RUcore: Rutgers University Community Repository
Predictive modeling for in-hospital mortality in pancreatic cancer patients
Descriptive
TitleInfo
Title
Predictive modeling for in-hospital mortality in pancreatic cancer patients
Name
(type = personal)
NamePart
(type = family)
Luo
NamePart
(type = given)
Fang
NamePart
(type = date)
1967-
DisplayForm
Fang Luo
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
MITAL
NamePart
(type = given)
DINESH P
DisplayForm
DINESH P MITAL
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Srinivasan
NamePart
(type = given)
Shankar
DisplayForm
Shankar Srinivasan
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Coffman
NamePart
(type = given)
Frederick
DisplayForm
Frederick Coffman
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = corporate)
NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
(type = corporate)
NamePart
School of Health Professions
Role
RoleTerm
(authority = RULIB)
school
TypeOfResource
Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
(encoding = w3cdtf);
(qualifier = exact)
2015
DateOther
(qualifier = exact);
(type = degree)
2015-10
CopyrightDate
(encoding = w3cdtf);
(qualifier = exact)
2015
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
Background: Pancreatic cancer is very aggressive with few symptoms before the cancer can diagnosed and usually the cancer is advanced when it was found. It is the most deadly type of cancer, and it is listed as the fourth leading cause of cancer-related death with a poor prognosis because of the late finding of the disease. To patients, the pancreatic cancer diagnosis is a life-changing disaster; however, to maximally extend the pancreatic cancer patients’ life is most important task after diagnosis. In this research study, we found certain statistical significant relationships between the death of pancreatic cancer patients and the comorbidities & demographics. Furthermore, patients with some comorbidities or demographics can make their life longer or shorter. Objectives: To develop a mathematic model to predict the death of pancreatic cancer patients using certain patients’ comorbidities and demographics. Also, pancreatic cancer patients with certain comorbidities or demographics can predict their rest of life will be longer or shorter. Methods: The study uses HCUP NIS year 2005-2009 data files as research source database. With retrieving pancreatic cancer patient from NIS data files, the database used in this study includes pancreatic cancer patients’ information with their comorbidities and some demographics. The algorithm used in this research study in 1) Logistic regression ROC curve calculation 2) Logistic regression Odds Ratio calculation. Results: 1) In output ROC curve, the area under the ROC curve (AUC) is 0.725 which is >0.5. It means when randomly pick one patient from the disease group (diagnosed as pancreatic cancer) and one from the no-disease group (not diagnosed as pancreatic cancer) and do the test on both. The patient with the more abnormal test result (Died) should be the one from the disease group (diagnosed as pancreatic cancer). 2) 11 comorbidities can significantly influence on life of pancreatic cancer patients, both LCL and UCL of odds ratio are either <1 or >1 in all 11 comorbidities, which means if patients were diagnosed as one of 11 comorbidities, they might either live longer or live shorter. Conclusions: The study results were cross verified by 3 types of cancer patients, which is pancreatic cancer, breast cancer and stomach cancer. Those 11 comorbidities have the same statistical significance effect on influencing patients’ life. So far no literatures can be found on such kind of study, this study can be considered as a new research field in the future.
Subject
(authority = RUETD)
Topic
Biomedical Informatics
Subject
(authority = ETD-LCSH)
Topic
Pancreas--Cancer--Treatment
Subject
(authority = ETD-LCSH)
Topic
Cancer--Patients
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
RelatedItem
(type = host)
TitleInfo
Title
School of Health Related Professions ETD Collection
Identifier
(type = local)
rucore10007400001
Identifier
ETD_6590
Identifier
(type = doi)
doi:10.7282/T3474CTK
PhysicalDescription
Form
(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xi, 98 p. : ill.)
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Fang Luo
Location
PhysicalLocation
(authority = marcorg);
(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Genre
(authority = ExL-Esploro)
ETD doctoral
Back to the top
Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Luo
GivenName
Fang
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2015-06-29 12:09:11
AssociatedEntity
Name
Fang Luo
Role
Copyright holder
Affiliation
Rutgers University. School of Health Related Professions
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top
Technical
RULTechMD
(ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem
(VERSION = 5.1)
windows xp
Back to the top
Statistical Profile