Factors Associated with Supportive Care Receipt Among Black Patients with Advanced Lung Cancer: An Exploratory Pilot Study

Abstract

Background:

Black patients with cancer are less likely to receive supportive care than non-Hispanic White patients. Studies examining supportive care use patterns specifically among Black patients are limited.

Objectives:

To describe supportive care receipt and explore its sociodemographic, clinical, and communication-related correlates in Black patients with advanced lung cancer.

Design:

Observational exploratory pilot study.

Setting:

Black patients with advanced lung cancer (N = 30) were recruited from thoracic oncology clinics in the United States.

Measurements:

Participants self-reported sociodemographic, clinical, and communication-related factors. Supportive care receipt (palliative medicine, chaplain, or mental health services) was abstracted from electronic medical records. Point-biserial correlations or Fisher’s exact tests (as appropriate) assessed relationships between key variables and supportive care receipt. Significance was set at 0.05, and results were interpreted with caution due to the exploratory focus.

Results:

Only six participants (20%) received supportive care during the three-month study. Supportive care receipt was more common in participants who were younger (r = −0.48, p = 0.007, 95% CI: [−0.82, −0.14]) or had experienced medical discrimination in the past 2 years (50% v. 9%, Fisher’s exact test, odds ratio (OR) = 8.98, p = 0.03, 95% confidence interval CI: [1.25, 88.17]). Those with poorer general quality of life (QOL) (r = −0.41, p = 0.025, 95% CI: [−0.76, −0.06]) or poorer lung cancer-specific QOL (r = −0.55, p = 0.002, 95% CI: [−0.88, −0.23]) also had higher rates of supportive care receipt.

Conclusion:

Among Black patients with advanced lung cancer, supportive care receipt varied by sociodemographic, clinical, and communication-related factors, suggesting future research avenues.

Keywords

African-American Black communication lung cancer palliative care supportive care

Background

Despite higher symptom burden, Black patients with cancer are less likely to receive supportive care (e.g., palliative care, spiritual support, and mental health services) than non-Hispanic White patients.^1–7 Factors underlying these disparities include differential access to supportive care, mistrust, discrimination, and cultural differences.^8,9

Although disparities between racial groups in supportive care receipt are well-documented, less is known about patterns within the substantially heterogeneous Black community.¹⁰ Factors affecting supportive care use in Black patients may or may not reflect findings from predominantly White samples. Accordingly, expert guidelines recommend prioritizing palliative care research among minoritized populations.¹¹ Determining factors associated with supportive care receipt among Black patients with cancer could inform tailored intervention approaches for increasing supportive care receipt specifically for this subgroup to reduce symptom management inequities.

Prior studies suggest factors affecting supportive care receipt. For example, palliative care use varies by gender, age, and socioeconomic status.^12,13 Because supportive care is especially relevant for those with higher disease burden, complex comorbidities, and more severe symptoms,^11,14,15 clinical factors may also play a role. In addition, patient-centered communication—prioritizing patient involvement and building patient-clinician relationships¹⁶—could promote symptom discussions, while communication barriers and prior experiences of discrimination in medical settings can complicate such discussions.^9,17–20 Yet, supportive care studies often over-represent White patients²¹ and rarely focus on minority health;^21–23 thus, there is a need to determine factors linked to supportive care use among Black patients specifically.

Advanced lung cancer is a unique clinical context to examine supportive care receipt among Black patients. Lung cancer survivorship is growing,²⁴ yet 64% of patients have advanced disease at diagnosis.²⁵ Compared to other cancers, those with lung cancer experience higher symptom burden, greater distress, and quality of life (QOL) challenges.^26,27 However, supportive care is underutilized in lung cancer care, especially among Black patients.^2–4,28

In summary, supportive care services are critical components of advanced lung cancer care,^11,14,29 but Black patients are less likely to receive them than non-Hispanic White patients despite higher symptom burden.^1–5 Determining factors associated with supportive care receipt specifically among Black patients can guide intervention approaches. In this exploratory pilot study, we described rates of supportive care receipt in Black patients with advanced lung cancer and examined whether receipt varied by sociodemographic, clinical, and communication-related factors in order to inform future larger research studies.

