The impact of immune-related adverse events on survival outcomes in a racially diverse population, with a focus on non-Hispanic Black patients

Abstract

Introduction

The development of immune-related adverse events (irAEs) has been associated with improved survival outcomes in non-small cell lung cancer (NSCLC). However, this association’s extent across race and ethnicity remains uncertain. We evaluated the association between the development of irAEs and treatment outcomes across racially diverse groups treated at a safety net hospital.

Methods

A retrospective chart review was performed to identify patients with advanced NSCLC treated between 2015 and 2020. The incidence of irAEs across racial subgroups was compared using logistic regression analysis. Cox regression analysis was performed to evaluate the association between the development of irAEs and treatment outcomes.

Results

We identified 138 NSCLC patients treated with immune checkpoint inhibitors (ICIs), of whom 50% identified as non-Hispanic Black (NHB). Incidence of irAEs was 28%, with no significant difference between NHB and other racial groups. However, females [OR 2.3, 95% CI, (1.1-4.8)] and patients with Medicaid or MassHealth insurance had a higher incidence of irAEs [OR 2.7 (1.2-5.7)]. Additionally, patients with irAEs had a lower risk of disease progression (multivariable HR 0.46, 95% CI, 0.23-0.92) compared to those without irAEs. The association between irAEs and improved progression free survival (PFS) in NHB patients was similar to the other racial group [median PFS 246 vs 181 days; HR 0.87 (0.58-1.29)].

Conclusion

We demonstrated a similar incidence of irAEs in NHB patients with NSCLC as compared to other racial groups. Patients who developed irAEs experienced significantly improved survival outcomes. This association remained independent of race and ethnicity, underscoring the importance of providing unbiased treatment recommendations.

The development of immune-related adverse events (irAEs) has been associated with improved survival outcomes in non-small cell lung cancer (NSCLC). This study evaluated the association between the development of irAEs and treatment outcomes across racially diverse groups treated at a safety net hospital.

Implications for practice.

Our study evaluates a more inclusive patient population with black patients comprising half the studied population. We show that there is a similar incidence of immune-related adverse events (irAEs) in black patients as compared to other racial groups and that patients who develop irAEs had better survival outcomes irrespective of race. This further emphasizes the necessity of actively addressing healthcare disparities among racial minorities by advocating for unbiased treatment recommendations for black patients with advanced lung cancer.

Introduction

Immune checkpoint inhibitors (ICIs) block the inhibitory effects of cancer cells on the immune cells, which up-regulates immunologic tumor control.¹ This, in turn, can lead to autoimmune inflammation of other organ systems, collectively called immune-related adverse events (irAEs).^2-4 These adverse events are distinct in mechanism and management from those of other systemic anti-cancer therapies.^5-7 While lower-grade irAEs are usually managed with temporary treatment interruption or immunosuppressive treatment, severe toxicity can be life-threatening and may require treatment discontinuation, and/or administration of higher-dose corticosteroids.²

These adverse events have also shown a correlation with improved survival outcomes. A recent meta-analysis encompassing 51 studies demonstrated that patients with metastatic melanoma and lung cancer who developed irAEs experienced better survival outcomes.⁸ Similarly, in renal cell carcinoma, urothelial cancer, and head and neck cancers, the development of irAEs was associated with improved treatment efficacy.⁸ Specifically, patients with advanced non-small cell lung cancer (NSCLC) who develop irAEs have been shown to have improved survival compared to those without an irAE.^9-12 However, it is important to note that clinical trials often lack representation from minority populations. The majority of available data stems from studies that predominantly enrolled White patients, with limited information regarding the non-White population.^9-14 Consequently, the impact of race on the incidence of irAEs and treatment outcomes with ICI therapy remains insufficiently studied, and the existing studies have presented conflicting results.^15-17 Therefore, this single-institution study aims to address these gaps by evaluating the association between the development of irAEs and survival outcomes in different racial groups. Additionally, the study seeks to determine the incidence and potential associations of irAEs with racial groups. By focusing on a diverse population, this study intends to provide insights into the relationship among race, irAEs, and treatment effectiveness, contributing to a more comprehensive understanding of ICI therapy.

