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研究生: 陳氏秋恆
Tran, Thi Thu Hang
論文名稱: 急性淋巴性白血病兒童的生活品質動態
Dynamic change in quality of life for children with acute lymphoblastic leukemia
指導教授: 黃美智
Huang, Mei-Chih
高綺吟
Kao, Chi-Yin
學位類別: 博士
Doctor
系所名稱: 醫學院 - 護理學系
Department of Nursing
論文出版年: 2024
畢業學年度: 112
語文別: 英文
論文頁數: 206
外文關鍵詞: Children, Acute lymphoblastic leukemia, Quality of life, Dynamic changes, Repeated cross-sectional design
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  • INTRODUCTION
    The five-year relative survival rate for childhood cancer has improved from 70% to 80 %, therefore QoL in this vulnerable population is of interest to ongoing research. Currently, two systematic reviews show that most of the published research evaluates the QoL of survivorship rather than the QoL during treatment. The QoL of children with acute lymphoblastic leukemia (ALL) would also change throughout the different phases of the treatment regimen as well as after ceasing treatment. The present study aims to evaluate the dynamic changes in QoL in pediatric patients with ALL after diagnosis.

    METHODS
    A repeated cross-sectional study was conducted with applying a mixed effect model to controlling all potential confounders. Pediatric patients with ALL were followed up by repeated measurements since diagnosis by using the PedsQL Generic Core Scales and the PedsQL Cancer Module. The Kernel smoothing method was used to capture dynamic change in QoL in children with ALL since diagnosis.

    RESULTS

    A total of 302 participants were classified to four age group as follow: 33.04% toddler aged 2-4 (3.31 ± 0.73), 26.09% young child aged 5-7(5.83 ± 0.74), 29.13% children aged 8-12 (10.03 ± 1.29), 11.74% adolescent aged 13-18(14.16 ± 1.17), with 59.60 percent of children are boys. Most of the proxy in this study are female (85.09%), married (94.70%), lives in rural (67.54%) and only finished high school (70.19%).
    For toddlers (aged 2-4), generic QoL domain scores of QoL of children with ALL aged 2-4 were good until three years after initial diagnosis, except frequently appeared procedural anxiety for constantly for two years and worried treatment during initial six months after diagnosis. Proxy data showed children (5-18 yrs) generic QoL domains were good, except physical (schooler in 1st year, adolescent in 2nd and 3rd years), emotional (adolescent in 3rd years), pain and nausea (in 2nd and 3rd years), procedural anxiety (young children and adolescent in 2nd and 3rd years). Proxy reported the young children and schoolers often concern appearance first two to three years after diagnosis. Children data showed impaired QoL domains, i.e, physical and nausea (schoolers in 6 initial months), pain for all three groups (from from 2nd to 3rd year).
    Analysis from data of proxy report for toddler aged 2-4 years, time after diagnosis was positively correlated with emotional, treatment anxiety domains. Physical in toddler was poor in unemployed proxy group. Toddlers had more procedural anxiety in unemployed proxy group. Treatment anxiety improves over time but worse in proxy group whose education below college level.
    Analysis from data of proxy report for children aged 5-18 years, young children (5-7 years) were better in cognition but worse in procedural anxiety compared with two elder groups (aged 8-12 years and aged 13-18 years). We found a positive correlation between time after diagnosis and seven QoL domains including: physical, emotional, pain, nausea, procedural anxiety, treatment anxiety, and worry domains. Proxy group whose education lower college level (<12 years of education) positively associated with pain, but negatively associated with cognition and perceived physical appearance anxiety domain.
    Analysis from data of children self-report for children aged 5-18 years, compared with two elder groups (aged 8-12 years and aged 13-18 years), young children (5-7 years) had better in physical but worse in procedural anxiety, treatment anxiety. We found the positive correlation between time after diagnosis and six QoL domains including: physical, pain, nausea, procedural anxiety, treatment anxiety, and worry domain. T-cell acute lymphoblastic leukemia had a positive correlation with perceived physical appearance anxiety. Proxy group whose education below college (<12 years of education) positively correlated to physical, pain, and cognition.

    CONCLUSION

    Proxy data revealed QoL in aged 2-4 years generally were good until three years after initial diagnosis, except frequently appeared procedural anxiety. Both proxy and children reported several similar deteriorated QoL domains (physical, emotional) as well distinct those (procedural anxiety, social, pain, nausea) for the initial three years after diagnosis. Time after diagnosis has profound effects on QoL in this population. Proxy’s characteristics (i.e., education, employment), child age, and immuno type as T-cell acute lymphoblastic leukemia have significant correlation with various QoL domains in divergent aged groups. The agreement level of self-reports and proxy reports is differently distributed by child age and PedsQL domains.

