Evidence map›Paper›PMID 38500655›Full record

ArticleFrontiers in oncology2024

Predictive value of serum albumin levels on cancer survival: a prospective cohort study.

Quan Tang, Xu Li, Chun-Rong Sun

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Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 2 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

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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

74 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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14 more citing papers are in PubMed but not listed here.

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

3 authors.

Quan Tang *Department of General Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.
Xu Li *Division of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Chun-Rong SunDepartment of General Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Serum albumin levels and cancer mortality are closely related, yet large-sample studies encompassing a broad spectrum of cancer types are lacking. Methods: This study encompassed patients diagnosed with cancer across the continuous 10 cycles of NHANES surveys from 1999 to 2018. The study population was stratified into two groups based on median albumin levels (≤ 4.2g/dL and > 4.2 g/dL) or cancer aggressiveness (well-survived cancers and poorly-survived cancers). Survival rates were estimated using the Kaplan-Meier method. The Cox proportional hazards model was employed to evaluate the association between serum albumin levels and cancer mortality. Restricted cubic spline (RCS) analysis was conducted to assess the nonlinear relationship between serum albumin levels and the risk of cancer mortality. Results: Kaplan-Meier curves demonstrated that patients with albumin levels ≤ 4.2 g/dL exhibited lower survival rates compared to those with levels > 4.2 g/dL, irrespective of cancer aggressiveness. Following adjustment for confounders, decreased albumin levels were associated with an elevated risk of cancer mortality across all groups [all cancers, HR (95%CI) = 2.03(1.73, 2.37); well survived cancers, HR (95%CI) = 1.78(1.38, 2.32); and poorly survived cancers, HR (95%CI) = 1.99(1.64, 2.42)]. RCS analyses revealed a stable nonlinear negative association between albumin levels and cancer mortality in all groups, regardless of confounder adjustment. Conclusion: Low serum albumin levels predict higher cancer mortality. Furthermore, a nonlinear negative association was observed between serum albumin levels and the risk of cancer mortality.

Indexed as

albumin levelscancer mortalitycardiovascular disease (CVD)National Health and Nutrition Examination Survey (NHANES)restricted cubic spline (RCS)

Identifiers

PMID38500655
PMCPMC10944876

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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.