Methods

This is a retrospective cohort study that included NSCLC patients who received ICIs at Boston Medical Center (BMC) between June 2015 and October 2020. Ethical approval was obtained from the Institutional review board, and clinical and laboratory data were collected from electronic health records. The study data were managed using Research Electronic Data Capture (REDCap) electronic data capture tools hosted at Boston University, CTSI 1UL1TR00143.¹⁸ The patients’ PD-L1 Tumor Proportion Score was assessed using Dako’s companion diagnostic for Keytruda 22C3 and dichotomized for analysis as <1 and ≥1%. Responses were evaluated, and the best response was reported. The progression-free survival (PFS) was calculated based on the verified progression date while on immunotherapy, as determined by the investigators’ review of radiology images such as CT chest/abdomen/pelvis, PET scan, and brain MRI-based restaging scans, without formal RECIST evaluation; as former studies has shown agreement between real-world and RECIST-based assessments.^10,19,20 The responses were graded as complete response (CR), partial response (PR), stable disease (SD), and progression of disease (PD). The best overall response rates (ORR) were defined as the combination of CR and PR, and the disease control rate (DCR) was defined as the combination of CR, PR, and SD. To evaluate the role of insurance, we divided the patients into two groups: those with Medicare or private insurance and those with Medicaid, BMC health, MassHealth insurance or uninsured. The rationale behind this categorization lies in the observed similarities in the socioeconomic status of patients within each insurance group. Typically, private insurance and Medicare beneficiaries tend to come from higher socio-economic backgrounds, whereas Medicaid/Masshealth and BMC healthnet recipients often represent individuals with lower socioeconomic status.

Details of irAEs were collected, including the type of irAEs, organ affected, grade, type of treatment given, start date and duration of treatment, outcomes, and resultant immunotherapy pause or discontinuation. Pneumonitis cases labeled as immunotherapy-related were identified based on imaging findings inconsistent with radiation-induced pneumonitis. Cases closer to radiation treatment were considered radiation-induced, and a multidisciplinary team evaluated each case. The patients were divided into 2 groups based on the presence or absence of irAEs, and the association between irAEs and socio-demographic variables was carried out using univariable and multivariable logistic regression analysis. For the multivariable model, variables were selected using the simple regression method. For analyzing the primary outcome, PFS, and secondary outcome, overall survival (OS), Cox regression analysis was carried out and Kaplan-Meier curves were used for its presentation. For multivariable analysis, the variables mentioned in Table 1 were included in the model using the simple cox regression method. Patients with missing values were excluded from the multivariable analysis. A sensitivity analysis to evaluate the associations between irAEs, and the PFS and OS at one year were conducted using univariable and multivariable logistic regression analysis. All statistical analysis was carried out using SPSS version 26 (IBM Corp.), and P-values < .05 were considered statistically significant.

Table 1.

Sociodemographic characteristics.

n (%)	NHB	Other racial groups	P value	Overall
Total	69 (50)	69 (50)		138
Age (mean ±SD)	66.0 ± 11	66.2 ± 8.6	.916	66 ± 10
Gender
Male	37 (63.6)	43 (62.3)	.301	80 (58)
Female	32 (46.4)	26 (47.7)		58 (42)
BMI
<30	54 (78.3)	57 (82.6)	.830	111 (80.4)
>/=30	15 (21.7)	12 (17.4)		27 (19.6)
Insurance
Group 1 (Medicare + private)	50 (72.5)	40 (58)	.074	90 (65.2)
Group 2 (Medicaid + BMC + MassHealth + uninsured)	19 (27.5)	29 (42)		48 (34.7)
Smoking status
Never smoker	11 (15.9)	5 (7.2)	.111	16 (11.6)
Current/former smoker	58 (84.1)	64 (92.8)		122 (88.4)
ECOG
0-1	50 (72.5)	55 (79.7)	.918	105 (76.1)
>/=2	19 (27.5)	14 (20.3)		33 (23.9)
CCI	8.5 ± 3.1	8.5 ± 3.4	.959	8.5 ± 3.3
Auto-immune disease	2 (2.9)	0 (0)	N/A	5 (3.6)
PD-L1
<1%	22 (31.9)	15 (21.7)	.202	37 (26.8)
≥1%	18 (26.1)	27 (39.1)		45 (32.6)
Not tested	29 (42.0)	27 (39.1)		56 (41.3)
Histologic subtype
Squamous cell carcinoma	26 (37.7)	21 (30.4)	.369	47 (34.1)
Other	43 (62.3)	48 (69.6)		91 (65.9)
Number of therapies before ICI
0	35 (50.7)	42 (60.9)	.230	77 (55.8)
>/=1	34 (49.3)	27 (39.1)		61 (44.2)
Immunotherapy given
Pembrolizumab	31 (44.9)	32 (46,4)	.474	63 (45.7)
Nivolumab	27 (39.1)	24 (40.9)		51 (40)
Nivolumab/ipilimumab	1 (1.7)	1 (1.7)		2 (1.4)
Durvalumab	10 (16.7)	12 (17.4)		22 (14.5)
Chemo-immunotherapy	28 (40.6)	32 (46.4)	.492	6043.5)

