The Analysis of Relationship between Diabetes and Cancer from

2006-2013 Hospital Inpatients

Shumei Miao

, Xiaoping Zhou

, Xin Zhang

, Hongwei Shan

, Xinyi Huang

, Yixin Zhu

Kai Leng

, Zhongmin Wang

, Jianqiu Kou

and Yun Liu

Department of Information, the First Affiliated Hospital, Nanjing Medical University, Nanjing 210029, China

Department of Geratology, the First Affiliated Hospital, Nanjing Medical University, Nanjing 210029, China

Keywords: Diabetes, Cancer, Big-Data, Statistical Analysis.

Abstract: Diabetes and cancer have become two major chronic diseases concerning human health. More and more

studies indicate that diabetes can increase the risk of cancer and affect the prognosis of cancer patients. In

this paper, the information technology tools and statistical knowledge are used to analyse the clinical data of

hospital inpatients from year 2006 to year 2013, and explore the relationship between diabetes and cancer.

This paper analyses statistical characteristics and reasoning of suffering diabetes and cancer, makes

preliminary research on clinical big-data, and provides statistical basis for clinical researchers, thus helps to

enhance the level of diagnosis and treatment of disease and improve public health.

1 INTRODUCTION

As economic develops, lifestyles changes, and

environmental pollution aggravated, incidence of

diabetes have been increasing over the past decades.

Meanwhile, the incidence of neoplastic diseases is

rising year by year, which has become the leading

killer threatening public health. Both cancer and

diabetes have become two major chronic diseases

concerning human health (Y.Liu et al., 2013; G.

Yang et al., 2013). In early twenties, Maynard

(Maynard GD, 1910) proposed that the incidence of

diabetes and cancer was statistically positively

correlated. In recent years, more and more studies

indicate that diabetes can cause increased risk of

cancer and affect cancer prognosis. In 2010,

American Diabetes Association (ADA) and the

Cancer Society (ACS) issued a joint statement that

the risk of cancers increased on patients with

diabetes, and this demonstrates that the complex

relationship between diabetes and cancer

(Giovannuci E. et al., 2010). In addition, a large

number of domestic and international studies have

found that there is a certain etiology relationship

between diabetes and cancer, namely the incidence

of malignant tumors increased significantly among

diabetic population.

IDC (International Data Corporation) predicted

that China’s big data market will increase by five

times in 2012 to 2016. With the accelerating

development of health information, the type and size

of medical data is growing at an unprecedented rate,

the health sector has entered the "era of big data".

These valuable health information resources are vital

for disease management, control and medical

research. A better way to utilize this massive

information resources to serve the management,

treatment, research and teaching in healthcare has

been popular research focus (Gao Hansong et al.,

2013; CaiJiahui, 2013).

In this paper, the information technology and

related statistical knowledge are used to analyze

clinical data of hospitalized patients during January

2006 to December 2013. The analyses of statistical

characteristics were explored and the relationship

between diabetes and cancer was analyzed. This

paper makes preliminary attempts in the aspect of

big-data, and provides statistical evidence for

researchers of cancer and diabetes diseases, thus

helps to improve public health.

2 MATERIALS AND METHODS

2.1 Materials Resources

Our research objects are patients who have been

hospitalized from January 2006 to December 2013,

483

Miao S., Zhou X., Zhang X., Shan H., Huang X., Zhu Y., Leng K., Wang Z., Kou J. and Liu Y..

The Analysis of Relationship between Diabetes and Cancer from 2006-2013 Hospital Inpatients.

DOI: 10.5220/0005233104830488

In Proceedings of the International Conference on Health Informatics (HEALTHINF-2015), pages 483-488

ISBN: 978-989-758-068-0

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

and the data we used are from MRS (Medical

Records System) and HIS (Hospital Information

System) of the First Affiliated Hospital of Nanjing

Medical University (Jiangsu Province Hospital). The

paper focuses on diabetes and cancer patients.

2.2 Disease Classification

Discharge diagnosis is coded by professional

medical record coders according to ICD-10 (World

Health Organization, 2005). Based on primary

diagnosis and other diagnosis, we established a

clinical database to classify different types of

diseases and calculated the number of patients of

each disease. The paper focuses on diabetes and

cancer patients, the principal diagnosis and eight

other diagnosis of HIS should be analysed all

together.

