Evidence map›Paper›PMID 29713185›Full record

ArticleOncoTargets and therapy2018

Preoperative apolipoprotein B/apolipoprotein A1 ratio: a novel prognostic factor for gastric cancer.

Ming-Zhe Ma, Shu-Qiang Yuan, Yong-Ming Chen, Zhi-Wei Zhou

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
2.3field-weighted citation impact, top 12% of its field
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

45 citing papers in PubMed, 2 syntheses or guidelines pooled it, 65 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Ming-Zhe Ma *State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, China.
Shu-Qiang Yuan *State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, China.
Yong-Ming ChenState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, China.
Zhi-Wei ZhouState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe correlations between lipid profile (lipid molecules and their derivative indexes) and clinical outcome have been widely testified in many carcinomas, but its prognostic value remains unknown in gastric cancer (GC). Our purpose in the study was to comprehensively evaluate the clinical significance of lipid profile in GC.

methodsWe retrospectively collected clinical information of 1,201 GC patients who received surgery at Sun Yat-sen University Cancer Center from 2005 to 2010. Kaplan-Meier analysis and Cox proportional hazards regression model were performed to determine its prognostic significance.

resultsLipid profile including cholesterol, triglyceride, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), LDL-C/HDL-C ratio, and ApoB/ApoA1 ratio were analyzed. For the first time, we found ApoB/ApoA1 ratio showed the biggest prognostic potency among all lipid-related variables and could act as an independent prognostic factor in GC. Patients with a high ApoB/ApoA1 ratio (≥1) had a shorter overall survival (hazard ratio: 1.373, 95% confidence interval: 1.123-1.68;

conclusionPreoperative serum ApoB/ApoA1 ratio might be used as a novel prognostic indicator of GC.

Indexed as

ApoB/ApoA1 ratiogastric cancermarkeroverall survivalprognosis

Identifiers

PMID29713185
PMCPMC5907890
OpenAlexW2796610307

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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.