Unfavorable early-stage Hodgkin lymphoma: assessment of patient characteristics in a real-world setting.

Aim: Unfavorable prognostic factors among classical Hodgkin lymphoma (cHL) patients in the real-world setting have yet to be fully characterized. Methods: In this retrospective study using the ConcertAI Oncology Dataset, patient characteristics, unfavorable prognostic factors and treatment patterns were evaluated among patients diagnosed with cHL. Results: Among 324 adult cHL patients diagnosed 2016-2021, 16.1% were classified as early favorable, 32.7% early unfavorable and 51.2% advanced disease. Early unfavorable patients were younger and had a larger nodal mass. The prognostic factor B symptoms was most frequently documented in early unfavorable patients (59.4%), followed by bulky disease (46.2%), >3 involved lymph node regions (31.1%), and erythrocyte sedimentation rate ≥50 (25.5%). Conclusion: In this analysis of real-world data, we found that nearly a third of newly diagnosed cHL patients had early unfavorable disease. Our analysis also showed differences in the proportion of patients for each unfavorable factor among patients with early-stage unfavorable cHL.

What is this article about? Lymphoma is a type of blood cancer that develops when white blood cells grow out of control. This study looked at a certain type of lymphoma called classical Hodgkin lymphoma (cHL). Patients with cHL are put into groups based on risk factors. Risk factors mean the cancer had certain characteristics that make it more likely to spread to other body parts and more difficult to treat. These can be symptoms like drenching night sweats, unexplained fever, sudden weight loss, or large swellings of the infection fighting glands of the body.What did we do? We studied the risk factors of patients with cHL, using data from electronic medical records. What were the results? About a third of the patients in this study had early stage cHL with unfavorable risk factors, and over half of the patients had advanced stage cHL. The patients who had early stage cHL with unfavorable risk factors were younger and had a larger lump in a lymph node. More than half of the patients experienced drenching night sweats, unexplained fever, or weight loss of more than 10%. What do the results mean? We found that nearly a third of new cHL patients had early-stage cHL with unfavorable risk factors. We also showed differences in the number of patients with each unfavorable risk factor among patients with early-stage unfavorable cHL. This study can help doctors and researchers group patients and determine the best treatment or research study for patients who have cHL.

Immune-Based Cancer Treatment: Addressing Disparities in Access and Outcomes.

Avoidable differences in the care and outcomes of patients with cancer (i.e., cancer care disparities) emerge or worsen with discoveries of new, more effective approaches to cancer diagnosis and treatment. The rapidly expanding use of immunotherapy for many different cancers across the spectrum from late to early stages has, predictably, been followed by emerging evidence of disparities in access to these highly effective but expensive treatments. The danger that these new treatments will further widen preexisting cancer care and outcome disparities requires urgent corrective intervention. Using a multilevel etiologic framework that categorizes the targets of intervention at the individual, provider, health care system, and social policy levels, we discuss options for a comprehensive approach to prevent and, where necessary, eliminate disparities in access to the clinical trials that are defining the optimal use of immunotherapy for cancer, as well as its safe use in routine care among appropriately diverse populations. We make the case that, contrary to the traditional focus on the individual level in descriptive reports of health care disparities, there is sequentially greater leverage at the provider, health care system, and social policy levels to overcome the challenge of cancer care and outcomes disparities, including access to immunotherapy. We also cite examples of effective government-sponsored and policy-level interventions, such as the National Cancer Institute Minority-Underserved Community Oncology Research Program and the Affordable Care Act, that have expanded clinical trial access and access to high-quality cancer care in general.

Association of Medicaid Expansion Under the Affordable Care Act With Stage at Diagnosis and Time to Treatment Initiation for Patients With Head and Neck Squamous Cell Carcinoma.

