1
RISK FACTORS OF LYMPHOMA AT DR. SOEBANDI HOSPITAL
IN JEMBER DISTRICT – EAST JAVA
Annisa Reykaningrum1
1Department of Epidemiology, Biostatistics and Population, Public Health Faculty, Jember University,
Jember
Correspondence: Jl. Kalimantan I/93 Jember. Telp (0331-337878). Fax (0331-322995). Mobile phone
085730607719. email : [email protected]
ABSTRACT
Background: In the world, the incidence of malignant lymphoma was rising but the
exact cause of this disease is unknown. Indonesia had not accurate data about malignant
lymphoma, but its predicted ranked 6th highest cancer incidence.
Objective: This research aims to analyze the risks factors of malignant lymphoma in
Jember District Hospital.
Methods: This research is an analytical study with cross sectional approach. The study
population was 97 patients in General Surgery Clinic in dr. Soebandi Jember District
Hospital. This research was analyzed using Chi-square test and multivariable analysis
using logistic regression technique.
Results: The relationship between age and race with lymphoma were not significant.
Risks Factors for lymphoma that significant were gender (male) (p-value=0,019;
OR=5,7; 95% CI=1,16-27,8), familial predisposition (p-value=0,012; OR=5,4; 95%
CI=1,44-20,34), history of illness (p-value=0,001, OR=10,8; 95% CI=2,59-45,19), and
exposure to pesticides (p-value=0,021, OR=9,1; 95% CI=1,12-74,31).
Conclusion: The factors that have the stronger relationship with lymphoma are familial
predisposition, history of illness and exposure to chemicals (pesticides). Base on this
research, developing multi sector approach between hospital, official health, department
of agriculture and Organization of Cancer in Indonesia must be built, to prevent and
decrease the incidence of lymphoma’.
Keywords: Pesticides, Familial Predisposition, History of Illness, Lymphoma
Introduction
Lymphoma is a malignancy that occurs due to activation of the abnormal gene
(mutated lymph cells or lymphocytes) specific to the lymphatic system (lymph nodes,
spleen, spinal marrow, and the thymus gland in the neck) which leads to the
uncontrolled growth of lymph node cells (1)
. Lymphoma is one rapidly increased cancer
incidence over the last 30 years, which increased 80% from 1973 to 1999. World Health
Organization (WHO) estimates that approximately 1.5 million people worldwide
currently live with lymphoma and 300 thousand people die from this disease each year
(2).
2
In 2007, the incidence of lymphoma in the United States was as many as 71,380
people and it was included five major cancers in men and women. In 2010, there were
65,540 people (35,380 men and 30,160 women) to be diagnosed with lymphoma. Of the
overall population suffering from lymphoma, 20,210 people died from this cancer
(10,710 men and 9,500 women) (2)
. Data on lymphoma incidence in Indonesia is still not
accurate. It is estimated that this cancer is ranked the sixth highest cancer incidence (3)
.
The results of preliminary study on the medical record at Poly Chemotherapy of dr.
Soebandi Hospital, Jember, stated that lymphoma was included in one of 2 major
cancers in the poly. Each year the number of lymph nodes of cancer patients has
increased. In the year 2008 it was recorded 124 patient visits to the hospital and in 2009
it reached 151 visits.
The exact cause of this disease remains unknown. Several previous
epidemiological studies stated that age, gender, exposure to chemicals, and a history of
infectious disease or other types of cancer may increase the risk of lymphoma (2)
.
Increased incidence of lymphoma was associated with age, especially in the age group >
55 years. As for gender, lymphoma was more in men than women, which was equal to
2:1. Race also may increase the risk of this cancer. The results of research in the United
States stated that lymphoma was found in 40-70% whites compared to blacks. As for
the continent of Asia, the race that had a high risk of this cancer was Chinese (4)
. History
of non-communicable diseases such as Diabetes Mellitus proved to have a significant
relationship to the incidence of lymphoma (5)
.