Methods

This exploratory pilot study included patient surveys and electronic medical record (EMR) abstraction between March 2022 and May 2023. The Georgetown-MedStar Joint Oncology Institutional Review Board approved the study (Protocol #00004381).

Participants and procedures

As previously described,³⁰ study team members recruited participants (n = 30) from three thoracic oncology clinics, confirmed eligibility, and obtained written informed consent. Participants were ages ≥18, Black or African American, English-speaking, and receiving care for advanced (Stages III-IV; extensive) lung cancer. Patients receiving hospice care or demonstrating severe cognitive impairment were excluded.

Participants completed surveys at baseline (T0), following a routine oncology appointment (T1), and one month later (T2). Trained staff abstracted EMR data.

Measures

Based on the social-ecological model,^31,32 shared decision-making frameworks,^33,34 and prior literature,³⁵ we examined patient-level (sociodemographic and clinical characteristics) and interpersonal factors (patient–clinician communication factors) expected to potentially impact supportive care receipt.

Sociodemographic characteristics

At T0, participants reported their age, gender, education, employment status, insurance status, and involvement of a support person in their care (yes/no). Single-item questions assessed financial toxicity, health literacy, and religious coping.

Clinical characteristics

Because QOL challenges, anxiety, and depressive symptoms signal a need for supportive care, participants reported these factors at T0 Functional Assessment of Cancer Therapy-General 7-item version; (FACT-G7),³⁶ Functional Assessment of Cancer Therapy-Lung; (FACT-L),³⁷ Generalized Anxiety Disorder 2-item scale; (GAD-2),³⁸ Patient Health Questionnaire 2-item scale; PHQ-2³⁹) Upon examining their distributions, FACT-G7 and FACT-L scores were used as continuous variables, while GAD-2 and PHQ-2 scores were recoded into binary variables (representing any/no symptoms). Time since diagnosis, treatment(s) received, comorbidities, and performance status were abstracted from the EMR.

Communication variables

At T0, participants reported patient-oncologist relationship quality (The Human Connection scale⁴⁰). At T1, participants reported perceived shared decision-making in a routine oncology appointment (CollaboRATE scale⁴¹). Because prior discrimination experiences may impact communication,^18,42 participants reported experiences of discrimination in medical settings within the past two years based on race, language spoken, gender, age, appearance, smoking history, or lung cancer status (adapted from the Commonwealth Fund Health Quality Survey⁴³); responses were dichotomized as any/none.

Supportive care receipt

Trained research staff abstracted EMR data on supportive care receipt (palliative care, chaplain, or mental health services) between study enrollment and T2 (M = 78 days, SD = 50 days). Length of study enrollment was not significantly related to supportive care receipt (p = 0.14).

Statistical analysis

Analyses were conducted with IBM SPSS (v29) and R (v4.5.2, exact2x2 package). To identify areas of focus for future studies, we examined descriptives and bivariate relationships between supportive care receipt and sociodemographic, clinical, and communication-related variables using point-biserial correlations and Fisher’s exact tests with corresponding 95% confidence intervals,⁴⁴ as appropriate. All tests were two-tailed; significance was set at α ≤ 0.05. Due to the exploratory nature of the study and multiple statistical comparisons, we interpreted analyses with extreme caution.

Results

Sample descriptives

Table 1 summarizes participant characteristics by supportive care receipt.

Table 1.