Importance: Medicaid expansions as part of the Patient Protection and Affordable Care Act (ACA) are associated with decreases in the percentage of uninsured patients who have received a new diagnosis of cancer. Little is known about the association of Medicaid expansions with stage at diagnosis and time to treatment initiation (TTI) for patients with head and neck squamous cell carcinoma (HNSCC). Objective: To determine the association of Medicaid expansions as part of the ACA with stage at diagnosis and TTI for patients with HNSCC. Design, Setting, and Participants: A retrospective cohort study was conducted at Commission on Cancer-accredited facilities among 90 789 patients identified from the National Cancer Database aged 18 to 64 years with HNSCC that was diagnosed during the period from January 1, 2010, to December 31, 2016. Statistical analysis was conducted from February 18 to November 8, 2019. Main Outcomes and Measures: Outcome measures included health insurance coverage, stage at diagnosis, and TTI. Absolute percentage change in health insurance coverage, crude and adjusted difference in differences (DD) in absolute percentage change in coverage, stage at diagnosis, and TTI before (2010-2013) and after (2014-2016) ACA implementation were calculated for Medicaid expansion and nonexpansion states. Results: Of the 90 789 nonelderly adults with newly diagnosed HNSCC (mean [SD] age, 54.7 [7.0] years), 70 907 (78.1%) were men, 72 911 (80.3%) were non-Hispanic white, 52 142 (57.4%) were between 55 and 64 years of age, and 54 940 (60.5%) resided in states with an ACA Medicaid expansion. Compared with nonexpansion states, the percentage of patients with HNSCC with Medicaid increased more in expansion states after the implementation of the ACA (adjusted DD, 4.6 percentage points [95% CI, 3.7-5.4 percentage points]). The percentage of patients with localized disease (American Joint Committee on Cancer stage I-II) at diagnosis increased in expansion states compared with nonexpansion states for the overall cohort (adjusted DD, 2.3 percentage points [95% CI, 1.1-3.5 percentage points]) and for the subset of patients with nonoropharyngeal HNSCC (adjusted DD, 3.4 percentage points [95% CI, 1.5-5.2 percentage points]). The mean TTI did not differ between expansion and nonexpansion states for the cohort (adjusted DD, -12.7 percentage points [95% CI, -27.4 to 4.2 percentage points]) but improved for patients with nonoropharyngeal HNSCC (adjusted DD, -26.5 percentage points [95% CI, -49.6 to -3.4 percentage points]). Conclusions and Relevance: This study suggests that Medicaid expansions were associated with a greater increase in the percentage of patients with HNSCC with Medicaid coverage, an increase in the percentage of patients with localized disease at diagnosis for the overall cohort of patients with HNSCC, and improved TTI for patients with nonoropharyngeal HNSCC.

Factors Associated With Oncologist Discussions of the Costs of Genomic Testing and Related Treatments.

BACKGROUND: Use of genomic testing is increasing in the United States. Testing can be expensive, and not all tests and related treatments are covered by health insurance. Little is known about how often oncologists discuss costs of testing and treatment or about the factors associated with those discussions. METHODS: We identified 1220 oncologists who reported discussing genomic testing with their cancer patients from the 2017 National Survey of Precision Medicine in Cancer Treatment. Multivariable polytomous logistic regression analyses were used to assess associations between oncologist and practice characteristics and the frequency of cost discussions. All statistical tests were two-sided. RESULTS: Among oncologists who discussed genomic testing with patients, 50.0% reported often discussing the likely costs of testing and related treatments, 26.3% reported sometimes discussing costs, and 23.7% reported never or rarely discussing costs. In adjusted analyses, oncologists with training in genomic testing or working in practices with electronic medical record alerts for genomic tests were more likely to have cost discussions sometimes (odds ratio [OR] = 2.09, 95% confidence interval [CI] = 1.19 to 3.69) or often (OR = 2.22, 95% CI = 1.30 to 3.79), respectively, compared to rarely or never. Other factors statistically significantly associated with more frequent cost discussions included treating solid tumors (rather than only hematological cancers), using next-generation sequencing gene panel tests, having higher patient volume, and working in practices with higher percentages of patients insured by Medicaid, or self-paid or uninsured. CONCLUSIONS: Interventions targeting modifiable oncologist and practice factors, such as training in genomic testing and use of electronic medical record alerts, may help improve cost discussions about genomic testing and related treatments.

