Automated patient selection and care coaches to increase advance care planning for cancer patients.

BACKGROUND: Advance care planning/serious illness conversations can help clinicians understand patients' values and preferences. There are limited data on how to increase these conversations, and their effect on care patterns. We hypothesized that using a machine learning survival model to select patients for serious illness conversations, along with trained care coaches to conduct the conversations, would increase uptake in cancer patients at high risk of short-term mortality. METHODS: We conducted a cluster-randomized stepped wedge study on the physician level. Oncologists entered the intervention condition in a random order over six months. Adult patients with metastatic cancer were included. Patients with <2 year computer-predicted survival and no prognosis documentation were classified as high-priority for serious illness conversations. In the intervention condition, providers received automated weekly emails highlighting high-priority patients and were asked to document prognosis for them. Care coaches reached out to these patients to conduct the remainder of the conversation. The primary endpoint was proportion of visits with prognosis documentation within 14 days. RESULTS: 6,372 visits in 1,825 patients were included in the primary analysis. The proportion of visits with prognosis documentation within 14 days was higher in the intervention condition than control condition: 2.9% vs 1.1% (adjusted odds ratio 4.3, p < .0001). The proportion of visits with advance care planning documentation was also higher in the intervention condition: 7.7% vs 1.8% (adjusted odds ratio 14.2, p < .0001). In high-priority visits, advance care planning documentation rate in intervention/control visits was 24.2% vs 4.0%. CONCLUSION: The intervention increased documented conversations, with contributions by both providers and care coaches.

Racial Disparities in Cancer Stage at Diagnosis and Survival for Adolescents and Young Adults.

Importance: There are limited studies assessing stage at diagnosis and risk of death among all 5 federally defined races in the US among adolescent and young adult (AYA) patients with cancer. Objective: To identify racial disparities in stage at diagnosis and survival among AYA patients with cancer. Design, Setting, and Participants: This retrospective cohort study used data from a US national hospital-based oncology database on AYA patients, aged 15 to 39 years, with the 10 deadliest cancers among AYA patients who received a diagnosis from January 1, 2004, to December 31, 2017, with 6 months or more of follow-up. Analyses by race were categorized by the 5 federally defined races in the US: American Indian or Alaska Native, Asian, Black, Native Hawaiian or Other Pacific Islander, and non-Hispanic White (hereafter, White). White patients served as the majority reference group. Statistical analysis was performed from November 2022 to September 2023. Main Outcomes and Measures: The primary end points were late stage at diagnosis (logistic regression with adjusted odds ratios [AORs] and 95% CIs) and overall survival (log-rank tests and Cox proportional hazards regression with adjusted hazard ratios [AHRs] and 95% CIs). Results: A total of 291 899 AYA patients (median age, 33 years [IQR, 28-37 years]; 186 549 female patients [64%]; 189 812 [65%] with stage I or II cancers) were evaluated. The cohort included 1457 American Indian or Alaska Native patients (1%), 8412 Asian patients (3%), 40 851 Black patients (14%), 987 Native Hawaiian or Other Pacific Islander patients (0.3%), and 240 192 White patients (82%). Cancers included breast (n = 79 195 [27%]), lymphoma (n = 45 500 [16%]), melanoma (n = 36 724 [13%]), testis (n = 31 413 [11%]), central nervous system (n = 26 070 [9%]), colon or rectum (n = 22 545 [8%]), cervix (n = 20 923 [7%]), sarcoma (n = 14 951 [5%]), ovary (n = 8982 [3%]), and lung (n = 5596 [2%]). Risk of late-stage diagnosis was higher for Asian (AOR, 1.20; 95% CI, 1.14-1.26), Black (AOR, 1.40; 95% CI, 1.36-1.43), and Native Hawaiian or Other Pacific Islander (AOR, 1.34; 95% CI, 1.16-1.55) patients compared with White patients. Overall survival differed by race for all cancer sites, except cancers of the central nervous system and ovary. Risk of death was higher for American Indian or Alaska Native (AHR, 1.15; 95% CI, 1.02-1.30), Black (AHR, 1.22; 95% CI, 1.19-1.26), and Native Hawaiian or Other Pacific Islander (AHR, 1.25; 95% CI, 1.09-1.44) patients but lower for Asian patients (AHR, 0.90; 95% CI, 0.85-0.95) compared with White patients. Conclusions and Relevance: This cohort study of AYA patients suggests that stage at diagnosis and survival varied across races for the 10 deadliest AYA cancers. These results support the need for tailored interventions and informed public policy to achieve cancer care equity for all races.

