Dataset Information

Estimating utility weights and quality-adjusted life year loss for colorectal cancer-related health states in Korea.

ABSTRACT: We aimed to assess utility weight of health states associated with colorectal cancer (CRC) that reflect the societal preference of the Korean population and to estimate the quality-adjusted life year (QALY) loss with CRC. We recruited 607 individuals from the Korean population; they were surveyed via face-to-face computer-assisted interviews. The participants evaluated each CRC-associated health state using standard gamble. Utility weight for each health state was calculated as the possibility of full health restoration. Moreover, we estimated total QALY loss due to CRC in Korean individuals aged ?30 years in 2013. To calculate QALY due to morbidity, we yielded utility weights and used epidemiologic data of CRC on severity from the National Cancer Control Institute. QALY loss due to mortality was calculated using mortality of CRC and life expectancy data from the Korean Statistical Information Service. The highest and lowest utility weights were assigned to "adenomatous polyps" and "metastatic colon cancer", respectively. Total QALY loss due to CRC in Korea was 173,662; these patients were more likely to be men or be included in the 70-74-year age group. These utility weights may be useful for conducting cost-utility studies of cancer screening for CRC and for measuring disease burden with QALY.

SUBMITTER: Lee JY

PROVIDER: S-EPMC5514107 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Estimating utility weights and quality-adjusted life year loss for colorectal cancer-related health states in Korea.

Lee Jin Yong JY Ock Minsu M Jo Min-Woo MW Son Woo-Seung WS Lee Hyeon-Jeong HJ Kim Seon-Ha SH Kim Hyun Joo HJ Lee Jong Lyul JL

Scientific reports 20170717 1

We aimed to assess utility weight of health states associated with colorectal cancer (CRC) that reflect the societal preference of the Korean population and to estimate the quality-adjusted life year (QALY) loss with CRC. We recruited 607 individuals from the Korean population; they were surveyed via face-to-face computer-assisted interviews. The participants evaluated each CRC-associated health state using standard gamble. Utility weight for each health state was calculated as the possibility o ...[more]

PMID: 28717246

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Project description:ObjectivesThe purpose of this research is to understand the thought processes that underpin responses to stated preference approaches for eliciting quality of life, in particular the standard gamble.MethodsWe utilize standard gamble preference elicitation survey techniques to elicit quality-adjusted life year weights for two reduced health states: chronic severe depression and total blindness. After the survey, we conduct open-ended qualitative interviews with respondents to determine their thought processes while taking the surveys and to shed light on what their quality-adjusted life year weight is capturing. Survey responses were coded and analyzed for themes in NVivo, the results of which were then formalized in the terminology of decision sciences.ResultsThe qualitative results of the cognitive interviews present systematic evidence for a type of cognitive bias present in standard gamble quality-adjusted life year weight elicitation, which has not been previously highlighted and which we call treatment bias. We define this treatment bias as the consideration of salient treatment alternatives correlated with a reduced health state, when these alternatives are not explicitly posed in the question. Our formalization of this cognitive behavior demonstrates that treatment bias will always bias the elicited health state utility of treating the illness in question downward.ConclusionThe treatment bias highlighted in this study has implications for economic evaluation when comparing treatment for illnesses where alternative treatments are widely publicized versus those that are not. For example, comparing the effectiveness of treating depression versus arthritis may be biased against depression if advertisements for anti-depressants are more widely viewed by survey respondents than advertisements for arthritis treatments. We propose a statement to be imbedded in all questionnaires regarding stated preference elicitation of quality-adjusted life year weights in order to correct for this bias in future stated preference surveys.

Project description:BackgroundLife expectancy is increasingly incorporated in evidence-based screening and treatment guidelines to facilitate patient-centered clinical decision-making. However, life expectancy estimates from standard life tables do not account for health status, an important prognostic factor for premature death. This study aims to address this research gap and develop life tables incorporating the health status of adults in the United States.MethodsData from the National Health Interview Survey (1986-2004) linked to mortality follow-up through to 2006 (age ≥ 40, n = 729,531) were used to develop life tables. The impact of self-rated health (excellent, very good, good, fair, poor) on survival was quantified in 5-year age groups, incorporating complex survey design and weights. Life expectancies were estimated by extrapolating the modeled survival probabilities.ResultsLife expectancies incorporating health status differed substantially from standard US life tables and by health status. Poor self-rated health more significantly affected the survival of younger compared to older individuals, resulting in substantial decreases in life expectancy. At age 40 years, hazards of dying for white men who reported poor vs. excellent health was 8.5 (95% CI: 7.0,10.3) times greater, resulting in a 23-year difference in life expectancy (poor vs. excellent: 22 vs. 45), while at age 80 years, the hazards ratio was 2.4 (95% CI: 2.1, 2.8) and life expectancy difference was 5 years (5 vs. 10). Relative to the US general population, life expectancies of adults (age < 65) with poor health were approximately 5-15 years shorter.ConclusionsConsiderable shortage in life expectancy due to poor self-rated health existed. The life table developed can be helpful by including a patient perspective on their health and be used in conjunction with other predictive models in clinical decision making, particularly for younger adults in poor health, for whom life tables including comorbid conditions are limited.

Dataset Information

Estimating utility weights and quality-adjusted life year loss for colorectal cancer-related health states in Korea.

Publications

Estimating utility weights and quality-adjusted life year loss for colorectal cancer-related health states in Korea.

Similar Datasets

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