Literature DB >> 34521732

Risk of tuberculosis in patients with cancer treated with immune checkpoint inhibitors: a nationwide observational study.

Seongman Bae1, Ye-Jee Kim2, Min-Ju Kim2, Jwa Hoon Kim3,4, Sung-Cheol Yun2, Jiwon Jung1, Min Jae Kim1, Yong Pil Chong1, Sung-Han Kim1, Sang-Ho Choi1, Yang Soo Kim1, Sang-Oh Lee5.   

Abstract

BACKGROUND: While some recent studies have reported the development of tuberculosis (TB) in patients exposed to immune checkpoint inhibitors (ICIs), there is limited evidence to date. Therefore, we evaluated the risk of TB in patients with cancer exposed to ICIs using the National Health Insurance claims data in South Korea.
METHODS: Patients with diagnostic codes for non-small cell lung cancer, urothelial carcinoma or melanoma between August 2017 and June 2019 were identified. The incidence rate and standardized incidence ratio (SIR) of TB were calculated for both the ICI exposure and non-exposure groups. The risk of TB according to ICI exposure was assessed using a multivariable Cox regression model.
RESULTS: During the study period, 141 550 patients with cancer and 916 new TB cases were identified. Among the 5037 patients exposed to ICIs, 20 were diagnosed with TB at a median of 2.2 months after the ICI was initiated. The crude incidence rate of TB per 100,000 person-years was 675.8 (95% CI 412.8 to 1043.8) for the ICI exposure group and 599.1 (95% CI 560.5 to 639.6) for the non-exposure group. The SIR for TB was 8.1 (95% CI 8.0 to 8.2) in the ICI exposure group. After adjusting for potential confounding factors, ICI treatment was not significantly associated with an increased risk of TB (HR: 0.73; 95% CI 0.47 to 1.14).
CONCLUSIONS: While the incidence of TB in cancer patients exposed to ICIs was eightfold higher than in the general population, the risk of patients with cancer developing TB did not significantly differ according to ICI exposure. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  immunotherapy; programmed cell death 1 receptor; tuberculosis

Mesh:

Substances:

Year:  2021        PMID: 34521732      PMCID: PMC8442094          DOI: 10.1136/jitc-2021-002960

Source DB:  PubMed          Journal:  J Immunother Cancer        ISSN: 2051-1426            Impact factor:   13.751


Background

Inhibiting the immune checkpoint pathway has been shown to be effective in treating patients with advanced solid cancers.1–3 Since immune checkpoint inhibitors (ICIs) were introduced, the use of these drugs to treat various types of cancer has increased, and a better understanding of adverse events, such as immune-related adverse events, is increasingly necessary.4 Recently, several studies have reported the development of tuberculosis (TB) in patients during or after ICI therapy.5–12 The development of active TB in patients with advanced cancer entails significant risks, including delayed antineoplastic therapy and death. The risk of developing active TB is two to three times higher in patients with solid cancer than in the general population.13–16 In addition, antineoplastic therapy was reported as an independent risk factor for active TB in patients with cancer.17 However, there are no specific guidelines for screening or treating latent tuberculosis infection (LTBI) in patients with cancer.18 19 Notably, the Society for Immunotherapy of Cancer (SITC) guideline recommends LTBI screening prior to initiating ICI20; however, this recommendation was made considering the potential use of corticosteroids or tumor necrosis factor (TNF) inhibitors for the treatment of immune-related adverse events during ICI use, rather than the direct association between ICI and the development of active TB. Therefore, it is necessary to evaluate the burden of active TB in patients with cancer receiving ICI as well as the association between ICI exposure and the subsequent development of active TB. Estimating the incidence of active TB in patients with cancer poses significant challenges in terms of the need for longitudinal studies with large sample sizes and long observation periods, especially in high-income countries where the burden of active TB is low (<30 cases/100,000 persons per year).21 South Korea is a high-income country with an intermediate TB burden (55/100,000 persons in 2017) and thus has a considerably higher incidence of TB than other developed countries.22 In this respect, South Korea provides a unique and promising study setting including: (1) accessibility to the database of the National Health Insurance (NHI) program covering 50 million people, (2) nationwide TB notification system, and (3) an intermediate TB burden; therefore, we presumed that the analysis of the NHI claims data of South Korea could provide an important answer to the clinicoepidemiologic question about the risk of TB in patient with cancer receiving ICIs.