Spending Analysis of Machine Learning-Based Communication Nudges in Oncology.

BACKGROUND: Serious illness conversations (SICs) in the outpatient setting may improve mood and quality of life among patients with cancer and decrease aggressive end-of-life care. Interventions informed by behavioral economics may increase rates of SICs between oncology clinicians and patients, but the impact of these interventions on end-of-life spending is unknown. METHODS: This study is a secondary analysis of a stepped-wedge cluster randomized, controlled trial that involved nine medical oncology practices and their high-risk patients at a large academic institution between June 2019 and April 2020. The study included 1187 patients who were identified by a machine-learning algorithm as high risk of 180-day mortality and who died by December 2020. The patients were randomly assigned to standard of care (controls) or to a behavioral intervention designed to increase clinician-initiated SICs. We abstracted spending - defined as inflation-adjusted costs for acute care (inpatient plus emergency room), office/outpatient care, intravenous systemic therapy, other therapy (e.g., radiation), long-term care, and hospice - from the institution's accounting system, and we captured spending at inpatient, outpatient, and pharmacy settings. To evaluate intervention impacts on spending, we used a two-part model, first using logistic regression to model zero versus nonzero spending and second using generalized linear mixed models with gamma distribution and log-link function to model daily mean spending in the last 180days of life. Models were adjusted for clinic and wedge fixed effects, and they were clustered at the oncologist level. For all patients with at least one SIC within 6 months of death, we also calculated their mean daily spending before and after SIC. RESULTS: Median age at death was 68years (interquartile range, 15.5), 317 patients (27%) were Black or of ethnicities other than white, and 448 patients (38%) had an SIC. The intervention was associated with lower unadjusted mean daily spending in the last 6 months of life for the intervention group versus controls ($377.96 vs. $449.92; adjusted mean difference, -$75.33; 95% confidence interval, -$136.42 to -$14.23; P=0.02), translating to $13,747 total adjusted savings per decedent and $13 million in cumulative savings across all decedents in the intervention group. Compared with controls, patients in the intervention group incurred lower mean daily spending for systemic therapy (adjusted difference, -$44.59; P=0.001), office/outpatient care (-$9.62; P=0.001), and other therapy (-$8.65; P=0.04). The intervention was not associated with differences in end-of-life spending for acute care, long-term care, or hospice. Results were consistent for spending in the last 1 and 3 months of life and after adjusting for age, race, and ethnicity. For patients with SICs, mean daily spending decreased by $37.92 following the first SIC ($329.87 vs. $291.95). CONCLUSIONS: A machine learning-based, behaviorally informed intervention to prompt SICs led to end-of-life savings among patients with cancer, driven by decreased systemic therapy and outpatient spending. (Funded by the Penn Center for Precision Medicine and the National Institutes of Health; ClinicalTrials.gov number, NCT03984773.).

Race and Ethnicity Representation in Phase 2/3 Oncology Clinical Trial Publications: A Systematic Review.

