Evidence map›Paper›PMID 36463253›Full record

ArticleScientific reports2022

Mapping algorithms for predicting EuroQol-5D-3L utilities from the assessment test of chronic obstructive pulmonary disease.

Chun-Hsiang Yu, Sheng-Mao Chang, Chih-Hui Hsu, Sheng-Han Tsai, Xin-Min Liao, Chang-Wei Chen, Ching-Hsiung Lin, Jung-Der Wang, Tzuen-Ren Hsiue, Chiung-Zuei Chen

Abstract read
In one paragraph

Article in Scientific reports, 2022. 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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  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

10 authors.

Chun-Hsiang YuDivision of Pulmonary Medicine, Department of Internal Medicine, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, No. 138 Sheng-Li Road, 704, Tainan, Taiwan.
Sheng-Mao ChangDepartment of Statistics, National Taipei University, New Taipei, Taiwan.
Chih-Hui HsuClinical Medicine Research Center, National Cheng Kung University Hospital, Tainan, Taiwan.
Sheng-Han TsaiDivision of General Medicine, Department of Internal Medicine, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, Tainan, Taiwan.
Xin-Min LiaoDivision of Pulmonary Medicine, Department of Internal Medicine, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, No. 138 Sheng-Li Road, 704, Tainan, Taiwan.
Chang-Wei ChenDivision of Pulmonary Medicine, Department of Internal Medicine, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, No. 138 Sheng-Li Road, 704, Tainan, Taiwan.
Ching-Hsiung LinDivision of Chest Medicine, Department of Internal Medicine, Changhua Christian Hospital, Changhua, Taiwan.
Jung-Der WangDepartment of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Tzuen-Ren HsiueDivision of Pulmonary Medicine, Department of Internal Medicine, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, No. 138 Sheng-Li Road, 704, Tainan, Taiwan.
Chiung-Zuei ChenDivision of Pulmonary Medicine, Department of Internal Medicine, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, No. 138 Sheng-Li Road, 704, Tainan, Taiwan. chen96@mail.ncku.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To predict 3-Level version of European Quality of Life-5 Dimensions (EQ-5D-3L) questionnaire utility from the chronic obstructive pulmonary disease (COPD) assessment test (CAT), the study attempts to collect EQ-5D-3L and CAT data from COPD patients. Response mapping under a backward elimination procedure was used for EQ-5D score predictions from CAT. A multinomial logistic regression (MLR) model was used to identify the association between the score and the covariates. Afterwards, the predicted scores were transformed into the utility. The developed formula was compared with ordinary least squares (OLS) regression models and models using Mean Rank Method (MRM). The MLR models performed as well as other models according to mean absolute error (MAE) and root mean squared error (RMSE) evaluations. Besides, the overestimation for low utility patients (utility ≤ 0.6) and underestimation for near health (utility > 0.9) in the OLS method was improved through the means of the MLR model based on bubble chart analysis. In conclusion, response mapping with the MLR model led to performance comparable to the OLS and MRM models for predicting EQ-5D utility from CAT data. Additionally, the bubble charts analysis revealed that the model constructed in this study and MRM could be a better predictive model.

Indexed as

Pulmonary Disease, Chronic ObstructiveQuality of LifeAlgorithmsHumansLogistic ModelsResearch

Identifiers

PMID36463253
PMCPMC9719462

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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.