History of infections and diseases associated with immune system, such as
congenital immunodeficiency, AIDS, use of immunosuppressive drugs after organ
transplants, Sicca syndrome, Rheumatoid arthritis, Celiac disease, EBV, HTLV-1,
Helicobacter pylori and Campylobacter, hepatitis C virus, Chlamydia psittaci and
exposure to chemicals such as pesticides, especially those containing 2,4-
dichlorophenoxyacetic acid, hexachlorocyclo hexane and benzene could also increase
the risk of developing lymphoma (4)
. The results of a study in California stated that
smoking had an influence on some incidence of lymphoma. Genetic factors or family
history of lymphoma or other types of cancer might also increase the risk of developing
lymphoma, but the increased risk was also influenced by exposure to carcinogenic
chemicals or ingredients (6-7)
.
3
Based on the high number of patients with lymphoma in dr. Soebandi Hospital,
Jember, which was included in the 2nd
highest cancer incidence after breast cancer at
chemotherapy Poly, it was necessary to do research to find out more about the factors
associated with the incidence of lymphoma in Jember District, especially at Dr.
Soebandi Hospital of Jember. This was needed so that preventive action could be done
in the community to expect to reduce the prevalence and risk factors in susceptible
people suffering from lymphoma.
Method
This study was an observational and analytical study with a cross-sectional
approach. The research was conducted at the General Surgery Outpatient Poly of dr.
Soebandi Hospital, Jember, because the poly is referral poly to identify the type of
lymphadenopathy. As for the research time, it was conducted during the months of
March to June 2011.
The population in this study was all patients who performed examinations or
outpatients at General Surgery Outpatient Poly of Dr. Soebandi diagnosed with
lymphoma or other types of disease, in order to obtain a sample size of 97 patients.
Patients diagnosed with other types of cancer were excluded. Sampling in this study
used systematic random sampling technique.
The dependent variable in this study was the status of lymphoma and the
independent variables were the age at diagnosis, gender, race, family history of the
respondents that had cancer, history of illnesses suffered by respondents (diabetes
mellitus, HIV / AIDS, Hepatitis C, Rheumatoid arthritis, another type of cancer) prior to
suffering lymphoma as well as other diseases, and exposure to chemicals (pesticides).
The needed data in this study were collected with a structured interview method
directly to the respondent with the help of a questionnaire to investigate the
characteristics of respondents consisting of age, gender, race, family history of cancer,
history of other diseases (diabetes mellitus, HIV / AIDS, Hepatitis C, Rheumatoid
arthritis, other types of cancer), and exposure to chemicals (pesticides). In addition, the
method of review of documents in this case medical records was also conducted to
obtain data on the results of laboratory examinations that included the staging of
4
respondents’ lymphoma and respondents’ age when diagnosed with lymphoma, and the
status of HIV / AIDS.
The collected data were analyzed with univariable, bivariable and multivariable
analysis with the help of SPSS data processing program and then presented in the form
of frequency distribution tables and contingency tables with narrative interpretation.
The univariable analysis was performed to describe the frequency distribution and the
proportion of each variable studied, both independent variables and the dependent
variable. The bivariable analysis was conducted to determine the relationship between
each independent variable with the dependent variable by using the Chi square test at
95% confidence interval (α = 0.05). The multivariable analysis was performed to
determine the variables most closely associated with the incidence of lymphoma by
using Logistic Regression test 95% confidence interval (α = 0.05).
Results and Discussion
Univariable Analysis
Table 1 explains that the majority of respondents did not suffer from lymphoma.
The majority of respondents who had cancer (81.8%) were diagnosed at stage III or IV
(advanced stage) and 18.2% were diagnosed at stage I or II (early stage). In the
respondents who suffered from cancer and non cancer, most chose to do self-medication
with drugs bought at pharmacies and traditional medicine, as well as alternative
treatments. Most respondents were aged ≤ 55 years (52.6%) and female (51.5%). In this
study, racial/ethnic categorization was also examined by Chinese and non-Chinese (Java
or Madura). The majority of respondents (94.8%) were classified as non-Chinese Race
(Java or Madura), while the Chinese respondents were only 5.1%. In the group of non-
Chinese race there were 39 Javanese and 53 Maduranese.
Table 1. Description of research variables
Respondent’s characteristics N Percentage (%)
Status
Cancer 11 11. 3
non Cancer 86 88. 7
Age
>55 years 46 47. 4
≤55 years 51 52. 6
Gender
Male 47 48. 5
Female 50 51. 5
Race
5
Chinese 5 5. 2
Non Chinese 92 94. 8
Family history of cancer
Yes 28 28. 9
No 69 71. 1
History of illness
Yes 25 25. 8
No 72 74. 2
Exposure to pesticides
Yes 55 56. 7
No 42 43. 3
Source: Processed Primary Data (2011)
Family cancer history was derived from the father’s parents, mother’s parents,
both father and mother. Only 28.9% of respondents had a family history of cancer. The
disease of cancer included breast cancer, uterine cancer, colon cancer and liver cancer.