Importance: The five 1997 Office of Management and Budget races in the US include American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White, with Hispanic ethnicity. Despite the Affordable Care Act mandating Office of Management and Budget-based collecting and reporting standards, race and ethnicity publishing in medical journals is inconsistent, despite being necessary to achieve health equity. Objective: To quantify race and ethnicity reporting rates and calculate representation quotients (RQs) in published oncology clinical trials. Evidence Review: In this systematic review, PubMed and Embase were queried for phase 2/3 clinical trials of the 6 most common noncutaneous solid cancers, published between January 1, 2012, and December 31, 2022, in 4 high-impact journals. Trial characteristics were recorded. The RQs for each race and ethnicity were calculated by dividing the percent of representation in each clinical trial publication by the percent of year-matched, site-specific incident cancers in the US, compared with Kruskal-Wallis tests with Bonferroni correction (BC). Reporting was compared between journal publications and ClinicalTrials.gov. Findings: Among 1202 publications evaluated, 364 met inclusion criteria: 16 JAMA, 241 Journal of Clinical Oncology, 19 Lancet, and 88 New England Journal of Medicine. Publications included 268 209 patients (171 132 women [64%]), with a median of 356 (IQR, 131-800) patients per publication. Reported race and ethnicity included American Indian or Alaska Native in 52 (14%) publications, Asian in 196 (54%), Black or African American in 215 (59%), Hispanic in 67 (18%), Native Hawaiian or Other Pacific Islander in 28 (8%), and White in 254 (70%). Median RQ varied across race (P < .001 BC), with 1.04 (IQR, 0.09-4.77) for Asian, 0.98 (IQR, 0.86-1.06) for White, 0.42 (IQR, 0.12-0.75) for Black or African American, and 0.00 (IQR, 0.00-0.00) for both American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander patients. Sensitivity analyses showed similar findings on subset analysis for US-only clinical trials. There was significantly less race and ethnicity reporting in the clinical trial publications compared with ClinicalTrials.gov documentation for American Indian or Alaska Native (14% vs 45%; P < .001 per McNemar χ2 test with continuity correction [MC]) and Native Hawaiian or Other Pacific Islander (8% vs 43%; P < .001 MC). Conclusions and Relevance: While most phase 2/3 oncology clinical trials published in high-impact journals report race and ethnicity, most did not report American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander racial categories. Our findings support a call to action for consistent journal policies and transparent race and ethnicity reporting, in alignment with Affordable Care Act-concordant race and ethnicity federal reporting requirements.

Coaches Activating, Reaching, and Engaging Patients to Engage in Advance Care Planning: A Randomized Clinical Trial.

Importance: Advance care planning (ACP) remains low among patients with advanced cancer. Multilevel interventions compared with clinician-level interventions may be more effective in improving ACP. Objective: To evaluate whether a multilevel intervention could improve clinician-documented ACP compared with a clinician-level intervention alone. Design, Setting, and Participants: This randomized clinical trial, performed from September 12, 2019, through May 12, 2021, included adults with advanced genitourinary cancers at an academic, tertiary hospital. Data analysis was performed by intention to treat from May 1 to August 10, 2023. Intervention: Participants were randomized 1:1 to a 6-month patient-level lay health worker structured ACP education along with a clinician-level intervention composed of 3-hour ACP training and integration of a structured electronic health record documentation template (intervention group) or to the clinician-level intervention alone (control group). Main Outcome and Measures: The primary outcome was ACP documentation in the electronic health record by the oncology clinician within 12 months after randomization. Secondary, exploratory outcomes included shared decision-making, palliative care use, hospice use, emergency department visits, and hospitalizations within 12 months after randomization. Results: Among 402 participants enrolled in the study, median age was 71 years (range, 21-102 years); 361 (89.8%) identified as male. More intervention group participants had oncology clinician-documented ACP than control group participants (82 [37.8%] vs 40 [21.6%]; odds ratio [OR], 2.29; 95% CI, 1.44-3.64). At 12-month follow-up, more intervention than control group participants had palliative care (72 [33.2%] vs 25 [13.5%]; OR, 3.18; 95% CI, 1.91-5.28) and hospice use (49 [22.6%] vs 19 [10.3%]; OR, 2.54; 95% CI, 1.44-4.51). There were no differences in the proportion of participants between groups with an emergency department visit (65 [30.0%] vs 61 [33.0%]; OR, 0.87; 95% CI, 0.57-1.33) or hospitalization (89 [41.0%] vs 85 [46.0%]; OR, 0.82; 95% CI, 0.55-1.22). Intervention group participants had fewer hospitalizations than control group participants (mean [SD] number of hospitalizations per year, 0.87 [1.60] vs 1.04 [1.77]) and a lower risk of hospitalization (incidence rate ratio, 0.80; 95% CI, 0.65-0.98). Conclusions and Relevance: In this randomized clinical trial, a multilevel intervention improved oncology clinician-documented ACP compared with a clinician-level intervention alone for patients with genitourinary cancer. The intervention is one approach to effectively increase ACP among patients with cancer. Trial Registration: ClinicalTrials.gov Identifier: NCT03856463.

Long-Term Engagement of Patients With Advanced Cancer: Results From the EPAC Randomized Clinical Trial.

