Correlation Analysis of Blood Lipid Metabolism Level and Liver

Malignant Tumor under Information System Medical Health Data

Juan Feng

and Yong Feng

Qingdao West Coast New District People's Hospital, Qingdao, Shandong, China

Keywords: Information System, Medical And Health Data Analysis, Liver Malignant Tumors, Blood Lipid Metabolism.

Abstract: Liver malignant tumor was the fifth most common malignant tumor in the world and the third leading cause

of cancer-related death. To explore the relationship between lipid metabolism level and liver malignant tumor,

in this paper, 142 patients with liver malignant tumors were selected as the experimental group by the method

of obtaining medical and health data through the hospital information system, and 803 health examiners were

selected as the control group with the the same period for visting the hosptical, it gave a correlation analysis

of the blood lipid detection data of the two groups. The performance of liver malignant tumor includes serum

total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, apolipoprotein AI and

apolipoprotein B, which were significantly lower than those of healthy people on physical examination. This

study verify that the blood lipid metabolism level of patients with liver malignant tumors were significantly

lower than that of the normal population with the help of information system medical health data, the blood

lipid metabolism level can be used as an important disease evaluation index for the development of liver

malignant tumors.

1 INTRODUCTION

Blood lipid was the general term for all lipid

components in human blood. Clinical medical tests

mainly detect serum total cholesterol (CHO),

triglycerides (TG), high-density lipoprotein (HDL-

C), low-density lipoprotein cholesterol (LDL),

apolipoprotein AI (ApoAI), Apolipoprotein B

(ApoB) and other indicators (Adegoke 2020,

Adeyanju 2020). The liver was the largest digestive

organ of the human body and was closely related to

the metabolism of blood lipids in the human body.

Studies have shown that human lipid metabolism

disorders were closely related to the occurrence (Sung

2021, NCD-RisC 2020, Yang 2013) and development

of cardiovascular diseases and tumors (Seko 2013,

Kitahara 2011). At present, the correlation analysis of

blood lipid metabolism level and malignant tumors in

international literature was based on the research and

analysis of small sample size, and there was no

literature to extract medical health data through

informatization to carry out large sample size analysis

(Rimessi 2016, Ahn 2009). In this study, with the help

https://orcid.org/0000-0002-7321-7732

https://orcid.org/0000-0002-4515-560X

of the hospital’s internal information system, after the

personal medical information was masked, the blood

lipid test data of 803 healthy medical examiners and

142 patients with clearly diagnosed liver malignant

tumors in the same period and the same age group

were collected. Then carry out two sets of correlation

analysis.

In this study, the information system was used to

retrieve the original medical and health data, and the

SPSS statistical software package was used to analyze

the research data. The measurement data was the

average value plus or minus the standard deviation to

indicate the index of abnormal blood lipid

metabolism. Parallel to the analysis of variance, the

abnormal blood lipid metabolism was compared

between the liver malignant tumor group and the

normal physical examination group. The use of

information systems to extract medical and health

data can effectively reduce statistical errors and

improve the accuracy of experimental results.

Through analysis, this study clarified that the

reduction of blood lipid metabolism can be used as an

important indicator of the deterioration of patients

Feng, J. and Feng, Y.

Correlation Analysis of Blood Lipid Metabolism Level and Liver Malignant Tumor under Information System Medical Health Data.

DOI: 10.5220/0011193400003444

In Proceedings of the 2nd Conference on Artiﬁcial Intelligence and Healthcare (CAIH 2021), pages 117-122

ISBN: 978-989-758-594-4

117

with liver malignant tumors, and provides a reference

for clinicians to observe the development of patients

with liver malignant tumors.

2 MATERIALS AND METHODS

2.1 Research Object

142 cases of liver malignant tumor patients treated in

tertiary hospitals from February 2020 to October

2021 were screened with the help of an information

system as the experimental group.

2.2 Standard Constrain

Standard constrain: (1) Diagnosed as liver malignant

tumor by pathological examination; (2) No history of

surgery, radiotherapy and chemotherapy; (3) The

patient had the result of fasting blood lipid level in the

early morning during hospitalization; (4) The clinical

data of the patient was completed.

Exclusion criteria: (1) Combined with abnormal

function of other important systems and organs; (2)

Combined with other types of malignant tumors; (3)

Patients had oral antihypertensive, lipid-lowering,

and hypoglycemic drugs; (4) Pregnant or lactating

women.

In the experimental group, there were 110 males

and 32 females with liver malignant tumors; they

were 43 to 90 years old, with an average age of

(62.04±8.87) years old.