History of illnesses associated with a decrease in the immune system affected only a
minority of respondents (25.8%). The illnesses were Rheumatoid arthritis (60%),
Diabetes Mellitus (40%), Hepatitis C (8%), and breast cancer and colon cancer (8%). In
this study the status of the respondents on pesticide exposure was viewed through
participation in agricultural or plantation activities; the level of exposure risk to
pesticides which was classified as moderate or high, the use of self equipment
protection which was not complete, ≥ 5 working hours in a day, and period of
employment in agricultural or plantation activity ≥ 5 years (made at least 3 of them). In
this research, it was noted that more respondents were exposed to pesticides (56.7%)
than those not exposed (43.3%).
Bivariable analysis
The bivariable analysis was conducted to determine the relationship between
each independent variable with the dependent variable. The independent variables
consisted of age, gender, race, family illness history, history of illness and exposure to
pesticides. In detail they can be observed in Table 2.
Table 2. Percentage, Odd’s Ratio and 95% Confidence Interval to the incidence of lymphoma
by age, gender, family history of cancer, history of illness and exposure to pesticides
Variabel
Lymphoma
p-value Odd’s
Ratio 95% CI Yes No
n % n %
Age
>55 years 7 7. 2 39 40. 2
0. 253
2. 1 0. 58-7. 74
≤55 years 4 4. 1 47 48. 5 1
Gender
Male 9 9. 2 38 39. 2 0. 019 5. 7 1. 16-27. 88
Female 2 2. 1 48 49. 5 1
Race
6
Chinese 1 1. 0 4 4. 1 0. 460 2. 1 0. 21-20. 19
Non Chinese 10 10. 3 82 84. 6 1
Family history of
cancer
Yes 7 7. 2 21 21. 7 0. 012 5. 4 1. 44-20. 34
No 4 4. 1 65 67. 0 1
History of illness
Yes 8 8. 2 17 17. 6 0. 001 10. 8 2. 59-45. 19
No 3 3. 1 69 71. 1 1
Exposure to pesticides
Yes 10 10. 3 45 46. 4 0. 021 9. 1 1. 12-74. 31
No 1 1. 0 41 42. 3 1
Source: Processed primary data of dr. Soebandi Hospital, Jember (2011)
Based on Table 2, more respondents who suffered from lymphoma were aged >
55 years (7.2%) and those who did not suffer were aged ≤ 55 years (48.5%). The
bivariable analysis results using Chi-square test showed p-value = 0.253 with OR 95%
CI (2.1; 0.58-7.74). This suggested that the age group > 55 years had a risk 2.1 times
more likely to have lymphoma than those aged ≤ 55 years. The results of this analysis
showed that the relationship of age with the incidence of lymphoma was insignificant
statistically.
Age is one major characteristic of an individual. Age has an influence to the
level of exposure, magnitude of risk and resistance. Different experiences of health
problems/diseases and decision-making are also influenced by the individual's age (8)
. In
general, the risk of non-Hodgkin's lymphoma increases with advancing age while
Hodgkin's lymphoma in the elderly is associated with a poorer prognosis than that
observed in younger patients. Increased incidence of lymphoma was associated with
age, especially in the age group> 55 years (4, 9-10)
.
Gender is a grouping of respondents based on genital traits, ie males and
females. Some diseases sometimes tend to infect a specific gender. That is because of
differences in physiological function, hormonal activity, and the need for certain
nutrients between men and women. Table 2 describes the respondents who suffered
from lymphoma that were more in male sex group (9.2%), while those not suffering
from lymphoma were more in female sex group (49.5%). Chi-square test results
showed that the sex variable had a p-value = 0.019 with OR, 95% CI (5.7; 1.16-27.88).
This suggests that men had a 5.7 time greater risk of suffering from lymphoma than
women. Thus, gender was significantly related to the incidence of lymphoma.
