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Journal of General Internal Medicine logoLink to Journal of General Internal Medicine
letter
. 2025 Mar 31;40(13):3289–3291. doi: 10.1007/s11606-025-09479-6

Disparities in Receipt of Chemotherapy at the End of Life among Patients with NSCLC

Khushi Kohli 1,#, Stephanie Wang 1,#, Shriya Garg 2, Yueao Zhang 3, Erin Jay G Feliciano 4, Puneeth Iyengar 5, Edward Christopher Dee 5,✉
PMCID: PMC12508332  PMID: 40164933

INTRODUCTION

Chemotherapy near end-of-life (EOL) may not prolong survival and can cause unnecessary suffering.1 While recent research has elucidated disparities in receipt of such futile care at EOL among Black and White patients, little is known about EOL disparities among other groups.2 Using chemotherapy receipt within 30 days of death as an indicator, we examined disparities in futile treatment near EOL for disaggregated race/ethnicity groups with non-small cell lung cancer (NSCLC).

METHODS

Using National Cancer Database (NCDB) data, we conducted a retrospective analysis of adult patients diagnosed with NSCLC (2004–2021) who died within 30 days of diagnosis as a proxy for EOL, and with known chemotherapy receipt status (defined binarily).

Using StataMP 18, we calculated adjusted odds ratios and 95% confidence intervals of receiving chemotherapy across racial/ethnic groups using a logistic regression model (Table 1, alpha < 0.05). The regression included a year*race interaction term to examine changes in futile chemotherapy receipt over time by race (alpha < 0.1).

Table 1.

a. Descriptive Statistics for Patients with Non-small Cell Lung Cancer who Died within 30 Days of Diagnosis. We Analyzed the Distributions of Year of Diagnosis, Race, Sex, Age, Insurance Status, Median Income Quartiles (2012–2016), Median Income Quartiles (2012–2016), Facility Type, Percent no High School Degree Quartiles (2012–2016), and CDCC Score

Covariate Frequency (Percent) Odds ratio 95% CI (Low) 95% CI (High) P-Value
Year of Diagnosis
2004–2012 66,777 (56.09%) Reference Group
2013–2021 52,269 (43.91%) 0.6481844 0.6159876 0.682064 <0.001
Race
White 102,130 (85.79%) Reference Group
Black 12,874 (10.81%) 0.7711968 0.6968462 0.8534803 <0.001
Southeast Asian 617 (0.52%) 0.5912312 0.3609767 0.968357 0.037
East Asian 853 (0.72%) 1.417838 1.038607 1.935539 0.028
South Asian 175 (0.15%) 1.526298 0.7805012 2.984731 0.217
Indigenous 349 (0.29%) 0.8826532 0.5088316 1.531109 0.657
Pacific Islander 158 (0.13%) 0.769688 0.3079672 1.923646 0.575
Other 1890 (1.59%) 0.9556306 0.7537277 1.211618 0.708
Year of Diagnosis*Race
2013–2021*Black - 1.048912 0.8910661 1.234719 0.566
2013–2021*Southeast Asian - 1.950384 0.987056 3.853882 0.055
2013–2021*East Asian - 0.886766 0.52307 1.503344 0.655
2013–2021*South Asian - 0.8930338 0.3196738 2.49476 0.829
2013–2021*Indigenous - 0.8257849 0.3355816 2.032056 0.677
2013–2021*Pacific Islander - 0.2372031 0.0269528 2.087552 0.195
2013–2021*Other - 0.9497646 0.6504454 1.386823 0.79
Sex
Male 70,224 (58.99%) Reference Group
Female 48,822 (41.01%) 0.8963773 0.8554933 0.9392151 <0.001
Age
18–64 30,335 (25.48%) Reference Group
65–74 37,190 (31.24%) 0.7278057 0.6819684 0.7767238 <0.001
75–79 20,623 (17.32%) 0.5388897 0.4974558 0.5837747 <0.001
80+ 30,898 (25.95%) 0.2725058 0.2502503 0.2967404 <0.001
Insurance Status
Not Insured 4973 (4.18%) Reference Group
Private Insurance 21,041 (17.67%) 1.333173 1.196192 1.485841 <0.001
Medicaid 7248 (6.09%) 0.9398208 0.8243014 1.071529 0.354
Medicare 81,716 (68.64%) 1.052618 0.9404349 1.178183 0.372
Other Government 1619 (1.36%) 0.8008956 0.6346842 1.010635 0.061
Insurance Status Unknown 2449 (2.06%) 0.9845522 0.8181819 1.184752 0.869
Median Income Quartiles (2012–2016)
< $40,227 28,050 (23.56%) Reference Group
$40,227-$50,353 30,134 (25.31%) 1.05663 0.9841304 1.134471 0.129
$50,354-$63,332 27,695 (23.26%) 1.10464 1.0227 1.193146 0.011
> = $63,333 33,167 (27.86%) 1.179805 1.083269 1.284944 <0.001
Facility Type
Community Cancer Program 11,607 (9.75%) Reference Group
Comprehensive Community Cancer Program 53,996 (45.36%) 1.16236 1.071004 1.261509 <0.001
Academic/Research Program (includes NCI-designated comprehensive cancer centers) 27,990 (23.51%) 0.9633653 0.8808646 1.053593 0.414
Integrated Network Cancer Program 25,453 (21.38%) 1.03641 0.9470069 1.134252 0.437
Percent No High School Degree Quartiles (2012–2016)
> = 17.6% 28,152 (23.65%) Reference Group
10.9–17.5% 35,349 (29.69%) 1.047909 0.9799002 1.120637 0.172
6.3–10.8% 32,935 (27.67%) 1.04271 0.9658591 1.125675 0.284
< 6.3% 22,610 (18.99%) 1.118769 1.022057 1.224633 0.015
CDCC Score
0 56,918 (47.81%) Reference Group
1 35,119 (29.5%) 0.9385472 0.890922 0.9887183 0.017
2 16,550 (13.9%) 0.82915 0.7712296 0.8914204 <0.001
> = 3 10,459 (8.79%) 0.6505406 0.5894587 0.7179519 <0.001

