Dataset Information

Disability Weights Measurement for 289 Causes of Disease Considering Disease Severity in Korea.

ABSTRACT: Background:For the Korean Burden of Disease (KBD) 2015 study, we have amended disability weights for causes of disease adapting the methodology of the KBD disability weight 2012 study. Methods:We conducted a self-administered web-based survey in Korea using ranking five causes of disease. A total of 605 physicians and medical college students who were attending in third or fourth grade of a regular course performed the survey. We converted the ranked data into paired comparison data and ran a probit regression. The predicted probabilities for each cause of disease were calculated from the coefficient estimates of the probit regression. 'Being dead (1)' and 'Full health (0)' were utilized as anchor points to rescale the predicted probability on a scale from 0 to 1. Results:As a result, disability weights for a total of 289 causes of disease were estimated. In particular, we calculated the disability weights of 60 causes of disease considering severity level. These results show that prejudice about the severity of cause of disease itself can affect the estimation of disability weight, when estimating the disability weight for causes of disease without consideration of severity. Furthermore, we have shown that disability weights can be estimated based on a ranking method which can maximize efficiency of data collection. Conclusion:Disability weights from this study can be used to estimate disability adjusted life year and healthy life expectancy. Furthermore, we expected that the use of the ranking method will increase gradually in disability weight studies.

SUBMITTER: Ock M

PROVIDER: S-EPMC6434154 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Disability Weights Measurement for 289 Causes of Disease Considering Disease Severity in Korea.

Ock Minsu M Park Bomi B Park Hyesook H Oh In-Hwan IH Yoon Seok-Jun SJ Cho Bogeum B Jo Min-Woo MW

Journal of Korean medical science 20190214 Suppl 1

<h4>Background</h4>For the Korean Burden of Disease (KBD) 2015 study, we have amended disability weights for causes of disease adapting the methodology of the KBD disability weight 2012 study.<h4>Methods</h4>We conducted a self-administered web-based survey in Korea using ranking five causes of disease. A total of 605 physicians and medical college students who were attending in third or fourth grade of a regular course performed the survey. We converted the ranked data into paired comparison da ...[more]

PMID: 30923484

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Project description:BackgroundThe disability weight (DW) quantifies the severity of health states from disease sequela and is a pivotal parameter for disease burden calculation. We conducted a national and subnational DW measurement in China.MethodsIn 2020-2021, we conducted a web-based survey to assess DWs for 206 health states in 31 Chinese provinces targeting health workers via professional networks. We fielded questions of paired comparison (PC) and population health equivalence (PHE). The PC data were analysed by probit regression analysis, and the regression results were anchored by results from the PHE responses on the DW scale between 0 (no loss of health) and 1 (health loss equivalent to death).FindingsWe used PC responses from 468,541 respondents to estimate DWs of health states. Eight of 11 domains of health had significantly negative coefficients in the regression of the difference between Chinese and Global Burden of Disease (GBD) DWs, suggesting lower DW values for health states with mention of these domains in their lay description. We noted considerable heterogeneity within domains, however. After applying these Chinese DWs to the 2019 GBD estimates for China, total years lived with disability (YLDs) increased by 14·9% to 177 million despite lower estimates for musculoskeletal disorders, cardiovascular diseases, mental disorders, diabetes and chronic kidney disease. The lower estimates of YLDs for these conditions were more than offset by higher estimates of common, low-severity conditions.InterpretationThe differences between the GBD and Chinese DWs suggest that there might be some contextual factors influencing the valuation of health states. While the reduced estimates for mental disorders, alcohol use disorder, and dementia could hint at a culturally different valuation of these conditions in China, the much greater shifts in YLDs from low-severity conditions more likely reflects methodological difficulty to distinguish between health states that vary a little in absolute DW value but a lot in relative terms.FundingThis work was supported by the National Natural Science Foundation of China [grant number 82173626], the National Key Research and Development Program of China [grant numbers 2018YFC1315302], Wuhan Medical Research Program of Joint Fund of Hubei Health Committee [grant number WJ2019H304], and Ningxia Natural Science Foundation Project [grant number 2020AAC03436].