^*Other race include Non-Hispanic White (NHW), Hispanic Whites, Hispanic Blacks, Asians and American Indians or Native Americans.

^*BMI, Body Mass Index; ; *CCI, Charlson Comorbidity Index; *ECOG, Eastern Cooperative Oncology group performance status.

^#Other Histologic groups include adenocarcinoma, adeno-squamous carcinoma, poorly differentiated carcinoma.

Results

Baseline clinical characteristics

In this study, we examined 138 patients with NSCLC who received ICIs. Of these patients, 58 (42.0%) were female, with a mean age of 66 ± 10 years. The study population was racially diverse, with 69 (50%) non-Hispanic Blacks (NHB) and 69 (50%) from other racial groups including 34% (47) as non-Hispanic White. The distribution of other races was: 8 Asians, 7 cases with unknown race, 5 Hispanic White, and 2 Hispanic African American. Based on TNM Staging (AJCC 8th Edition), 47 patients had stage III at diagnosis while 91 had stage IV at diagnosis. The majority of patients (65.2%) had Medicare or private insurance, 30.4% had Medicaid/MassHealth/BMC insurance, and 4.3% were uninsured. Most patients (88.4%) had a history of smoking, and 20.3% had a history of alcohol use. The average mean Charlson Comorbidity Index (CCI) was 8.5 ± 3.3. Of the 82 patients with known PD-L1 status, 37 (45.1%) had a PD-L1 expression level of <1%, and 45 (54.9%) had ≥1% [19 (23.2%) had pdL1 expression of 1%-49%, and 26 (31.7%) had pdL1 expression of ≥50%]. The most commonly administered ICIs were pembrolizumab (45.7%), nivolumab (38.4%), and durvalumab by 14.5% (administered as part of the consolidation phase). Furthermore, 77 patients 55.8% received immunotherapy as their initial treatment of which 52 had stage IV disease (67.5%). Concurrent chemo-immunotherapy was administered to 43.5% of patients (Table 1).

Association between irAEs and race

A total of 39 patients (28.26%) developed 47 irAEs, with 6 patients reporting 2 irAEs and 1 patient reporting 3 irAEs during their treatment course. The most common irAEs were pneumonitis (13, 27.7%) and thyroiditis (10, 21.2%), followed by pericarditis (5,3,6%) and others (Table 2). Among the 10 thyroiditis cases, one patient experienced an initial phase of hyperthyroidism requiring methimazole treatment, while the remaining 9 patients developed hypothyroidism without a preceding hyperthyroid phase. Of 47 irAEs, 20 (42.6%) were of grade 3 or 4. There were no deaths developed due to irAEs. Regarding the management of irAEs, patients who continued immunotherapy after experiencing irAEs generally had lower-grade toxicities (grades 1-2). In contrast, immunotherapy was discontinued in cases where patients developed more severe toxicities (grades 3-4), which were more likely to lead to permanent discontinuation of therapy. Specifically, 16 patients (41.0%) had to stop immunotherapy due to toxicities, while 10 (25.6%) patients experienced an interruption in treatment, with a median time of 40.5 days before resumption. Of those 40 patients, 23 required systemic corticosteroids, one patient required colchicine, and 6 required effusion drainage (Table S1).

Table 2.

