or regional breast cancer. All 3 models were adjusted by individual-level and area-level characteristics from Table 1.

    Abbreviations: aHR, adjusted hazard ratio; aRR, adjusted risk ratio.

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