Project description:The search for the genetic foundation of multiple sclerosis (MS) severity remains elusive. It is, in fact, controversial whether MS severity is a stable feature that predicts future disability progression. If MS severity is not stable, it is unlikely that genotype decisively determines disability progression. An alternative explanation tested here is that the apparent instability of MS severity is caused by inaccuracies of its current measurement. We applied statistical learning techniques to a 902 patient-years longitudinal cohort of MS patients, divided into training (n?=?133) and validation (n?=?68) sub-cohorts, to test four hypotheses: (1) there is intra-individual stability in the rate of accumulation of MS-related disability, which is also influenced by extrinsic factors. (2) Previous results from observational studies are negatively affected by the insensitive nature of the Expanded Disability Status Scale (EDSS). The EDSS-based MS Severity Score (MSSS) is further disadvantaged by the inability to reliably measure MS onset and, consequently, disease duration (DD). (3) Replacing EDSS with a sensitive scale, i.e., Combinatorial Weight-Adjusted Disability Score (CombiWISE), and substituting age for DD will significantly improve predictions of future accumulation of disability. (4) Adjusting measured disability for the efficacy of administered therapies and other relevant external features will further strengthen predictions of future MS course. The result is a MS disease severity scale (MS-DSS) derived by conceptual advancements of MSSS and a statistical learning method called gradient boosting machines (GBM). MS-DSS greatly outperforms MSSS and the recently developed Age Related MS Severity Score in predicting future disability progression. In an independent validation cohort, MS-DSS measured at the first clinic visit correlated significantly with subsequent therapy-adjusted progression slopes (r?=?0.5448, p?=?1.56e-06) measured by CombiWISE. To facilitate widespread use of MS-DSS, we developed a free, interactive web application that calculates all aspects of MS-DSS and its contributing scales from user-provided raw data. MS-DSS represents a much-needed tool for genotype-phenotype correlations, for identifying biological processes that underlie MS progression, and for aiding therapeutic decisions.

Project description:BackgroundDisability weights (DWs) are weight factors that reflect the severity of health states for estimates of disability-adjusted life years. A new set of global DWs was published for the Global Burden of Diseases and Injuries (GBD) 2013 study, which relied on sampling from various world regions, but included little data for countries in East Asia. This study aimed to measure DWs in Japan using comparable methods, and compare the results with previous estimates from the GBD 2013 DW study.MethodsWe conducted a web-based survey in 2019 to estimate DWs for 231 health states for the Japanese population. The survey included five new health states but otherwise followed the method of the GBD DW measurement study. The survey consisted of 15 paired comparison (PC) questions and 3 population health equivalence questions (PHE) per respondent. We analyzed PC data using probit regression and rescaled results to DW units between 0 (equivalent to full health) and 1 (equivalent to death).FindingsWe considered 37,318 nationally representative respondents. The values of the resulting DWs ranged from 0.707 (95% uncertainty interval (UI) 0.527-0.842) for spinal cord injury at neck level (untreated) to 0.004 (UI 0.001-0.009) for mild anemia. High correlation between Japanese DW and GBD 2013 DW was observed, but there was considerable disagreement. Out of 226 comparable health states, 55 (24.3%) showed more than a factor-of-two difference, of which 41 (74.6%) had a higher value in Japanese DW. Many of the health states with higher DW in the Japan study were injuries, including amputation and fracture, and hearing and vision loss, while mental, behavioral, and substance use disorders generally tended to be lower.ConclusionsThis study has created an empirical basis for assessment of Japanese DWs of health status. The findings from this study based on the Japanese population suggest that there might be contextual differences in rating the severity of health states compared to previous surveys conducted elsewhere.

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Disability Weights Measurement for 289 Causes of Disease Considering Disease Severity in Korea.

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Disability Weights Measurement for 289 Causes of Disease Considering Disease Severity in Korea.

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