ArticleTranslational cancer research2025
Association of the aggregate index of systemic inflammation in cancer survivors with all-cause, cardiovascular, and cancer-related mortality.
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Association between preoperative inflammatory biomarkers and postoperative pulmonary complications in stage I-II non-small cell lung cancer: a retrospective study.Frontiers in medicine · 2026Article
- Association and incremental predictive value of preoperative AISI and CALLY for postoperative pulmonary complications after McKeown esophagectomy following neoadjuvant chemoimmunotherapy.Frontiers in immunology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The relationship between the aggregate index of systemic inflammation (AISI) and the mortality risk of pan-cancer patients in the US population remains unclear. This study aimed to investigate the relationship between baseline AISI and all-cause mortality and specific types of mortality in adult cancer survivors in the United States. Methods: We used the data from the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2018. A multivariate Cox regression analysis model was constructed to determine the relationship between baseline AISI and outcomes. Outcome events include all-cause, cardiovascular disease (CVD), and cancer-related mortality. Nonlinear correlations were analyzed via restricted cubic spline (RCS) analysis. Subgroup analysis and interaction tests were also conducted. Results: A total of 3,773 adult cancer survivors were recruited in this study. Among them, 1,772 (42.99%) were male, with an average age of 62.83±14.32 years. The AISI was respectively divided into the quartiles (Q1-Q4) as follows: ≤179.23, 179.24-279.03, 279.04-442.59, and >442.59. During a median follow-up period of 87 months, 1,137 (30.14%) all-cause deaths occurred. Among these deaths, 314 were attributed to CVD and 343 to cancer. For every additional standard deviation increase in AISI, the risks of all-cause mortality, CVD mortality, and cancer-related mortality increased by 16% [hazard ratio (HR) =1.16, 95% confidence interval (CI): 1.12-1.21], 21% (HR =1.21, 95% CI: 1.14-1.29), and 9% (HR =1.09, 95% CI: 1.01-1.18), respectively. The RCS analysis results showed that the AISI index had a significant linear relationship with all-cause and CVD mortality. However, AISI showed a significant nonlinear relationship with cancer-related mortality (P for nonlinearity =0.01). Similar findings were also revealed in the subgroup analysis. Conclusions: Elevated AISI is positively correlated with all-cause mortality in cancer survivors, and the AISI may thus serve as a valuable indicator of poor prognosis among cancer survivors.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.