Importance: The long-term effect of interventions that assist patients with establishing their end-of-life care preferences among patients with cancer remain relatively unknown. Objective: To evaluate the association of a long-term intervention of a lay health worker-led advance care planning intervention among patients with advanced stages of cancer with overall survival and end-of-life health care use and costs. Design, Setting, and Participants: This follow-up study of the EPAC randomized clinical trial conducted between August 2013 and February 2015 used data from 9.4 years after the first patient was enrolled with a data cut-off date of February 1, 2023. Overall, 213 participants with stage 3 or 4 or recurrent cancer in the US Veterans Affairs Palo Alto Health Care System were included. Interventions: A 6-month lay health worker-led education and support intervention to assist patients with establishing their end-of-life preferences vs usual care. Main Outcomes and Measures: The outcomes of interest were overall survival, risk of death, restricted mean survival time, and palliative care, hospice, and acute care use in the final 30 days before death for participants who died. Results: Among 213 participants randomized and included in the intention-to-treat analysis, the mean (SD) age was 69.3 (9.1) years; 211 (99.1%) were male, 2 (0.90%) were female. There were no demographic or clinical characteristic imbalances at enrollment. As of February 1, 2023, 188 had died. The intervention group had a 25% reduction in risk of death (hazard ratio, 0.75; 95% CI, 0.56-0.98); more palliative care (44 [50.0%] vs 35 [35.0%]) and hospice use (64 [72.7%] vs 53 [53.0%]); and lower emergency department use (20 [22.7%] vs 47 [47.0%]), hospitalizations (17 [19.3%] vs 46 [46.0%]), and median (IQR) total health care costs (median [IQR], $1637 [$383-$9026] vs $18 520 [$4790-$50 729]) than control group participants. Conclusions and Relevance: The effects of the lay health worker-led intervention remain durable, with nearly complete follow-up, supporting integration into routine cancer care. Trial Registration: ClinicalTrials.gov Identifier: NCT02966509.

Let Us Have the Conversation: Serious Illness Communication in Oncology: Definitions, Barriers, and Successful Approaches.

Serious illness communications are crucial elements of care delivery for patients with cancer. High-quality serious illness communications are composed of open, honest discussions between patients, caregivers, and clinicians regarding patient's communication preferences, expected illness trajectory, prognosis, and risks and benefits of any recommended care. High-quality communication ideally starts at the time of a patients' cancer diagnosis, allows space for and response to patient emotions, elicits patients' values and care preferences, and is iterative and longitudinal. When integrated into cancer care, such communication can result in improved patient experiences with their care, care that matches patients' goals, and reduced care intensity at the end of life. Despite national recommendations for routine integration of these communication into cancer care, a minority of patients with cancer receive such communication. In this chapter, we describe elements of high-quality serious illness communication, patient-, clinician-, institution-, and payer-level barriers, and successful strategies that can routinely integrate such communication into cancer care delivery.

Racial and Ethnic Disparities in Intensity of Care at the End of Life for Patients With Lung Cancer: A 13-Year Population-Based Study.

PURPOSE: Lung cancer is the leading cause of cancer death in the United States. Disparities in lung cancer mortality among racial and ethnic minorities are well documented. Less is known as to whether racial and ethnic minority patients with lung cancer experience higher rates of intensity of care at the end of life (EOL) compared with non-Hispanic White (NHW) patients. METHODS: We conducted a population-based analysis of patients 18 years and older with a lung cancer diagnosis who died between 2005 and 2018 using the California Cancer Registry linked to patient discharge data abstracts. Our primary outcome was intensity of care in the last 14 days before death (defined as any hospital admission or emergency department [ED] visit, intensive care unit [ICU] admission, intubation, cardiopulmonary resuscitation [CPR], hemodialysis, and death in an acute care setting). We used multivariable logistic regression models to evaluate associations between race and ethnicity and intensity of EOL care. RESULTS: Among 207,429 patients with lung cancer who died from 2005 to 2018, the median age was 74 years (range, 18-107) and 106,821 (51%) were male, 146,872 (70.8%) were NHW, 1,045 (0.5%) were American Indian, 21,697 (10.5%) were Asian Pacific Islander (API), 15,490 (7.5%) were Black, and 22,325 (10.8%) were Hispanic. Compared with NHW patients, in the last 14 days before death, API, Black, and Hispanic patients had greater odds of a hospital admission, an ICU admission, intubation, CPR, and hemodialysis and greater odds of a hospital or ED death. CONCLUSION: Compared with NHW patients, API, Black, and Hispanic patients who died with lung cancer experienced higher intensity of EOL care. Future studies should develop approaches to eliminate such racial and ethnic disparities in care delivery at the EOL.