Participant Sociodemographic, Clinical, and Communication-Related Characteristics, by Receipt of Supportive Care Services

	Did not receive supportive care services (n = 24)	Received supportive care services (n = 6)	Point-biserial correlation or odds ratio for Fisher’s exact test (95% CI)	p Value
	M(SD) or N (%)	M(SD) or N (%)		p Value
Sociodemographic Characteristics
Age (years; range 48–81)	67.04 (7.63)	57.33 (5.99)	−0.48 (−0.82, −0.14)	0.007
Gender			0.22 (0.02, 1.45)	0.156
Man	7 (29%)	4 (67%)
Woman	17 (71%)	2 (33%)
Education			7.26 (0.70, 193.47)	0.080
High school degree or less	14 (58%)	1 (17%)
Post-high school education	9 (37%)	5 (83%)
Employment status			^a	0.155
Currently working	8 (33%)	0 (0%)
Not working	16 (67%)	6 (100%)
Private health insurance			1.41 (0.22, 12.39)	1.000
Yes	10 (42%)	2 (33%)
No	14 (58%)	4 (67%)
Public health insurance			2.41 (0.25, 19.98)	0.571
Yes	20 (83%)	4 (67%)
No	4 (17%)	2 (33%)
Financial toxicity (range: 1–4)	1.92 (1.10)	2.83 (1.17)	0.32 (−0.04, 0.69)	0.082
Health literacy (range: 1–5)	2.00 (0.89)	2.33 (1.75)	0.13 (−0.26, 0.51)	0.509
Support person involved in care			^a	0.557
Yes	20 (83%)	6 (100%)
No	4 (17%)	0 (0%)
Is religion involved in understanding/dealing with your health?			6.15 (0.73, 64.80)	0.091
Yes	18 (75%)	2 (33%)
No	4 (17%)	3 (50%)
Missing	2 (8%)	1 (17%)
Clinical Characteristics
Time since diagnosis			0.15 (0.01, 1.55)	0.169
Less than 1 year	10 (42%)	5 (83%)
≥1 year	14 (58%)	1 (17%)
FACT-G7^b (range: 0–28)	19.79 (6.03)	12.67 (8.71)	−0.41 (−0.76, −0.06)	0.025
FACT-L^c (range: 0–28)	21.24 (3.74)	12.67 (7.81)	−0.55 (−0.88, −0.23)	0.002
Anxiety symptoms (GAD-2^d)			9.23 (0.89, 246.65)	0.061
None (GAD-2 = 0)	16 (67%)	1 (17%)
Any (GAD-2 >0)	8 (33%)	5 (83%)
Depression symptoms (PHQ-2^e)			1.96 (0.30, 17.08)	0.657
None (PHQ-2 = 0)	12 (50%)	2 (33%)
Any (PHQ-2 >0)	12 (50%)	4 (66%)
Charlson Comorbidity Index (range: 0–33)	6.88 (1.30)	6.50 (0.55)	−0.13 (−0.51, 0.26)	0.498
ECOG Score^f (range: 0–5)	0.87 (0.63)	1.00 (0.71)	0.08 (−0.31, 0.46)	0.682
Received chemotherapy during study			^a	0.074
Yes	14 (58%)	6 (100%)
No	10 (42%)	0 (0%)
Received radiation during study			^a	1.000
Yes	3 (12%)	0 (0%)
No	21 (88%)	6 (100%)
Received immunotherapy during study			0.34 (0.01, 3.75)	0.633
Yes	15 (63%)	5 (83%)
No	9 (37%)	1 (17%)
Received targeted therapy during study			^a	0.553
Yes	5 (21%)	0 (0%)
No	18 (75%)	6 (100%)
Communication Variables
Prior experiences of discrimination in medical settings			8.98 (1.25, 88.17)	0.029
Yes	4 (17%)	4 (67%)
No	20 (83%)	2 (33%)
Patient-oncologist relationship quality (range: 16–64)	59.33 (6.16)	55.03 (5.84)	−0.28 (−0.65, 0.09)	0.134
Perceived shared decision-making during routine oncology appointment (range: 0–100)	94.21 (11.27)	91.98 (12.49)	−0.08 (−0.48, 0.32)	0.676

Bolded values indicate statistically significant result (p < 0.05).