The results of this study were in line with previous research which stated that
most patients with lymphoma were male with a comparison between men and women
7
by 2:1. Risk difference was probably caused by other factors such as exposure to
carcinogenic materials received between men and women, including the exposure to
chemicals (pesticides), the lifestyle associated with consumption patterns, as well as
susceptibility to certain infectious diseases. Other causes of these differences were
caused by different physiological functions between men and women who led in a
particular gender which was more prone to suffer from a disease (4)
. Risk differences of
developing lymphoma in men and women were also caused by hormonal functions in
the body. In his research, Nelson found that most women suffering from lymphoma
took oral contraceptives or hormone replacement therapy (11)
.
Race is a category for a group of individuals / human hereditary with similar
physical features and biological characteristics. Table 2 shows that the majority of
respondents who suffered from lymphoma (10.3%) were non-Chinese Race (Java or
Madura). Similarly, the respondents who did not suffer from lymphoma were also the
majority of non-Chinese race (84.6%). Chi-square test results prevailed that the race
variable had a p-value = 0.460 with OR, 95% CI (2.1; 0.21-20.19). The results of the
analysis indicated that the Chinese race had 2.1 times greater risk of developing
lymphoma than non-Chinese race, but race was not significantly associated with
incidence of lymphoma statistically.
The results of this research were in line with the previous research which stated
that in the continent of Asia, the race that had a high risk of cancer was the Chinese
race. That is because in Chinese patients it is found that many of them were infected
with Epstein-Barr virus and Human T-cell leukemia / lymphoma virus type 1 (HTLV-1)
which are one of the infectious causes of lymphoma (4)
.
Table 2 shows that most respondents who suffered from lymphoma (7.4%) had a
family history of cancer, whereas the respondents who did not have lymphoma (67.0%)
did not have a family history of cancer. Chi-square test results prevailed that the family
cancer history variable had a p-value = 0.012 with OR, 95% CI (5.4; 1.44-20.34). The
analysis results showed that people who had a history of family cancer risk were 5.4
times more likely to have lymphoma than those not having a family history of cancer.
Statistically, a family history of cancer was also significantly associated with incidence
of lymphoma.
8
Genetic factors or family history of cancer may increase the risk of developing
lymphoma, but the increased risk is also influenced by exposure to chemicals or
materials that are carcinogenic. That is because there is a gene (DNA) derived by
certain parents who can be a cancer trigger in the offspring (7)
. People who have an
inherited immune disorder from their parents are at risk of suffering from lymphoma.
This risk will increase if the person is also exposed to carcinogenic materials on a
continuous basis, either through work, lifestyle, and diet which are a predisposing factor
in people who have a genetic abnormality in the immune system. But until now there
have still been no studies that examine what genes are found in patients with lymphoma
(12).
History of previous illness has an influence on the occurrence of lymphoma,
especially diseases associated with decreased immunity or disruption of the immune
system in acute and chronic. Based on Table 2, the majority of respondents who
suffered from lymphoma (8.2%) had a history of illness, whereas the respondents who
did not suffer from lymphoma were known mostly (71.1%) without history of illness.
Chi-square test results prevailed that the variable of the history of the disease had a p-
value = 0.001 with OR, 95% CI (10.8; 2.59-45.19). The analysis results showed that
people who had a history of illness (Diabetes Mellitus, HIV / AIDS, Hepatitis C and
Rheumatoid arthritis, as well as other types of cancer) had a risk 10.8 times likely to
suffer from lymphoma than those with no history of illness. Statistically, the history of
illness was also related significantly to the incidence of lymphoma.
Diabetes Mellitus Patients who routinely take insulin are at increased risk of
developing lymphoma. The risk is also influenced by genetic (family history of cancer),
environmental, and infectious agent factors. Diabetes Mellitus Patients also often
experience complications resulting in physiology function that they cannot work
optimally which often causes to be infected with multiple diseases (5).
Patients with
Hepatitis C virus has the risk of suffering from this disease due to chronic infection
caused by a virus that can cause changes in B cells, causing mutations and B cells
become malignant and proliferate uncontrollably (13-16)
.
