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Real-World Care Patterns and Health Outcomes in Elderly Cancer
Taiwan (FMS-Taiwan) - Fu Jen University, Taipei
School of medicine
Required: English Accepted: Chinese
Type of Research Project
- Clinical Project without Laboratory work
What is the background of the project?
Conventional cancer clinical trials can be slow and costly, often produce results with limited external validity, and are difficult for patients to participate in.There are no standard guidelines for cancer care among the elderly. With a growing elderly population in the real world, there is a substantial need for evidence-based cancer treatment and management guidelines in this age group. Recent technological advances and a dynamic policy landscape in the United States have created a fertile ground for the use of real-world data (RWD) to improve current methods of clinical evidence generation. Sources of RWD include electronic health records, insurance claims, patient registries, and digital health solutions outside of conventional clinical trials. A definition focused on the original intent of data collected at the point of care can distinguish RWD from conventional clinical trial data. When the intent of data collection at the point of care is research, RWD can be generated using experimental designs similar to those employed in conventional clinical trials, but with several advantages that include gains in efficient execution of studies with an appropriate balance between internal and external validity. RWD can support active pharmacovigilance, insights into the natural history of disease, and the development of external control arms. Prospective collection of RWD can enable evidence generation based on pragmatic clinical trials (PCTs) that support randomized study designs and expand clinical research to the point of care. To fill this gap, This study will use Taiwan's National Health Insurance database, cancer registration database, and national death registration database to assess the patterns of cancer care in elderly patients in the Taiwan, and compare these patterns across these cancer sites. Specifically, we will examine cancer care patterns and comorbidities impact choices of cancer treatment and cancer prognosis and survival.
What is the aim of the project?
To describe patterns of care and treatment of elderly cancer in a population-based health care system and to evaluate the impact of these factors on outcomes.
What techniques and methods are used?
Following study aims the major steps/stages in this project are: 1.Characterize patterns and trends of cancer incidence, mortality, and survival, as well as clinical presentation of cancer, in elderly individuals by five-year age groups in the taiwan to inform priorities for cancer control in the elderly. This will be carried out using the Taiwan cancer registry database (1979-2016). 2.Develop algorithms (or identify and use validated existing algorithms) to characterize common chronic conditions (comorbidities) in elderly cancer patients, using the Taiwan Cancer Registry database merge to Taiwan National Health Insurance database. These chronic conditions include hypertension, periodontal disease, arthritis, chronic joint symptoms, diabetes, heart disease, osteoporosis, Alzheimer’s disease, chronic obstructive pulmonary disease, chronic kidney disease, and depression. 3.Apply the algorithms and analytic procedures to assess the impact of common comorbidities on outcomes among several selected cancers, including prostate, breast, colorectal, liver, and stomach cancers, using Taiwan Cancer Registry database, Taiwan National Health Insurance database, Taiwan death registry. Outcomes include hospitalizations, hospice services, polypharmacy, and cancer mortality.For the data an alysis perform logistic regression modeling to calculate relative risks and 95 confidence intervals, epidemiology and biostatistics methods is required, the statistical analyses were performed using SAS software (Version 9.4, SAS Institute Inc., Cary, NC, USA).
What is the role of the student?
- The student will mainly observe
- The student will observe the practical experiments but will be highly involved in the analysis of the results
- The tasks of the student will be performed on his/her own
- The tasks will be done under supervision
What are the tasks expected to be accomplished by the student?
1.Learn population health science basis. 2.First perform a critical review of the literature to identify any validated algorithms of the him interest, 3.Interoperate and refine results in the context of elderly cancer care/treatment problems 4. Biostatistics or similar with experience in a quantitative biosciences. 5. Software skills proficiency with SAS programming language and/or other scripting languages 6. Analyze and integrate data generated by population health database. At final student need to understand any methodological challenges in assessing treatment outcomes using population disease registry data. and to build a report of treatment and patient outcomes in Taiwan.
Will there be any theoretical teaching provided (preliminary readings, lectures, courses, seminars etc)
Practice on survival analysis performed by senior researchers
What is expected from the student at the end of the research exchange? What will be the general outcome of the student?
- The student will prepare a poster - The student will prepare a presentation - The student will prepare a scientific report - The student will prepare an abstract - The student’s name will be mentioned in a future publication - The student will have the opportunity to present the results together with the supervisor at a conference
What skills are required of the student? Is there any special knowledge or a certain level of studies needed?
Previous experience with: epidemiology/biostatistics
Are there any legal limitations in the student’s involvement
Type of students accepted
This project accepts: - Medical students - Graduated students (less than 6 months)
- JAMA Intern Med. 2015;175(9):1527-1529. doi:10.1001/jamainternmed.2015.3540 J Formos Med Assoc. 2016 Dec;115(12):1076-1088. doi: 10.1016/j.jfma.2015.10.011. Epub 2016 Jan 16.
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