Methods

Study design, population, and database

This population-based retrospective cohort study was conducted using the nationwide claims database in South Korea. The NHI system in South Korea provides universal healthcare coverage to the entire population residing in the country. The healthcare providers are required to claim their medical services for reimbursement, and all these claims are collected and reviewed by the Health Insurance and Review Assessment Service (HIRA).23 The data collected by the HIRA encompasses all the claimed healthcare records, including medical visits, prescriptions, procedures and surgeries. The HIRA database is available for research purposes after the encryption and deidentification process is complete. Using the HIRA data repository, the burden of TB was estimated in patients with cancer according to ICI exposure. To determine the incidence of TB in patients receiving ICIs compared with the general population, annual statements regarding reported cases of TB and the official statistical database of the annual population census in South Korea were used.22 24 In South Korea, NHI coverage for ICIs have been approved for the following: nivolumab and pembrolizumab for advanced non-small cell lung cancer (NSCLC) since August 2017; atezolizumab for advanced NSCLC or urothelial carcinoma since January 2018; and nivolumab and pembrolizumab for advanced melanoma since February 2018. Insurance coverage for ICIs in patients with NSCLC and urothelial carcinoma are approved for patients who were previously treated with platinum-containing chemotherapy. We conducted an analysis on adult patients with cancer (aged ≥18 years) with diagnostic codes for NSCLC, urothelial carcinoma, or melanoma from August 2017 to June 2019. The exclusion criteria were as follows: (1) history of active TB, (2) HIV infection, (3) solid organ transplant, (4) inflammatory bowel disease, (5) hematologic malignancy, (6) past medication history of immunosuppressants, or (7) no available records after the first visit (lost to follow-up). The need for written or verbal consent was waived by the review board due to the observational nature of the study and the fact that the patient identifiers were fully encrypted prior to analysis.

Definitions and outcomes

Cancer patients with NSCLC, urothelial carcinoma, and melanoma were identified using International Classification of Diseases-10 (ICD-10) codes (C34, C66, C67, and C43) as primary or secondary diagnoses. ICI exposure was defined as the presence of a prescription for ICIs at least once during the study period. The remaining patients were categorized into the non-exposure group. The index date was defined as the date of the first administration of the ICI for the exposure group and the date of the first visit with diagnostic codes for cancer during the study period for the non-exposure group. The date of the last follow-up was determined by the last documented claim record for each individual during the study period. The main outcome of interest was the development of active TB requiring treatment. New cases of TB were identified by the presence of relevant diagnostic codes for active TB (ICD-10 code A15, A16, A17, A18, or A19) and prescription records for anti-TB medications as described in our previous study.25 In addition, the following potential confounding factors in the development of TB were identified based on claims records present during the study period or in the preceding 12 months: age, sex, hypertension, diabetes, dyslipidemia, chronic lung disease, chronic kidney disease, chronic liver disease, rheumatic disease, previous history of latent TB infection (LTBI) treatment, active chemotherapy, and concomitant use of corticosteroids or immunosuppressants. The use of corticosteroids was defined as the presence of prescription records for prednisone equivalents ≥15 mg/day for at least 14 days. The diagnostic and drug codes used in this study are summarized in online supplemental table 1.

Statistical analysis

Categorical data were compared using the χ2 test, and continuous variables were analyzed using the independent t-test. Incidence rates were presented as the number of TB episodes per 100,000 person-years (PYs) of follow-up. The CIs for the incidence rates were estimated under the assumption that the number of TB cases followed a Poisson distribution. To estimate the burden of TB in patients with cancer relative to the general population, standardized incidence ratios (SIRs) and 95% CIs were calculated. The risk factors for TB were identified using the Cox proportional hazard model. In the multivariable Cox regression model, baseline covariates including age, sex, health insurance type, type of cancer, diabetes, hypertension, chronic lung disease, chronic kidney disease, chronic liver disease, rheumatic disease, history of treatment for latent TB infection, active chemotherapy, concomitant use of corticosteroids, and concomitant use of immunosuppressants were included. A number of sensitivity analyses were performed to test the robustness of our findings. First, we repeatedly measured the outcome of TB as defined by diagnostic codes regardless of receiving anti-TB agents. In addition, we reanalyzed the study cohort after excluding TB cases diagnosed within 30 days after cancer diagnosis. We performed analyses in subgroups defined according to age (<50 years vs ≥50 years), sex, and cancer type. The presence of interactions in these subgroups was evaluated. Considering the comprehensive nature of the claims data, we assumed that the database has minimal or no missing values. All reported p values are two sided, and a p value less than 0.05 was considered statistically significant. Data processing and statistical analyses were conducted using SAS Enterprise Guide V.7.1 (SAS Institute).

Results

During the study period, a total of 160,742 adult patients (aged >18 years) with diagnostic codes for NSCLC, urothelial carcinoma, or melanoma were identified (figure 1). After excluding patients according to the exclusion criteria, 141,550 patients with NSCLC, urothelial carcinoma, or melanoma were included in the analysis. Of these, 5037 (3.6%) were in the ICI exposure group, and the remaining 136,513 (96.4%) patients were in the ICI non-exposure group. Among the 5037 patients in the exposure group, 1972 (39.2%), 2593 (51.5%) and 472 (9.4%) received nivolumab, pembrolizumab, and atezolizumab, respectively. The baseline characteristics of the study population are shown in table 1. We found that most of the cancer patients included in this study were male, were elderly, and had lung cancer. Patients in the ICI exposure group differed significantly from those in the ICI non-exposure group in terms of age, sex, type of cancer, comorbidities, active chemotherapy, and concomitant use of corticosteroids. No differences concerning a previous history of LTBI treatment were found between the ICI exposure and non-exposure groups.
Figure 1

Flow chart of study population. ICD-10, International Classification of Diseases-10; ICI, immune checkpoint inhibitor.