Rheumatoid arthritis is a disease associated with the incidence of lymphoma. It
is linked to the impact or side effects of Methoxtrexate (MTX) and Anti-Tumor
Necrosis Factor (Anti-TNF) therapy often given to patients with Rheumatoid arthritis
9
(Wolfe and Michaud, 2004). In congenital immunodeficiency, it is known that the
immune system of patients with the disease is not able to fight viral and bacterial
pathogens in the respiratory and digestions that cause the immune system disorders
continuously which can cause mutations in B cells (12)
. In people with HIV/AIDS, the
immune system has a significant reduction. Eighty-two percent of HIV / AIDS patients
suffer from lymphoma . Therefore, the diagnosis in patients with lymphoma should also
be conducted along with tests to determine HIV infection (17)
. Chronic diseases
associated with immune system can reduce lymphokine and lower natural killer cell
activity (NK). It triggers B cells mutation to become malignant and proliferate
uncontrollably (18-19)
.
Table 2 describes the respondents who suffered from lymphoma who were
exposed more to chemicals (pesticides), as well as those who were not suffering from
lymphoma. Chi-square test results prevailed that the variable of exposure to chemicals
(pesticides) had a p-value = 0.021 with OR, 95% CI (9.1; 1.12-74.31). The analysis
results showed that people exposed to chemicals (pesticides) had a 9.1 times greater risk
of suffering from lymphoma than those not exposed to chemicals (pesticides).
Statistically, exposure to chemicals (pesticides) was significantly associated with the
incidence of lymphoma.
Exposure to chemicals such as pesticides, especially those containing 2.4-
dichlorophenoxyacetic acid, hexachlorocyclohexane and benzene can increase the risk
of lymphoma (20-22)
. Pesticides can enter the human body through various routes,
including through the skin, respiratory system and digestive system. Pesticide residues
pose an indirect effect on humans, but in the long run lead to health problems including
neurological disorders and metabolic enzymes (23)
.
Chemicals from the content of pesticides can poison the body cells or affect
specific organs that may be related to the nature of the chemical or chemicals associated
with a place to enter the body or also known as target organs (24)
. Pesticides contain
carcinogenic; the carcinogenic substances can cause or increase the risk of cancer
because exposure to chemicals continuously for long periods can lead to mutations
(changes) of genes (DNA) from cells of the body so that it continues to develop into
abnormal proliferation uncontrollably. The mechanism of the effect of pesticides on the
body is through two stages, namely the pharmacokinetics and pharmacodynamics. Thus,
10
in work or activities with the use of pesticides, preferably one uses Self Protective
Equipment (PPE) which consists of work clothes, mask (goggles or face shield), hat,
gloves, and boots (25)
.
Multivariable Analysis
The independent variables included to logistic regression test were those that
had a p-value <0.25. The results of the bivariable analysis using chi-square test included
gender, family cancer history, history of illness and exposure to chemicals (pesticides).
Selection of the best logistic regression model was performed with backward LR
method. The results of logistic regression test analysis with backward LR method
produced some value at each stage, namely:
a. Value for goodness of fit test 0.128 means that logistic regression model was proper
to be used for further analysis, since there was no real difference between the
predicted classification and the observed classifications.
b. The coefficient value of Negelkerke determination indicated that 4 predictors in step
1 were able to explain 45.3% of the total diversity of the response variable. In step 2
they could explain 44.4%. This means that the regression model for the coefficient
determination was good enough to predict the incidence of lymphoma.
c. Assessment of the feasibility of regression model in predicting performed used Chi-
square test of Hosmer and Lameshow. Hosmer and Lameshow value presented a
significance value of 0.01 in step 1 and of 0.214 in step 2. Hosmer and Lameshow
value in step 2 was greater than the p-value of 0.05, so that Ho was accepted, or in
other words, the estimated model was in accordance with the actual data used.
d. Percentage of the overall value of each step was in the range of 91.8%. The high
overall percentage value indicated that the accuracy of prediction had been very good
to use to predict the incidence of lymphoma at Dr. Soebandi Hospital, Jember.
e. Significance value of the multivariable analysis results (regression test with LR
backward method) revealed that there were 3 variables related significantly to the
incidence of lymphoma at Dr. Soebandi Hospital, Jember, namely family history of
cancer, history of illness, and exposure to chemicals (pesticides).
