published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Medicine / Master / Doctor of Medicine

Song, Qingkun. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 144-157). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

by Kai-Hang Choi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 217-232). / Abstract also in Chinese. / ABSTRACT --- p.i / ACKNOWLEDGMENT --- p.iv / TABLE OF CONTENTS --- p.v / LIST OF FIGURES --- p.viii / LIST OF TABLES --- p.xiii / Chapter CHAPTER I --- INTRODUCTION --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Role of GIS in Health Studies --- p.4 / Chapter 1.3 --- Research Objectives --- p.5 / Chapter 1.4 --- Organization of the Thesis --- p.6 / Chapter CHAPTER II --- LITERATURE REVIEW --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- Human cancer --- p.8 / Chapter 2.3 --- Environment and Cancer --- p.10 / Chapter 2.4 --- Cancer Etiology and Epidemiology --- p.13 / Chapter 2.5 --- Observational Cancer Epidemiology --- p.15 / Chapter 2.6 --- Geography of Cancer --- p.17 / Chapter 2.7 --- Geographical Epidemiology of Cancer --- p.19 / Chapter 2.7.1 --- Geographical Variation in Cancer Occurrence --- p.21 / Chapter 2.7.1.1 --- Cancer Mapping --- p.24 / Chapter 2.7.1.2 --- Spatial Autocorrelation --- p.26 / Chapter 2.7.2 --- Identifying Causal Association --- p.29 / Chapter 2.7.3 --- Environmental Factors of Cancer --- p.31 / Chapter 2.8 --- Geographical Information Systems --- p.40 / Chapter 2.9 --- GIS and Health --- p.41 / Chapter 2.9.1 --- GIS Applications in Health Planning --- p.42 / Chapter 2.9.2 --- GIS Applications in Health Research --- p.43 / Chapter 2.10 --- Cancer Studies with GIS --- p.45 / Chapter 2.11 --- Conclusion --- p.47 / Chapter CHAPTER III --- THE STUDY AREA AND RESEARCH METHODOLOGY --- p.49 / Chapter 3.1 --- Introduction --- p.49 / Chapter 3.2 --- Disease Transition in Hong Kong --- p.49 / Chapter 3.3 --- Cancer in Contemporary Hong Kong --- p.52 / Chapter 3.3.1 --- Trends of Cancer Mortality and Incidence --- p.52 / Chapter 3.3.2 --- The Common Types of Cancer --- p.55 / Chapter 3.3.3 --- Geographical Variation of Cancer in Hong Kong --- p.58 / Chapter 3.4 --- The Research --- p.61 / Chapter 3.4.1 --- Cartographic Analysis --- p.62 / Chapter 3.4.2 --- Statistical Analyses --- p.63 / Chapter 3.4.3 --- Cancer Variables --- p.67 / Chapter 3.4.4 --- Environmental Variables --- p.70 / Chapter 3.5 --- Conclusion --- p.71 / Chapter CHAPTER IV --- DATABASE CONSTRUCTION --- p.73 / Chapter 4.1 --- Introduction --- p.73 / Chapter 4.2 --- Data Collection --- p.73 / Chapter 4.2.1 --- Base Maps --- p.73 / Chapter 4.2.2 --- Cancer Data --- p.74 / Chapter 4.2.3 --- Socio-demographic Data --- p.75 / Chapter 4.2.4 --- Air Pollution --- p.76 / Chapter 4.2.5 --- ELF EMFs --- p.77 / Chapter 4.3 --- Data Input --- p.77 / Chapter 4.3.1 --- Spatial Data --- p.77 / Chapter 4.3.1.1 --- Base Maps --- p.78 / Chapter 4.3.1.2 --- Point Data --- p.78 / Chapter 4.3.1.3 --- Line Data --- p.79 / Chapter 4.3.2 --- Attribute Data --- p.79 / Chapter 4.4 --- Data Editing and Conversions --- p.80 / Chapter 4.4.1 --- Spatial Data --- p.80 / Chapter 4.4.1.1 --- Standard Coverage Editing Procedures --- p.80 / Chapter 4.4.1.2 --- Specific Coverage Editing Procedures --- p.81 / Chapter 4.4.2 --- Attribute Data --- p.83 / Chapter 4.4.2.1 --- Cancer Rates --- p.83 / Chapter 4.4.2.2 --- Socio-economic Status --- p.85 / Chapter 4.5 --- Data Pre-processing and Manipulation --- p.86 / Chapter 4.5.1 --- Socio-economic Variables --- p.86 / Chapter 4.5.1.1 --- Interpretation of Factor Scores --- p.97 / Chapter 4.5.2 --- Compromised Traffic Index --- p.99 / Chapter 4.5.3 --- ELFEMFs --- p.104 / Chapter 4.6 --- Conclusion --- p.106 / Chapter CHAPTER V --- RESULTS AND DISCUSSIONS --- p.111 / Chapter 5.1 --- Introduction --- p.111 / Chapter 5.2 --- Geographical Analysis of Cancer Patterns --- p.111 / Chapter 5.2.1 --- Results --- p.112 / Chapter 5.2.1.1 --- Total Cancer --- p.113 / Chapter 5.2.1.2 --- Cancer of the Female Breast --- p.118 / Chapter 5.2.1.3 --- Cancer of the Cervix Uteri (Cervical Cancer) --- p.121 / Chapter 5.2.1.4 --- Cancer of the Colon and Rectum (Colorectal Cancer) --- p.124 / Chapter 5.2.1.5 --- Cancer of the Stomach (Gastric Cancer) --- p.129 / Chapter 5.2.1.6 --- Leukaemia --- p.129 / Chapter 5.2.1.7 --- Cancer of the Liver --- p.134 / Chapter 5.2.1.8 --- Cancer of the Lung --- p.143 / Chapter 5.2.1.9 --- Cancer of the Nasopharynx (NPC) --- p.149 / Chapter 5.2.1.10 --- Cancer of the Oesophagus --- p.154 / Chapter 5.3 --- Correlation among Cancer Variables --- p.160 / Chapter 5.3.1 --- Correlation among Cancer types --- p.160 / Chapter 5.3.2 --- Temporal Correlation among Cancers --- p.168 / Chapter 5.3.3 --- Correlation between Cancer Mortality and Incidence --- p.170 / Chapter 5.4 --- Correlation between Cancer and Environmental Variables --- p.172 / Chapter 5.4.1 --- Results --- p.174 / Chapter 5.5 --- Weighted Stepwise Regression Modeling --- p.182 / Chapter 5.5.1 --- Results --- p.183 / Chapter 5.5.1.1 --- Total Cancer --- p.184 / Chapter 5.5.1.2 --- Cancer of the Female Breast --- p.186 / Chapter 5.5.1.3 --- Cancer of the Cervix Uteri (Cervical Cancer) --- p.188 / Chapter 5.5.1.4 --- Cancer of the Colon and Rectum --- p.189 / Chapter 5.5.1.5 --- Cancer of the Stomach (Gastric Cancer) --- p.191 / Chapter 5.5.1.6 --- Leukaemia --- p.193 / Chapter 5.5.1.7 --- Cancer of the Liver --- p.195 / Chapter 5.5.1.8 --- Cancer of the Lung --- p.197 / Chapter 5.5.1.9 --- Cancer of the Nasopharynx (NPC) --- p.199 / Chapter 5.5.1.10 --- Cancer of the Oesophagus --- p.201 / Chapter 5.6 --- Interpretations of Results --- p.203 / Chapter CHAPTER VI --- CONCLUSION --- p.207 / Chapter 6.1 --- Summary of Findings --- p.207 / Chapter 6.1.1 --- Summary on Geographical Analysis of Cancer Patterns --- p.207 / Chapter 6.1.2 --- Summary on Statistical Analysis of Cancer Variables --- p.209 / Chapter 6.1.3 --- Summary on Associations between Cancers and Environment --- p.211 / Chapter 6.2 --- Research Limitations --- p.212 / Chapter 6.3 --- Implications for Future Studies --- p.215 / BIBLIOGRAPHY --- p.217 / APPENDICES --- p.233 / Appendix I Community Map of hong Kong --- p.234 / Appendix II List of Communities and their Components --- p.236 / Appendix III Tertiary Planning Units (TPUs) - Community Conversion Lists --- p.240 / Appendix IV BASIC Program for Calculating Moran and Geary Indices --- p.244