Low physical function following cancer diagnosis is associated with higher mortality risk in postmenopausal women.

BACKGROUND: Postmenopausal women with cancer experience an accelerated physical dysfunction beyond what is expected through aging alone due to cancer and its treatments. The aim of this study was to determine whether declines in physical function after cancer diagnosis are associated with all-cause mortality and cancer-specific mortality. METHODS: This prospective cohort study included 8068 postmenopausal women enrolled in the Women's Health Initiative with a cancer diagnosis and who had physical function assessed within 1 year of that diagnosis. Self-reported physical function was measured using the 10-item physical function subscale of the 36-Item Short Form Health Survey. Cause of death was determined by medical record review, with central adjudication and linkage to the National Death Index. Death was adjudicated through February 2022. RESULTS: Over a median follow-up of 7.7 years from cancer diagnosis, 3316 (41.1%) women died. Our results showed that for every 10% difference in the physical function score after cancer diagnosis versus pre-diagnosis, all-cause mortality and cancer-specific mortality were reduced by 12% (hazard ratio [HR] = 0.88, 95% confidence interval [95% CI] = 0.87 to 0.89 and HR = 0.88, 95% CI = 0.86 to 0.91, respectively). Further categorical analyses showed a significant dose-response relationship between postdiagnosis physical function categories and mortality outcomes (P < .001 for trend), where the median survival time for women in the lowest physical function quartile was 9.1 years (Interquartile range [IQR] = 8.6-10.6 years) compared with 18.4 years (IQR = 15.8-22.0 years) for women in the highest physical function quartile. CONCLUSION: Postmenopausal women with low physical function after cancer diagnosis may be at higher risk of mortality from all causes and cancer-related mortality.

Lay healthcare worker financial toxicity intervention: a pilot financial toxicity screening and referral program.

PURPOSE: Financial toxicity is a source of significant distress for patients with urologic cancers, yet few studies have addressed financial burden in this patient population. METHODS: We developed a financial toxicity screening program using a lay health worker (LHW) and social worker (SW) to assess and mitigate financial toxicity in a single academic medical clinic. As part of a quality improvement project, the LHW screened all newly diagnosed patients with advanced stages of prostate, kidney, or urothelial cancer for financial burden using three COST tool questions and referred patients who had significant financial burden to an SW who provided personalized recommendations. The primary outcome was feasibility defined as 80% of patients with financial burden completing the SW consult. Secondary outcomes were patient satisfaction, change in COST Tool responses, and qualitative assessment of financial resources utilized. RESULTS: The LHW screened a total of 185 patients for financial toxicity; 82% (n = 152) were male, 65% (n = 120) White, and 75% (n = 139) reported annual household income >$100,000 US Dollars; 60% (n = 114) had prostate cancer. A total of 18 (9.7%) participants screened positive for significant financial burden and were referred to the SW for consultation. All participants (100%) completed and reported satisfaction with the SW consultation and had 0.83 mean lower scores on the COST Tool post-intervention assessment compared to pre-intervention (95% confidence interval [0.26, 1.41]). CONCLUSION: This multidisciplinary financial toxicity intervention using an LHW and SW was feasible, acceptable, and associated with reduced financial burden among patients with advanced stages of urologic cancers. Future work should evaluate the effect of this intervention among cancer patients in diverse settings.

Challenges and Solutions to Support Oncology Professionals Serving Underserved Populations With Cancer in the United States: Results From the ASCO Serving the Underserved Task Force.

