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IMPORTANCE: Patients who are uninsured and belong to racial and ethnic minority groups or have low socioeconomic status have suboptimal access to health care, likely affecting outcomes. The association of the Affordable Care Act’s Medicaid expansion with survival among patients with metastatic breast cancer is unknown. OBJECTIVE: To examine the association between Medicaid expansion and mortality disparity among patients with de novo stage IV breast cancer. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional, population-based study of survival using Cox proportional hazards regression and difference-in-difference (DID) analysis of data from the National Cancer Database and patients diagnosed as having de novo stage IV breast cancer between January 1, 2010, and December 31, 2016, residing in states that underwent Medicaid expansion on January 1, 2014. The preexpansion period was January 1, 2010, to December 31, 2013; the postexpansion period was January 1, 2014, to December 31, 2016. Data were analyzed between September 4, 2020, and November 16, 2021. EXPOSURES: Comparison of survival improvement between patients of racial and ethnic minority groups and White patients in the preexpansion and postexpansion periods. Because of small numbers in the specific racial and ethnic minority groups, these patients were combined into 1 category for comparisons. MAIN OUTCOMES AND MEASURES: Overall survival (OS) and 2-year mortality rate. RESULTS: Among 9322 patients included (mean [SD] age, 55 [7] years), 5077 were diagnosed in the preexpansion and 4245 in the postexpansion period. The racial and ethnic minority group comprised 2545 (27.3%), which included 500 (5.4%) Hispanic (any race), 1515 (16.3%) non-Hispanic Black, and 530 (5.7%) non-Hispanic other including 25 (0.3%) American Indian or Alaska Native, 357 (3.8%) Asian or Pacific Islander, and 148 (1.6%) unknown, and 6777 (72.7%) were in the White patient group. In the preexpansion period, White patients had increased OS compared with patients of racial and ethnic minority groups (adjusted hazard ratio [aHR], 1.22; 95% CI, 1.10-1.35); this difference was not observed in the postexpansion period (aHR, 0.96; 95% CI, 0.86-1.08). A reduction in 2-year mortality was observed between the preexpansion and postexpansion periods (32.2% vs 26.0%). The adjusted 2-year mortality decreased from 40.6% to 36.3% among White patients and from 45.6% to 35.8% among patients of racial and ethnic minority groups (adjusted DID, −5.5%; 95% CI, −9.5 to −1.6; P = .006). Among patients in the lowest income quartile (n = 1510), patients of racial and ethnic minority groups had an increased risk of death in the preexpansion period (aHR, 1.28; 95% CI, 1.01-1.61) but lower risk in the postexpansion period (aHR, 0.75; 95% CI, 0.59-0.95). In this subset of patients, those of racial and ethnic minority groups had a greater reduction in 2-year mortality compared with White patients (adjusted DID, −12.8%; 95% CI, −22.2 to −3.5; P = .007). CONCLUSIONS AND RELEVANCE: In this cross-sectional study, survival differences observed between patients of racial and ethnic minority groups and White patients in the preexpansion period were no longer present in the postexpansion period. A greater reduction in 2-year mortality was observed among patients of racial and ethnic minority groups compared with White patients. These results suggest that policies aimed at improving equity and increasing access to health care may reduce racial and ethnic disparities in breast cancer outcomes.