Table 1

Baseline characteristics of patients with cancer in the immune checkpoint inhibitor (ICI) exposure and non-exposure groups

ICI exposureP value*
Nivolumab(n=1972)Pembrolizumab(n=2593)Atezolizumab(n=472)Total ICI exposure(n=5037)ICI non-exposure(n=136,513)
Age, year, mean (SD)65.8 (9.7)65.5 (10.2)67.7 (9.9)65.8 (10.0)68.5 (11.1)<0.001
Sex<0.001
 Male1522 (77.2)1858 (71.7)372 (78.8)3752 (74.5)92 050 (67.4)
 Female450 (22.8)735 (28.3)100 (21.2)1285 (25.5)44 463 (32.6)
Type of insurance<0.001
 National Health Insurance1779 (90.2)2380 (91.8)425 (90.0)4584 (91.0)127 201 (93.2)
 Medical aids†156 (7.9)193 (7.4)45 (9.5)394 (7.8)8495 (6.2)
 Veterans37 (1.9)20 (0.8)2 (0.4)59 (1.2)817 (0.6)
Type of cancer<0.001
 NSCLC1796 (91.1)2038 (78.6)154 (32.6)3988 (79.2)94 208 (69.0)
 Urothelial carcinoma9 (0.5)10 (0.4)318 (67.4)337 (6.7)39 268 (28.8)
 Melanoma167 (8.5)545 (21.0)0 (0)712 (14.1)4086 (3.0)
Underlying diseases
 Diabetes mellitus641 (32.5)804 (31.0)145 (30.7)1590 (31.6)39 015 (28.6)<0.001
 Hypertension968 (49.1)1220 (47.0)251 (53.2)2439 (48.4)71 349 (52.3)<0.001
 Chronic lung disease1163 (59.0)1392 (294.9)210 (44.5)2765 (54.9)55 289 (40.5)<0.001
 Chronic kidney disease72 (3.7)72 (15.3)55 (11.7)199 (4.0)6346 (4.6)0.02
 Chronic liver disease37 (1.9)34 (7.2)6 (1.3)77 (1.5)1506 (1.1)0.01
 Rheumatic disease49 (2.5)73 (15.5)17 (3.6)139 (2.8)2873 (2.1)0.002
Predisposing factors
 History of LTBI treatment19 (1.0)28 (1.1)2 (0.4)49 (1.0)1686 (1.2)0.10
 Active chemotherapy569 (28.9)675 (26.0)70 (14.8)1314 (26.1)31 870 (23.3)<0.001
 Concomitant use of corticosteroid459 (23.3)533 (20.6)71 (15.0)1063 (21.1)12 603 (9.2)<0.001
 Concomitant use of immunosuppressant14 (0.7)34 (1.3)26 (5.5)74 (1.5)1889 (1.4)0.69

Data are n (%).

*Comparison of total ICI exposure group to non-exposure group.

†Medical aid is a public assistance program that targets impoverished people in need of medical assistance as part of the South Korean social welfare program.

LTBI, latent tuberculosis infection; NSCLC, non-small cell lung cancer.

Flow chart of study population. ICD-10, International Classification of Diseases-10; ICI, immune checkpoint inhibitor. Baseline characteristics of patients with cancer in the immune checkpoint inhibitor (ICI) exposure and non-exposure groups Data are n (%). *Comparison of total ICI exposure group to non-exposure group. †Medical aid is a public assistance program that targets impoverished people in need of medical assistance as part of the South Korean social welfare program. LTBI, latent tuberculosis infection; NSCLC, non-small cell lung cancer. There were 916 cases of TB infections in the 141,550 patients included in this study, 20 of which occurred in the ICI exposure group. Detailed characteristics of these 20 cases of TB are summarized in table 2. Most of the patients were male (80% (16/20)) and most had NSCLC (95% (19/20)). Of the 20 cases of TB, 12 occurred in patients who had received pembrolizumab, and eight occurred in patients who had received nivolumab. No cases of TB occurred in patients who received atezolizumab or patients with urothelial carcinoma. TB developed a median of 2.2 months (range: 0.4–16.5) after ICI treatment was initiated, and most of the cases of TB (80% (16/20)) were pulmonary infections. Eight (40%) patients were taking corticosteroids concomitantly.
Table 2

