Evidence map›Paper›PMID 27138963›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2016

Refined comorbidity index based on dimensionality of comorbidity for use in studies of health-related quality of life.

Huang-Tz Ou, Chung-Ying Lin, Steven R Erickson, Rajesh Balkrishnan

Abstract read
PubMed Publisher
In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Huang-Tz OuInstitute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan. huangtz@mail.ncku.edu.tw.
Chung-Ying LinDepartment of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
Steven R EricksonDepartment of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA.
Rajesh BalkrishnanDepartment of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo refine two subscales of the health-related quality of life comorbidity index (HRQoL-CI) into a single index measure.

methodsThe 2010 and 2012 Medical Expenditure Panel Surveys were utilized as development and validation datasets, respectively. The least absolute shrinkage and selection operator was applied to select important comorbidity candidates associated with HRQoL. Exploratory factor analysis and confirmatory factor analysis (CFA) were used to assess dimensionality in comorbidity. Statistical weights were derived based on standardized factor loadings from CFA and regression coefficients from the model predicting HRQoL. Prediction errors and model R(2) values were compared between HRQoL-CI and Charlson CI (CCI).

resultsEighteen comorbid conditions were identified. CFA models indicated that the second-order multidimensional comorbidity structure had a better fit to the data than did the first-order unidimensional structure. The predictive performance of the refined scale under a multidimensional structure utilizing statistical weights outperformed the original scale and CCI in terms of average prediction error and R(2) in the prediction models (R(2) values from refined scale model are 0.25, 0.30, and 0.28 versus those from CCI of 0.10, 0.09, and 0.06 for general health, SF-6D, and EQ-5D, respectively).

conclusionThe dimensionality of comorbidity and the weight scheme significantly improved the performance of the refined HRQoL-CI. The refined single HRQoL-CI measure appears to be an appropriate and valid instrument specific for risk adjustment in studies of HRQoL. Future research that validates the refined scales for different cultures, age groups, and healthcare settings is warranted.

Indexed as

Sickness Impact ProfileAdolescentAdultAgedComorbidityFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultComorbidity indexDimensionalityFactor analysisHealth-related Quality of lifeLeast absolute shrinkage and selection operatorRisk prediction model

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.