The control group used the information system to

screen out 803 healthy people who came to the

hospital for physical examination during the same

period. Among them, there were 584 males and 219

females; they were 54 to 71 years old, with an average

age of (60.82±4.99) years old.

There was no statistically significant difference in

baseline information between the two groups (all

P>0.05), and they were comparable. All researches

were approved by the hospital ethics committee. The

blood test information of all subjects has been masked

before being extracted from the information system.

All data in this research does not involve personal

privacy.

2.3 Method

In the liver malignant tumor group, 3ml of fasting

peripheral venous blood was taken in the early

morning of hospitalization and delivered to the

laboratory Beckman AU5800 automatic biochemical

analyzer for unified testing. Reference standards for

each test item: total cholesterol: 0-5.17mmol/L,

triglycerides: 0-2.3mmol/L, high-density lipoprotein

cholesterol: 1.29-1.55mmol/L, low-density

lipoprotein cholesterol: 0-3.37 mmol/L,

Apolipoprotein AI: 1.0-1.6g/L, Apolipoprotein B:

0.6-1.1g/L.

2.4 Statistical Analysis

The SPSS statistical software package was used to

analyze the research data. The measurement data was

represented by ⎯x±s parallel analysis of variance or t

test, and the count data was represented by n (%)

parallel X

test. P<0.05 indicated that the difference

was statistically significant.

3 RESULT

3.1 Comparison of Baseline Data

Comparison of different genders between the

experimental group and the control group. There were

110 males and 32 females in the experimental group;

584 males and 219 females in the control group

during the same period. The gender difference

between the two groups was not statistically

significant (P>0.05). See Table 1 and Figure 1 for

details.

Table 1. Comparison of the two groups of different genders.

Group Male (%) Female (%)

Liver cancer 110 (77.46) 32 (22.54)

Control 584 (72.73) 219 (27.27)

Chi-square with Yates' correction 1.156

P-value 0.282

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Figure 1: Gender distribution of liver malignant tumor group and healthy population.

3.2 Comparison of Abnormal Blood

Lipid Metabolism of Different

Genders

Serum total cholesterol (CHO) ≥ 5.17mmol/L in the

experimental group was abnormal, with 18 males

(60%) and 12 females (40%); Triglyceride (TG) ≥

2.3mmol/L was abnormal, 5 males (62.5%), 3

females (37.5%); high-density lipoprotein (HDL-C) ≤

1.29mmol/L was abnormal, 81 males (82.65%), 17

cases (17.35%) were female; Low-density lipoprotein

(LDL) ≥ 3.37mmol/L is abnormal, 13 cases were

male (65%), 7 cases were female (35%);

Apolipoprotein AI (ApoAI) ≤ 1.0g/L was reduced, 56

cases were male ( 83.58%), 11 female cases

(16.42%); Apolipoprotein AI (ApoAI) ≥ 1.6g/L was

elevated, 0 males and 4 females (100%);

Apolipoprotein B (ApoB) ≤ 0.6g/L was reduced, 28

males (93.33%), 2 cases of female (6.67%)

apolipoprotein B (ApoB) ≥ 1.1g/L were elevated, 23

cases of male (69.70%), 10 cases of female (30%).

The difference between the two groups was

statistically significant (P<0.05). See Table 2.

Table 2: Comparison of abnormal blood lipid metabolism of different sexes in the experimental group.

-------

Male Female

Chi-squ

P-value

Abnormality

(n)

Proportion

(%)

Abnormality

(n)

Proportion

(%)

Cho

18 60% 12 40%

30.00 <0.0001

5 62.5% 3 37.5%

HDL-C

81 82.65% 17 17.35%

LDL

13 65% 7 35%

ApoAI

(

reduction

)

56 83.58% 11 16.42%

ApoAI

(

ascension

)

0 0 4 100%

ApoB

(

reduction

)

28 93.33% 2 6.67%

ApoB

(

ascension

)

23 69.70% 10 30%

3.3 Comparison of the Distribution of

Dyslipidemia between the Two

Groups

Serum total cholesterol (CHO) ≥ 5.17mmol/L was

abnormal, of which 30 cases in the experimental

group were abnormal, accounting for 21.13%; 500

cases in the control group were abnormal, accounting

for 62.27%. The difference between the two groups

was statistically significant (P<0.05).

Triglyceride (TG) ≥ 2.3mmol/L was abnormal, of

which 8 cases in the experimental group were

abnormal, accounting for 5.63%; 154 cases in the

control group were abnormal, accounting for 19.18%.