Characteristics of the 20 patients with tuberculosis following ICI exposure

Patient numberAge, yearsSexCancer typeOther comorbiditiesType of ICITotal ICI cycles receivedInterval* (months)Type of TBConcomitant corticosteroidConcomitant immunosuppressant
173MaleLung cancerNoneNivolumab55.7PulmonaryNoNo
280MaleLung cancerHypertension and chronic lung diseaseNivolumab11.3PulmonaryNoNo
365MaleLung cancerChronic lung diseaseNivolumab81.7MiliaryNoNo
482MaleLung cancerChronic lung diseasePembrolizumab61.3PulmonaryNoNo
574FemaleLung cancerHypertension, diabetes and chronic kidney diseasePembrolizumab20.4MeningitisYesNo
681FemaleMelanomaHypertension and chronic lung diseasePembrolizumab20.7PulmonaryNoNo
765MaleLung cancerNonePembrolizumab32.8VertebraYesNo
844FemaleLung cancerHypertensionNivolumab21.5PulmonaryNoNo
961MaleLung cancerChronic lung diseasePembrolizumab74.7PericarditisNoNo
1064MaleLung cancerHypertension and diabetesPembrolizumab75.3PulmonaryYesNo
1158MaleLung cancerNonePembrolizumab22.3PulmonaryNoNo
1259MaleLung cancerHypertension and chronic lung diseasePembrolizumab10.9PulmonaryYesNo
1371MaleLung cancerHypertension and chronic lung diseaseNivolumab20.6PulmonaryNoNo
1453MaleLung cancerChronic lung diseaseNivolumab107.5PulmonaryYesNo
1554MaleLung cancerDiabetes and chronic lung diseasePembrolizumab22.8PulmonaryNoNo
1679MaleLung cancerChronic lung diseasePembrolizumab32.0PulmonaryYesNo
1767FemaleLung cancerHypertension and diabetesNivolumab1016.5PulmonaryYesNo
1878MaleLung cancerChronic lung diseasePembrolizumab1013.6PulmonaryNoYes
1961MaleLung cancerHypertension, diabetes and chronic lung diseasePembrolizumab20.6PulmonaryYesNo
2083MaleLung cancerChronic lung diseaseNivolumab109.1PulmonaryNoNo

*Interval from the first administration of the ICI to the development of TB

ICI, immune checkpoint inhibitor; TB, tuberculosis.

Characteristics of the 20 patients with tuberculosis following ICI exposure *Interval from the first administration of the ICI to the development of TB ICI, immune checkpoint inhibitor; TB, tuberculosis.

Incidence rate and standardized incidence ratio of TB in the ICI exposure and non-exposure groups

The total observation time was 152,521 PY for all the patients with cancer included in this study. Of this, 2959 PY was attributed to the ICI exposure group, and 149,562 PY to the ICI non-exposure group, with average follow-up periods of 0.59 and 1.10 years, respectively. The crude TB incidence per 100,000 PY was 675.8 in the ICI exposure group and 599.1 in the ICI non-exposure group (table 3). The SIR of TB in the ICI exposure group was 8.1 (95% CI 8.0 to 8.2), 6.0 (95% CI 5.9 to 6.1), and 10.9 (95% CI 10.7 to 11.1) for the total, male, and female participants, respectively (table 4). The SIR estimates of TB for the total, male, and female participants in the non-exposure group were 8.2 (95% CI 8.1 to 8.3), 8.4 (95% CI 8.2 to 8.4), and 7.9 (95% CI 7.8 to 8.1), respectively.
Table 3

The incidence rate of TB in patients with cancer exposed to ICIs

ICI exposureICI non-exposure
n (%)TB eventsPerson-yearsIncidence* (95% CI)n (%)TB eventsPerson-yearsIncidence* (95% CI)
Total5037 (100.0)202959675.8 (412.8 to 1043.8)136 513 (100.0)896149 562599.1 (560.5 to 639.6)
Sex
 Male3752 (74.5)162173736.5 (421.0 to 1196.0)92 050 (67.4)67698 733684.7 (634.0 to 738.3)
 Female1285 (25.5)4787508.3 (138.5 to 1301.6)44 463 (32.6)22050 829432.8 (377.5 to 494.0)
Age (years)
 20–298 (0.2)05288 (0.2)3319939.7 (193.8 to 2746.1)
 30–3940 (0.8)0261278 (0.9)61464409.9 (150.4 to 892.2)
 40–49269 (5.3)1184544.4 (13.8 to 3033.0)5805 (4.3)286992400.5 (266.1 to 578.8)
 50–59976 (19.4)4607658.7 (179.5 to 1686.6)20 749 (15.2)8625 013343.8 (275.0 to 424.6)
 60–691793 (35.6)61058567.3 (208.2 to 1234.7)40 364 (29.6)25847 363544.7 (480.3 to 615.4)
 70–791615 (32.1)5914546.8 (177.5 to 1276.0)46 003 (33.7)33549 406678.1 (607.4 to 754.7)
 ≥80336 (6.7)41652422.3 (660.0 to 6202.1)22 026 (16.1)18019 006947.1 (813.8 to 1096.1)
Type of cancer
 NSCLC3988 (79.2)192336813.2 (489.6 to 1269.9)94 208 (69.0)75296 624778.3 (723.6 to 836.0)
 Urothelial carcinoma337 (6.7)017338 931 (28.5)13549 047275.3 (230.8 to 325.8)
 Melanoma712 (14.1)1450222.0 (5.6 to 1237.0)3374 (2.5)93891231.3 (105.8 to 439.0)

*Indicates incidence rate per 100,000 person-years.

