Applying a Computer-Assisted Measurement System to Investigate Change Patterns of Quality of Life and Symptoms in Hcc Patients Receiving Radiotherapy.

  • Chen, Mei-Ling (PI)
  • Chang, Joseph Tung-Chieh (CoPI)
  • Hong, Ji-Hong (CoPI)
  • Huang, Bing Shen (CoPI)

Project: National Science and Technology CouncilNational Science and Technology Council Academic Grants

Project Details

Abstract

Hepatocellular carcinoma (HCC) is the second leading cause of cancer mortality in Taiwan. Not many HCC patients can be treated with surgical resection or liver transplantation. The use of radiotherapy (RT) in treating HCC has been increasing due to the technologic advances, particularly for those unsuitable for or refractory to other local therapies. Patient-reported outcome are seldom studies in HCC patients under RT. The main purposes of this 3-year project are to (1) develop a computer-assisted measurement system for patient-reported outcomes (PROs) including health-related quality of life (HRQOL), symptoms, and treatment satisfaction, and (2) using the above systems to examine the longitudinal change patterns of PROs in patients with hepatocellular carcinoma (HCC) receiving radiotherapy (RT). The computer computer-assisted measurement system for PROs will be developed in such a way that is easy for both patients and health care providers to report/enter data along with an individual real-time printed report of measurement results. This ePROs measurement system will be tested for feasibility and equivalence. After validation, this measurement system will be applied to collect PROs in 140 patients with HCC receiving either photon or proton RT. The specific outcomes included in this study are HRQOL measured by the FACT-Hep, fatigue measured by the FACIT-F, pain measured by the BPI-SF, symptom distress measured by the MSAS-SF, and treatment satisfaction measured by the FACIT-TS-G. The above mentioned instruments all have satisfactory reliability and validity in cancer patients. Data will be analyzed using chi-square test, logistic regression, hierarchical linear model, and latent growth mixture modeling.

Project IDs

Project ID:PC10401-0753
External Project ID:MOST103-2314-B182-049-MY3
StatusFinished
Effective start/end date01/08/1531/07/16

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