PURPOSE: Little data exist regarding approaches to support oncology professionals who deliver cancer care for underserved populations. In response, ASCO developed the Serving the Underserved Task Force to learn from and support oncology professionals serving underserved populations. METHODS: The Task Force developed a 28-question survey to assess oncology professionals' experiences and strategies to support their work caring for underserved populations. The survey was deployed via an online link to 600 oncology professionals and assessed respondent and patient demographic characteristics, clinic-based processes to coordinate health-related social services, and strategies for professional society support and engagement. We used chi-square tests to evaluate whether there were associations between percent full-time equivalent (FTE) effort serving underserved populations (<50% FTE v ≥50% FTE) with responses. RESULTS: Of 462 respondents who completed the survey (77% response rate), 79 (17.1%) were Asian; 30 (6.5%) Black; 43 (9.3%) Hispanic or Latino/Latina; and 277 (60%) White. The majority (n = 366, 79.2%) had a medical doctor degree (MD). A total of 174 (37.7%) had <25% FTE, 151 (32.7%) had 25%-50% FTE, and 121 (26.2%) had ≥50% FTE effort serving underserved populations. Most best guessed patients' sociodemographic characteristics (n = 388; 84%), while 42 (9.2%) used data collected by the clinic. Social workers coordinated most health-related social services. However, in clinical settings with high proportions of underserved patients, there was greater reliance on nonclinical personnel, such as navigators (odds ratio [OR], 2.15 [95% CI, 1.07 to 4.33]) or no individual (OR, 2.55 [95% CI, 1.14 to 5.72]) for addressing mental health needs and greater reliance on physicians or advance practice practitioners (OR, 2.54 [95% CI, 1.11 to 5.81]) or no individual (OR, 1.91 [95% CI, 1.09 to 3.35]) for addressing childcare or eldercare needs compared with social workers. Prioritization of solutions, which did not differ by FTE effort serving underserved populations, included a return-on-investment model to support personnel, integrated health-related social needs screening, and collaboration with the professional society on advocacy and policy. CONCLUSION: The findings highlight crucial strategies that professional societies can implement to support oncology clinicians serving underserved populations with cancer.

Randomized Trial of a Volunteer-Led Symptom Assessment Intervention on Documentation, Patient-Reported Outcomes, and Health Care Use Among Veterans With Lung Cancer.

PURPOSE: Identification and documentation of Veterans' symptoms are crucial for optimal lung cancer care delivery. The objective of this study was to determine whether a volunteer-led proactive telephone symptom assessment intervention could improve comprehensive symptom documentation. METHODS: Veterans with lung cancer were randomly assigned to usual care (control group) or usual care with proactive symptom assessment in which a peer volunteer made weekly phone calls to assess patient symptoms under nurse practitioner supervision. The primary outcome was oncologist documentation of symptoms in the electronic health record at all clinical visits within 6 months after enrollment. Secondary outcomes included patient satisfaction with decision, patient activation, health-related quality of life (HRQOL), and symptom burden, measured at baseline, and 3, 6, and 9 months after enrollment, and acute care use within 9 months after enrollment. RESULTS: Among 60 Veterans randomly assigned, median (range) age was 70.2 (50-86) years; 57 (95.0%) were male. More intervention participants had oncologist documentation of symptoms than control group participants (24 [77.4%] v seven [24.1%], respectively; odds ratio, 16.46 [95% CI, 4.58 to 59.16]). Intervention group participants had greater improvements over time in HRQOL (expected mean difference, 25.3 [95% CI, 15.00 to 35.70]) and patient activation (expected mean difference, 13.6 [95% CI, 3.79 to 23.39]), lower symptom burden (expected mean difference, -6.39 [95% CI, -15.21 to -2.46]), lower rates of emergency room visits (incidence rate ratio, 0.48 [95% CI, 0.30 to 0.75]), and hospitalizations (incidence rate ratio, 0.47 [95% CI, 0.28 to 0.77]) than control group participants. CONCLUSION: This symptom assessment intervention is an effective strategy for Veterans with lung cancer.

Effect of a Community Health Worker-Led Intervention Among Low-Income and Minoritized Patients With Cancer: A Randomized Clinical Trial.

PURPOSE: To determine whether a community health worker (CHW)-led intervention could improve health-related quality of life (HRQoL; primary outcome) more than usual care among low-income and racial and ethnic minoritized populations newly diagnosed with cancer. METHODS: This randomized clinical trial was conducted from November 1, 2018, until August 31, 2021, in outpatient cancer clinics in Atlantic City, NJ, and Chicago, IL. Hourly low-wage worker members of an employer union health fund age 18 years or older with newly diagnosed solid tumor and hematologic malignancies were randomly assigned 1:1 to usual care (control group) or usual care augmented with a trained CHW for 12 months (intervention group). The CHW assisted participants with advance care planning (ACP), proactively screened symptoms, and referred participants to community-based resources for identified health-related social needs. Usual care comprised nurse case management and benefits redesign (waived copayments and free transportation for any cancer care received at preferred oncology clinics in each city). The primary outcome was HRQoL. Secondary outcomes included patient activation, satisfaction with decision, ACP documentation, health care use, total health care costs, and overall survival. RESULTS: A total of 160 participants were enrolled. Intervention group participants had a greater increase in mean HRQoL scores at 4-month and 12-month follow-up as compared with baseline than control group participants (expected mean difference, 11.25 [95% CI, 7.28 to 15.22]; 11.29 [95% CI, 6.96 to 15.62], respectively). CONCLUSION: In this randomized trial, a CHW-led intervention significantly improved HRQoL for low-income and racial and ethnic minoritized patients with cancer more than usual care alone.