2.3 Statistical Methods

Entry data with Excel and set up database with

ACCESS software, then valuable information is

chosen and analysed. SPSS software is also used for

statistical analysis. Chi-square calibration equation

is used to calculate P-value, P-value and OR value

are used to analyse the relationship between two

difference diseases.

Chi-square calibration equation is:

()









（）

(1)

Where, the actual observation number is fo, the

theoretical number is fe, we check χ2 table to get P-

values. When P is less than 0.005, the factor analysis

has a very significant difference. When P is less than

0.01, the comparison differences are statistically

significant, While P is larger than 0.05, the

comparison difference is not statistically significant.

OR value is calculated as:

OR= ad/ bc (2)

In statistics , OR refers to odds ratio, which means

the indicators of disease are associated with the risk

factors described in case control study. If OR is not

less than 3, the disease associated with the

correlation index greatly.

3 RESULTS

3.1 Overview of the Investigation

During the eight years from 2006 to 2013, there

were 531718 discharges in our hospital. The average

number is 66465 per year. Women account for

50.64%. The number of discharged patients

increased year by year from 37105 in 2006 to 93040

in 2013. Both cancer and type II diabetes are ranked

in the top ten diseases in our hospital in 2013. They

have common risk factors such as age, high body

weight index, central obesity, sedentary lifestyle,

excessive intake of carbohydrates, and lack of

physical activity, drinking and smoking (Haidong

Wang et al., 2012). In this paper, information of

eight years is used to do analyses, the common

features and relationship of cancer patients and

diabetes patients are proposed from statistical view.

3.2 Overview of Diabetes Disease

During the eight years from 2006 to 2013, the

number of diabetes patients increased year by year,

it increased from 2422 cases in 2006 to 9704 cases

in 2013. The data in Table 1 shows the patients in

year 2006 to 2011 with diabetes in elderly group was

significantly higher than non-elderly group, age

differences were highly significant (P <0.005, OR>

3), which proves diabetes and age have a significant

positive correlation. Age differences of patients in

year 2012 to 2013 were significant (P <0.005, OR>

2). The non-elderly group of diabetes has increased

annually, this conclusion is consistent with Yang

Wenying‘s (Yang W et al., 2010) paper in 2010.

Rapid urbanization and disordered unhealthy diet

style leads to diabetes threatening the younger’s

health more obvious (Bener A et al., 2014).

3.3 Overview of Cancer Disease

During the eight years from 2006 to 2013, the

number of cancer patients also increased year by

year, it increased from 9381 cases in 2006 to 30599

cases in 2013. The incidence of cancer is also

increasing every year. The data in Table 2 shows

that the patients in year 2006 to 2011 with cancer in

the elderly group were significantly higher than the

non-elderly group. Age differences were statistically

significant (P <0.005, OR> 1.4), which proves

diabetes and age have a significant positive

correlation. Cancer is also a disease of old age, but

in comparison with diabetes, the age of onset cancer

is more advanced. In recent years, OR value

becomes less, which indicates that the age of onset

of tumors growing in advance, the results remain

consistent with the phenomenon of early onset

diabetes, unhealthy living diet has a significant

impact on this phenomenon (F. Bray et al., 2012; J.

Traebert et al., 2013).

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3.4 General Situation of Patients with

Diabetes and Cancer

Figure 1: Trend of Diabetes, Cancer, and both in 2006-

2013. The horizontal axis represents year and the vertical

axis represents the ratio between number of different

disease cases and the total number of inpatients every

year.

Last two sections analyzed the diabetes and cancer

respectively, and the correlation of them is explored.

Both of them are closely related to age. The

occurrence of diabetes and cancer is related to age,

economic development, lifestyle, and environmental

etc (R. Prakash et al., 2013). We combined the

primary diagnosis and other diagnosis of

hospitalization data to analyze diabetes and cancer,

the number of patients with both diabetes and cancer

rose from 220 cases in 2006 to 1623 cases in 2013.

The proportion of cancer patients in diabetes patients

has also increased every year. Table 3 describes

annual cases of diabetes, cancer, and both from year

2006 to year 2013. The ratio between the cases and

the annual total number of hospitalizations is also

shown. Figure 1 describes the percentage change of

the three categories of patients in visually showed.

All of them are in an increasing trend, especially

since year 2010, the rate of increase is more evident.

The cancer incidence in diabetic patients is

calculated from data in Table 3. It rose from 9.08%

in 2006 to 16.72% in 2013. Compared to society

crowd cancer incidence 0.29% announced in 2013,

cancer incidence in diabetes patients was

significantly greater than in the general population,

and the relationship between cancer and diabetes

deserve further study.