The difference between the two groups was

statistically significant (P<0.05).

High-density lipoprotein (HDL-C) ≤ 1.29mmol/L

was abnormal, of which 98 cases in the experimental

group were abnormal, accounting for 69.01%; 190

cases in the control group are abnormal, accounting

110

587

219

-200

200

400

600

800

1000

Male Female

Liver cancer

Control

Correlation Analysis of Blood Lipid Metabolism Level and Liver Malignant Tumor under Information System Medical Health Data

119

for 23.66%. The difference between the two groups

was statistically significant (P<0.05).

Low-density lipoprotein (LDL) ≥ 3.37mmol/L

was abnormal, of which 20 cases in the experimental

group were abnormal, accounting for 14.08%; 207

cases in the control group were abnormal, accounting

for 25.78%. The difference between the two groups

was statistically significant (P<0.05).

Apolipoprotein AI (ApoAI) ≤ 1.0g/L was a

decrease, and apolipoprotein AI (ApoAI) ≥ 1.6g/L

was an increase. The above two conditions were

abnormal. Among them, 67 cases were abnormally

decreased in the experimental group, accounting for

47.18%, 4 cases were abnormally increased,

accounting for 2.82%; 2 cases in the control group

were abnormally decreased, accounting for 0.25%,

and 246 cases were abnormally increased, accounting

for 30.64%. The difference between abnormal

increase and abnormal decrease between the two

groups was statistically significant (P<0.05).

Apolipoprotein B (ApoB) ≤ 0.6g/L means a

decrease, and apolipoprotein B (ApoB) ≥ 1.1 g/L

means an increase. Both conditions were abnormal.

Among them, 30 cases in the experimental group

were abnormally decreased, accounting for 21.13%,

33 cases were abnormally increased, accounting for

23.24%; 56 cases in the control group were

abnormally decreased, accounting for 6.97%, and 328

cases were abnormally increased, accounting for

40.85%. The difference between abnormal increase

and abnormal decrease between the two groups was

statistically significant (P<0.05). See Table 3.

Table 3: Comparison of the distribution of dyslipidemia between the two group.

-----

Liver cancer

Control

Chi-square with Yates’

correction

P value

Abnormality

(n)

Proportion

(%)

Abnormality

(n)

Proportion

(%)

Cho 30 21.13 500 62.27 81.25 <0.0001

TG 8 5.63 154 19.18 14.64 <0.0001

HDL-C 98 69.01 190 23.66 115.0 <0.0001

LDL 20 14.08 207 25.78 8.41 <0.005

ApoAI

(reduction)

67 47.18 2 0.25 385.8 <0.0001

oAI

(

ascension

)

4 2.82 246 30.64 46.57 <0.0001

ApoB(reduction) 30 21.13 56 6.97 27.53 <0.0001

(

ascension

)

33 23.24 328 40.85 15.11 <0.0001

3.4 Comparison of Blood Lipid

Determination Results between the

Two Groups

Experimental group CHO (4.64±2.52) mmol/L, TG

(1.33±0.64) mmol/L, HDL-C (1.14±0.39) mmol/L,

LDL (2.58±1.64) mmol/L, ApoAI (1.04±0.32) ) g/L,

ApoB (0.92±0.36) g/L metabolic level was lower than

the control group CHO (5.57±1.17) mmol/L, TG

(1.78±1.35) mmol/L, HDL-C (1.53±0.34) mmol /L,

LDL (2.91±0.82) mmol/L, ApoAI (1.48±0.20) g/L,

ApoB (1.02±0.26) g/L, the differences were

statistically significant (all P<0.05).See Table 4,

Figure 2.

Table 4: Comparison of the results of blood lipid determination between the two groups.

Group n Cho TG HDL-C LDL ApoAI ApoB

Liver cancer 142

4.64±2.52 1.33±0.64 1.14±0.39 2.58±1.64 1.04±0.32 0.92±0.36

Control 803

5.57±1.17 1.78±1.35 1.53±0.34 2.91±0.82 1.48±0.20 1.02±0.26

t, value 4.335 6.169 11.18 2.315 15.64 3.044

P value <0.0001 <0.0001 <0.0001 <0.05 <0.0001 <0.0001

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Figure 2: Comparison of blood lipid results between the two groups.

