Cancer Mortality Analysis Report

7/25/2019 Cancer Mortality Analysis Report

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Data Analysis & Decision

Model

Cancer Mortality Analysis Report

Prepared by:

Aakash Parwani

Sumit Sameriya

Kshitij Tiwari

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ContentsAbstract......................................................................................................................2

Introduction................................................................................................................ 3

Literature Review....................................................................................................... 6

Factors........................................................................................................................ 8

Sex.......................................................................................................................... 8

State...................................................................................................................... 10

Age Grou............................................................................................................. 11

!ancer Sites.......................................................................................................... 13

"t#nicit$................................................................................................................ 16

Resu%ts & ana%$sis.....................................................................................................20

!orre%ation Ana%$sis...............................................................................................20

'eat#s & Age Grou...........................................................................................21

'eat#s & !ancer Sites.......................................................................................22

'eat#s & State................................................................................................... 2(

'eat#s & "t#nicit$............................................................................................. 2)

*u%tivariate Ana%$sis............................................................................................. 28

*u%tivariate ana%$sis s$ste+s nor+a%%$ uti%i,ed -or............................................28

it# *u%tivariate Ana%$sis $ou can.....................................................................2/

Ana%$sis.............................................................................................................. 2/

!onc%usion................................................................................................................ 31

Future "n#ance+ent................................................................................................ 32

Acnow%edge+ent.................................................................................................... 32

Re-erences................................................................................................................33

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AbstractCancer is a noteworthy general wellbeing issue in the United States and numerous different parts

of the world. t is presently the second dri!ing reason for death in the United States" and is

re#uired to surpass heart sic$nesses as the main source of death in the following couple of years.

n this Report" we will concentrate on the central point that is identified with Cancer passings.

%he components that gi!e some dissected proof of growth demise. e will be doing Regression

Analysis to locate the most ideal relationship between the autonomous !ariables and the reliant

!ariable" which will gi!e enough proof to consider the relationship into down to earth.

'or this in!estigation" we will consider information from ())) to *+(*. e will be supporting

the e,amination through diagrams which will itself picture the conclusion. n the middle of" we

will be indicating growth passings in light of age gathering" se," state and e!ery single tumor site

which are our autonomous !ariables.

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IntroductionCancer is a disease in which body tissue gets destroyed by the abnormal cells present in the body.

Some of the symptoms of cancer are une,plained weight loss" abnormal bleeding" a new lump" a

prolonged cough and change in bowel mo!ements of human body. hile these all symptoms are

indicators of cancer" there are also some other issues through which it can occur. %he #uantity of

indi!iduals li!ing past a disease finding came to about (-. million in *+(- and is relied upon to

ascend to right around () million by *+*-. /ational consumptions for tumor care in the United

States totaled almost 0(* billion in *+(+ and could reach 0(1 billion in *+*+2Murphy" *+(34.

%he deaths due to cancer are increasing in USA. n order to analy5e the situations in cancer"

American Cancer Society was established in May" ()(3. t was de!eloped to showcase the

increasing cancer deaths o!er the years through facts and figures. %heir main focus is on the new

cases that are occurring and the deaths that can ta$e place in each year to find the total

contemporary cancer burden. %hey concentrate on the past years deaths and pro!ide the trend for

ne,t years and the new symptoms coming in picture. %he society has helped o!er the years to

help people sur!i!e and reco!er from cancer disease26owlader" *+(-4.

%he 7rgani5ations in USA ha!e built some numerical related facts and figures based on cancer

deaths which ha!e helped for future forecast for total number of deaths. %here are many types of

Cancer disease that are based on different body parts such as brain" chest" respiratory system"

eye" anal" etc. Some of the cancers that ha!e caused ma,imum deaths o!er the years are Male

and 'emale 8reast Cancer" Digesti!e System Cancer" Respiratory System Cancer" Male 9enital

System and many more. 'rom ())) to *+(*" Respiratory System Cancer and Male and 'emale

8reast Cancer ha!e caused more than + thousand deaths. Among all of the Cancer diseases

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Respiratory System Cancer and Male and 'emale 8reast Cancer has been the maor death

resulting disease in Cancer types. e will discuss few of them2Copeland" *+(-4.