The impact of dependent coverage expansion under the Affordable Care Act on time to breast cancer treatment among young women.

INTRODUCTION: Breast cancer in young women tends to be more aggressive, but timely treatment may not be always available, particularly to those without health insurance. We aim to examine whether the dependent coverage expansion under the Affordable Care Act (ACA-DCE) implemented in 2010 was associated with changes in time to treatment among women diagnosed with early stage breast cancer. METHODS: A total of 7,176 patients diagnosed with early stage breast cancer in 2007-2009 (pre-ACA) and 2011-2013 (post-ACA) were identified from the National Cancer Database. A quasi-experimental design difference-in-differences (DD) approach was used, with patients aged 19-25 (targeted by the policy) considered as the intervention group, and patients aged 26-34 years (not affected by the policy) as the control group. Changes in the following treatment outcomes were examined: time from diagnosis to surgery, time from surgery to adjuvant chemotherapy, and time from adjuvant chemotherapy to radiation. RESULTS: Compared with the control group of patients aged 26-34, young patients aged 19-25 experienced a statistically nonsignificant decrease of 2.7 percentage points (95% CI [-1.2, 6.5]) in the uninsured rate. This did not translate into more reduction in delays to surgery (DD = 2.7 days, 95% CI [-3.2, 8.3]), chemotherapy (DD = -1.0 days, 95% CI [-7.2, 5.2]) or radiation (DD = 5.3 days, 95% CI [-15.6, 26.3]) in the younger cohort than the older cohort. CONCLUSIONS AND RELEVANCE: No significant changes in time to treatment were found among young women diagnosed with early stage breast cancer after the implementation of the ACA-DCE. Future studies examining impacts of health care policy reform on breast cancer care are warranted to include patients from low-income families and to consider effects from Medicaid expansion.

Factors That Contribute to Differences in Survival of Black vs White Patients With Colorectal Cancer.

BACKGROUND & AIMS: Previous studies reported that black vs white disparities in survival among elderly patients with colorectal cancer (CRC) were because of differences in tumor characteristics (tumor stage, grade, nodal status, and comorbidity) rather than differences in treatment. We sought to determine the contribution of differences in insurance, comorbidities, tumor characteristics, and treatment receipt to disparities in black vs white patients with CRC 18-64 years old. METHODS: We used data from the National Cancer Database, a hospital-based cancer registry database sponsored by the American College of Surgeons and the American Cancer Society, on non-Hispanic black (black) and non-Hispanic white (white) patients, 18-64 years old, diagnosed from 2004 through 2012 with single or first primary invasive stage I-IV CRC. Each black patient was matched, based on demographic, insurance, comorbidity, tumor, and treatment features, with 5 white patients, from partially overlapping subgroups, using propensity score and greedy matching algorithms. We used the Kaplan-Meier method to estimate 5-year survival and Cox proportional hazards models to generate hazard ratios. RESULTS: The absolute 5-year survival difference between black and white unmatched patients with CRC was 9.2% (57.3% for black patients vs 66.5% for white patients; P < .0001). The absolute difference in survival did not change after patient groups were matched for demographics, but decreased to 4.9% (47% relative decrease [4.3% of 9.2%]) when they were matched for insurance and to 2.3% when they were matched for tumor characteristics (26% relative decrease [2.4% of 9.2%]). Further matching by treatment did not reduce the difference in 5-year survival between black and white patients. In proportional hazards model, insurance and tumor characteristics matching accounted for the 54% and 27% excess risk of death in black patients, respectively. CONCLUSIONS: In an analysis of data from the National Cancer Database, we found that insurance coverage differences accounted for approximately one half of the disparity in survival rate of black vs white patients with CRC, 18-64 years old; tumor characteristics accounted for a quarter of the disparity. Affordable health insurance coverage for all populations could substantially reduce differences in survival times of black vs white patients with CRC.