Could not be estimated due to cell(s) with count = 0.

FACT-G7: Functional Assessment of Cancer Therapy—General, 7-item Version; assesses health-related quality of life.

FACT-L: Functional Assessment of Cancer Therapy—Lung; assesses lung cancer-specific quality of life.

GAD-2: Generalized Anxiety Disorder 2-item scale; assesses symptoms of anxiety in the last 2 weeks.

PHQ-2: Patient Health Questionnaire 2-item scale; assesses symptoms of depression in the last 2 weeks.

ECOG: Eastern Cooperative Oncology Group Performance Status Scale; assesses performance status.

Frequency of supportive care receipt

Six participants (20%) received supportive care services during the study (Table 2); some received multiple services.

Table 2.

Receipt of Supportive Care Services

Supportive care services	N (%)
Palliative medicine	3 (10.0%)
Chaplain	1 (3.3%)
Mental health services (i.e., psychologist, psychiatrist, social worker)	5 (16.7%)
Any of the above	6 (20.0%)

Factors related to supportive care receipt

Sociodemographic characteristics

Younger participants received supportive care services more frequently than older participants (r = −0.48, p = 0.007, 95% CI: [−0.82, −0.14], Fig. 1A). Supportive care receipt was not significantly associated with other sociodemographic characteristics (p-values ≥ 0.08; Table 1).

FIG. 1.

Boxplots demonstrating receipt of supportive care services by (A) age, (B) overall quality of life (Functional Assessment of Cancer Therapy-General 7-item version, FACT-G7; higher scores indicate better quality of life), and (C) lung cancer-specific quality of life (Functional Assessment of Cancer Therapy-Lung; FACT-L; higher scores indicate better quality of life).

Clinical characteristics

Supportive care receipt was higher among participants with poorer general QOL (r = −0.41, p = 0.025, 95% CI: [−0.76, −0.06], Fig. 1B) and poorer lung-cancer specific QOL (r = −0.55, p = 0.002, 95% CI: [−0.88, −0.23], Fig. 1C). Supportive care receipt was not significantly associated with other clinical characteristics (p-values ≥ 0.06; Table 1).

Communication variables

Participants who experienced prior medical discrimination had higher rates of supportive care receipt compared to those without these experiences (50% vs. 9%; Fisher’s exact test; OR = 8.98, p = 0.03, 95% CI: [1.25, 88.17]; Fig. 2). Supportive care receipt was not significantly associated with other communication factors (p-values > 0.13; Table 1).

FIG. 2.

Proportion of participants reporting prior experiences of discrimination in medical settings by receipt of supportive care services.

Discussion

Despite disparities in supportive care use,^1–5 little is known about factors associated with its receipt specifically among Black patients. We explored supportive care receipt among Black patients with advanced lung cancer. Consistent with prior literature,^45,46 only 20% of participants received supportive care. Those who were younger, previously experienced medical discrimination, and had worse QOL were more likely to receive supportive care. These exploratory results offer pathways for future research.

While they must be interpreted with extreme caution, these findings can inform future clinical and research efforts to identify those who may be less likely to receive yet still benefit from supportive care. For example, older adults received supportive care at lower rates than younger patients. Older Black adults may benefit from tailored interventions promoting supportive care.⁴⁷ In contrast, patients experiencing worse QOL were more likely to receive supportive care, which aligns with clinical guidelines.¹¹ However, we could not determine the timing of supportive care relative to symptom onset, an area for future work given the benefits of early palliative care integration.^29,48 Furthermore, those with lower symptom burden may still benefit from supportive care.¹⁴

Interestingly, those who experienced prior medical discrimination were more likely to receive supportive care, an unexpected finding. It is possible that people with prior discrimination experiences may have higher symptom burden, self-advocate more in clinical visits, and/or prompt different referral patterns from clinicians.^18,49 Future work examining links between communication and supportive care receipt in larger samples is needed.