8reast cancer is the group of cells that starts growing in the breast or chest of human. t can also

affect the entire body. 8reast Cancer is the *ndmost common cancer in women. American Cancer

Society has made a total estimation of *3(;-+ new cases that will occur in women in *+(. 7f

which -+*)+ women indications incorporate trouble gulping and weight reduction. 6a5ard elements

incorporate smo$ing" li#uor use" and a little rate of patients with continuous acid reflu,. 9astric

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2stomach4 cancer is a great deal less normal in the United States than some different parts of the

world howe!er chance !ariables incorporate contamination with 6elicobacter pylori and eating a

ton of sustenance


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Literature Review%he primary =ubMed search produced ++ citations" of which *13 met the inclusion criteria. %he

first published study that met our inclusion criteria was published in ()B by S@@R" which is

authoritati!e source of information on cancer incidence" mortality and sur!i!al in the United

States.

All the reports present on S@@R was in the public domain" which can be used for analysis. t

pro!ided information on Mortality rate of () age groups and then Regression is applied on that

data to find relationship between Age 9roup of patients and Mortality Rate. %his Regression

resulted in B* 2RS#uare4.

%he second published study that met our criteria was published by CDC 2Centers for Disease

Control and =re!entions4" this study was about Cancer Rates by U.S. State and Se,. %his study

was done on data between years ()))*+(*. 'or understanding the relationship MultiEinear

Regression was applied between Mortality Rate 2Dependent Fariable4 and Se," Age9roup" State

2ndependent Fariables4. %his Regression analysis resulted in ;+ 2RS#uare4.

%o understand which type of Cancer is most fre#uent in the US Citi5ens" we found help from

CDC 2Centers for Disease Control and =re!entions4. According to recent studies done Eeu$emia

& Eymphoma is the most fre#uent Caner Site in US Citi5ens. Also" a particular society named

GEeu$emia & Eymphoma SocietyH is de!eloped to fight against this Cancer.


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Factors

Sex

Se, is one of our independent !ariable in the analysis. Cancer deaths differ based on gender. t is

found that male ha!e more higher death rates of cancer than women. Research shows that cancer

death fre#uency in men is more is higher and the sur!i!al becomes e!en worse once it occurs in

them. Coo$ has published his study in GCancer Epidemiology, Biomarkers and preventionH

which shows that if the causes of both the genders in cancer incidence can be identified" then

pre!enti!e measures can be ta$en to reduce the burden created by cancer on men and women.

%he #uantity of new instances of malignancy 2tumor occurrence4 is --.; for e!ery (++"+++ men

and ladies for each year 2ta$ing into account *++;*+(* cases4. %he #uantity of disease passings

2malignancy mortality4 is (B(.* for e!ery (++"+++ men and ladies for e!ery year 2in light of

*++;*+(* passings4.

Coo$ and his entire research team analy5ed in depth USA data from a huge database" which had

statistics on appro,imately 3 cancers by se, and age from ()BB to *++1. %heir findings included

that Male cancer deaths are higher than women 26an$ey" *++*4.

Researchers also focused on the year sur!i!al rate of the people with different types of cancer.

