Evidence map›Paper›PMID 38664760›Full record

SynthesisBMC cancer2024

Prognosis stratification of cancer patients treated with immune checkpoint inhibitors through lung immune prognostic index: a meta-analysis and systematic review.

Yusheng Guo, Yao Pan, Jiayu Wan, Bingxin Gong, Yi Li, Xuefeng Kan, Chuansheng Zheng

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
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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

7 authors.

Yusheng Guo *Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430022, Wuhan, China.
Yao Pan *Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Fujian Medical University, 362000, Quanzhou, China.
Jiayu Wan *Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430022, Wuhan, China.
Bingxin GongDepartment of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430022, Wuhan, China.
Yi LiDepartment of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430022, Wuhan, China.
Xuefeng KanDepartment of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430022, Wuhan, China. xkliulang1314@163.com.
Chuansheng ZhengDepartment of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430022, Wuhan, China. hqzcsxh@sina.com.

Funding

National Natural Science Foundation of China Nos. 82372069 and 82072041Outstanding Youth Science Foundation of Hubei Province, China 2023AFA107
6 · The paper itself

Abstract

backgroundAlthough numerous studies have reported the prognostic value of the lung immune prognostic index (LIPI) in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), the prognostic value of the LIPI in a pancancer setting remains unclear.

methodsA comprehensive search was conducted until July 2023 across the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant studies evaluating the prognostic value of the LIPI in cancer patients treated with ICIs. The outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). We described and compared the pooled outcomes by stratifying the patients based on different groupings of LIPI (good vs. intermediate [0 vs. 1], good vs. poor [0 vs. 2], and good vs. intermediate / poor [0 vs. 1 + 2]).

resultsA total of 9959 patients in 35 studies were included. A higher score of LIPI was associated with impaired OS. The pooled HRs were 1.69 (95% CI: 1.55-1.85, p < 0.001; 0 vs. 1), 3.03 (95% CI: 2.53-3.63, p < 0.001; 0 vs. 2), and 2.38 (95% CI: 1.97-2.88, p < 0.001; 0 vs. 1 + 2). A higher LIPI score was associated with shorter PFS. The pooled HRs were 1.41 (95% CI: 1.31-1.52, p < 0.001; 0 vs. 1), 2.23 (95% CI: 1.87-2.66, p < 0.001; 0 vs. 2), and 1.65 (95% CI: 1.46-1.86, p < 0.001; 0 vs. 1 + 2). Similarly, a higher LIPI score was associated with a lower ORR. The pooled ORs were 0.63 (95% CI: 0.54-0.75, p < 0.001; 0 vs. 1) and 0.38 (95% CI: 0.29-0.50, p < 0.001; 0 vs. 2). A higher LIPI score was associated with a lower DCR. The pooled ORs were 0.47 (95% CI: 0.35-0.61, p < 0.001; 0 vs. 1) and 0.19 (95% CI: 0.12-0.30, p < 0.001; 0 vs. 2).

conclusionIn patients with NSCLC or other solid tumours, the lung immune prognostic index could robustly stratify the clinical outcomes into three groups among the patients who receive ICIs. LIPI is a low-cost, simple, accessible, and accurate prognostic tool in a pancancer setting and it may contribute to the evaluation of risk stratification in patients treated with ICIs.

Indexed as

Immune Checkpoint InhibitorsLung NeoplasmsCarcinoma, Non-Small-Cell LungHumansPrognosisProgression-Free SurvivalImmune Checkpoint InhibitorsImmune checkpoint inhibitorsLung immune prognostic indexPrognosis stratification

Identifiers

PMID38664760
PMCPMC11047037

What OpenQuestion holds

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Registered trials

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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.