published_or_final_version / Anatomy / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Pathology / Doctoral / Doctor of Philosophy

Xie, Shaohua = 室內燃香與香港華人的鼻咽癌發病風險 : / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 124-153). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese; appendixes includes Chinese. / Xie, Shaohua = Shi nei ran xiang yu Xianggang Hua ren de bi yan ai fa bing feng xian :

Yu, Kai Shing. / "November 2010." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 103-114). / Abstracts in English and Chinese. / Abstract --- p.2 / 中文摘要 --- p.6 / List of Contents --- p.9 / List of Table --- p.12 / Abbreviation --- p.13 / Acknowledgement --- p.14 / Chapter Chapter 1: --- Introduction --- p.15 / Chapter 1.1 --- Epidemiology of lung cancer --- p.15 / Chapter 1.2 --- Overview of significant prognostic factors for patients with NSCLC --- p.18 / Chapter 1.2.1 --- Tumor related factors --- p.19 / Chapter 1.2.2 --- Patient related factors --- p.21 / Chapter 1.3 --- Overview of significant prognostic factors for SCLC patients --- p.22 / Chapter Chapter 2: --- Literature Review --- p.25 / Chapter 2.1 --- Prevalence of co-morbidity among lung cancer patients --- p.25 / Chapter 2.2 --- Impact of co-morbidity on non small cell lung cancer patients --- p.28 / Chapter 2.3 --- Impact of co-morbidity on small cell lung cancer patients --- p.36 / Chapter 2.4 --- Summary of evidence from literature review --- p.40 / Chapter Chapter 3: --- Aim and Objectives --- p.42 / Chapter 3.1 --- General aim --- p.42 / Chapter 3.2 --- Specific objectives --- p.42 / Chapter 3.3 --- Main hypothesis --- p.42 / Chapter Chapter 4: --- Methodology --- p.43 / Chapter 4.1 --- Research design --- p.43 / Chapter 4.2 --- Study population --- p.43 / Chapter 4.3 --- Sample size estimation --- p.45 / Chapter 4.4 --- Data collection --- p.47 / Chapter 4.4.1 --- Demographic information --- p.47 / Chapter 4.4.2 --- Co-morbidity --- p.51 / Chapter 4.4.3 --- Adverse symptoms --- p.51 / Chapter 4.4.4 --- Disease characteristics --- p.52 / Chapter 4.4.5 --- Baseline laboratory findings --- p.53 / Chapter 4.4.6 --- Treatment data --- p.53 / Chapter 4.4.7 --- Follow up --- p.53 / Chapter 4.5 --- Statistical analyses --- p.54 / Chapter Chapter 5: --- Results --- p.56 / Chapter 5.1 --- Description of cohort --- p.56 / Chapter 5.2 --- Baseline characteristics --- p.58 / Chapter 5.3 --- Symptom presentation --- p.62 / Chapter 5.4 --- Histological characteristics --- p.64 / Chapter 5.5 --- Treatment characteristics --- p.67 / Chapter 5.6 --- Haematological characteristics of study population --- p.69 / Chapter 5.7 --- Prevalence of co-morbidity --- p.71 / Chapter 5.8 --- Overall survival --- p.74 / Chapter 5.8.1 --- Univariate and multivariate survival analysis for SCLC patients --- p.75 / Chapter 5.8.2 --- Univariate and multivariate survival analysis for NSCLC patients --- p.77 / Chapter 5.8.3 --- In-depth analyses for the Impact of co-morbidity on lung cancer survival --- p.79 / Chapter 5.8.4 --- Selected underlying causes of death --- p.84 / Chapter Chapter 6: --- Discussion --- p.85 / Chapter 6.1 --- Prognostic factors --- p.85 / Chapter 6.2 --- Prevalence of co-morbidity --- p.89 / Chapter 6.3 --- Impact of co-morbidity on lung cancer survival --- p.92 / Chapter 6.4 --- Strengths and limitations of this study --- p.97 / Chapter Chapter 7: --- Conclusions --- p.101 / Chapter Chapter 8: --- Implications and Recommendations for medial practice --- p.102 / References --- p.103