%hey found that Male had !ery bad sur!i!al as compared to female. %hey also said that in future

research should be based on factors that ha!e higher diagnosis rate of cancer among men.

n youth cancer" males are again at a higher danger than females. %he se, differential in the

fre#uency of adolescence cancer is settled and reliable around the world 2Ashley" ()1)>

9reenberg and Shuster" ();> Einet and De!esa" ())(> =earce and =ar$er" *++(> Cartwright et

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al." *++*> Desandes et al." *++-4. %he M:' proportion for e!ery single occurrence cancer is

around (.*. Special cases to the male o!erabundance in youth cancer incorporate newborn child

leu$emia" thyroid carcinoma" threatening melanoma" and al!eolar delicate part sarcoma. As in

grownups" /6E demonstrates a steady male o!erabundance in all age bunches amid

adolescence and immature period 2range I (.BJ3.*4" while 6odg$in lymphoma 26E4

demonstrates an intriguing agesubordinate !ariety in its M:' proportion 2Ries et al." ()))4. %he

general rate of 6E in youngsters is more noteworthy in females than in males 2M:' ratio I +.;4"

yet the se, circulation is agesubordinate" with the stri$ing M:' proportion in 6E in more

youthful ages when the disease is uncommon switching for teenagers when it turns out to be

more basic 2Spit5 et al." ();14. %he S@@R information from ())+ to ()) period show M:'

proportions of .3 2K year4" (.- 2J) year4" (.( 2(+J(- year4" and +.; 2(J()> Ries et al." ()))4

2@bru" *+(*4.

Cancer Male to 'emale Death Ratio

Eip Cancer .( to (

Earyn, .3B to (

6ypopharny, -.B( to (

@sophagus -.+; to (

8ladder Cancer 3.31 to (

Eung Cancer *.3( to (

Colorectal Cancer (.-* to (

=ancreatic Cancer (.3B to (

Eeu$emia (.B to (

8ile Duct Cancer *.*3 to (

State

California" and maybe soon /ew Lor$" is confronting a concei!able growth scourge of more

noteworthy e,tent than as of now e,ists. %his is of real sympathy toward all fol$s and youngsters

o!er the US on the grounds that as California goes" so goes the country. 8ills are being

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presented and mar$ed all through the United States that are e!acuating your restorati!e decision

and educated assent. 8eginning in *+(1" California will re#uire all go!ernment funded school

$ids to be infused with $nown growth ma$ing fi,ings all together get an instruction. n /ew

Lor$" a comparati!e bill has been presented.

Maybe the most e!ident and warmed point for families confronting this medicinal ambush is the

way that it is obscure if the immuni5ations being constrained onto the $ids cause growth. %he

genuine immuni5ation paper embeds 2or online =D'4 for e!ery antibody e,presses the

accompanying:

%his immuni5ation has not been assessed for its cancercausing or mutagenic possibilities or

debilitation of ripeness.

@ach antibody contains a huge number of dangerous fi,ings" or adu!ants" which are each

cancercausing in their own particular right. %he fi,ings are Aluminum" 'ormaldehyde and

Mercury.

A recent report distributed in Molecular Carcinogenesis indicated reliably lifted dangers for

pancreatic malignancy in people wor$ing in the aluminum creation and metalwor$ing

commercial !entures. A recent report distributed in the Nournal of Applied %o,icology found that

the impact of aluminum on cell multiplication and cell senescence is stri$ingly li$e that of

enacted oncogenes in human epithelial mammary tissue.

'ormaldehyde presentation is an e,ceptional sympathy toward $ids and the elderly. Loungsters

may get to be touchy to formaldehyde all the more effortlessly" which may ma$e it more

probable they will get to be wiped out2=ic$le" *++B4.

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A study in the Scandina!ian Nournal of or$" @n!ironment and 6ealth presumed that methyl

mercury chloride causes $idney tumors in male mice and mercury chloride has demonstrated

some cancercausing mo!ement in male rats. %he concentrate li$ewise e,pressed that

epidemiological information indicates the li$elihood of a danger of lung" $idney" and focal

sensory system tumors.

Age Group

%he cancer can occur at any point of life. %he age has a !ery important effect in the death due to

the cancer. %he GAge 9roupH category represented in the following analysis is the age of the

cancer patient at which heOshe died. Chart in 'ig *. 9i!es a good !iew of !ariation in death rate

because of Cancer with Age. As we can see number of deaths obser!ed in cancer patients of age

less than ( year is !ery less and patients of age group 11) and B+B- has obser!ed highest

deaths. 8ut one thing to notice here is that death rate for cancer are higher among middleaged

and elderly populations29hosh" *+(*4.

