Evidence map›Paper›PMID 39104905›Full record

ArticleJournal of inflammation research2024

Predictive Efficacy of the Advanced Lung Cancer Inflammation Index in Hepatocellular Carcinoma After Hepatectomy.

Xin Qiu, Shuang Shen, Donghong Lu, Nizhen Jiang, Yifei Feng, Jindu Li, Chenglei Yang, Bangde Xiang

Abstract read
In one paragraph

Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. The association of the advanced lung cancer inflammation index with the risk ofFrontiers in cellular and infection microbiology · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

8 authors.

Xin Qiu *Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Shuang Shen *Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.ORCID 0000-0002-0845-2533
Donghong LuDepartment of Gastroenterology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People's Republic of China.
Nizhen JiangGuangxi Medical University Cancer Hospital, Nanning, People's Republic of China.ORCID 0009-0006-1752-0397
Yifei FengGuangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Jindu LiDepartment of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Chenglei YangDepartment of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Bangde XiangDepartment of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) presents a significant global health challenge due to its poor prognosis and high recurrence rates post-surgery. This study examines the predictive efficacy of the Advanced Lung Cancer Inflammation Index (ALI) in assessing the post-hepatectomy prognosis of patients with HCC. Methods: A cohort comprising 1654 HCC patients who underwent hepatectomy at Guangxi Medical University Cancer Hospital from 2013 to 2019 was enrolled. Patients were stratified into two groups according to the median ALI level, and then subjected to propensity score matching (PSM) in a 1:1 ratio. Kaplan-Meier survival curves, the traditional Cox proportional hazards (CPH) model, and machine learning (ML) models were employed to analyze and evaluate ALI's prognostic significance. Furthermore, ALI's prognostic value in digestive system tumors was validated via analysis of the National Health and Nutrition Examination Survey (NHANES) database. Results: After applying PSM, a final cohort of 1284 patients, categorized into high and low ALI groups, revealed a significantly reduced survival time in the low ALI cohort. Univariate and multivariate Cox analyses identified ALI, BCLC stage, CK19, Hepatitis B virus (HBV) DNA, lymph node metastasis, and microvascular invasion (MVI) as independent predictors of prognosis. Both traditional CPH and ML models incorporating ALI demonstrated excellent predictive accuracy, validated through calibration curves, time-dependent ROC curves, and decision curve analysis. Furthermore, the prognostic value of ALI in digestive tumors was confirmed in the NHANES database. Conclusion: The ALI exhibits potential as a prognostic predictor in patients with HCC following hepatectomy, providing valuable insights into postoperative survival.

Indexed as

advanced lung cancer inflammatory indexALICox regressionHCChepatocellular carcinomamachine learningMLprognosis

Identifiers

PMID39104905
PMCPMC11299648

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.