All Articles
View
Split Viewer
Korean J Orthod 2024; 54(6): 374-391 https://doi.org/10.4041/kjod24.051
First Published Date July 26, 2024, Publication Date November 25, 2024
Copyright © The Korean Association of Orthodontists.
Samer Mheissena 
, Haris Khanb , Mays Aldandanc , Despina Koletsid,e
aPrivate Practice, Damascus, Syria
bCMH Institute of Dentistry Lahore, National University of Medical Sciences, Lahore, Pakistan
cPrivate Practice, Daraa, Syria
dClinic of Orthodontics and Pediatric Dentistry, Center of Dental Medicine, University of Zurich, Zurich, Switzerland
eMeta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA
Correspondence to:Samer Mheissen.
Specialist Orthodontist, Private Practice, Damascus 00963, Syria.
Tel +963-15833179 e-mail Mheissen@yahoo.com
How to cite this article: Mheissen S, Khan H, Aldandan M, Koletsi D. Unaccounted clustering assumptions still compromise inferences in cluster randomized trials in orthodontic research. Korean J Orthod 2024;54(6):374-391. https://doi.org/10.4041/kjod24.051
Objective: This meta-epidemiological study aimed to determine whether optimal sample size calculation was applied in orthodontic cluster randomized trials (CRTs). Methods: Orthodontic randomized clinical trials with a cluster design, published between January 1, 2017 to December 31, 2023, in leading orthodontic journals were sourced. Study selection was undertaken by two independent authors. The study characteristics and variables required for sample size calculation were also extracted by the authors. The design effect for each trial was calculated using an intra-cluster correlation coefficient of 0.1 and the number of teeth in each cluster to recalculate the sample size. Descriptive statistics for the study characteristics, summary values for the design effect, and sample sizes were provided. Results: One-hundred and five CRTs were deemed eligible for inclusion. Of these, 100 reported sample size calculation. Nine CRTs (9.0%) did not report any effect measures for the sample size calculation, and a few did not report any power assumptions or significance levels or thresholds. Regarding the specific variables for the cluster design, only one CRT reported a design effect and adjusted the sample size accordingly. Recalculations indicated that the sample size of orthodontic CRTs should be increased by a median of 50% to maintain the same statistical power and significance level. Conclusions: Sample size calculations in orthodontic cluster trials were suboptimal. Greater awareness of the cluster design and variables is required to calculate the sample size adequately, to reduce the practice of underpowered studies.
Keywords: Cluster, Trials, Orthodontic, Cluster randomized trials
Korean J Orthod 2024; 54(6): 374-391 https://doi.org/10.4041/kjod24.051
First Published Date July 26, 2024, Publication Date November 25, 2024
Copyright © The Korean Association of Orthodontists.
Samer Mheissena , Haris Khanb , Mays Aldandanc , Despina Koletsid,e
aPrivate Practice, Damascus, Syria
bCMH Institute of Dentistry Lahore, National University of Medical Sciences, Lahore, Pakistan
cPrivate Practice, Daraa, Syria
dClinic of Orthodontics and Pediatric Dentistry, Center of Dental Medicine, University of Zurich, Zurich, Switzerland
eMeta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA
Correspondence to:Samer Mheissen.
Specialist Orthodontist, Private Practice, Damascus 00963, Syria.
Tel +963-15833179 e-mail Mheissen@yahoo.com
How to cite this article: Mheissen S, Khan H, Aldandan M, Koletsi D. Unaccounted clustering assumptions still compromise inferences in cluster randomized trials in orthodontic research. Korean J Orthod 2024;54(6):374-391. https://doi.org/10.4041/kjod24.051
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Objective: This meta-epidemiological study aimed to determine whether optimal sample size calculation was applied in orthodontic cluster randomized trials (CRTs). Methods: Orthodontic randomized clinical trials with a cluster design, published between January 1, 2017 to December 31, 2023, in leading orthodontic journals were sourced. Study selection was undertaken by two independent authors. The study characteristics and variables required for sample size calculation were also extracted by the authors. The design effect for each trial was calculated using an intra-cluster correlation coefficient of 0.1 and the number of teeth in each cluster to recalculate the sample size. Descriptive statistics for the study characteristics, summary values for the design effect, and sample sizes were provided. Results: One-hundred and five CRTs were deemed eligible for inclusion. Of these, 100 reported sample size calculation. Nine CRTs (9.0%) did not report any effect measures for the sample size calculation, and a few did not report any power assumptions or significance levels or thresholds. Regarding the specific variables for the cluster design, only one CRT reported a design effect and adjusted the sample size accordingly. Recalculations indicated that the sample size of orthodontic CRTs should be increased by a median of 50% to maintain the same statistical power and significance level. Conclusions: Sample size calculations in orthodontic cluster trials were suboptimal. Greater awareness of the cluster design and variables is required to calculate the sample size adequately, to reduce the practice of underpowered studies.