3.4.1 Age Distribution of Patients with

Diabetes and Cancer

The age distribution of Cancer patients with diabetes

is shown in Figure 2. Age is divided into three

Categories: under 41 years-old, 41 to 60 years-old,

above 60 years-old. Cancer with diabetes is common

for the elders. In recent years, especially since 2010,

patients under age 41 years-old group and 41 to 60

years-old group are increasing year by year,

suggesting a trend of younger age with diabetes and

cancer disease (J.M. Lopez et al., 2014).

Figure 2: The Age Distribution of Diabetes with Cancer

Patients. The horizontal axis represents year and the

vertical axis represents the number of cases with both

diabetes and cancer diseases.

Figure 3 shows the incidence rate of cancer for

diabetes patients at different age group. Diabetic

patients over 60 years account for the largest

percentage of incidence of cancers, especially in

recent year, and the cancer incidence rate of the

older increased significantly. Diabetic patients

between 41 years and 60 years took the second

largest percentage of incidence of cancers, the

indicator also has slightly improvement. The cancer

incidence rate of diabetic patients under 41 years old

remained virtually unchanged in recent years. The

analysis result shows high risk of cancer in elderly

diabetes mellitus patients (Trosko J. E. et al., 1980;

Zoncu R. et al., 2011).

3.4.2 Gender Distribution of Patients with

Diabetes and Cancer

Figure 3: The Incidence of Cancer in Diabetes Patients.

The horizontal axis represents year and the vertical axis

present the ratio between the cases of cancer patients in

diabetes and the cases of diabetes every year.

TheAnalysisofRelationshipbetweenDiabetesandCancerfrom2006-2013HospitalInpatients

485

Table 1: The analysis of diabetes patients in year 2006-2013.

Year 2006 2007 2008 2009 2010 2011 2012 2013

Age

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

Total 18624 18481 25947 25323 26666 27233 28544 33661 31943 37358 34694 42927 38144 49128 39328 53683

Number

of Cases 411 2011 583 3028 705 3368 797 4203 930 4787 1210 5699 1931 6824 1993 7711

P <0.005 <0.005 <0.005 <0.005 <0.005 <0.005 <0.005 <0.005

OR 4.93 5.32 4.68 4.47 4.40 3.81 2.74 2.83

Table 2: The Analysis of Cancer Patients in Year 2006-2013.

Year 2006 2007 2008 2009 2010 2011 2012 2013

Age

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

1-49

≥

Total 18624 18481 25947 25323 26666 27233 28544 33661 31943 37358 34694 42927 38144 49128 39328 53683

Number

of Cases 3400 5981 4553 8099 5022 9173 6002 11438 6935 13001 8176 15177 9266 17678 10469 20130

P <0.005 <0.005 <0.005 <0.005 <0.005 <0.005 <0.005 <0.005

OR 1.77 1.82 1.79 1.62 1.60 1.50 1.48 1.41

Table 3: The Gender situation of Diabetes with Cancer Patients in Year 2006-2013.

Year 2006 2007 2008 2009 2010 2011 2012 2013

No. of

Cases

No. of

Cases

No. of

Cases

No. of

Cases

No. of

Cases

No. of

Cases

No. of

Cases

No. of

Cases

Total 37105 51270 53903 62205 69301 77621 87273 93040

Diabetes 2422 6.53 3611 7.04 4073 7.56 5000 8.04 5717 8.25 6909 8.90 8755 10.03 9704 10.43

Cancer 9381 25.28 12652 24.68 14195 26.33 17440 28.04 19936 28.77 23353 30.09 26944 30.87 30599 32.89

Diabetes

& Cancer

220 0.59 331 0.65 400 0.74 527 0.85 660 0.95 903 1.16 1337 1.53 1623 1.74

The gender composition of diabetes with cancers

patients is shown in Figure 4. The figure shows,

cancer patients suffering from diabetes mellitus

occurs more in male patients than female patients,

and in recent years the proportion is increasing more

evidently.

3.4.3 Gender Distribution of Patients with

Diabetes and Cancer

The gender composition of diabetes with cancers

patients is shown in Figure 4. The figure shows,

cancer patients suffering from diabetes mellitus

occurs more in male patients than female patients,

and in recent years the proportion is increasing more

evidently.