4 DISCUSSION

Serum total cholesterol, triglycerides, high-density

lipoprotein, low-density lipoprotein, apolipoprotein

AI, and apolipoprotein B were the main components

of human blood lipids, and they were also key test

indicators in clinical laboratories. The relevant test

data was easy to obtain and easy Perform dynamic

assessments. These indicators participate in signal

transduction, inflammation, vascular factor

regulation and other activities in the human body, and

participate in the formation of cell membranes.

Abnormal blood lipid metabolism was not only

related to human cardiovascular and cerebrovascular

diseases, but also closely related to the occurrence

and development of tumors.

In the experimental group, 60% of men in the

experimental group had abnormal serum cholesterol

metabolism, 62.5% of triglyceride metabolism,

82.65% of high-density lipoprotein metabolism, and

65% of low-density lipoprotein metabolism, the

abnormal decrease in apolipoprotein AI accounted for

83.58%, and the abnormal decrease in apolipoprotein

B accounted for 93.33%. The abnormal metabolism

of the above indicators accounted for higher

proportions than women. The reason may be that the

severity of liver damage in male patients with liver

malignant tumors is generally higher than that in

female patients, and the proportion of liver damage

and alcohol consumption in male patients was higher

than that in female patients. The specific reasons still

need to be confirmed by further experiments, and

there was no relevant literature report at home and

abroad.

The metabolic level of the experimental group

(CHO (4.64±2.52) mmol/L, TG (1.33±0.64) mmol/L,

HDL-C (1.14±0.39) mmol/L, LDL (2.58±1.64)

mmol/L, ApoAI (1.04±0.32) g/ L, ApoB (0.92±0.36)

g/L) was lower than that of the control group. Lipids

were an important part of the cell membrane. When

cells become cancerous, the lipids on the cell

membrane will be destroyed. Abnormalities will

occur during the normal absorption, synthesis, and

metabolism of lipids, resulting in a decrease in blood

lipid metabolism. The reduction of blood lipid

metabolism will further induce the normal

construction of the body's cell membrane, leading to

the continuous development of the body's tumor cells.

r c

rou

Cho(mmoL/L)

=4.335

P<0.0001

iver

cancer gr

oup

ontro

l gr

TG(mmoL/L

）

=2.345

P<0.05

ive

can

ntr

grou

HDL-C(mmoL/L)

=11.18

P<0.0001

ver

can

cer

oup

ontro

l g

rou

LDL-C(mmoL/L)

=11.18

P<0.0001

iver c

r g

oup

ontrol

grou

ApoA1(g/L)

=15.64

P<0.0001

ver

r g

ontrol g

ApoB(g/L)

=3.044

P<0.005

Correlation Analysis of Blood Lipid Metabolism Level and Liver Malignant Tumor under Information System Medical Health Data

121

On the other hand, the liver parenchyma of patients

with liver malignant tumors has been severely

damaged. With liver damage, the liver will have more

and more serious effects on the metabolism of blood

lipids, and its ability to convert into lipids will

gradually weaken. Serum total cholesterol,

triglycerides, high-density lipoproteins, low-density

lipoproteins, apolipoproteins AI, apolipoprotein B

and other indicators will gradually decrease

compared with the normal physical examination

population.

Compared with the traditional small number of

medical samples, the data comparison results were

more accurate in the liver malignant tumor patient

population and the same period. In this study, with the

support of informatized medical health data, the

correlation analysis between blood lipid metabolism

and liver malignancies was carried out to provide a

more accurate reference for the treatment and

prognosis of liver cancer patients.

5 CONCLUSIONS

It was an important method to analyze the correlation

between blood lipid and tumor by using health data

measurement. In this paper, a large number of

measurement data were collected through

information system, and the correlation analysis

between abnormal lipid metabolism and liver

malignant tumor was carried out by chi-square test. It

selected the performance index as an evaluation

criterion including the metabolism of serum total

cholesterol, triglycerides, high-density lipoprotein,

low-density lipoprotein, apolipoprotein AI, and

apolipoprotein B in patients with liver malignant

tumors. Studies have found that the performance

index was much lower than that of the normal

population. Studies have shown that there were

statistically significant differences in the distribution

of abnormal blood lipid metabolism in patients with

liver malignant tumors in different genders and

different age groups. This study can assist clinicians

to more quickly and accurately assess the

development of liver malignant tumors, and provide

a reference for the treatment of liver malignant

tumors in the future.

With the rapid development of artificial

intelligence and medical health data analysis

technology, the application of information systems in

the medical field has become more and more in-

depth. In the next step, we will further use the

information system to extract a large number of

experimental data to carry out clinical research and

analysis, and promote the deep integration of

"medical and industrial" fields.

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