Strengths and limitations

Study strengths include its focus on Black patients and multidimensional data from participant reports and EMRs. However, due to the exploratory nature of the study, the small convenience sample precluded adjusted analyses, restricted statistical power to detecting large effect sizes, and limited generalizability to the broader population of Black patients with advanced lung cancer (e.g., those of various ancestries, those treated in community settings). As expected due to the study’s exploratory nature, post-hoc power analysis indicated that the study was underpowered to detect small and medium effects; additional relationships may be revealed in larger studies. Because we studied supportive care use specifically in Black patients to understand their experiences,⁵⁰ we cannot draw conclusions about whether these findings are unique to Black patients. Multi-method studies examining supportive care receipt prospectively from diagnosis and including clinician factors (which influence referral patterns⁵¹) are needed.

Conclusion

Only 20% of Black patients with advanced lung cancer received supportive care services during this three-month exploratory pilot study. Exploratory findings indicated that those who were younger, experienced prior medical discrimination, and had worse QOL had higher rates of supportive care receipt. Future research should explore these relationships prospectively in larger samples to confirm findings and inform interventions promoting supportive care receipt.

Authors’ Contributions

Conceptualization: All authors. Methodology: H.M.D.-V. and C.C.C. Funding acquisition: H.M.D.-V., C.K., and C.C.C. Supervision: H.M.D.-V. and C.C.C. Project administration: A.K., J.D.R., H.M.D.-V., and C.C.C. Formal analysis: A.K., C.C.C. Investigation: A.K., J.D.R., O.M.B., J.D.R., H.K., E.T., and A.S. Resources: C.K., I.V., J.W., and M.G. Data curation: A.K. and C.C.C. Visualization: A.K. and C.C.C. Writing—original draft: H.M.D.-V., A.K., B.M., O.M.B., and C.C.C. Writing—review and editing: All authors.

Footnotes

Acknowledgments

The study team expresses their appreciation to the patients who participated in this study, to the members of the Project TLC Community Advisory Board, to Dr. Lora Kasselman and Dr. Valeriy Korostyshevskiy for statistical consultation, and to Dr. Lisa Carter-Bawa for feedback on the draft manuscript.

Data Availability Statement

Deidentified data are publicly available on Open Science Framework and can be accessed at . Sociodemographic data are omitted for privacy reasons, and can be requested from the corresponding author.

Author Disclosure Statement

C.C.C. has received grant funding from Pfizer. M.G. has received consulting fees from Guardant, honoraria for speakers bureau activity from BMS and Merck MSD, and stock in COTA Healthcare. C.K. has received consulting fees from Daiichi Sankyo, Regeneron, Sanofi, Takeda, J&J, Pinetree, Boehringer Ingelheim, BMS, Bicycle, Bayer, Onviv, Bio-Thera, and his institution has received research funding from AstraZeneca, Novartis, Regeneron, Janssen, Genentech, Lyell, Daiichi Sankyo, Gilead, Macrogenics, Boehringer Ingelheim, Black Diamond Therapeutics, ORIC. All other authors have no conflicts of interest to disclose.

Funding Information

This research was supported by a Developmental Funds Award from the Lombardi Comprehensive Cancer Center (LCCC) Cancer Center Support Grant (P30CA051008; PI: Weiner) and by the National Cancer Institute (T32CA261787, PI: O’Neill; K08CA270402, PI: Conley). This research was also supported by the LCCC Survey, Recruitment, and Biospecimen Collection Shared Resource (SRBSR), which is partially supported by NIH/NCI grant P30CA051008 (PI: Weiner).

Abbreviations

References

Griggs

. Disparities in palliative care in patients with cancer. J Clin Oncol, 2020; 38(9):974–979; doi: 10.1200/JCO.19.02108

Bulls

, Chang

, Brownstein

, et al. Patient-reported symptom burden in routine oncology care: Examining racial and ethnic disparities. Cancer Rep (Hoboken), 2022; 5(3):e1478; doi: 10.1002/cnr2.1478

Mazor

, Li

, Morillo

, et al. Disparities in supportive care needs over time between racial and ethnic minority and non-minority patients with advanced lung cancer. J Pain Symptom Manage, 2022; 63(4):563–571.