Diversity in Cancer Care: Current Challenges and Potential Solutions to Achieving Equity in Clinical Trial Participation.

ABSTRACT: Access to and participation in cancer clinical trials determine whether such data are applicable, feasible, and generalizable among populations. The lack of inclusion of low-income and marginalized populations limits generalizability of the critical data guiding novel therapeutics and interventions used globally. Such lack of cancer clinical trial equity is troubling, considering that the populations frequently excluded from these trials are those with disproportionately higher cancer morbidity and mortality rates. There is an urgency to increase representation of marginalized populations to ensure that effective treatments are developed and equitably applied. Efforts to ameliorate these clinical trial inclusion disparities are met with a slew of multifactorial and multilevel challenges. We aim to review these challenges at the patient, clinician, system, and policy levels. We also highlight and propose solutions to inform future efforts to achieve cancer health equity.

Understanding Barriers and Facilitators to High-Quality Cancer Care Among Veterans With Lung Cancer: A Qualitative Study.

PURPOSE: Veteran populations have higher lung cancer incidence and worse overall survival compared with non-Veteran populations. Although recent clinical advancements have reduced lung cancer death rates, these advances are not routinely received among Veteran populations because of multilevel factors, including Veterans' complex comorbidities, limited health literacy, and other economic and social disadvantages. This study aimed to assess Veterans' perspectives regarding their lung cancer care with a specific focus on identifying modifiable barriers to evidence-based care delivery. METHODS: We conducted 1:1 semistructured interviews with 24 Veterans diagnosed with lung cancer at the Veterans Affairs Palo Alto Health Care System. All interviews were recorded, transcribed, and analyzed using the constant comparative method of qualitative analysis. RESULTS: Four themes emerged. These included (1) social and economic disadvantages can prevent routine delivery of evidence-based cancer care; (2) fragmented care contributes to worsening patient mental and emotional well-being; (3) lack of health system interventions to address limited health literacy inhibits patient engagement in shared decision making regarding diagnosis, genomic and molecular testing, targeted and other treatments, and end-of-life care; and (4) deep appreciation for care and VA trustworthiness facilitates adherence to cancer care recommendations. CONCLUSION: This study revealed critical gaps in lung cancer care delivery and the role of institution-engendered trust in overcoming barriers in the VA system. Targeted solutions should address the identified barriers to routine, evidence-based lung cancer care delivery among Veterans.

Assessing the Needs of Those Who Serve the Underserved: A Qualitative Study among US Oncology Clinicians.

BACKGROUND: The American Society of Clinical Oncology established the 'Supporting Providers Serving the Underserved' (SUS) Task Force with a goal to develop recommendations to support cancer clinicians who deliver care for populations at risk for cancer disparities. As a first step, the Task Force explored barriers and facilitators to equitable cancer care delivery. METHODS: Clinicians across the United States who deliver care predominantly for low-income and racially and ethnically minoritized populations were identified based on lists generated by the Task Force and the Health Equity Committee. Through purposive sampling based on geographical location, clinicians were invited to participate in 30-60 min semi-structured interviews to explore experiences, barriers, and facilitators in their delivery of cancer care. Interviews were recorded, transcribed, imported into qualitative data management software, and analyzed using thematic analysis. RESULTS: Thematic analysis revealed three major themes regarding barriers (lack of executive leadership recognition of resources; patient-related socio-economic needs; clinician burnout) and two major themes regarding facilitators (provider commitment, experiential training). CONCLUSIONS: Findings reveal modifiable barriers and potential solutions to facilitate equitable cancer care delivery for populations at risk for cancer disparities.

Leveraging Goals of Care Interventions to Deliver Personalized Care Near the End of Life.

This Viewpoint discusses barriers to and opportunities for incorporating goal of care communications into end-of-life care.