    ABSTRACT V ACKNOWLEDGEMENT VIII LIST OF TABLE XIII LIST OF FIGURE XV LIST OF APPENDIX XVII TABLE OF CONTENTS IX CHAPTER 1- INTRODUCTION 1 1.1 Research background 1 1.2 Statement of problem 3 1.3 Significance of the study 5 1.4 Purposes of the study 6 CHAPTER 2- LITERATURE REVIEW 7 2.1 Clinical characteristics of Vietnamese children with ALL 7 2.2. Status of treatment and care in children with ALL 8 2.2.1 Treatment for children with ALL in Vietnam 8 2.2.2 Treatment periods of children with ALL 9 2.2.3 Treatment outcome of children with ALL 10 2.2.4 Complication and relapse in ALL 10 2.3 Assessment of QoL in children with ALL 10 2.3.1 QoL in children- Concept analysis 11 2.3.2 Definition of QoL in children with cancer 11 2.3.3 Structure of QoL in children with cancer 12 2.3.4 Theoretical basis of the instrument of QoL 12 2.3.5 Methodology aspect 15 2.3.5.1 Overview instruments measured QoL in pediatric population 15 2.3.5.2 Psychometric properties in QoL measurement: Reliability, Validity and Responsiveness 16 2.3.5.3 Age pertinent for QoL measures in children 18 2.3.5.4 Agreement between proxy report and child self-report for QoL in children 18 2.4 QoL in children with ALL 20 2.5 Factors related to QoL in children with ALL 21 2.6 Effects of QoL assessment in clinical oncology pediatric practice 23 CHAPTER 3- METHODOLOGY 25 3.1 Repeated cross-sectional design 25 3.2 Sample and setting 25 3.2.1 Sample size 25 3.2.2 Time period for data collection and study population 26 3.2.3 Participant inclusion / exclusion 27 3.2.4 Setting 28 3.2.5 Training research assistants 30 3.2.5 Enrollment procedure 30 3.3 Instruments 31 3.3.1 The socio-demographic 32 3.3.2 Treatment information 32 3.3.3 QoL measurement in children with ALL by using the PedsQL Generic and the PedsQL Cancer module 32 3.3.3.1 Validity, reliability, and feasibility of PedsQL instrument 32 3.3.3.2 Interpretation and analysis of missing data 36 3.3.3.3 Cross-cultural translation process 36 3.4 Research procedures 37 3.5 Data analysis 38 3.5.1 Data set 38 3.5.2 Data cleaning 38 3.5.3 Data analysis 39 3.5.3.1 Analysis software 39 3.5.3.2 Descriptive statistics 39 3.5.3.3 Inference statistic 40 3.6Ethical considerations 41 CHAPTER 4-RESULTS 43 4.1 Demographic characteristics of participants and summary outcome 43 4.2 Proxy report QoL in children with ALL 43 4.2.1 Dynamic change in quality of life for children with acute lymphoblastic leukemia after diagnosis from proxy’s perspective 44 4.2.2 Factors determine QoL in children with ALL from proxy’s perspective 46 4.3 ALL Children with self-report of QoL 46 4.3.1 Dynamic change in quality of life for children with ALL after diagnosis from child’s perspective 47 4.3.2 Factors determine QoL in children with ALL from child’s perspective 48 4.4 Agreement between QoL assessed using proxy and child self-report among children with ALL 49 4.4.1 Demographic characteristics of participants 49 4.4.2 Score distribution in self-reports from child-proxy dyads 49 4.4.3 Discordance in child self-report and proxy report PedsQL Scores 49 4.4.4 Agreement level between proxy report and child self-report 50 CHAPTER 5- DISCUSSION 52 5.1 Dynamic changes of QoL and determine factors related to QoL among children with ALL 52 5.1.1 Demographic characteristics 52 5.1.2 Proxy reports QoL in children with ALL 53 5.1.2.1 Dynamic change in QoL for children aged 2-4 years old with ALL after diagnosis 54 5.1.2.2 Factors determine QoL in toddler aged 2-4 years with ALL analysis from proxy data 54 5.1.2.3 Dynamic change in QoL for children aged 5-18 years old with ALL after diagnosis 54 5.1.2.4 Factors determine QoL in children aged 5-18 years with ALL analysis from proxy data 57 5.1.3 Self-report QoL of children with ALL after diagnosis 58 5.1.3.1 Dynamic change in QoL for children aged 5-18 years with ALL from children data 58 5.1.3.2 Factors determine QoL in children aged 5-18 years with ALL analysis from child self-report 59 5.2 Agreement between QoL assessed using proxy and child self-report among children with ALL 59 5.2.1 Divergency scoring between child self-report and their proxy 61 5.2.2 Agreement levels 61 CHAPTER 6- CONCLUSION 63 6.1 Implication for research 64 6.2 Implications for practice 64 6.3 Implications for policy 64 6.4 Limitation 64 REFERENCES 66 Table 78 Figure 94 APPENDIX 105

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