Evidence map›Paper›PMID 28733768›Full record

ArticleInternational urology and nephrology2017

Estimates of health utility scores in chronic kidney disease.

Nigar Sekercioglu, Bryan Curtis, Sean Murphy, Gord Blackhouse, Brendan Barrett

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Article in International urology and nephrology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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2citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Nigar SekerciogluDepartment of Clinical Epidemiology, Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada. nigars2003@yahoo.com.
Bryan CurtisDepartment of Clinical Epidemiology, Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada.
Sean MurphyDepartment of Clinical Epidemiology, Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada.
Gord BlackhousePrograms for Assessment of Technology in Health, McMaster University, 3 Charlton Ave E, 2nd Floor, Hamilton, ON, L8N 1Y3, Canada.
Brendan BarrettDepartment of Clinical Epidemiology, Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCoverage decisions in publicly funded healthcare systems require a formal, systematic and transparent assessment process for policies related to distribution of resources. The process is complex and employs multiple types of information, such as clinical effectiveness, costs and health utility scores which are used to produce quality-adjusted life years. The purpose of this study was to create health utility scores for CKD patients within the Canadian population.

methodsThis is a cross-sectional study of CKD patients. We administered the Short-Form 36 Quality of Life Questions to all participants and employed the Short-Form 6 Dimension index to create health utility scores which were created using a set of parametric preference weights, nonparametric preference weights and ordinal health state valuation techniques obtained from a sample of the general population.

resultsUtility values in the dialysis group were lower than in the non-dialysis group. There was a significant relationship between age and health utility scores: As age increases, health utility scores decrease. Diabetes was associated with lower health utility scores in dialysis patients, whereas other covariates did not reach levels of statistical significance in our stepwise regression models. The parametric Bayesian model and standard gamble approach yielded the same results, while the correlation between the nonparametric and parametric methods was above 0.9.

conclusionHealth utility scores were low relative to the general population norm in our study cohort. Longitudinal assessment of CKD patients to capture possible fluctuations in health utility scores may add useful information.

Indexed as

Quality of LifeAgedAge FactorsAlgorithmsBayes TheoremCanadaComorbidityCost-Benefit AnalysisCross-Sectional StudiesDiabetes MellitusFemaleHumansMaleMiddle AgedRenal DialysisRenal Insufficiency, ChronicChronic kidney diseaseCost-utility analysisDiscrete choice experimentParametric inference

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.