As the population ages" numerous diseases that o!erwhelmingly influence more seasoned people

will turn out to be more common. n addition numerous conditions that influence the elderly will

happen in mi," in this way muddling watch o!er a particular condition 2"14. =ropelling age is a

high ha5ard element for cancer" with persons more than 1 representing 1+ of recently

analy5ed malignancies and B+ of e!ery single cancer death 2B";4. %he age balanced cancer

fre#uency rate is *((O(++"+++ population for those more than 1 contrasted with *+;O(++"+++

for those under 1 2B";4. @ssentially" the age balanced cancer death rate for those more than 1 is

(+1;O(++"+++ contrasted with 1BO(++"+++ for those under 1 2B";4. n this manner" the fre#uency

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of cancer in those more than 1 is (+ times more prominent than in those more youthful than 1

and the cancer death rate is (1 times more noteworthy in patients more than 1 contrasted with

more youthful patients. More than B+ of the mortality connected with numerous cancers

including prostate" bladder" colon" uterus" pancreas" stomach" rectum and lung happen in patients

1 and more established 2B";4. ndeed" e!en with a dynamic diminishing in the cancer fre#uency

and death rate" maturing of the population will be oined by a chec$ed increment in the aggregate

number of patients with cancer and the re#uirement for doctors and guardians to ha!e

e,traordinary aptitude in both oncology and geriatrics.

%he turning gray demographics in the United States and the way that cancer rate in people rises

e,ponentially in the last many years of life" recommends that cancer may soon supplant coronary

illness as the main source of death in this nation. %hese demographics raise basic difficulties to

be met by American pharmaceutical. Despite e,hibiting the criticalness of wanting to deal with

the e,tended weight of growth" these data offer climb to different re#uest regarding the

association of de!eloping to cancer2Robert" *++14"

0

100000

200000

300000

(00000

)00000

600000

'eat# it# Age Grous

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Fig 2. I%%ustrates #ow !ancer 'eat# rate varies wit# Age.


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Cancer Sites

Another most important factor which influences cancer death is the Gcancer sitesH. %here are

certain parts of the body which are more prone to the cancer cells. %he Gcancer sitesH in the

following study represents the area of the body which was affected from cancer and causes the

death of the patient.

n below table we can see the estimated new cases and deaths in the year *+(. 'rom the table"

we can conclude that Eung and bronchus Cancer which is respiratory cancer and breast cancer

ha!e ma,imum new cases and deaths in *+(.

n relation analysis section we would try to find out any relationship between death and cancer

site using Einear Regression2alter" *+(34.

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Somewhere around *+(+ and *+*+" we e,pect the #uantity of new cancer cases in the United

States to go up around *- in men to more than ( million cases for e!ery year" and by around

*( in women to more than )++"+++ cases for each year.

%he sorts of cancer we hope to build the most are?

Melanoma 2the deadliest sort of s$in cancer4 in white men and women.

=rostate" $idney" li!er" and bladder cancers in men.

Eung" breast" uterine" and thyroid cancers in women.

%hroughout the following decade" we anticipate that cancer rate rates will stay about the same>

howe!er the #uantity of new cancer cases to go up" for the most part due to a maturing white

population and a de!eloping dar$ population. Since cancer patients general are li!ing longer" the

#uantity of cancer sur!i!ors is relied upon to go up from around ((.B million in *++B to (;

million by *+*+.

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Cigarette smo$ing is connected to numerous sorts of cancer" particularly lung cancer. n the

United States" smo$ing has declined following the first Surgeon 9enerals Report on Smo$ing

and 6ealth was distributed in ()1-. n li$e manner" new instances of lung cancer ha!e gone

down subse#uent to the mid();+s in men and the late ())+s in women?#uic$er in men than

women. %he #uantity of new lung cancer cases in men is re#uired to finish what has been started

somewhere around *+(+ and *+*+" yet more than (+"+++ e,tra new lung cancer cases are relied

upon to be found in women e!ery year by *+*+.