Cancer is the leading cause of death in Hong Kong (21,300 new cases and 11,500 deaths in 2003), with nasopharyngeal carcinoma (NPC), esophageal cancer (ESCC), and colorectal cancer (CRC) among the common ones. For these tumors, most patients present with advanced stage disease and poor treatment outcome, with an urge of early detection. Epigenetic inactivation of tumor suppressor genes (TSG) by CpG methylation represents an important mechanism of tumorigenesis, in addition to genetic abnormalities. Tumor-specific methylation can also be used as biomarkers for the identification of novel TSGs and for cancer early diagnosis and prognosis prediction. / Finally, for the purpose of development of epigenetic biomarker for cancer molecular diagnosis, I screened gene methylation in the serum samples. Aberrant methylation of PCDH10 and DLC1 was detected in serum samples (2/14 (14%) and 4/14 (29%) respectively) from tumor patients but not in normal controls. It suggests that screening for PCDH10 and DLC1 methylation in sera could be a tumor-specific and non-invasive epigenetic biomarker for molecular diagnosis and prognostics. (Abstract shortened by UMI.) / In the second approach, 1-Mb array-based comparative genomic hybridization (aCGH) was carried out to detect DNA copy number aberrations, which contain potential TSG loci, in a panel of NPC and ESCC cell lines. Frequent deletions include: 1p36.3, 3p14-11, 4p16-15, 5p13-q12, 6p21-12, 8p22-cent, 9p, 9q22-31, 10p, 13q12, 14q32, 16q23-24, 17q11.2, 18q in NPC, and 1p21, 4q21, 7p21, 7q35, 8p22-23, 8q11, 10p11, 11q22, 13q31, 14q32, 18q11-23 in ESCC. Several deletions (3p14-11 and 16q23) were further investigated in detail in this study. More than 12 genes were identified to be frequently silenced by methylation in tumors, including FHIT (3p14), WNT5A (3p14), ADAMTS9 (3p14), FEZF2 (3p14), ROBO (3p12), CADM2 (3p12), EPHA3 (3p11), RAB (11q22), ADAMTS18 (16q23), and TUSC8 (16q23), while homozygous deletion of these genes was infrequently detected. Aberrant methylation of these genes was also frequently detected in primary tumors in a tumor-specific manner. The tumor suppressor functions of TUSC8, WNT5A, CADM2 and ROBO were further investigated and validated. Further experiment indicated that induction of tumor cell apoptosis may contribute to the tumor suppressor function of TUSC8. / Modified genomic methylation subtractive approaches using uracil-DNA glycosylase or combined with pharmacological demethylation were developed. GADD45G, PCDH10, ROR2, DLC1L1 were among a series of novel methylated targets identified by these approaches. Methylation-associated silencing of these genes was frequently detected in various types of tumor cell lines and primary tumors including NPC, ESCC and CRC, in a tumor-specific manner. Ectopic expression of these genes strongly suppressed tumor cell growth and colony formation of silenced tumor cells. Epigenetic inactivation of GADD45G is the major mechanism for the loss of its response to environmental stresses. Reintroduction of PCDH10 strongly suppressed tumor cell migration and invasion. Ectopic expression of DLC1L1 in silenced tumor cells resulted in a remarkable suppression of tumor cell clonogenicity, which depends on its GAP activity. Furthermore, DLC1L1, but not its inactivating mutants, inhibited Ras mediated oncogenic transformation. Thus, these identified genes are functional TSGs. / Ying Jianming. / "July 2007." / Adviser: Qian Tao. / Source: Dissertation Abstracts International, Volume: 69-01, Section: B, page: 0083. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 147-173). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

by Siu-Fai Leung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 80-81). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Mortality and Socioeconomic Status --- p.1 / Chapter 1.2 --- Research Plan and Difficulties Encountered in the Study --- p.4 / Chapter 2 --- Imputation and File Merging --- p.8 / Chapter 2.1 --- Structure and Contents of Data Sets --- p.8 / Chapter 2.2 --- Imputation of Missing Values --- p.14 / Chapter 2.3 --- Merging Data Sets --- p.22 / Chapter 2.3.1 --- Merging Death Data and Census Data --- p.22 / Chapter 2.3.2 --- Merging Two Census Data Sets --- p.29 / Chapter 2.3.3 --- Final Data Set Used in Modeling --- p.31 / Chapter 3 --- Modeling and Estimation --- p.33 / Chapter 3.1 --- Discrete-Time Hazard Function Analysis --- p.33 / Chapter 3.1.1 --- The Hazard Function --- p.34 / Chapter 3.1.2 --- Logistic Regression --- p.36 / Chapter 3.2 --- Application of Discrete-Time Hazard Model on the Death Data Set --- p.37 / Chapter 3.2.1 --- Preparing the Person-Period Data Set --- p.38 / Chapter 3.2.2 --- Modeling the Person-Period Data Set --- p.41 / Chapter 3.3 --- Combining Results from different imputed data sets --- p.47 / Chapter 3.4 --- Estimation of Cell Probabilities --- p.51 / Chapter 4 --- Model Adequacy Checking --- p.52 / Chapter 4.1 --- The Definition of Residuals in Multiple Imputation --- p.52 / Chapter 4.2 --- Residual Analysis of The Cancer Mortality Model --- p.59 / Chapter 5 --- Conclusion --- p.63 / Chapter 5.1 --- The Cancer Mortality --- p.63 / Chapter 5.2 --- Competing Risk --- p.68 / Chapter 5.3 --- Discussion --- p.72 / Appendix A: Coding Description of District --- p.75 / Appendix B: Results of the Heart Diseases Mortality Model --- p.76 / Bibliography --- p.80