IrAE based on demographic variables. (univariable and multivariable analysis).

n (%)	IrAE	No irAE	Overall	Univariable analysis		Multivariable analysis
Total	39	99	138	OR (95% CI)	P-value & $	OR (95% CI)	P-value & $
Age
<65 (Ref.)	15 (23.8)	48 (76.2)	63	1.506 (0.707-3.207)	.289	1.657 (0.550-4.989)	.370
>/=65	24 (32)	51 (68)	75
Gender
Male (Ref.)	17 (21.3)	63 (78.7)	80	2.265 (1.066-4.813)	.034	2.570 (0.831-7.946)	.101
Female	22 (37.9)	36 (62.1)	58
Race
Non-Hispanic Black	20 (29)	49 (71)	69	0.931 (0.444-1.954)	.850	1.011 (0.325-3.143)	.984
Others (including non-Hispanic Whites) (ref.)	19 (27.5)	50 (72.5)	69
Insurance
Group 1 (Medicare + private) (ref)	19 (21.1)	71 (78.9)	90	2.669 (1.242- 5.737)	.012	3.553 (1.234-10.229)	.019
Group 2 (Medicaid + BMC + MassHealth + uninsured)	20 (41.7)	28 (58.3)	48
Smoking status
Never smoker (ref.)	5 (31.2)	11 (68.8)	16	0.850 (0.275-2.628)	.778	1.011 (0.212-4.820)	.989
Current/former smoker	24 (27.9)	88 (72.1)	122
ECOG
0-1 (ref.)	31 (29.5)	74 (70.5)	105	0.869 (0.563- 1.341)	.526	0.590 (0.261-1.333)	.204
>/=2	8 (24.2)	25 (75.8)	33
PD-L1
<1% (ref.)	11(29.7)	26 (70.3)	37	1.067 (0.414-2.750)	.892	1.301 (0.434-3.991)	.646
≥1%	14 (31.1)	31 (68.9)	45
Immunotherapy given
Pembrolizumab (ref.)	19 (30.2)	44 (69.8)	63	1.187 (0.565-2.495)	.650	N/A	N/A
Nivolumab	12 (23.5)	39 (76.5)	51
Nivolumab/ipilimumab	0 (0)	2 (100)	2
Durvalumab	8 (36.4)	14 (63.6)	22

^*BMI, body mass index*CCI: Charlson Comorbidity Index; .; *ECOG: Eastern Cooperative Oncology group performance status.

In terms of racial differences, NHB patients were observed to have a slightly higher incidence of severe pneumonitis (including grade 4) (8.11.6% vs 5.7.2%) and a higher number of grades 1-2 thyroiditis cases (6.8.7% vs 3.4.3%) compared to other racial groups. However, no significant association between race and the overall development of irAEs was observed in both univariable [OR = 0.931 (0.444-1.954), P = .850] and multivariable analyses [OR = 1.011 (0.325-3.143), P = .984]. However, female gender [OR = 2.27 (1.07-4.81), P = .034], and patients with group 2 insurance (Medicaid + BMC + MassHealth + uninsured) [OR = 2.67, (1.24-5.74) P = .012) were associated with a significantly increased risk of irAEs on univariable analysis with group 2 insurance (Medicaid + BMC + MassHealth + uninsured) still showing significant association on multivariable analysis. No significant associations were found between irAEs and age, body mass index (BMI), race, smoking status, Eastern Cooperative Oncology Group (ECOG) performance status, CCI, PD-L1 expression, histologic subtype, or number of therapies before ICI. (Table 3).

Table 3:

Immune-related adverse .events

	irAE (n = 47)	Grade		ICI			n (% per 138 patients)
		1/2	3/4	Pembrolizumab	Nivolumab	Durvalumab
1	Pneumonitis	7	6	8	3	2	13 (9.4)
2	Endocrine side effects (Thyroiditis, Adrenalitis, Hypophysisitis)	10	2	7	3	2	12 (8.7)
3	Gastrointestinal side effects (colitis, cholangitis, hepatitis)	4	3	5	2	0	7 (5.1)
4	Pericardial effusion / Pericarditis	0	5	1	3	2	5 (3.6)
5	Pleural effusion	0	2	0	1	1	2 (1.4)
6	Others (Nephritis, Dermatitis, Arthritis, Neuritis)	6	2	4	2	2	8 (5.8)
Total events:		27	20	25	14	8