ICI, immune checkpoint inhibitor; NSCLC, non-small cell lung cancer; TB, tuberculosis.

Table 4

The standardized incidence ratio of TB in patients with cancer exposed to ICIs

Standardized TB incidence rate*95% CITB incidence rate in general population*95% CIStandardized incidence ratio95% CIP value
ICI exposure
 Total494.4492.3 to 496.561.460.6 to 62.18.18.0 to 8.2<0.001
 Male428.2425.3 to 431.071.670.4 to 72.26.05.9 to 6.1<0.001
 Female559.3556.1 to 562.551.450.4 to 52.310.910.7 to 11.1<0.001
ICI non-exposure
 Total502.6500.5 to 504.861.460.6 to 62.18.28.1 to 8.3<0.001
 Male600.0596.7 to 603.471.670.4 to 72.28.48.2 to 8.5<0.001
 Female407.1404.4 to 409.951.450.4 to 52.37.97.8 to 8.1<0.001

*Indicates incidence rate per 100,000 person-years.

ICI, immune checkpoint inhibitor; TB, tuberculosis.

The incidence rate of TB in patients with cancer exposed to ICIs *Indicates incidence rate per 100,000 person-years. ICI, immune checkpoint inhibitor; NSCLC, non-small cell lung cancer; TB, tuberculosis. The standardized incidence ratio of TB in patients with cancer exposed to ICIs *Indicates incidence rate per 100,000 person-years. ICI, immune checkpoint inhibitor; TB, tuberculosis.

Risk factors for TB in patients with cancer

The univariable Cox analysis (table 5) revealed that the following risk factors were significantly associated with TB: increasing age (HR 1.02; 95% CI 1.02 to 1.03), male sex (HR 1.54; 95% CI 1.33 to 1.79), medical aids (HR 1.40; 95% CI 1.10 to 1.78), lung malignancy (HR 3.35; 95% CI 1.80 to 6.25), diabetes (HR 1.22; 95% CI 1.07 to 1.41), hypertension (HR 1.18; 95% CI 1.04 to 1.34), chronic lung disease (HR 1.77; 95% CI 1.55 to 2.01), active chemotherapy (HR 1.72; 95% CI 1.50 to 1.98), and the concomitant use of corticosteroids (HR 1.56; 95% CI 1.29 to 1.88). As a risk factor, ICI treatment was not found to be significantly associated with the development of TB in the univariable analysis (HR 0.85; 95% CI 0.55 to 1.33) and in the multivariable Cox regression analysis (HR 0.73; 95% CI 0.47 to 1.14).
Table 5

Risk of tuberculosis in patients with cancer

Total,(n)TB cases, (n)Person-yearsUnadjustedAdjusted
HR (95% CI)P valueHR (95% CI)P value
Age, year1.02 (1.02 to 1.03)<0.0011.03 (1.02 to 1.03)<0.001
Sex
 Male95,802692100 9051.54 (1.33 to 1.79)<0.0011.61 (1.39 to 1.89)<0.001
 Female45,74822451,6161 (reference)1 (reference)
Health insurance type
 National health insurance127,201837142,7161 (reference)0.021 (reference)
 Medical aids*84957385441.40 (1.10 to 1.78)0.011.28 (1.01 to 1.63)0.04
 Veterans8147612620.90 (0.40 to 2.01)0.800.77 (0.34 to 1.72)0.52
Type of cancer
 NSCLC98,19677198,9603.35 (1.80 to 6.25)<0.0012.43 (1.30 to 4.54)0.01
 Urothelial carcinoma39,26813549,2201.27 (0.67 to 2.41)0.470.91 (0.48 to 1.73)0.76
 Melanoma40861043421 (reference)<0.0011 (reference)
Underlying diseases
 Diabetes mellitus40,60529542,1491.22 (1.07 to 1.41)0.0041.07 (0.93 to 1.24)0.34
 Hypertension73,78850978,0741.18 (1.04 to 1.34)0.010.99 (0.86 to 1.14)0.86
 Chronic lung disease58,05449159,3441.77 (1.55 to 2.01)<0.0011.32 (1.15 to 1.51)<0.001
 Chronic kidney disease65455369881.28 (0.97 to 1.69)0.081.29 (0.97 to 1.72)0.08
 Chronic liver disease15831515601.56 (0.94 to 2.60)0.881.38 (0.83 to 2.31)0.22
 Rheumatic disease30122731591.42 (0.97 to 2.09)0.071.31 (0.89 to 1.93)0.17
Predisposing factors
 History of LTBI treatment17351119030.97 (0.54 to 1.76)0.930.97 (0.54 to 1.76)0.92
 Active chemotherapy33,18430632,3531.72 (1.50 to 1.98)<0.0011.45 (1.24 to 1.69)<0.001
 Concomitant use of corticosteroid13,66612513,1961.56 (1.29 to 1.88)<0.0011.09 (0.89 to 1.34)0.4
 Concomitant use of immunosuppressant19631422731.03 (0.61 to 1.75)0.900.98 (0.58 to 1.68)0.95
 ICI treatment50372029590.85 (0.55 to 1.33)0.480.73 (0.47 to 1.14)0.17

