Annika Dohmen, Alexander Obbarius, Milan Kock, Sandra Nolte, Christopher J Sidey-Gibbons, Jose M Valderas, Jens Rohde, Kathrin Rieger, Felix Fischer, Ulrich Keilholz, Matthias Rose, Christoph Paul Klapproth
{"title":"在一项横断面研究中,EORTC QLU-C10D 比 PROPr 和 EQ-5D-5L 更能区分癌症患者和普通人群。","authors":"Annika Dohmen, Alexander Obbarius, Milan Kock, Sandra Nolte, Christopher J Sidey-Gibbons, Jose M Valderas, Jens Rohde, Kathrin Rieger, Felix Fischer, Ulrich Keilholz, Matthias Rose, Christoph Paul Klapproth","doi":"10.1016/j.jclinepi.2024.111592","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the EORTC QLU-C10D, the PROMIS Preference Score (PROPr) and the EQ-5D-5L, yield different HSU values due to different modelling and different underlying descriptive scales. E.g. the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population.</p><p><strong>Study design and setting: </strong>EORTC QLU-C10D, PROPr, and EQ-5D-5L scores were obtained for a convenience sample of 484 outpatients of the Department of Oncology, Charité - Universitätsmedizin Berlin, Germany. Convergent and known-groups validity were assessed using Pearson's correlation, intraclass correlation coefficients. We assessed each descriptive dimension score's discriminatory power and compared them to those of the general population (n>1,000) using effect size (ES; Cohen's d) and area under the curve (AUC).</p><p><strong>Results: </strong>Mean scores of QLU-C10D (0.64; 95%CI 0.62-0.67), PROPr (0.38; 95%CI 0.36-0.40), and EQ-5D-5L (0.72; 95%CI 0.70-0.75) differed significantly, irrespective of sociodemographic factors, condition, or treatment. Conceptually similar descriptive scores as obtained from the HSU instruments showed varying degrees of discrimination in terms of ES and AUC between patients and the general population. The QLU-C10D and its dimensions showed the largest ES and AUC.</p><p><strong>Conclusion: </strong>The QLU-C10D and its domains distinguished best between health states of the two populations, compared to the PROPr and EQ-5D-5L. As the EORTC QLQ-C30 is widely used in clinical practice, its data is available for economic evaluation.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111592"},"PeriodicalIF":7.3000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The EORTC QLU-C10D distinguished better between cancer patients and the general population than PROPr and EQ-5D-5L in a cross-sectional study.\",\"authors\":\"Annika Dohmen, Alexander Obbarius, Milan Kock, Sandra Nolte, Christopher J Sidey-Gibbons, Jose M Valderas, Jens Rohde, Kathrin Rieger, Felix Fischer, Ulrich Keilholz, Matthias Rose, Christoph Paul Klapproth\",\"doi\":\"10.1016/j.jclinepi.2024.111592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the EORTC QLU-C10D, the PROMIS Preference Score (PROPr) and the EQ-5D-5L, yield different HSU values due to different modelling and different underlying descriptive scales. E.g. the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population.</p><p><strong>Study design and setting: </strong>EORTC QLU-C10D, PROPr, and EQ-5D-5L scores were obtained for a convenience sample of 484 outpatients of the Department of Oncology, Charité - Universitätsmedizin Berlin, Germany. Convergent and known-groups validity were assessed using Pearson's correlation, intraclass correlation coefficients. We assessed each descriptive dimension score's discriminatory power and compared them to those of the general population (n>1,000) using effect size (ES; Cohen's d) and area under the curve (AUC).</p><p><strong>Results: </strong>Mean scores of QLU-C10D (0.64; 95%CI 0.62-0.67), PROPr (0.38; 95%CI 0.36-0.40), and EQ-5D-5L (0.72; 95%CI 0.70-0.75) differed significantly, irrespective of sociodemographic factors, condition, or treatment. Conceptually similar descriptive scores as obtained from the HSU instruments showed varying degrees of discrimination in terms of ES and AUC between patients and the general population. The QLU-C10D and its dimensions showed the largest ES and AUC.</p><p><strong>Conclusion: </strong>The QLU-C10D and its domains distinguished best between health states of the two populations, compared to the PROPr and EQ-5D-5L. As the EORTC QLQ-C30 is widely used in clinical practice, its data is available for economic evaluation.</p>\",\"PeriodicalId\":51079,\"journal\":{\"name\":\"Journal of Clinical Epidemiology\",\"volume\":\" \",\"pages\":\"111592\"},\"PeriodicalIF\":7.3000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Clinical Epidemiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jclinepi.2024.111592\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jclinepi.2024.111592","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
The EORTC QLU-C10D distinguished better between cancer patients and the general population than PROPr and EQ-5D-5L in a cross-sectional study.
Objective: Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the EORTC QLU-C10D, the PROMIS Preference Score (PROPr) and the EQ-5D-5L, yield different HSU values due to different modelling and different underlying descriptive scales. E.g. the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population.
Study design and setting: EORTC QLU-C10D, PROPr, and EQ-5D-5L scores were obtained for a convenience sample of 484 outpatients of the Department of Oncology, Charité - Universitätsmedizin Berlin, Germany. Convergent and known-groups validity were assessed using Pearson's correlation, intraclass correlation coefficients. We assessed each descriptive dimension score's discriminatory power and compared them to those of the general population (n>1,000) using effect size (ES; Cohen's d) and area under the curve (AUC).
Results: Mean scores of QLU-C10D (0.64; 95%CI 0.62-0.67), PROPr (0.38; 95%CI 0.36-0.40), and EQ-5D-5L (0.72; 95%CI 0.70-0.75) differed significantly, irrespective of sociodemographic factors, condition, or treatment. Conceptually similar descriptive scores as obtained from the HSU instruments showed varying degrees of discrimination in terms of ES and AUC between patients and the general population. The QLU-C10D and its dimensions showed the largest ES and AUC.
Conclusion: The QLU-C10D and its domains distinguished best between health states of the two populations, compared to the PROPr and EQ-5D-5L. As the EORTC QLQ-C30 is widely used in clinical practice, its data is available for economic evaluation.
期刊介绍:
The Journal of Clinical Epidemiology strives to enhance the quality of clinical and patient-oriented healthcare research by advancing and applying innovative methods in conducting, presenting, synthesizing, disseminating, and translating research results into optimal clinical practice. Special emphasis is placed on training new generations of scientists and clinical practice leaders.