Outcomes

For the overall population, 13 patients (9.4%) experienced a CR, 52 (37.7%) experienced a PR, and 17 (12.3%) showed SD, corresponding to an ORR and DCR of 47.1% and 59.4%, respectively. Specifically, among the 20 patients treated with Durvalumab, 3 patients (13.6%) achieved CR, 15 patients (68.2%) had PR, 2 patients (9.1%) had SD, and 2 patients (9.1%) experienced PD. Patients with irAEs had significantly higher ORR (64.1% vs 49.4%, P = .012), DCR (79.5% vs 60.5%, P = .002), 1-year OS (76.9% vs 55.6%, P = .020), and 1-year PFS (61.5% vs 31.3%, P = .001) compared to patients without irAEs (Table 4). Additionally, patients with irAEs had a lower risk of disease progression (multivariable HR 0.46, 95% CI 0.23-0.92) compared to those without irAEs (Table 4 and Figure 1). On multivariable analysis, the association between irAEs and improved PFS and OS in NHB patients was similar to the other racial group with median PFS 246 vs 181 days; HR 0.87 (0.58-1.29) and median OS 401 vs 346 days; HR 0.53 (0.26--1.09). Also, several factors were identified as independently associated with worse PFS, including the absence of irAEs, age below 65, higher ECOG score, higher CCI, and receiving ICI as a second or subsequent line (Tables 5 and 6). These findings were consistent with the results depicted in our Forest Plot (Figure 2), which highlighted the association between irAEs and improved PFS and OS at the one-year mark. The Kaplan-Meier curves reinforce this observation, demonstrating a trend toward improved survival outcomes in NHB patients with irAEs compared to other racial group who also experienced irAEs. The log-rank test for overall survival (chi square 10.986, P = .012) and PFS (chi square 13.940, P = .003) further supports this trend (Figure 3).

Table 4.

Clinical Outcomes

n (%)	IrAE	No irAE	Overall	P-value& $
Total	39	99	138
Best response (number)
CR	5 (12.8)	8 (8.1)	13 (9.4)
PR	20 (51.3)	32 (41.3)	52 (37.7)
SD	6 (15.4)	11 (11.1)	17 (12.3)
PD	8 (20.5)	36 (36.3)	44 (31.9)
ORR (CR + PR)	25 (64.1)	40 (49.4)	65 (47.1)	.012 &
DCR (CR + PR + SD)	31 (79.5)	51 (60.5)	82 (59.4)	.002 &
Overall survival at 1 year	30 (76.9)	55 (55.6)	85 (61.6)	.020 &
PFS at 1 year	24 (61.5)	31 (31.3)	55 (39.9)	.001 &
Median OS (days)	534	323	363	.223
Median PFS (days)	510	173	208	.015

^&chi-square test was used for the analysis of categorical variables.

^$Student’s t-test was used for the analysis of quantitative variables.

^*CR: complete response; *DCR: disease control rate; *ORR: overall response rates; *PD: progressive disease; *PR: partial response; *SD: stable disease; .

Figure 1.

Kaplan Meier Curves depicting (A) Progression Free Survival in patients with and without irAEs and (B) Overall Survival in patients with and without irAEs. (A) Redline indicates patients who had irAEs, whereas the blue line indicates those who did not have irAEs. (B) Redline indicates patients who had irAEs, whereas the blue line indicates those who did not have irAEs.

Table 5.