*Medical aid is a public assistance program that targets impoverished people in need of medical assistance as part of the South Korean social welfare program.

ICI, immune checkpoint inhibitor; LTBI, latent tuberculosis infection; NSCLC, non-small cell lung cancer; TB, tuberculosis.

Risk of tuberculosis in patients with cancer *Medical aid is a public assistance program that targets impoverished people in need of medical assistance as part of the South Korean social welfare program. ICI, immune checkpoint inhibitor; LTBI, latent tuberculosis infection; NSCLC, non-small cell lung cancer; TB, tuberculosis.

Subgroup and sensitivity analyses

In the subgroup analyses, no significant difference in incidence for TB was observed between the ICI exposure and ICI non-exposure groups, regardless of age group, sex, and type of cancer (all p values for interaction >0.05) (table 6). The results were robust in sensitivity analyses in which the definition of TB was made by diagnostic codes regardless of anti-TB medication. In the sensitivity analysis conducted in the study cohort, excluding TB cases diagnosed within 30 days of cancer diagnosis, no significant difference in TB incidence was observed between the ICI exposure and ICI non-exposure groups (table 6).
Table 6

Subgroup and sensitivity analyses

TB events in non-exposure group, (n)TB events in ICI exposure group, (n)HR (95% CI)P value
Subgroup analyses*
 Age0.98†
  <503710.62 (0.09 to 4.55)0.64
  ≥50859190.69 (0.44 to 1.09)0.11
 Sex0.56†
  Male676160.71 (0.43 to 1.16)0.17
  Female22040.89 (0.33 to 2.42)0.83
 Cancer subtype0.98†
  NSCLC752190.76 (0.48 to 1.19)0.23
  Urothelial carcinoma13500.93 (0.06 to 15.15)0.96
  Melanoma910.84 (0.14 to 5.15)0.85
Sensitivity analyses*
 Defining TB by ICD-10 codes only1765440.83 (0.61 to 1.12)0.21
 Excluding TB cases within 30days following cancer diagnosis637150.89 (0.53 to 1.50)0.67

*All subgroup and sensitivity analyses were adjusted for age, sex, health insurance type, type of cancer, diabetes, hypertension, chronic lung disease, chronic kidney disease, chronic liver disease, rheumatic disease, active chemotherapy, concomitant immunosuppressant use, concomitant use of corticosteroid, and history of treatment for latent TB infection.

†P value for interaction.

ICD-10, International Classification of Diseases code version 10; ICI, immune checkpoint inhibitor; NSCLC, non-small cell lung cancer; PS, propensity matching; TB, tuberculosis.

Subgroup and sensitivity analyses *All subgroup and sensitivity analyses were adjusted for age, sex, health insurance type, type of cancer, diabetes, hypertension, chronic lung disease, chronic kidney disease, chronic liver disease, rheumatic disease, active chemotherapy, concomitant immunosuppressant use, concomitant use of corticosteroid, and history of treatment for latent TB infection. †P value for interaction. ICD-10, International Classification of Diseases code version 10; ICI, immune checkpoint inhibitor; NSCLC, non-small cell lung cancer; PS, propensity matching; TB, tuberculosis.

