Evidence map›Paper›PMID 38609918›Full record

ArticleBMC pulmonary medicine2024

Impact of immune checkpoint inhibitors (ICIs) therapy on interferon-γ release assay (IGRA) and diagnostic value in non-small cell lung cancer (NSCLC) patients.

Yijiao Xu, Qingwei Zhang, Zhisheng Chen, Shuwen Yang, Haiyan Chen, Xiong Xiao, Hongni Jiang

Open access · goldAbstract read
In one paragraph

Article in BMC pulmonary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Yijiao Xu *Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.ORCID http://orcid.org/0000-0002-4685-2378
Qingwei Zhang *Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Zhisheng Chen *Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Shuwen YangZhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Haiyan ChenZhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Xiong XiaoZhongshan Hospital (Xiamen), Fudan University, Xiamen, China. xiao.xiong@zsxmhospital.com.
Hongni JiangZhongshan Hospital (Xiamen), Fudan University, Xiamen, China. jiang.hongni@zs-hospital.sh.cn.
Fudan University · CNXiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis (TB), a highly contagious respiratory disease, presents a significant global health threat, with a notable increase in incidence reported by the WHO in 2022. Particularly, the interplay between TB and non-small cell lung cancer (NSCLC) gains attention, especially considering the rising use of immune checkpoint inhibitors (ICIs) in cancer treatment. This interplay may influence TB diagnostics and reactivation, warranting a closer examination.

methodsA retrospective analysis was conducted on clinical data of NSCLC patients with positive T-SPOT results before undergoing anti-tumor treatment at Zhongshan Hospital (Xiamen), Fudan University, from January 1, 2021 to December 31, 2022. We assessed the incidence of tuberculosis reactivation and treatment outcomes among these patients. Moreover, we compared the differences in tuberculosis activity between the ICIs and non-ICIs treatment groups. Additionally, we observed the changes in T-SPOT spot count before and after immunotherapy, analyzing their association with tuberculosis activity and prognosis.

resultsA total of 40 NSCLC patients with positive T-SPOT results before treatment were included in the study, with 26 patients in the ICIs treatment group and 14 patients in the non-ICIs treatment group. The study found no significant differences between the two groups in terms of gender, age, stage, histological type, performance status, driver gene expression, and distant metastasis. With a median follow-up time of 10.0 (6.0-14.5) months, three cases (11.5%) in the ICIs treatment group developed tuberculosis activity, diagnosed at 2, 3, and 12 months after ICIs treatment initiation. Conversely, no tuberculosis activity was observed in the non-ICIs treatment group, and the difference between the two groups was not significant (P = 0.186). Among the 32 patients who received ICIs treatment, spot count dynamics were diverse: four cases (12.5%) showed an increase, 12 cases (37.5%) had no change, and 16 cases (50.0%) had a decrease. During the follow-up, the progression rate (PD) was 50.0%, 75.0%, and 62.5% in the three groups, respectively (P = 0.527). Similarly, the mortality rate was 0%, 25.0%, and 25.0%, respectively (P = 0.106). Interestingly, among the patients with decreased spot counts, three cases (18.75%) were diagnosed with active pulmonary tuberculosis.

conclusionsFor NSCLC patients with a positive T-SPOT response undergoing ICIs treatment, our study observed indications of active tuberculosis. The varied T-SPOT spot count changes post-ICIs treatment suggest a complex interaction, potentially linking T-SPOT spot count reduction to tuberculosis reactivation risk. These preliminary findings underscore the importance of further research to more accurately assess T-SPOT's diagnostic utility in this context.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsTuberculosis, PulmonaryHumansImmune Checkpoint InhibitorsInterferon-gamma Release TestsRetrospective StudiesImmune Checkpoint InhibitorsImmune checkpoint inhibitors (ICIs)Non-small cell lung cancer (NSCLC)ReactivationTreatment outcomesT-SPOTTuberculosis

Identifiers

PMID38609918
PMCPMC11010406
OpenAlexW4394753979

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.