7!erweight and obesity raise ha5ard for female breast" colorectal" esophageal" uterine" pancreas"

and $idney cancers. n the wa$e of e,panding in the course of recent decades" around 11 of

grownups and 33 of youngsters are currently o!erweight or fat. ith the e,ception of breast

and colorectal cancers" the #uantity of weightrelated cancers is re#uired to go up 3+ to -+ by

*+*+.

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Cancers brought on by contaminations are li$ewise anticipated that would increment. /ew

instances of li!er cancer are relied upon to go up more than half" li$ely the aftereffect of the

increment in hepatitis diseases" especially in indi!iduals concei!ed somewhere around ()- and

()1. 7ral cancers in white men are relied upon to increment by around 3+" li$ely the

conse#uence of more human papilloma!irus 26=F4 contamination 2%hompson" *+(4.

Ethnicity

Another effecti!e e,planatory !ariable found out to be is GethnicityH of the people. 'rom the

Data collected o!er the years" we pro!ide some relation between the ethnicity and the death rate

due to cancer in USA. @thnicity in the study is categori5ed maorly into /on6ispanic hite"

American ndianOAlas$a /ati!e" 6ispanic" and AsianO=acific slander women.

%he below table shows ncidence and Death Rates by Site" Race" and @thnicity" United States"

*++B to *+((2Anderson" *+(34.

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'rom ()))J*+(*" the rate of indi!iduals $ic$ing the buc$et from cancer has shifted" contingent

upon their race and ethnicity. %he diagram underneath demonstrates that in *+(*" among men"

dar$ men will probably pass on of cancer than whate!er other gathering" trailed by white"

6ispanic" American ndianOAlas$a /ati!e" and AsianO=acific slander men. Among ladies" dar$

ladies will probably bite the dust of cancer than whate!er other gathering" trailed by white"

American ndianOAlas$a /ati!e" 6ispanic" and AsianO=acific slander ladies.

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Findings

8elow" we ha!e written few findings from articles which include bac$ground" methods" results"

conclusions" impact:

8ac$ground: A relationship between Newish ethnicity and pancreatic cancer danger was

recommended by in!estigations loo$ing at pancreatic cancer death rates in the middle of News

and nonNews in /ew Lor$ in the ()+s. %hese e,aminations needed data on potential perple,ing

!ariables and the relationship between Newish ethnicity and pancreatic cancer has not been

analy5ed in any contemporary U.S. populace or in any accomplice study2Nacobs" *++)4.

Methods: Analy5ed the relationship between Newish ethnicity and pancreatic cancer mortality

among roughly ( million members in the Cancer =re!ention Study companion. Members

finished a sur!ey at enlistment in ();* which included data on religion" smo$ing" corpulence"

and diabetes. Amid followup through *++1" there were 1"B*B pancreatic cancer passings"

including -;+ among Newish members. Relati!e perils displaying was utili5ed to figure

multi!ariable rate proportions 2RR42Nemal" *++)4.

Results: After conforming for age" se," smo$ing" body mass list" and diabetes" pancreatic cancer

mortality was higher among Newish members than among nonNewish whites 2RR I (.-3> )

C" (.3+J(.B4. n in!estigations by origin" RRs were (.) 2) C" (.3(J(.)34 for /orth

AmericanJborn News with /orth AmericanJborn fol$s" (.-3 2) C" (.*BJ(.1(4 for /orth

AmericanJborn News with ( or more fol$s concei!ed outside /orth America" and (.+3 2+.B3"

(.--4 for News concei!ed outside /orth America 2=heterogeneity I +.+B4 2Coughlin" *+++4.

Conclusions: %hese results bolster a higher danger of creating pancreatic cancer among U.S.