Discussion

In this nationwide population-based study, the incidence of TB in the patients exposed to ICIs was approximately eightfold higher relative to the general population. However, there were no significant differences in risk for TB in patients with cancer according to ICI exposure. These findings suggest that the development of TB in patients with cancer receiving ICIs was associated with the underlying malignancy rather than the exposure to ICIs. To the best of our knowledge, this is the first study illustrating the burden of TB in cancer patients with or without ICI exposure. Similar to findings in several chronic infections, including HIV, immune checkpoint proteins (programmed death-1 [PD-1] and programmed death-ligand 1 [PD-L1]) were overexpressed in the monocytes or natural killer cells collected from patients with active TB.26 27 An enhanced PD1/PD-L1 pathway can contribute to chronic and persistent infections through the dysfunction of immune effector cells. Inhibiting the immune checkpoint pathway may therefore prevent TB reactivation by interfering with the ability of mycobacterium to exploit the PD1/PD-L1 pathway for immune evasion. In animal models, however, PD-1 deficient mice were more susceptible to mycobacterium than wild-type mice, and they showed more evidence of fulminant infectious processes.28–30 Thus, the PD-1/PD-L1 pathway may aid in controlling tissue damage by preventing the excessive production of IFN-gamma in effector T cells activated by TB antigens.31 However, whether TB susceptibility in patients with cancer could be clinically affected by the use of ICIs has not yet been clarified. We found that there was no significant difference in the TB incidence among cancer patients according to ICI exposure. This finding was consistently observed before and after adjusting for multiple variables including age, sex, cancer type, underlying comorbidities, previous treatment of LTBI, active chemotherapy, and concomitant use of corticosteroids. Therefore, the high rate of TB in the ICI exposure group in our study was likely due to the underlying malignancy rather than exposure to ICIs, given that 19 out of 20 TB cases previously exposed to ICI were patients with lung cancer. In addition, the use of immunosuppressive medications such as corticosteroids to manage immune-related adverse events following ICI administration may also have contributed to the development of TB in this patient population.32 Considering the increased risk for TB with corticosteroid use, there may be an additive risk of developing TB in patients with cancer receiving concomitant corticosteroids.33 Therefore, prescreening for LTBI should be considered in patients with cancer using ICI as recommended by the SITC guideline regarding the possibility of immune-related adverse events requiring the use of corticosteroids or TNF inhibitors.20 32 It has been reported that patients with solid cancers have a risk of developing active TB that is two to three times greater that of the general population.13–15 In particular, the incidence of TB in patients with lung cancer was reported to be six to nine times that of the general population.15 16 Consistent with these findings, our study showed that patients with cancer (including those with lung, urothelial, and skin cancers) had about an eightfold higher rate of developing active TB compared with the general population in South Korea. Given the greater risk of TB in patients with lung cancer compared with those with other types of cancer, the high TB incidence observed in our study was likely due to the large proportion of patients with lung cancer in the study population. Considering the high risk for TB in patients with cancer regardless of ICI exposure, further targeted study is needed to evaluate the cost-effectiveness of prescreening and treatment for LTBI in patients with cancer. There were several strengths to this study. To the best of our knowledge, this is the first population-based study reporting the risk of TB following ICI exposure. By identifying those exposed to ICIs in a nationwide sample from a country with an intermediate burden of TB, we were able to effectively determine the incidence of the disease in those exposed to ICIs and thus assess whether ICIs were associated with TB occurrence. In addition, an SIR was accurately calculated based on annual statistics of reported TB cases and population census data published by the Korean government. We also excluded individuals with suppressed cellular immunity, which is a known risk factor for the development of TB. In the risk factor analysis, a multivariable analysis was conducted to control for potential confounders after adjusting for a range of variables. In addition, we performed several subgroup and sensitivity analyses to confirm the robustness of our results. There were several limitations to our study. First, due to the observational nature of the claims database, it cannot be ruled out that TB cases may have been misclassified. The methods used to identify cases of TB in the national claims data and the national reported data were not the same. However, healthcare providers are required to report new cases of TB through a web-based notification system in South Korea,22 34 and the completeness of the TB reporting data has been found to be over 90% in comparison with the reimbursement data from the NHI.35 Therefore, misclassification bias is expected to be low in this study. Second, data on TB severity were not assessed. Since concerns have been raised about the more fulminant course of TB after ICI treatment, as seen in animal studies, further studies are needed to address the severity of TB following ICI exposure. Third, only a limited number of ICIs (nivolumab, atezolizumab, and pembrolizumab) and types of cancer (lung cancer, urothelial carcinoma, and skin cancer) were assessed in this study. Therefore, the risk of TB in patients with other types of cancers, as well as in those receiving other types of ICIs, such as CTLA-4 inhibitors, were not evaluated in this study. Fourth, detailed information on PD-1 expression, cancer stage, performance status, surgical history, and prior radiation therapy in patients with cancer were not collected as raw data and therefore not included in the analysis. Fifth, the observation period in the ICI exposure group was relatively short compared with the ICI non-exposure group. Due to the nature of the slow-growing mycobacteria and the shorter observation period in the ICI exposure group, the number of TB events may have been underestimated in current study. Further studies with a longer follow-up periods may provide better answers in the future. Sixth, because the claims data did not contain the information on exposure history to the index TB patient, it was not possible to distinguish between recently transmitted TB and reactivation of remote infection among the cases of active TB. Therefore, the results of this study should be interpreted with caution, especially in areas with low TB burden where remote infection rather than recent transmission substantially contributes to the burden of active TB.36 In our study, the incidence of TB in patients with cancer receiving ICIs was eight times higher than in the general population. However, no significant differences were observed among patients with cancer according to ICI exposure. These findings suggest that patients with cancer undergoing chemotherapy are at risk for developing TB regardless of the type of treatment they are receiving. Further studies are needed to evaluate the cost-effectiveness of testing for and treating LTBI in patients with cancer receiving systemic chemotherapy.
  33 in total

1.  Risk of Active Tuberculosis in Patients with Cancer: A Systematic Review and Meta-Analysis.

Authors:  Matthew P Cheng; Claire Nour Abou Chakra; Cedric P Yansouni; Sonya Cnossen; Ian Shrier; Dick Menzies; Christina Greenaway
Journal:  Clin Infect Dis       Date:  2016-12-16       Impact factor: 9.079

2.  Management of toxicities from immunotherapy: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.

Authors:  J B A G Haanen; F Carbonnel; C Robert; K M Kerr; S Peters; J Larkin; K Jordan
Journal:  Ann Oncol       Date:  2017-07-01       Impact factor: 32.976

3.  Infectious complications associated with the use of immune checkpoint inhibitors in oncology: reactivation of tuberculosis after anti PD-1 treatment.