Univariable and multivariable analysis for PFS

Variable	Patients	PFS	Univariable analysis		Multivariable analysis
IrAE			HR (95% CI)	P value	HR (95% CI)	P value
Yes	39	510	0.415 (0.251-0.688)	.001	0.463 (0.233-0.922)	.028
No (ref.)	99	173
Age; y
<65 (ref.)	63	187	0.994 (0.973-1.015)	.551	0.969 (0.940-0.998)	.039
>/=65	75	238
Gender
Male (ref.)	80	191.5	0.724 (0.477-1.098)	.128	0.657 (0.339-1.273)	.213
Female	58	258.5
BMI
<30 (ref.)	111	196	0.885 (0.755-1.038)	.132	1.099 (0.855-1.412)	.461
>/=30	27	264
Race
Non-Hispanic Black	69	246	0.866 (0.580-1.293)	.482	0.928 (0.500-1.722)	.812
Other (ref.)	69	181
Insurance
Group 1 (Medicare + private)	90	117.5	1.298 (0.846-1.992)	.232	0.866 (0.462-1.623)	.653
Group 2 (Medicaid + BMC + Mass health + uninsured) (ref.)	48	297
Smoking status
Never smoker (ref.)	16	234	0.883 (0.487-1.600)	.681	0.626 (0.257-1.527)	.303
Current/former smoker	122	208
ECOG
0-1 (ref.)	103	210	1.376 (1.106-1.711)	.004	1.551 (0.999- 2.408)	.050
>/=2	33	196
CCI
Low (< 5) (ref.)	16	343.5	1.075 (1.013-1.141)	.017	1.117 (1.020-1.222)	.017
High (>/=5)	122	180.5
PD-L1
<1% (Ref.)	37	206	0.955 (0.715-1.276)	.756	0.881 (0.621-1.250)	.478
≥1%	45	224
Histologic subtype
Squamous cell carcinoma	47	280	0.903 (0.592-1.377)	.636	1.139 (0.610-2.123)	.683
Other (Ref.)	91	196
Number of therapies before ICI
0 (Ref.)	77	314	1.283 (1.033-1.592)	.024	1.459 (1.136-1.872)	.003
>/=1	61	163
TNM Staging
Stage III (Ref.)	47	457	1.918 (1.227-2.999)	.004	1.333 (0.714-2.485)	.367
Stage IV	91	174
Chemo-immunotherapy
No (Ref.)	78	186	0.982 (0.655-1.472)	.929	0.543 (0.287-1.028)	.061
Yes	60	230

^*PD-L1 not tested patients considered as missing values and therefore, not accounted in PD-L1 and multivariable analysis.

^*BMI, Body Mass Index; *CCI: Charlson Comorbidity Index; *ECOG: Eastern Cooperative Oncology group performance status.

Table 6.

Univariable and multivariable analysis for OS.

Variable	Patients	OS	Univariable analysis		Multivariable analysis
IRAE			HR (95% CI)	P value	HR (95% CI)	P value
Yes (ref.)	39	534	0.471 (0.262-0.844	.011	0.687 (0.312-1.512)	.351
No	99	323
Age; y
<65 (ref.)	63	369	1.006 (0.983-1.030)	.622	0.965 (0.931-1.000)	.053
>/=65	75	357
Gender
Male (Ref.)	80	354	0.594 (0.363-0.972)	.038	0.694 (0.334-1.442)	.328
Female	58	411.5
BMI
<30 (Ref.)	111	351	0.911 (0.755-1.098)	.326	1.047 (0.783-1.399)	.757
>/=30	27	401
Race
Non-Hispanic Black	69	401	0.731 (0.459-1.163)	.186	0.531 (0.258-1.092)	.085
Others (ref.)	69	346
Insurance
Group 1 (Medicare + private)	90	318.5	1.444 (0.882-2.365)	.144	1.299 (0.614-2.752)	.494
Group 2 (Medicaid + BMC + Mass health + uninsured) (ref.)	48	487.5
Smoking status
Never smoker (ref.)	16	495.5	1.002 (0.513-1.959)	.995	0.770 (0.252-2.350)	.646
Current/former smoker	122	354
ECOG
0-1 (ref.)	103	397	1.643 (1.292-2.089)	<.001	2.186 (1.351-3.537)	.001
>/=2	33	331
CCI
Low (< 5) (ref.)	16	617.5	1.128 (1.055-1.205)	<.001	1.178 (1.065-1.303)	.001
High (>/=5)	122	327
PD-L1
<1% (ref.)	37	377	1.062 (0.766-1.473)	.718	0.927 (0.621-1.383)	.710
≥1%	45	446
Histologic subtype
Squamous cell carcinoma	47	498	1.045 (0.650-1.679)	.855	1.325 (0.649-2.707)	.439
Other (Ref.)	91	331
Number of therapies before ICI
0 (ref.)	77	464	1.053 (0.801-1.385)	.711	1.579 (1.180-2.112)	.002
>/=1	61	279
TNM sstaging
Stage III (ref.)	47	592	2.207 (1.294-3.764)	.004	1.140 (0.564-2.303)	.715
Stage IV	91	280
Chemo-immunotherapy
No (Ref.)	78	368.5	1.080 (0.679-1.718)	.746	0.591 (0.277-1.260)	.174
Yes	60	363

^*PD-L1 not tested patients considered as missing values and therefore, not accounted in PD-L1 and multivariable analysis.