Figure 4: The Gender Distribution of diabetes with cancer

patients. The horizontal axis represents year and the

vertical axis represent the number of patients suffering

both diabetes and cancer.

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3.4.4 Cancer Types of Different Gender with

Diabetes

Patients suffering from both diabetes and cancers are

chosen to analyse cancer types of different gender.

Liver cancer is ranked at top for male diabetes

patients. For female diabetes patients, the incidence

of breast cancer and uterine cancer is the highest. To

briefly illustrate the situation, Table 4 only list top

five cancer disease for male and female in 2013.

Table 4: Top five cancer disease in 2013.

POS.

Male Female

Liver Cancer Colorectal cancer

Prostate Cancer Uterine fibroids

Esophageal Breast Cancer

Pancreatic Cancer Lung Cancer

Colorectal cancer Pancreatic Cancer

4 DISCUSSIONS

The incidence of diabetes and cancer is rising, both

of them have become the major diseases threatening

human health and a worldwide epidemic,

meanwhile, the prevalence of both diseases is rising.

Cancer is a kind of disease of high consumption. For

diabetes patients, due to a lack of insulin, sugar,

protein and imbalance of fat metabolism, many

complications are caused. When the two diseases

coexist, they interact with each other, affects

prognosis, and worsen patient’s wellbeing. (Wan

Guilin et al., 2005).

In this paper, clinical data of inpatients from year

2006 to year 2013 is used for analysis, which

includes 46191 cases of diabetes, and 6001 cases of

diabetes with cancer. The numbers of diabetes

disease and cancer disease grow rapidly in recent

year, so is the number of diabetes with cancer

patients. The number also increases with age growth.

Both of them are significantly correlated to age. The

number of diabetes and cancer cases over 40 years

increased obviously, as the aging population is one

factor. Meanwhile, statistical analysis showed that

the prevalence of non-elderly group also increased

year by year, this conclusion is consistent with Yang

Wenying’s (CaiJiahui et al., 2013) findings in an

article. Disorderly rapid urbanization life and

unhealthy diet leads to these two chronic diseases

appearing in younger population.

From the perspective of gender, there are more

male patients than female patients. In the analyses of

diabetes mellitus with cancers patients, the incidence

of liver cancer makes a comparatively large

proportion in male patients. Many men have

drinking, smoking and other bad habits, which lead a

direct impact on this. While uterine fibroids and

breast cancer make a large proportion in female

patients. The identity of gender is obvious, which

also explain impact of diabetes on sex hormones

from the statistical view. Meanwhile, epidemiology

confirmed obesity, insulin resistance state and

diabetes significantly increased the incidence of

cancer. Basic science presents reasonable

mechanism leading to cancer disease. Once the

diabetic disease is diagnosed, the inspection of liver

cancer, colorectal cancer, uterine cancer, breast

cancer and etc are recommended to add in their

regular medical examinations. Thus early cancer

detection and intervention is recommended. The

occurrence of cancer is a complex and slow process,

and is influenced by many factors. The follow-up

studies need to further consider the type of diabetes,

duration of treatment, the degree of control and etc.

The complex mechanism between diabetes and

cancer need more epidemiological studies to verify

the relationship.

As healthcare information technology develops, a

lot of data has been accumulated. The level of

medical information has great influence on medical,

teaching and research. To better support clinical

decisions and scientific researches, the construction

of data exchange platform and clinical data

repository become the emphasis in information

technology development. In this paper, the data

warehouse of diabetes and cancer is built to perform

data analysis. Then the clinical big-data is used in

clinical medical research. As medical information

systems develop, a lot of data has already been

accumulated. Healthcare workers can promote

health care reformation through information

technology, by fully exploiting big data for medical

to support clinical research paramedic, and

improving the quality of medical management.

ACKNOWLEDGEMENTS

This work was supported by grants from the

National Natural Science Foundation of China

(Grant no. 81270952), the Jiangsu Province’s Key

Provincial Talents Program (BE 2011802), the

Project funded by the Priority Academic Program

Development of Jiangsu Higher Education

Institutions, the Program for Development of

Innovative Research Team in the First Affiliated

Hospital of NJMU (no. 20113012), and Nanjing

TheAnalysisofRelationshipbetweenDiabetesandCancerfrom2006-2013HospitalInpatients

487

Medical University Science and Technology

Development Foundation (2012NJMU122). Yun Liu

is the guarantor of this paper.

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