Badger

, Segrin

, Crane

, et al. Social determinants of health and symptom burden during cancer treatment. Nurs Res, 2023; 72(2):103–113; doi: 10.1097/NNR.0000000000000636

Lee

, Gani

, Canner

, et al. Racial disparities in utilization of palliative care among patients admitted with advanced solid organ malignancies. Am J Hosp Palliat Care, 2021; 38(6):539–546; doi: 10.1177/1049909120922779

Giap

, Ma

, Oladeru

, et al. Palliative care utilization and racial and ethnic disparities among women with de novo metastatic breast cancer in the United States. Breast Cancer Res Treat, 2023; 200(3):347–354; doi: 10.1007/s10549-023-06963-7

Freeman

, Omoleye

, Zhao

, et al. Palliative care use trends, racial/ethnic disparities, and overall survival differences among patients with metastatic breast cancer. J Palliat Med, 2024; 27(6):763–775; doi: 10.1089/jpm.2023.0547

Gardner

, Doherty

, Bates

, et al. Racial and ethnic disparities in palliative care: A systematic scoping review. Fam Soc, 2018; 99(4):301–316; doi: 10.1177/1044389418809083

Cain

, Surbone

, Elk

, et al. Culture and palliative care: Preferences, communication, meaning, and mutual decision making. J Pain Symptom Manage, 2018; 55(5):1408–1419.

10.

Oduro

, Jackson

, Fu

, et al. Palliative care experiences among adults from underrepresented racial and ethnic groups in the United States: A scoping review. Am J Hosp Palliat Care, 2025; 42(8):735–745; doi: 10.1177/10499091241273403

11.

Sanders

, Temin

, Ghoshal

, et al. Palliative care for patients with cancer: ASCO guideline update. J Clin Oncol, 2024; 42(19):2336–2357; doi: 10.1200/JCO.24.00542

12.

Nelson

, Wright

, Peeler

, et al. Sociodemographic disparities in access to hospice and palliative care: An integrative review. Am J Hosp Palliat Care, 2021; 38(11):1378–1390; doi: 10.1177/1049909120985419

13.

Frasca

, Orazio

, Amadeo

, et al. Palliative care referral in cancer patients with regard to initial cancer prognosis: A population-based study. Public Health, 2021; 195:24–31; doi: 10.1016/j.puhe.2021.03.020

14.

Temel

, Petrillo

, Greer

. Patient-centered palliative care for patients with advanced lung cancer. J Clin Oncol, 2022; 40(6):626–634; doi: 10.1200/JCO.21.01710

15.

Chan

, Rout

, ‘Adamo

CRD

, et al. Palliative referrals in advanced cancer patients: Utilizing the supportive and palliative care indicators tool and rothman index. Am J Hosp Palliat Care, 2022; 39(2):164–168; doi: 10.1177/10499091211017873

16.

Epstein

, Street

. Patient-Centered Communication in Cancer Care: Promoting Healing and Reducing Suffering. National Cancer Institute, US Department of Health and Human Services, National Institutes of Health: Bethesda, MD; 2007.

17.

Parajuli

, Hupcey

. A systematic review on barriers to palliative care in oncology. Am J Hosp Palliat Care, 2021; 38(11):1361–1377; doi: 10.1177/1049909120983283

18.

Do Bú

, Eggly

, Penner

, et al. “The doctor will see you now… but not for long”: Linking physicians’ racial attitudes and patients’ discrimination experiences to racial disparities in the duration of medical consultations. Patient Educ Couns, 2025; 134:108653; doi: 10.1016/j.pec.2025.108653

19.

Brown

, Marshall

, Snyder

, et al. Perspectives about racism and patient-clinician communication among black adults with serious illness. JAMA Netw Open, 2023; 6(7):e2321746-e2321746.