Variations in Receipt of Curative-Intent Surgery for Early-Stage Non-Small Cell Lung Cancer (NSCLC) by State.

BACKGROUND: Previous studies reported racial and socioeconomic disparities in receipt of curative-intent surgery for early-stage non-small cell lung cancer (NSCLC) in the United States. We examined variation in receipt of surgery and whether the racial disparity varies by state. METHODS: Patients in whom stage I or II NSCLC was diagnosed from 2007 to 2011 were identified from 38 state and the District of Columbia population-based cancer registries compiled by the North American Association of Central Cancer Registries. Percentage of patients receiving curative-intent surgery was calculated for each registry. Adjusted risk ratios were generated by using modified Poisson regression to control for sociodemographic (e.g., age, sex, race, insurance) and clinical (e.g., grade, stage) factors. Non-Hispanic (NH) whites and Massachusetts were used as references for comparisons because they had the lowest uninsured rates. RESULTS: In all registries combined, 66.4% of patients with early-stage NSCLC (73,475 of 110,711) received curative-intent surgery. Receipt of curative-intent surgery for early-stage NSCLC varied substantially by state, ranging from 52.2% to 56.1% in Wyoming, Louisiana, and New Mexico to 75.2% to 77.2% in Massachusetts, New Jersey, and Utah. In a multivariable analysis, the likelihood of receiving curative-intent surgery was significantly lower in all but nine states/registries compared with Massachusetts, ranging from 7% lower in California to 25% lower in Wyoming. Receipt of curative-intent surgery for early-stage NSCLC was lower for NH blacks than for NH whites in every state, although statistically significant in Florida and Texas. CONCLUSIONS: Receipt of curative-intent surgery for early-stage NSCLC varies substantially across states in the United States, with northeastern states generally showing the highest rates. Further, receipt of treatment appeared to be lower in NH blacks than in NH whites in every state, although statistically significant in Florida and Texas.

Association of race/ethnicity, socioeconomic status, and breast cancer subtypes in the National Cancer Data Base (2010-2011).

To estimate the odds of breast cancer subtypes in minority populations versus non-Hispanic (NH) whites stratified by socioeconomic status (SES) [a composite of individual-level SES (insurance status) and area-level SES (median household income quartile from 2000 U.S. Census data)] using a large nationwide cancer database. We used the National Cancer Data Base to identify breast cancer cases diagnosed in 2010 and 2011, the only 2 years since U.S. cancer registries uniformly began collecting HER2 results. Breast cancer cases were classified into five subtypes based on hormone receptor (HR) and HER2 status: HR+/HER2-, HR+/HER2+, HR-/HER2+ (HER2-overexpressing), HR-/HER2- (TN), and unknown. A polytomous logistic regression was used to estimate odds ratios (ORs) comparing the odds of non-HR+/HER2-subtypes to HR+/HER2- for racial/ethnic groups controlling for and stratifying by SES, using a composite of insurance status and area-level income. Compared with NH whites, NH blacks and Hispanics were 84 % (OR = 1.84; 95 % CI 1.77-1.92) and 17 % (OR = 1.17; 95 % CI 1.11-1.24) more likely to have TN subtype versus HR+/HER2-, respectively. Asian/Pacific Islanders (API) had 1.45 times greater odds of being diagnosed with HER2-overexpressing subtype versus HR+/HER2- compared with NH whites (OR = 1.45; 95 % CI 1.31-1.61). We found similar ORs for race in high and low strata of SES. In a large nationwide hospital-based dataset, we found higher odds of having TN breast cancer in black women and of HER2-overexpressing in API compared with white women in every level of SES.