Research Objectives, Statistical Analyses and Interpretation of Health-Related Quality of Life Data in Glioma Research: A Systematic Review
Abstract
:Simple Summary
Abstract
1. Introduction
2. Methods
2.1. Search Strategy
2.2. Selection Criteria
2.3. Data Extraction
3. Results
3.1. Search Results
3.2. HRQoL Instruments
3.3. Research Objectives
3.4. Statistical Methods
3.5. Group and Individual Level
3.6. Minimally Clinical Important Difference
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Characteristics of Included Articles (n = 170) | Articles (n, %) |
Published in 2015–2020 Published in 2009–2014 Published in 2004–2009 Published in 1999–2003 | 87 (51) 54 (32) 15 (9) 14 (8) |
Study design | |
Cross-sectional (i.e., one timepoint only) Observational cohort Observational case-control Interventional randomized Interventional non-randomized | 27 (16) 60 (35) 11 (7) 41 (24) 31 (18) |
Research objectives concerning HRQoL (≥1 objective per article possible, n = 279) | |
Compare mean scores between groups at one time point Association with other outcome (i.e., fatigue, mood) Prediction model: HRQoL as covariate Prediction model: HRQoL as outcome Compare over time in one group: cross-sectional Compare over time in one group: longitudinal Compare mean scores between groups at multiple time points: cross-sectional Compare mean scores between groups at multiple time points: longitudinal | 56 (33) 66 (39) 13 (8) 6 (4) 41 (24) 14 (8) 49 (29) 34 (20) |
1 research objective regarding HRQoL ≥2 research objectives regarding HRQoL | 83 (49) 87 (51) |
MCID mentioned and interpreted in longitudinal studies (n = 138) that compared HRQoL over time in one or more groups | 58 (42) |
Analyses at group level only Analyses at both group and individual level Analyses at individual level only | 146 (86) 18 (10) 6 (4) |
Characteristics of Included Studies (n = 154) | Studies (n, %) |
HRQoL instrument of included studies | |
Generic only Cancer-specific only Brain tumor-specific only Generic and brain tumor-specific Cancer-specific and brain tumor-specific | 26 (17) 15 (10) 37 (24) 6 (4) 70 (45) |
HRQoL instrument used (≥1 instrument per article possible) | |
EORTC QLQ-C30 | 87 (33) |
EORTC QLQ-BN20 FACT-Br SF-36 | 81 (31) 37 (14) 13 (5) |
FACT-G | 9 (3) |
EQ-5D MDASI Other | 12 (5) 10 (4) 13 (5) |
Research Objectives Concerning HRQoL | n | Statistical Test (≥1 Test Per Research Objective Possible) |
---|---|---|
One timepoint | ||
Association of HRQoL with other outcome (i.e., fatigue, mood) | 66 | Spearman/Pearson correlation analyses (n = 27) Regression analysis (n = 21) Linear model (n = 6) Mann–Whitney U/Kruskal–Wallis/Wilcoxon test (n = 4) ANOVA/ANCOVA (n = 2) Unknown (n = 2) Actor-partner independence model (n = 1) Chi square test (n = 1) Bland–Altman (n = 1) Student’s t-test (n = 1) Rank-sum test (n = 1) Bootstrap mediation analyses (n = 1) Descriptive (n = 1) |
Compare mean scores between groups at one time point | 56 | Mann–Whitney U test/Wilcoxon rank sum test/Kruskal–Wallis test (n = 17) Student’s t-test (n = 12) Descriptive (n = 11) ANOVA/ANCOVA (n = 7) Chi-square test (n = 3) Unknown (n = 2) Paired signed-rank test (n = 1) Kolmogorov–Smirnov test (n = 1) |
Prediction model: HRQoL as covariate | 13 | Cox model (n = 11) Regression analysis (n = 2) |
Prediction model: HRQoL as outcome | 9 | Regression analysis (n = 5) Cox model (n = 2) Principal components analysis (n = 1) Unknown (n = 1) |
Multiple timepoints: cross-sectional | ||
Compare mean scores between groups | 49 | Descriptive (n = 16) Unknown (n = 11) Mann–Whitney U/Kruskal–Wallis/Wilcoxon test (n = 9) Student’s t-test (n = 7) Chi-square test (n = 3) ANOVA (n = 2) Reliable change index (n = 1) Area under the curve (n = 1) Fishers exact test (n = 1) Difference-in-difference approach (n = 1) |
Compare HRQoL over time in one group | 41 | Mann–Whitney U/Kruskal–Wallis/Wilcoxon test (n = 16) Student’s t-test (n = 12) Descriptive (n = 9) Unknown (n = 3) Chi-square test (n = 1) ANOVA/ANCOVA (n = 1) |
Multiple time-points: longitudinal | ||
Compare mean scores between groups | 34 | Mixed-effect models (n = 14) Survival analysis (n = 9) Other linear models (n = 5) Joint model (n = 2) Regression analysis (n = 2) Reliable change index (n = 1) GEE models (n = 1) Two-sample proportion test (n = 1) Descriptive (n = 1) |
Compare HRQoL over time in one group | 14 | Descriptive (n = 7) Mixed effects model (n = 6) Regression model (n = 4) Area under the curve (n = 2) Reliable change index (n = 1) Survival analysis (n = 1) |
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Coomans, M.B.; Peeters, M.C.M.; Koekkoek, J.A.F.; Schoones, J.W.; Reijneveld, J.; Taphoorn, M.J.B.; Dirven, L. Research Objectives, Statistical Analyses and Interpretation of Health-Related Quality of Life Data in Glioma Research: A Systematic Review. Cancers 2020, 12, 3502. https://doi.org/10.3390/cancers12123502
Coomans MB, Peeters MCM, Koekkoek JAF, Schoones JW, Reijneveld J, Taphoorn MJB, Dirven L. Research Objectives, Statistical Analyses and Interpretation of Health-Related Quality of Life Data in Glioma Research: A Systematic Review. Cancers. 2020; 12(12):3502. https://doi.org/10.3390/cancers12123502
Chicago/Turabian StyleCoomans, Marijke B., Marthe C.M. Peeters, Johan A.F. Koekkoek, Jan W. Schoones, Jaap Reijneveld, Martin J.B. Taphoorn, and Linda Dirven. 2020. "Research Objectives, Statistical Analyses and Interpretation of Health-Related Quality of Life Data in Glioma Research: A Systematic Review" Cancers 12, no. 12: 3502. https://doi.org/10.3390/cancers12123502