News that is not clarified by built up danger elements.

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mpact: 'uture studies might clear up the part of particular ecological or hereditary components

in charge of higher danger among U.S. News. Cancer @pidemiol 8iomar$ers.

Results & analysis

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Correlation Analysis

n correlation analysis" we gauge an e,ample correlation coefficient" all the more particularly the

=earson =roduct Moment correlation coefficient. %he specimen correlation coefficient" meant r"

ranges between ( and P( and e!aluates the course and #uality of the straight relationship

between the two !ariables. %he correlation between two !ariables can be sure 2i.e." larger

amounts of one !ariable are connected with more ele!ated amounts of the other4 or negati!e 2i.e."

more ele!ated amounts of one !ariable are connected with lower le!els of the other4.

%he indication of the correlation coefficient shows the bearing of the affiliation. %he greatness of

the correlation coefficient shows the #uality of the affiliation.

'or instance" a correlation of r I +.) proposes a solid" positi!e relationship between two

!ariables" though a correlation of r I +.* recommend a frail" negati!e affiliation. A correlation

near 5ero proposes no direct relationship between two persistent !ariables2Mu$a$a" *+(*4.

e will be highlighting separate analysis of relationship between dependent !ariable i.e.

Number of Deaths because of Cancer and independent !ariables i.e. Age Group, State,

Ethnicity, Cancer Sites. %hese relations are generated on data ta$en between years ()))*+(*

2Midthune" *+++4.

eaths & Age Group

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%o understand relationship between these two !ariables in a better way" we del!e into analysis

using Einear Regression with A/7FA and 'ig 3. llustrates the results.

Fig 3. Linear regression resu%ts using S4A4 add5in.

'rom abo!e statistics we can say" Cancer is primarily a disease of older people" with mortality

rates increasing with age for most cancers.

eaths & Cancer Sites

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Chart in 'ig -.gi!es a good idea of how Death count !aries with different Cancer Sites between

years ()))*+(*. Cancer in Digesti!e System has caused highest number of deaths 2B(1B)(4"

and cancer at @ye & 7rbit 2-(14 has caused least number of deaths.

0200000(00000600000800000

eaths & Cancer Sites

Fig (. I%%ustrates #ow !ancer 'eat# rate varies wit# dierent cancer sites.

'rom 'ig . e can analy5e the most fre#uent cancer sites" data suggests that Eymphomas"

Eeu$emia are the most fre#uent cancer sites. 7n the other hand @ye and 7rbit is the least

fre#uent cancer site2ard" *+(*4.

0200(00600800

1000

Cancer sites with Fre!uency

Fre7uenc$

Fig ). !ancer sites wit# -re7uenc$.

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eaths & State

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Rates of dying from cancer !ary from state to state. n the following maps" the U.S. states are

di!ided into groups based on the rates at which people died from cancer till *+(*" which is the

most recent year with numbers a!ailable.

'or now we ha!e analy5ed death rates in two states only /ew Lor$ and California from 'ig B.

e can easily analy5e that California State has obser!ed more death 2*+-*(B)4 because of

cancer and /ew Lor$ has got less 2(1;1++34 number of death2Qramer" ();)4.

!a%i-ornia ew9or0

)00000

1000000

1)00000

2000000

2)00000

State & eaths

Fig . Gra# to i%%ustrate state5wise rate o- d$ing -ro+ cancer.

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eaths & Ethnicity

'rom ()))J*+(*" the rate of people dying from cancer has !aried" depending on their race and

ethnicity. %he graph in 'ig ; below shows that in *+(*" among men" blac$ men were more li$ely

to die of cancer than any other group" followed by white" 6ispanic" American ndianOAlas$a

/ati!e" and AsianO=acific slander men.

Fig 8. Gra# to i%%ustrate state5wise rate o- d$ing -ro+ cancer.