^*BMI: Body Mass Index; *CCI: Charlson Comorbidity Index; *ECOG: Eastern Cooperative Oncology group performance status.

Figure 2.

Association of demographic variables and development of irAE with (A) progression free survival and (B) overall survival. (a) Progression free survival. (b) overall survival

Figure 3.

Kaplan Meier Curves depicting survival in patients with and without irAEs based on racial groups. (a) Progression free survival by irAE status and race. (b) Overall survival by irAE status and race.

Discussion

• Our study, like previous studies, demonstrated that the development of irAEs was associated with improved survival outcomes with ICIs.^9-12 In this study, we investigated the potential association between race and irAEs in patients receiving ICIs. Our multivariable analysis did not reveal any significant difference in irAE incidence or survival outcomes based on race. While previous studies have suggested a higher proportion of irAEs in the Caucasian population,¹⁵ to our knowledge, only a few studies have investigated the association between NHB patients and irAEs. We also observed a higher proportion of irAEs in female patients. A few clinical trials in the past have reported gender differences in ICIs, with males obtaining more relative benefits than females with ICI treatment, while meta-analyses have shown no gender-associated differences.²¹ A recent analysis of the FDA adverse reporting system suggested disproportionate signals for various irAEs between males and females,²² highlighting the need for further studies to better understand gender differences in ICI therapy. We also observed that patients with group 2 insurance (Medicaid, BMC, MassHealth, and uninsured) had an increased risk of irAEs in both univariable and multivariable analyses. This association may be reflective of the fact that individuals covered by these insurance plans often belong to lower socioeconomic groups. Lower socioeconomic status can contribute to disparities in healthcare access, timely treatment, and overall health management, potentially leading to an increased vulnerability to adverse events.

• Even though previous studies have suggested a relationship between irAEs and improved survival outcomes, there is limited data available on the non-White population.^9-14,23-27 Studies have shown worse lung cancer outcomes in Black patients, and according to a recent database analysis, the disparity persists, showing worse mortality in Black males.^28,29 In the past, an analysis of Surveillance, Epidemiology and End Results (SEER) program showed that Blacks (69.4%) had significantly higher f5-year cancer-specific mortality as compared to Whites (65.5%).²⁸ Similar trends were also evident in national 5-year survival analysis with higher survival rates in Whites as compared to Blacks³⁰ Several factors have been hypothesized to contribute to these survival disparities, including the stage at presentation, tumor characteristics, higher smoking-adjusted risk of developing lung cancer, low lung cancer screening uptake, and a lower likelihood of receiving standard-of-care interventions.^28,31-42

• The literature has demonstrated that Black and White patients experience comparable survival rates in lung cancer after controlling for stage and socioeconomic factors.^43,44 Our study supports these findings and suggests that the disparities observed in survival outcomes between different racial groups may primarily arise from suboptimal care. Furthermore, existing evidence suggests that providing equal access to care may help to reduce these racial disparities.^37,38,45-48 We believe that we provide equal access to care at our institution which translated to comparable survival outcomes among the different racial groups. Therefore, it is critical to address the underlying factors contributing to unequal care delivery to improve lung cancer outcomes and reduce racial disparities in cancer care.

• The most common irAE observed in our study population was pneumonitis, followed by thyroiditis. In past reports, pneumonitis rates varied widely from 3% to 26%, with higher rates reported in lung cancer patients.^49,50 Some studies have reported cutaneous manifestations as the most common irAEs. However, we observed this in only 3.5% of the patients.^12,51 Higher rates of irAEs have been previously reported in patients with preexisting autoimmune conditions.⁵² In our study population, only 5 patients had pre-existing autoimmune conditions; therefore, we could not observe any association with rates of irAE or outcomes and survival.

There is contradictory evidence regarding the association between treatment interruption or permanent discontinuation and prognosis. Some studies have shown that the interruption or permanent discontinuation of ICIs because of an irAE does not result in worse survival outcomes, the rationale being that anti-cancer effects continue even after their discontinuation.⁵³ In contrast, other studies have revealed detrimental effects after discontinuing ICIs due to irAEs.⁵⁴ There is evolving data regarding rechallenging after ICI interruption as an effective and safe strategy.^55-57 The decision regarding continuing ICI should be based on the initial severity and grade of the irAE. When possible, rechallenge should be tried with close monitoring.⁵⁵ In our study group, ICI treatment was continued without interruption in 13, temporarily interrupted in 10, and permanently discontinued in the remaining 16 patients. Patients who required discontinuation had a higher grade of irAE. Due to the small number in each group, we could not analyze the impact of therapy interruption or permanent discontinuation on survival outcomes.

