Psychometric properties of Functional Assessment of Cancer Therapy-Prostate (FACT-P) in Chinese patients with prostate cancer

Qual Life Res. 2015 Oct;24(10):2397-402. doi: 10.1007/s11136-015-0993-8. Epub 2015 Apr 16.

Abstract

Purpose: The aim of the study was to assess the validity, reliability and sensitivity of the FACT-P (version 4) in Chinese males with prostate cancer.

Methods: Construct validity was assessed using Spearman's correlation test against the 12-item Short Form Health Survey (SF-12v2). Internal consistency and test-retest reliability were assessed using Cronbach's α coefficient and intra-class correlation coefficient, respectively. Sensitivity was determined by performing known-group comparisons by independent t test.

Results: FACT-P subscale scores had a moderate correlation with the corresponding SF-12v2 domain score that conceptually measures the similar construct providing evidence for adequate construct validity. Internal consistency was acceptable (α: 0.687-0.900) for all subscales aside from the Prostate Cancer Subscale (α: 0.505) and Trial Outcome Index (α: 0.562). FACT-P subscale and total scores showed good test-retest reliability (range 0.753-0.913). All total scales and most of the subscales were sensitive in detecting differences between patients with different levels of functional impairment but not different cancer stages or levels of prostate-specific antigen.

Conclusions: The measure is a valid and reliable measure to assess the health-related quality of life of Chinese males with prostate cancer. The FACT-P is sensitive to detect difference between patients with varying functional status.

Keywords: Chinese; Prostate cancer; Psychometrics; Quality of life; Reliability; Validity.

Publication types

  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Asian Continental Ancestry Group*
  • China
  • Health Surveys
  • Humans
  • Male
  • Prostatic Neoplasms / diagnosis*
  • Prostatic Neoplasms / drug therapy
  • Prostatic Neoplasms / psychology
  • Psychometrics / methods*
  • Quality of Life
  • Reproducibility of Results
  • Sickness Impact Profile*
  • Socioeconomic Factors
  • Surveys and Questionnaires