Evidence map›Paper›PMID 35902848›Full record

ArticleBMC medicine2022

Increased blood-based intratumor heterogeneity (bITH) is associated with unfavorable outcomes of immune checkpoint inhibitors plus chemotherapy in non-small cell lung cancer.

Juan Zhou, Minwei Bao, Guanghui Gao, Yiran Cai, Lihong Wu, Lei Lei, Jing Zhao, Xianxiu Ji, Ying Huang, Chunxia Su

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
2.9field-weighted citation impact, top 8% 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.

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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

10 authors at 3 institutions in 1 country.

Juan Zhou *Department of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200043, China.
Minwei Bao *Department of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200043, China.
Guanghui Gao *Department of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200043, China.
Yiran CaiBurning Rock Biotech, Guangzhou, China.
Lihong WuBurning Rock Biotech, Guangzhou, China.
Lei LeiBurning Rock Biotech, Guangzhou, China.
Jing ZhaoDepartment of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200043, China.
Xianxiu JiDepartment of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200043, China.
Ying HuangDepartment of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200043, China.
Chunxia SuDepartment of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200043, China. susu_mail@126.com.
Tongji University · CNBurning Rock Biotech (China) · CNShanghai Pulmonary Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe combination of immune checkpoint inhibitors (ICIs) and chemotherapy has been the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) patients with driver-gene negative. However, efficacy biomarkers for ICIs-based combination therapy are lacking. We aimed to identify potential factors associated with outcomes of ICIs plus chemotherapy at baseline and dynamic changes in peripheral blood.

methodsWe collected plasma samples of 51 advanced NSCLC patients without EGFR/ALK/ROS1 alteration at baseline and/or after two treatment cycles of ICIs plus chemotherapy. A blood-based intratumor heterogeneity (bITH) score was calculated based on the allele frequencies of somatic mutations using a 520-gene panel. bITH-up was defined as a ≥ 10% increase in bITH score from baseline, with a second confirmatory measurement after treatment.

resultsAt baseline, the number of metastatic organs and lung immune prognostic index (LIPI) were significantly associated with shorter progression-free survival (PFS) of ICIs plus chemotherapy, while bITH and other common molecular biomarkers, including ctDNA level, blood-based tumor mutational burden (bTMB), and PD-L1 expression, had no effect on PFS. LRP1B mutation at baseline was significantly associated with favorable outcomes to ICIs plus chemotherapy. There were 37 patients who had paired samples at baseline and after two cycles of treatment, with the median interval of 53 days. Intriguingly, patients with bITH-up had significant shorter PFS (HR, 4.92; 95% CI, 1.72-14.07; P = 0.001) and a lower durable clinical benefit rate (0 vs 41.38%, P = 0.036) than those with bITH-stable or down. Case studies indicated that bITH was promising to predict disease progression.

conclusionsThe present study is the first to report that increased bITH is associated with unfavorable outcomes of ICIs plus chemotherapy in advanced NSCLC patients.

Indexed as

Antineoplastic Agents, ImmunologicalCarcinoma, Non-Small-Cell LungLung NeoplasmsHumansImmune Checkpoint InhibitorsProtein-Tyrosine KinasesProto-Oncogene ProteinsAntineoplastic Agents, ImmunologicalImmune Checkpoint InhibitorsProtein-Tyrosine KinasesProto-Oncogene ProteinsBlood-based intratumor heterogeneity (bITH)Blood biopsyImmune checkpoint inhibitors (ICIs) plus chemotherapyLRP1B mutationNon-small cell lung cancer (NSCLC)

Identifiers

PMID35902848
PMCPMC9335993
OpenAlexW4288423296

What OpenQuestion holds

Textmetadata
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.