We categorized patients into bins for age (18–64, 65–74, 75–79, and 80 + years old), diagnosis year (2004–2008, 2009–2013, 2014–2018, 2019–2021), and race/ethnicity (White, Black, Southeast Asian, East Asian, South Asian, Pacific Islander, and Other)

RESULTS

119,046 individuals died within 30d of diagnosis. Of these, 85.9% identified as White (n = 102,130), 10.81% as Black (n = 12,874), 0.52% as Southeast Asian (n = 617), 0.72% as East Asian (n = 853), 0.15% as South Asian (n = 175), 0.29% as American Indian, Aleutian, or Eskimo (n = 349), 0.13% as Pacific Islander (n = 158) and 1.59% as Other (n = 1,890). 56.09% of patients were diagnosed between 2004–2012 (n = 66,777) and 43.91% between 2013–2021 (n = 52,269).

Chemotherapy was administered for 7.1% of White patients, 5.7% of Black patients, 5.8% of Southeast Asian patients, 8.1% of East Asian patients, 9.7% of South Asian patients, 6.3% of American Indian, Aleutian, or Eskimo patients, 3.8% of Pacific Islander patients, and 6.6% of patients of other racial/ethnic groups (Fig. 1). East Asian patients were 1.42 × more likely (P = 0.028), Black patients were 0.77 × as likely (P < 0.001), and Southeast Asian patients were 0.59 × as likely (P = 0.037) to receive chemotherapy compared to White patients (Table 1).

Figure 1.

Figure 1

Rate of chemotherapy receipt by racial/ethnic group for patients with NSCLC who died within 30 days of diagnosis, stratified by year of diagnosis

Of Southeast Asian patients diagnosed between 2013–2021 who died within 30 days of diagnosis, 6.3% received chemotherapy, compared with 5.4% among those diagnosed from 2004-2012, compared with a nominal decrease over time for all other groups, suggesting a significant increase in futile chemotherapy receipt for Southeast Asian patients (Table 1). The year*race term was significant for Southeast Asian patients, suggesting that the improvement (lower rate) of futile chemotherapy over time was not equitably distributed (95%, Pinteraction = 0.055, compared with decreases for the reference group).

The rate of receipt of futile chemotherapy has decreased in recent years. Older patients, female patients, patients with non-insurance, patients with greater comorbidity, and patients in ZIP codes with lower socioeconomic status were less likely to undergo futile chemotherapy.

DISCUSSION

We found increased odds of chemotherapy receipt at EOL for Southeast Asian patients in more recent years, suggesting trends of burdensome treatment for this population. Greater odds of aggressive EOL treatment for Southeast Asian patients is concerning considering the importance of pain minimization and symptom management as the primary palliative care priorities among many AA subgroups.3 While Southeast Asian subgroups remain comparatively understudied, many AAs are less likely to be enrolled in hospice care and more likely to die in the hospital.4,5

Our findings highlight the need to facilitate values-concordant, QOL-maximizing EOL care for diverse patients. Raising awareness about EOL care options instead of aggressive treatments can address misconceptions and stigma surrounding palliative care in diverse sociocultural communities.

Declarations

Conflicts of Interest

P.I. and E.C.D. are funded in part through the Prostate Cancer Foundation and through the Cancer Center Support Grant from the National Cancer Institute (P30 CA008748). P.I. received research grants from Incyte (to the institution) and has participated in the Advisory Board of AstraZeneca, Novocure, Johnson and Johnson, BioConvergent Health, Pfizer, and NGM Biosciences. All other authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Khushi Kohli and Stephanie Wang contributed equally.

References

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