Importance: As the COVID-19 pandemic continues, understanding the clinical outcomes of patients with cancer and COVID-19 has become critically important. Objective: To compare the outcomes of patients with or without cancer who were diagnosed with COVID-19 and to identify the factors associated with mortality, mechanical ventilation, intensive care unit (ICU) stay, and hospitalization. Design, Setting, and Participants: This cohort study obtained data from the Optum de-identified COVID-19 electronic health record data set. More than 500 000 US adults who were diagnosed with COVID-19 from January 1 to December 31, 2020, were analyzed. Exposures: The patient groups were (1) patients without cancer, (2) patients with no recent cancer treatment, and (3) patients with recent cancer treatment (within 3 months before COVID-19 diagnosis) consisting of radiation therapy or systemic therapy. Main Outcomes and Measures: Mortality, mechanical ventilation, ICU stay, and hospitalization within 30 days of COVID-19 diagnosis were the main outcomes. Unadjusted rates and adjusted odds ratios (ORs) of adverse outcomes were presented according to exposure group. Results: A total of 507 307 patients with COVID-19 were identified (mean [SD] age, 48.4 [18.4] years; 281 165 women [55.4%]), of whom 493 020 (97.2%) did not have cancer. Among the 14 287 (2.8%) patients with cancer, 9991 (69.9%) did not receive recent treatment and 4296 (30.1%) received recent treatment. In unadjusted analyses, patients with cancer, regardless of recent treatment received, were more likely to have adverse outcomes compared with patients without cancer (eg, mortality rate: 1.6% for patients without cancer, 5.0% for patients with no recent cancer treatment, and 7.8% for patients with recent cancer treatment). After adjustment, patients with no recent cancer treatment had similar or better outcomes than patients without cancer (eg, mortality OR, 0.93 [95% CI, 0.84-1.02]; mechanical ventilation OR, 0.61 [95% CI, 0.54-0.68]). In contrast, a higher risk of death (OR, 1.74; 95% CI, 1.54-1.96), ICU stay (OR, 1.69; 95% CI, 1.54-1.87), and hospitalization (OR, 1.19; 95% CI, 1.11-1.27) was observed in patients with recent cancer treatment. Compared with patients with nonmetastatic solid tumors, those with metastatic solid tumors and hematologic malignant neoplasms had worse outcomes (eg, mortality OR, 2.36 [95% CI, 1.96-2.84]; mechanical ventilation OR, 0.87 [95% CI, 0.70-1.08]). Recent chemotherapy and chemoimmunotherapy were also associated with worse outcomes (eg, chemotherapy mortality OR, 1.84 [95% CI, 1.51-2.26]). Conclusions and Relevance: This cohort study found that patients with recent cancer treatment and COVID-19 had a significantly higher risk of adverse outcomes, and patients with no recent cancer treatment had similar outcomes to those without cancer. The findings have risk stratification and resource use implications for patients, clinicians, and health systems.

Importance Triple-negative breast cancer (TNBC) classified by transcriptional profiling as the mesenchymal subtype frequently harbors aberrations in the phosphoinositide 3-kinase (PI3K) pathway, raising the possibility of targeting this pathway to enhance chemotherapy response. Up to 30% of mesenchymal TNBC can be classified histologically as metaplastic breast cancer, a chemorefractory group of tumors with a mixture of epithelial and mesenchymal components identifiable by light microscopy. While assays to identify mesenchymal TNBC are under development, metaplastic breast cancer serves as a clinically identifiable surrogate to evaluate potential regimens for mesenchymal TNBC. Objective To assess safety and efficacy of mammalian target of rapamycin (mTOR) inhibition in combination with liposomal doxorubicin and bevacizumab in patients with advanced metaplastic TNBC. Design, Setting, and Participants Phase 1 study with dose escalation and dose expansion at the University of Texas MD Anderson Cancer Center of patients with advanced metaplastic TNBC. Patients were enrolled from April 16, 2009, to November 4, 2014, and followed for outcomes with a cutoff date of November 1, 2015, for data analysis. Interventions Liposomal doxorubicin, bevacizumab, and the mTOR inhibitors temsirolimus or everolimus using 21-day cycles. Main Outcomes and Measures Safety and response. When available, archived tissue was evaluated for aberrations in the PI3K pathway. Results Fifty-two women with metaplastic TNBC (median age, 58 years; range, 37-79 years) were treated with liposomal doxorubicin, bevacizumab, and temsirolimus (DAT) (N = 39) or liposomal doxorubicin, bevacizumab, and everolimus (DAE) (N = 13). The objective response rate was 21% (complete response = 4 [8%]; partial response = 7 [13%]) and 10 (19%) patients had stable disease for at least 6 months, for a clinical benefit rate of 40%. Tissue was available for testing in 43 patients, and 32 (74%) had a PI3K pathway aberration. Presence of PI3K pathway aberration was associated with a significant improvement in objective response rate (31% vs 0%; P = .04) but not clinical benefit rate (44% vs 45%; P > .99). Conclusions and Relevance Using metaplastic TNBC as a surrogate for mesenchymal TNBC, DAT and DAE had notable activity in mesenchymal TNBC. Objective response was limited to patients with PI3K pathway aberration. A randomized trial should be performed to test DAT and DAE for metaplastic TNBC, as well as nonmetaplastic, mesenchymal TNBC, especially when PI3K pathway aberrations are identified.