2)


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'rom 'ig ). e can say that blac$ women were more li$ely to die of cancer than any other

group" followed by white" American ndianOAlas$a /ati!e" 6ispanic" and AsianO=acific slander

women25mirlian" *+(34.

Fig /. Gra# to i%%ustrate state5wise rate o- d$ing -ro+ cancer.

%o better understand the relation between Death and @thnicity factor" we performed linear

regression using =6S%A% and 'ig (+ is showing the results of linear regression" here ethnicity is

ta$en as Categorical !ariable. 6owe!er" !alue of RS#uare from this analysis is ((.

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"ultivariate Analysis

Multi!ariate Data Analysis alludes to any factual system used to dissect data that emerges from

more than one !ariable. %his basically models reality where e!ery circumstance" item" or choice

includes more than a solitary !ariable. %he data age has brought about masses of data in each

field. n spite of the #uantum of data accessible" the capacity to ac#uire a reasonable picture of

what is going on and settle on $een choices is a test. At the point when accessible data is put

away in database tables containing lines and sections" Multi!ariate Analysis can be utili5ed to

handle the data in a significant manner.

"ultivariate analysis syste#s nor#ally utili$ed %or

8uyer and statistical sur!eying

uality control and #uality certification o!er a scope of businesses" for e,ample" nourishment

and refreshment" paint" pharmaceuticals" chemicals" !itality" information transfers" and so forth =rocess enhancement and process control

nno!ati!e wor$

ith "ultivariate Analysis you can

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Ac#uire an outline or a diagram of a table. %his analysis is fre#uently called =rincipal

Components Analysis or 'actor Analysis. n the diagram" it is concei!able to recogni5e the

predominant e,amples in the data" for e,ample" bunches" anomalies" patterns" et cetera.

Dissect bunches in the table" how these gatherings !ary" and to which aggregate indi!idual table

lines ha!e a place. %his $ind of analysis is called Classification and Discriminant Analysis. Disco!er connections between segments in data tables" for occurrence connections between

procedure operation conditions and item #uality. %he goal is to utili5e one arrangement of

!ariables 2segments4 to foresee another" with the end goal of streamlining" and to disco!er which

sections are imperati!e in the relationship. %he relating analysis is called Multiple Regression

Analysis or =artial Eeast S#uares 2=ES4" contingent upon the span of the data table 2a$$ee"

*+(-4.

Analysis

After completing correlation analysis of cancer mortality with indi!idual !ariables" it


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Fig 11. *u%ti%e Regression resu%ts using S4A4 add5in.

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Conclusion

'rom abo!e single and multi!ariable analysis we can draw few !aluable conclusions

(4 More than three#uarters 2B;4 of cancer deaths occur in people aged 1 years and o!er" and

more than half 2*4 occur in those aged B years and o!er. Einear regression Model 2Death &

Age 9roup4 has shown accuracy of B3 with data set of )+++.

*4 California State has obser!ed highest death because of cancer. Also" multi linear regression

model has produced result of ;+ which is selfe,planatory for drawing this conclusion.

Future Enhance#ent

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Although" we ha!e tried to dig hard some !aluable facts about cancer disease. 8ut" data analysis

is a field which always produces some interesting facts as much you del!e inside it. Same

happened with our team because> in current analysis we ha!e focused mainly on cancer death

rate dependency on different factors 2Mariotto" *++;4. n future we as a team has decided to

analy5e two interesting things which has got satisfactory effect on sur!i!al of cancer patients:

(.4 6ow might physical acti!ity affect cancer sur!i!orship*.4 6ow healthy eating affect cancer sur!i!orship

Ac'nowledge#ent

e would li$e to than$s =rofessor Nohn ang for pro!iding !aluable suggestions in our analysis.

Re%erences

Anderson: *. ;2013


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CDC. ;n.d.>wonder.cdc.gov>!ancer*ort5

v2012.#t+%

!oe%and: G. ;201(


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Ed,e: R. ;200(

Documents

Cancer Mortality Analysis Report