20.

Bakitas

, Tosteson

, Li

, et al. Early versus delayed initiation of concurrent palliative oncology care: Patient outcomes in the ENABLE III randomized controlled trial. J Clin Oncol, 2015; 33(13):1438–1445; doi: 10.1200/JCO.2014.58.6362

21.

Rhodes

, Barrett

, Ejem

, et al. A review of race and ethnicity in hospice and palliative medicine research: Representation matters. J Pain Symptom Manage, 2022; 64(5):e289–e299; doi: 10.1016/j.jpainsymman.2022.07.009

22.

Rosa

, Garcia

, Mardones

, et al. Integrating health equity in the ASCO guideline agenda: Recommendations from members of the palliative care expert panel. JCO Oncol Pract, 2024; 20(10):1300–1303; doi: 10.1200/OP.24.00291

23.

Johnson

, Bullock

, Smith

, et al. Evaluation of reporting of race and ethnicity in hospice and palliative care research. J Palliat Med, 2025; 28(6):708–715; doi: 10.1089/jpm.2023.0694

24.

Howlader

, Forjaz

, Mooradian

, et al. The effect of advances in lung-cancer treatment on population mortality. N Engl J Med, 2020; 383(7):640–649; doi: 10.1056/NEJMoa1916623

25.

Siegel

, Kratzer

, Wagle

, et al. Cancer statistics, 2026. CA Cancer J Clin, 2026; 76(1):e70043; doi: 10.3322/caac.70043

26.

Joshy

, Thandrayen

, Koczwara

, et al. Disability, psychological distress and quality of life in relation to cancer diagnosis and cancer type: Population-based Australian study of 22,505 cancer survivors and 244,000 people without cancer. BMC Med, 2020; 18(1):372; doi: 10.1186/s12916-020-01830-4

27.

Jensen

, Potosky

, Moinpour

, et al. United States population-based estimates of patient-reported outcomes measurement information system symptom and functional status reference values for individuals with cancer. J Clin Oncol, 2017; 35(17):1913–1920; doi: 10.1200/JCO.2016.71.4410

28.

John

, Kawachi

, Lathan

, et al. Disparities in perceived unmet need for supportive services among patients with lung cancer in the cancer care outcomes research and surveillance consortium. Cancer, 2014; 120(20):3178–3191; doi: 10.1002/cncr.28801

29.

Temel

, Greer

, Muzikansky

, et al. Early palliative care for patients with metastatic non–small-cell lung cancer. N Engl J Med, 2010; 363(8):733–742; doi: 10.1056/NEJMoa1000678

30.

AuBuchon

, Khoudary

, Rodriguez

, et al. Shared decision making in routine oncology appointments with black patients with lung cancer. Support Care Cancer, 2025; 33(4):250.

31.

Bronfenbrenner

. Ecological systems theory. In: Six Theories of Child Development: Revised Formulations and Current Issues. Jessica Kingsley Publishers; 1992; pp. 187–249.

32.

McLeroy

, Bibeau

, Steckler

, et al. An ecological perspective on health promotion programs. Health Educ Q, 1988; 15(4):351–377; doi: 10.1177/109019818801500401

33.

Elwyn

, Frosch

, Thomson

, et al. Shared decision making: A model for clinical practice. J Gen Intern Med, 2012; 27(10):1361–1367; doi: 10.1007/s11606-012-2077-6

34.

Eggly

, Albrecht

, Kelly

, et al. The role of the clinician in cancer clinical communication. J Health Commun, 2009; 14 Suppl 1(sup1):66–75; doi: 10.1080/10810730902806778

35.

Bazargan

, Bazargan-Hejazi

. Disparities in palliative and hospice care and completion of advance care planning and directives among non-Hispanic blacks: A scoping review of recent literature. Am J Hosp Palliat Care, 2021; 38(6):688–718; doi: 10.1177/1049909120966585

36.