Authors:  H Picchi; C Mateus; C Chouaid; B Besse; A Marabelle; J M Michot; S Champiat; A L Voisin; O Lambotte
Journal:  Clin Microbiol Infect       Date:  2017-12-18       Impact factor: 8.067

4.  Risk of tuberculosis in patients with solid cancers and haematological malignancies: a systematic review and meta-analysis.

Authors:  Claudia C Dobler; Kelvin Cheung; John Nguyen; Andrew Martin
Journal:  Eur Respir J       Date:  2017-08-24       Impact factor: 16.671

5.  CD4 T cells promote rather than control tuberculosis in the absence of PD-1-mediated inhibition.

Authors:  Daniel L Barber; Katrin D Mayer-Barber; Carl G Feng; Arlene H Sharpe; Alan Sher
Journal:  J Immunol       Date:  2010-12-20       Impact factor: 5.422

6.  Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer.

Authors:  Julie Brahmer; Karen L Reckamp; Paul Baas; Lucio Crinò; Wilfried E E Eberhardt; Elena Poddubskaya; Scott Antonia; Adam Pluzanski; Everett E Vokes; Esther Holgado; David Waterhouse; Neal Ready; Justin Gainor; Osvaldo Arén Frontera; Libor Havel; Martin Steins; Marina C Garassino; Joachim G Aerts; Manuel Domine; Luis Paz-Ares; Martin Reck; Christine Baudelet; Christopher T Harbison; Brian Lestini; David R Spigel
Journal:  N Engl J Med       Date:  2015-05-31       Impact factor: 91.245

7.  Programmed death (PD)-1:PD-ligand 1/PD-ligand 2 pathway inhibits T cell effector functions during human tuberculosis.

Authors:  Javier O Jurado; Ivana B Alvarez; Virginia Pasquinelli; Gustavo J Martínez; María F Quiroga; Eduardo Abbate; Rosa M Musella; H Eduardo Chuluyan; Verónica E García
Journal:  J Immunol       Date:  2008-07-01       Impact factor: 5.422

8.  Anti-PD1 Antibody Treatment and the Development of Acute Pulmonary Tuberculosis.

Authors:  Kohei Fujita; Tsuyoshi Terashima; Tadashi Mio
Journal:  J Thorac Oncol       Date:  2016-07-14       Impact factor: 15.609

9.  T cells from Programmed Death-1 deficient mice respond poorly to Mycobacterium tuberculosis infection.

Authors:  Sultan Tousif; Yogesh Singh; Durbaka Vijaya Raghava Prasad; Pawan Sharma; Luc Van Kaer; Gobardhan Das
Journal:  PLoS One       Date:  2011-05-12       Impact factor: 3.240

10.  Cancer-specific incidence rates of tuberculosis: A 5-year nationwide population-based study in a country with an intermediate tuberculosis burden.

Authors:  Gi Hyeon Seo; Min Jae Kim; Soyoung Seo; Boram Hwang; Eugene Lee; Yujin Yun; Minsun Choi; Moonsuk Kim; Jin Won Kim; Eu Suk Kim; Hong Bin Kim; Kyoung-Ho Song
Journal:  Medicine (Baltimore)       Date:  2016-09       Impact factor: 1.889

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  3 in total

Review 1.  Immune-checkpoint inhibitors: long-term implications of toxicity.

Authors:  Douglas B Johnson; Caroline A Nebhan; Javid J Moslehi; Justin M Balko
Journal:  Nat Rev Clin Oncol       Date:  2022-01-26       Impact factor: 65.011

Review 2.  The relationship between previous pulmonary tuberculosis and risk of lung cancer in the future.

Authors:  Yongwei Qin; Yujie Chen; Jinliang Chen; Kuang Xu; Feifan Xu; Jiahai Shi
Journal:  Infect Agent Cancer       Date:  2022-05-07       Impact factor: 3.698

Review 3.  Multidisciplinary approach to treatment with immune checkpoint inhibitors in patients with HIV, tuberculosis, or underlying autoimmune diseases.

Authors:  Juan Aguilar-Company; Maria A Lopez-Olivo; Isabel Ruiz-Camps
Journal:  Front Med (Lausanne)       Date:  2022-07-15
  3 in total

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