Keywords: Cluster, Trials, Orthodontic, Cluster randomized trials
Table 1 . Characteristics of included cluster randomized trials according to whether sample size calculations were reported.
| Characteristic | Overall (n = 105) | No (n = 5) | Yes (n = 100) |
|---|---|---|---|
| Authors’ number | 4 (3, 6) | 4 (2, 5) | 4 (3, 6) |
| Continent | |||
| Americas | 18 (17.1) | 0 (0) | 18 (18.0) |
| Asia/others | 39 (37.1) | 2 (40.0) | 37 (37.0) |
| Europe | 48 (45.7) | 3 (60.0) | 45 (45.0) |
| Journal/book | |||
| AJODO | 31 (29.5) | 2 (40.0) | 29 (29.0) |
| AO | 35 (33.3) | 1 (20.0) | 34 (34.0) |
| EJO | 27 (25.7) | 2 (40.0) | 25 (25.0) |
| KJO | 5 (4.8) | 0 (0) | 5 (5.0) |
| OCR | 1 (1.0) | 0 (0) | 1 (1.0) |
| PIO | 6 (5.7) | 0 (0) | 6 (6.0) |
| Publication year | |||
| 2017 | 8 (7.6) | 2 (40.0) | 6 (6.0) |
| 2018 | 18 (17.1) | 3 (60.0) | 15 (15.0) |
| 2019 | 13 (12.4) | 0 (0) | 13 (13.0) |
| 2020 | 15 (14.3) | 0 (0) | 15 (15.0) |
| 2021 | 20 (19.0) | 0 (0) | 20 (20.0) |
| 2022 | 14 (13.3) | 0 (0) | 14 (14.0) |
| 2023 | 17 (16.2) | 0 (0) | 17 (17.0) |
| Centers | |||
| Multi | 6 (5.7) | 1 (20.0) | 5 (5.0) |
| Single | 99 (94.3) | 4 (80.0) | 95 (95.0) |
| Number of arms | |||
| 2 | 84 (80.0) | 3 (60.0) | 81 (81.0) |
| 3 | 15 (14.3) | 2 (40.0) | 13 (13.0) |
| 4 | 6 (5.7) | 0 (0) | 6 (6.0) |
| Design | |||
| Crossover | 2 (1.9) | 0 (0) | 2 (2.0) |
| Parallel | 76 (72.4) | 4 (80.0) | 72 (72.0) |
| Split mouth | 27 (25.7) | 1 (20.0) | 26 (26.0) |
| Protocol registration | |||
| Yes | 58 (55.2) | 1 (20.0) | 57 (57.0) |
| No | 14 (13.3) | 0 (0) | 14 (14.0) |
| Not reported | 33 (31.4) | 4 (80.0) | 29 (29.0) |
Values are presented as median (interquartile range) or number (%)..
AJODO, American Journal of Orthodontics and Dentofacial Orthopedics; AO, The Angle Orthodontist; EJO, European Journal of Orthodontics; KJO, Korean Journal of Orthodontics; OCR, Orthodontics & Craniofacial Research; PIO, Progress in Orthodontics..
Table 2 . Reporting of sample size calculation in cluster randomized trials when it was feasible.
| Item | n = 100 |
|---|---|
| Effect measure | |
| Effect size | 31 (31.0) |
| Mean difference | 44 (44.0) |
| Relative risk reduction | 4 (4.0) |
| Risk difference | 12 (12.0) |
| ni | 9 (9.0) |
| Value of the effect measure | |
| Effect size | 0.50 (0.43, 0.80) |
| Mean difference | 1.04 (0.50, 2.00) |
| Relative risk reduction | 0.15 (0.08, 0.20) |
| Risk difference | 0.25 (0.20, 0.66) |
| Level of significance (α) | |
| 0.001 | 1 (1.0) |
| 0.01 | 3 (3.0) |
| 0.0125 | 1 (1.0) |
| 0.025 | 1 (1.0) |
| 0.05 | 86 (86.0) |
| Not reported | 8 (8.0) |
| Power | |
| 80% | 60 (60.0) |
| 81–85% | 11 (11.0) |
| 90% | 19 (19.0) |
| > 90% | 8 (8.0) |
| Not reported | 2 (2.0) |
| Accounting for cluster effect | |
| Yes | 1 (1.0) |
| No | 99 (99.0) |
| ICC | |
| None | 100 (100.0) |
Values are presented as number (%) or median (interquartile range)..
ICC, intra-cluster correlation coefficient; ni, no information..
Table 3 . Recalculation of sample size and sensitivity analysis for CRT with parallel design.
| Re-calculation (100 CRTs) | Sensitivity analysis (72 CRTs) | |
|---|---|---|
| Design effect | 1.5 (1.3, 1.9) | 1.5 (1.3, 2.2) |
| Number of individuals per cluster | 6 (4, 10) | 6 (4, 13) |
| Number of clusters | 18.5 (12.5, 27.0) | 18.0 (14.0, 24.5) |
| Sample size in the paper | 40 (26.5, 59.0) | 40 (30.0, 57.5) |
| Number of required participants | 67.6 (36.2, 108.0) | 68.5 (36.9, 114.0) |
| Percentage | 50% (30%, 90%) | 50% (30%, 120%) |
Values are presented as median (interquartile range)..
CRTs, cluster randomized trials..
PDF
Standard view
Export citation
Share 
Download
Download