Yanez

, Pearman

, Lis

, et al. The FACT-G7: A rapid version of the functional assessment of cancer therapy-general (FACT-G) for monitoring symptoms and concerns in oncology practice and research. Ann Oncol, 2013; 24(4):1073–1078.

37.

Butt

, Webster

, Eisenstein

, et al. Quality of life in lung cancer: The validity and cross-cultural applicability of the functional assessment of cancer therapy–lung scale. Hematol Oncol Clin North Am, 2005; 19(2):389–420.

38.

Kroenke

, Spitzer

, Williams

JBW

, et al. Anxiety disorders in primary care: Prevalence, impairment, comorbidity, and detection. Ann Intern Med, 2007; 146(5):317–325; doi: 10.7326/0003-4819-146-5-200703060-00004

39.

Löwe

, Kroenke

, Gräfe

. Detecting and monitoring depression with a two-item questionnaire (PHQ-2). J Psychosom Res, 2005; 58(2):163–171.

40.

Mack

, Block

, Nilsson

, et al. Measuring therapeutic alliance between oncologists and patients with advanced cancer: The human connection scale. Cancer, 2009; 115(14):3302–3311; doi: 10.1002/cncr.24360

41.

Elwyn

, Barr

, Grande

, et al. Developing CollaboRATE: A fast and frugal patient-reported measure of shared decision making in clinical encounters. Patient Educ Couns, 2013; 93(1):102–107.

42.

Hausmann

LRM

, Hannon

, Kresevic

, et al. Impact of perceived discrimination in health care on patient-provider communication. Med Care, 2011; 49(7):626–633; doi: 10.1097/MLR.0b013e318215d93c

43.

Ngo-Metzger

, Telfair

, Sorkin

, et al. Cultural competency and quality of care: Obtaining the patient’s perspective. Commonw Fund, 2006; 963:1–50.

44.

Fay

. Confidence intervals that match Fisher’s exact or Blaker’s exact tests. Biostatistics, 2010; 11(2):373–374; doi: 10.1093/biostatistics/kxp050

45.

Cole

, Nguyen

, Meirkhanov

, et al. Association of care at minority-serving vs non–minority-serving hospitals with use of palliative care among racial/ethnic minorities with metastatic cancer in the United States. JAMA Netw Open, 2019; 2(2):e187633; doi: 10.1001/jamanetworkopen.2018.7633

46.

Islam

, Braithwaite

, Zhang

, et al. Racial and ethnic inequities of palliative care use among advanced non-small cell lung cancer patients in the US. Cancer Med, 2023; 12(7):8567–8580; doi: 10.1002/cam4.5538

47.

Nipp

, Subbiah

, Loscalzo

. Convergence of geriatrics and palliative care to deliver personalized supportive care for older adults with cancer. J Clin Oncol, 2021; 39(19):2185–2194; doi: 10.1200/JCO.21.00158

48.

Hoerger

, Wayser

, Schwing

, et al. Impact of interdisciplinary outpatient specialty palliative care on survival and quality of life in adults with advanced cancer: A meta-analysis of randomized controlled trials. Ann Behav Med, 2019; 53(7):674–685.

49.

Hagiwara

, Penner

, Gonzalez

, et al. Racial attitudes, physician-patient talk time ratio, and adherence in racially discordant medical interactions. Soc Sci Med, 2013; 87:123–131; doi: 10.1016/j.socscimed.2013.03.016

50.

Whitfield

, Allaire

, Belue

, et al. Are comparisons the answer to understanding behavioral aspects of aging in racial and ethnic groups? J Gerontol B Psychol Sci Soc Sci, 2008; 63(5):P301–P308; doi: 10.1093/geronb/63.5.p301

51.

Enguidanos

, Cardenas

, Wenceslao

, et al. Health care provider barriers to patient referral to palliative care. Am J Hosp Palliat Care, 2021; 38(9):1112–1119; doi: 10.1177/1049909120973200