Importance We previously described and validated a breast cancer staging system (CPS+EG, clinical-pathologic scoring system incorporating estrogen receptor–negative disease and nuclear grade 3 tumor pathology) for assessing prognosis after neoadjuvant chemotherapy using pretreatment clinical stage, posttreatment pathologic stage, estrogen receptor (ER) status, and grade. Development of the CPS+EG staging system predated routine administration of trastuzumab in patients with ERBB2 -positive disease (formerly HER2 or HER2/neu ). Objective To validate the CPS+EG staging system using the new definition of ER positivity (≥1%) and to develop an updated staging system (Neo-Bioscore) that incorporates ERBB2 status into the previously developed CPS+EG. Design, Setting, and Participants Retrospective review of data collected prospectively from January 2005 through December 2012 on patients with breast cancer treated with neoadjuvant chemotherapy at The University of Texas MD Anderson Cancer Center. Main Outcomes and Measure Prognostic scores were computed using 2 versions of the CPS+EG staging system, one with ER considered positive if it measured 10% or higher, the other with ER considered positive if it measured 1% or higher. Fits of the Cox proportional hazards model for the 2 sets of prognostic scores were compared using the Akaike Information Criterion (AIC). Status of ERBB2 was added to the model, and the likelihood ratio test was used to determine improvement in fit. Results A total of 2377 patients were included; all were women (median age, 50 years [range, 21-87 years]); ER status was less than 1% in 28.9%, 1% to 9% in 8.3%, and 10% or higher in 62.8%; 591 patients were ERBB2 positive. Median follow-up was 4.2 years (range, 0.5-11.7 years). Five-year disease-specific survival was 89% (95% CI, 87%-90%). Using 1% or higher as the cutoff for ER positivity, 5-year disease-specific survival estimates determined using the CPS+EG stage ranged from 52% to 98%, thereby validating our previous finding that the CPS+EG score facilitates more refined categorization into prognostic subgroups than clinical or final pathologic stage alone. The AIC value for this model was 3333.06, while for a model using 10% or higher as the cutoff for ER positivity, it was 3333.38, indicating that the model fits were nearly identical. The improvement in fit of the model when ERBB2 status was added was highly significant, with 5-year disease-specific survival estimates ranging from 48% to 99% ( P ERBB2 into the staging system defined the Neo-Bioscore, which provided improved stratification of patients with respect to prognosis. Conclusions and Relevance The Neo-Bioscore improves our previously validated staging system and allows its application in ERBB2 -positive patients. We recommend that treatment response and biologic markers be incorporated into the American Joint Committee on Cancer staging system.

The American Joint Committee on Cancer (AJCC) eighth edition staging manual introduced a new prognostic stage for breast cancer incorporating biologic factors in addition to traditional anatomic factors.To perform a validation study of the AJCC eighth edition prognostic stage in a single-institution cohort and a large population database.Patients with breast cancer treated with surgery as an initial intervention were identified in a prospective institutional database from The University of Texas MD Anderson Cancer Center and the California Cancer Registry. Vital status data were complete through December 31, 2016, in The University of Texas MD Anderson cohort and through December 31, 2014, in the California Cancer Registry cohort. Patients receiving neoadjuvant systemic therapy, those with inflammatory or rare breast cancers, and those with unknown clinicopathologic factors were excluded. Factors evaluated included T, N, and M categories and tumor grade, as well as estrogen receptor, progesterone receptor, and HER2 status.Disease-specific survival was calculated by the Kaplan-Meier method. The Harrell concordance index (C index) was used to quantify models' predictive performance, and the Akaike information criterion (AIC) was used to compare model fits.A total of 3327 patients with stage I to IIIC breast cancer treated between 2007 and 2013 at The University of Texas MD Anderson Cancer Center (median follow-up of 5 years) with complete clinicopathologic data were identified. Compared with the AJCC anatomic stage, the prognostic stage upstaged 29.5% of patients and downstaged 28.1%. The prognostic stage (C index, 0.8357 and AIC, 816.8) provided more accurate stratification with respect to disease-specific survival than the anatomic stage (C index, 0.737 and AIC, 1039.8) (P .001 for the C index). A total of 54 727 patients with stage I to IV breast cancer treated between 2005 and 2009 were identified in the California Cancer Registry (median follow-up of 7 years). The prognostic stage upstaged 31.0% of patients and downstaged 20.6%. The prognostic stage (C index, 0.8426 and AIC, 80 661.68) performed better than the anatomic stage (C index, 0.8097 and AIC, 81 577.89) (P .001 for the C index).The prognostic stage provided more accurate prognostic information than the anatomic stage alone in both a single-institution cohort and a large population database, thereby supporting its use in breast cancer staging.

This analysis of patients with breast cancer insured through the health insurance marketplace assesses their quality of care by examining patterns of radiation therapy.