Based on the results of multivariable analysis (logistic regression test with LR
backward method), there were three variables that had a significant relationship
11
(statistically significant) on the incidence of lymphoma, namely family history of
cancer, history of illness, and exposure to chemicals (pesticides). It was based on the p-
value of the 3 variables that was less than α = 0.05. The variable having the most
powerful relationship to the incidence of lymphoma was a history of illnesses suffered
by the respondents. Here were alternative models generated from multivariable analysis:
In logistic regression, the value of E(Y/X) would always be between zero and
one (0 ≤ E (Y / X) ≤ 1). Constant value of 0.962 stated that if there was no family
history of cancer, no history of illness and no exposure to chemicals (pesticides), the
incidence of lymphoma was 0.32%. It can be seen from the following calculation:
The logistic regression model alternative could be used to predict the likelihood
of a person or a respondent to suffer from lymphoma based on the most influential
factors, namely family history of cancer, history of illness, and exposure to chemicals
(pesticides) by entering a code categorization of each variable to in the logistic
regression model as follows:
Some respondents probably had lymphoma:
a. Likelihood of the respondents to suffer from lymphoma occurred if there were a
family history of cancer, a history of illness, but no exposure to pesticides.
Family history of cancer = 1, illness history = 1, and exposure to pesticides = 0
The possibility or chance of suffering from lymphoma that occurred if they had a
family history of cancer, a history of illness, but no exposure to pesticides was 4.3%.
b. Likelihood of the respondents to suffer from lymphoma occurred if there were no
family history of cancer, a history of illness, and no exposure to pesticides.
Family history of cancer = 0, illness history = 1, and exposure to pesticides = 0
12
The possibility or chance of suffering from lymphoma that occurred if the
respondents did not have a family history of cancer, a history of illness, and no
exposure to pesticides was 28%.
c. Likelihood of respondents to suffer from lymphoma occurred if there were a family
history of cancer, no history of illness, and exposure to pesticides.
Family history of cancer = 1, illness history = 0, and exposure to pesticides = 1
The possibility or chance of suffering from lymphoma that occurred if the
respondents had a family history of cancer, no history of illness, and exposure to
pesticides was 2.1%.
d. Likelihood of the respondents to suffer from lymphoma occurred if there were no
family history of cancer, a history of illness, and exposure to pesticides.
Family history of cancer = 0, illness history = 1, and exposure to pesticides = 1
The possibility or chance of suffering from lymphoma that occurred if the
respondents did not have a family history of cancer, had a history of the disease, and
had exposure to pesticides was 2.6%.
e. Likelihood of the respondents to suffer from lymphoma occurred if there were no
family history of cancer, no history of illness, and exposure to pesticides.
Family history of cancer = 0, illness history = 0, and exposure to pesticides = 1
The possibility or chance of suffering from lymphoma that occurred if the
respondents did not have a family history of cancer, history of illness, and had
exposure to pesticides was 15.5%.
f. Likelihood of the respondents to suffer from lymphoma occurred if there were a
family history of cancer, no history of illness, and no exposure to pesticides.
Family history of cancer = 1, illness history = 0, and exposure to pesticides = 0
13
The possibility or chance of suffering from lymphoma that occurred if the
respondents had a family history of cancer, no history of illness, and no exposure to
pesticides was 23.6%.
g. Likelihood of the respondents to suffer from lymphoma occurred if there were a
family history of cancer, a history of illness, and exposure to pesticides.
Family history of cancer = 1, illness history = 1, and exposure to pesticides = 1
The possibility or chance of suffering from lymphoma that occurred if the
respondents had a family history of cancer, a history of illness, and exposure to
pesticides was 72.4%.
The logistic regression model alternative could be used to predict the likelihood
of a person or a respondent to suffer from lymphoma based on the factors having the
most powerful relationship, namely family history of cancer, history of previous illness,
and exposure to chemicals (pesticides).
Conclusion
Based on the results of data analysis and discussion, it can be concluded as
follows: 1) There was a significant relationship between gender, family history of
cancer, illness history, and exposure to pesticide and the incidence of lymphoma, but it
did not happen for the variables of age and race, 2) Factors that could predict the
incidence of lymphoma were a family history of cancer, history of illness, and exposure
to chemicals (pesticides).
Recommendation
There is a need for increasing cooperation across sectors including hospitals,
Indonesia Cancer Foundation, health office, Ministry of Agriculture and the business
industry in developing prevention programs and reducing cancer incidence through
increased use of personal protective equipment from exposure to chemicals primarily in
people who have a history of cancer in their family and have a history of illness in their
immune system.
14
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