Evidence map›Paper›PMID 40636135›Full record

ReviewiLIVER2022

Application of immune checkpoint inhibitors in hepatobiliary cancers.

Jiajia Yuan, Lingxiao Xu, Jun Zhou, Lin Shen

Abstract readReview
In one paragraph

Review in iLIVER, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

4 authors.

Jiajia YuanDepartment of Gastrointestinal Oncology, Peking University Cancer Hospital, 52 Fucheng Road, Haidian District, Beijing, 100142, China.
Lingxiao XuDepartment of Gastrointestinal Oncology, Peking University Cancer Hospital, 52 Fucheng Road, Haidian District, Beijing, 100142, China.
Jun ZhouDepartment of Gastrointestinal Oncology, Peking University Cancer Hospital, 52 Fucheng Road, Haidian District, Beijing, 100142, China.
Lin ShenDepartment of Gastrointestinal Oncology, Peking University Cancer Hospital, 52 Fucheng Road, Haidian District, Beijing, 100142, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatobiliary cancers are primarily categorized into hepatocellular carcinoma (HCC) and biliary tract cancers (BTC). HCC is one of the most common malignant cancers, with increasing global incidence. Immune checkpoint inhibitors (ICIs) have changed the approach of HCC management in recent years. The combination of atezolizumab and bevacizumab has surpassed sorafenib as the standard regimen for first-line treatment of advanced unresectable HCC. However, the optimal choice for second-line treatment after initial treatment with ICIs lacks clinical trial confirmation. In addition, limited clinical trial data on ICIs combined with locoregional and perioperative therapies have been reported. Unlike HCC, clinical studies have found that immunotherapy is effective only for BTC with specific molecular markers. Moreover, the molecular characteristics governing immune responses and evasion remain unclear. This review provides information on the application of immunotherapy for HCC and prospects over the next few years. In addition, current evidence from clinical trials of BTC has made BTC immunotherapy a research hotspot again. Based on the findings in the literature, future clinical trials are being planned. Furthermore, biomarkers used in immunotherapies for hepatobiliary cancers that may shed light on the management of these diseases in the future were discussed.

Indexed as

BiomarkersClinical trialsHepatobiliary cancersImmunotherapy

Identifiers

PMID40636135
PMCPMC12212596

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.