This study has several strengths that contribute to the current understanding of irAEs and their association with outcomes in advanced lung cancer. Firstly, the study population was diverse, with an equal representation (50%) of the NHB population. To our knowledge, only a few studies have evaluated the association of race with the incidence of irAEs in advanced lung cancer.^15-17 However, there are also some limitations that should be considered when interpreting the results. This was a retrospective, single-center study, which inherently presents limitations such as residual confounding. The sample size of the study was relatively small, and a larger study may provide more definitive conclusions. In our study, 44% of patients did not receive ICI as the first line. This percentage includes patients who were treated before the first-line approval of ICI, which occurred in June 2017. As our study period started from 2015, the cohort encompasses individuals who received ICI treatment in second-line settings prior to the FDA’s authorization for first-line use in June 2017.Also, PD-L1 testing was lacking in 40% of both cohorts as during the initial phases of our study, the approval for ICI in the second line was irrespective of PD-L1 status. Subsequent to our data collection period, the field experienced advancements, and guidelines evolved, leading to a more widespread adoption of uniform PD-L1 testing. In addition, the PFS was calculated based on the verified progression date while on immunotherapy, as determined by the investigators’ review of radiology images such as CT chest/abdomen/pelvis, PET scan, and brain MRI-based restaging scans, without formal RECIST evaluation; as former studies has shown agreement between real-world and RECIST-based assessments.^10,19,20 Finally, while the association between irAEs and survival outcomes may be influenced by time bias, it is important to note that our study primarily examines association rather than causation. Also, previous studies have shown that median onset of irAEs is approximately 40 days indicating that majority of irAEs usually occur in the earlier time period of treatment.⁵⁸ Despite these limitations, this study is the first to demonstrate the association between irAEs and better survival outcomes in patients with NSCLC in a predominantly Black population, further supporting the importance of unbiased treatment recommendations without regard to race or ethnicity.

Conclusion

In this single-institution study, we demonstrated a similar incidence of irAEs in NHB patients with NSCLC as compared to other racial groups. Consistent with previous research, our findings suggest that patients receiving ICIs and developing irAEs experienced significantly better survival outcomes. Notably, we found that the association between irAE development and improved survival outcomes was not influenced by patients’ race or ethnicity. This supports the need for unbiased treatment recommendations without considering these factors.

Author contributions

Amr Radwan: Conception/Design, Collection and/or assembly of data, Data analysis and interpretation, Manuscript writing, Final approval of manuscript. Chinmay Jani: Conception/Design, Collection and/or assembly of data, Data analysis and interpretation, Manuscript writing, Final approval of manuscript. Omar Al Omari: Collection and/or assembly of data, Manuscript writing, Final approval of manuscript. Mohini Patel: Collection and/or assembly of data, Manuscript writing, Final approval of manuscript. Laura Burns: Collection and/or assembly of data, Manuscript writing, Final approval of manuscript.Zoe Mackay: Collection and/or assembly of data, Manuscript writing, Final approval of manuscript. Liuping Li: Data analysis and interpretation, Final approval of manuscript. Kiana Mahdaviani: Conception/Design, Data analysis and interpretation, Final approval of manuscript. Arielle Davidson: Manuscript writing, Final approval of manuscript. Janice Weinberg: Data analysis and interpretation, Final approval of manuscript. Peter C. Everett: Provision of study material or patients, Manuscript writing, Final approval of manuscript. Kei Suzuki: Provision of study material or patients, Manuscript writing, Final approval of manuscript. Kimberley S. Mak: Provision of study material or patients, Manuscript writing, Final approval of manuscript. Matthew H. Kulke: Conception/Design, Data analysis and interpretation, Manuscript writing, Final approval of manuscript. Umit Tapan: Provision of study material or patients, Conception/Design, Data analysis and interpretation, Manuscript writing, Final approval of manuscript.

Funding

None declared.

Conflicts of Interest

All of the authors have no conflicts of interest to declare. Authors have given final approval of the contents of the manuscript and there is no financial interest to report.

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author.