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CONDITIONAL SURVIVAL ANALYSES OF MALIGNANT GLIOMA PATIENTS
IN LOS ANGELES COUNTY FROM THE YEARS 1990 TO 2000
by
Jia Hu
_____________________________________________________________________
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(APPLIED BIOSTATISTICS AND EPIDEMIOLOGY)
December 2007
Copyright 2007 Jia Hu
Object Description
| Title | Conditional survival analyses of malignant glioma patients in Los Angeles County from the years 1990 to 2000 |
| Author | Hu, Jia |
| Author email | jiahu@usc.edu |
| Degree | Master of Science |
| Document type | Thesis |
| Degree program | Biostatistics |
| School | Keck School of Medicine |
| Date defended/completed | 2007-10-18 |
| Date submitted | 2007 |
| Restricted until | Unrestricted |
| Date published | 2007-10-25 |
| Advisor (committee chair) | Groschen, Susan G. |
| Advisor (committee member) |
Xiang, Anny Hui Sposto, Richard |
| Abstract | Background: Malignant brain tumor has one of the worst prognosis in medicine. However the current estimates of survival probabilities are estimated at the time of diagnosis which provide limited information for post-diagnosis survival.; Methods: Conditional survival probabilities are used in the current study to estimate the post-diagnosis survival in 2974 malignant glioma patients in Los Angeles County during the year 1990 to 2000. Conditional survival probabilities and median survival for patients surviving 1, 2, 3, 4, or 5 years after diagnosis and their 90 % confidence intervals are presented. In addition, potential risk factors are examined individually both at the time of diagnosis and after six months from diagnosis.; Results: The conditional probabilities of surviving one additional year increase as the post-diagnosis survival time increases (from 43% conditioned on surviving 1 year after diagnosis to 91% conditioned on surviving 5 years after diagnosis). Patients diagnosed of lower WHO grade tumor have higher conditional survival probabilities than those diagnosed of higher WHO grade tumor. However, as the years after diagnosis increases, the differences in the conditional probabilities across the groups are attenuated. Both at the time of diagnosis and conditioned on surviving 6 months after diagnosis, the age at diagnosis, race, tumor histology (WHO grade), tumor site and primary treatment are statistically significantly associated with the survival for these patients after also adjusting for sex and marital status.; Conclusion: Conditional survival probability is useful statistic of predicting the prognosis for patients with not only malignant glioma, but diseases with changing risks over time. |
| Keyword | conditional; survival; malignant; glioma; probability; risk |
| Geographic subject (county) | Los Angeles |
| Geographic subject (state) | California |
| Geographic subject (country) | USA |
| Coverage date | 1990/2000 |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m913 |
| Rights | Hu, Jia |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Hu-20071107 |
| Archival file | uscthesesreloadpub_Volume48/etd-Hu-20071107.pdf |
Description
| Title | Page 1 |
| Full text | CONDITIONAL SURVIVAL ANALYSES OF MALIGNANT GLIOMA PATIENTS IN LOS ANGELES COUNTY FROM THE YEARS 1990 TO 2000 by Jia Hu _____________________________________________________________________ A Thesis Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE (APPLIED BIOSTATISTICS AND EPIDEMIOLOGY) December 2007 Copyright 2007 Jia Hu |
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