To the Editor:
As readers of The Lancet Regional Health – Western Pacific, along with the fact that measles outbreaks have been warned of perfect storm of conditions for within 2022 by UNICEF and WHO, we pay a significant interest to the content of the paper entitled “Measles outbreak in the Philippines: Epidemiological and clinical characteristics of hospitalized children, 2016–2019” published earlier within the same journal.1,2 However, upon reproducing the results, we suspect that the authors has made several computational errors.
First, in Table 1, the authors did not state the referenced group within two characteristics, vitamin A supplementation and clinical information. This prevents readers from understanding the related context of the odds ratios (ORs), while also obstructs us from re-evaluating the calculation of the crude ORs within these sub-groups.
Table 1.
Variable | Reported number and percentages in the original article | Calculated percentages (if different) by the authors of this letter | Reported crude ORS within the original article |
Re-calculated crude ORs by the authors of this letter |
||
---|---|---|---|---|---|---|
OR (95% CI) | P value | OR (95% CI) | P value | |||
Age group (months) | ||||||
<3 | 1.07 (0.29–3.90) | 0.919 | 0.87 (0.21–3.66) | 0.926 | ||
3–5 | 1.82 (1.13–2.93) | 0.013 | 1.82 (1.13–2.93) | 0.016 | ||
6–8 | 1.29 (0.83–2.01) | 0.256 | 1.29 (0.82–2.02) | 0.261 | ||
9–11 | 1.14 (0.67–1.94) | 0.622 | 1.13 (0.66–1.93) | 0.648 | ||
12–24 | 1.72 (1.12–2.66) | 0.014 | 1.72 (1.12–1.66) | 0.015 | ||
>24 | Ref | Ref | ||||
Sex | ||||||
Male | Ref | Ref | ||||
Female | 0.96 (0.71–1.29) | 0.765 | 0.95 (0.71–1.29) | 0.761 | ||
Region of residence | ||||||
In NCR | Ref | Ref | ||||
Outside NCR | 1.55 (1.04–2.31) | 0.032 | 1.53 (1.02-2.29) | 0.046 | ||
Admission timing | ||||||
Non-epidemic | Ref | Ref | ||||
Epidemic | 3.52 (1.22–10.20) | 0.020 | 4.09 (1.30–12.88) | 0.003 | ||
Vaccine status | ||||||
Vaccinated (≥1 doses) | Ref | Ref | ||||
Non-vaccinated | 1.75 (1.05–2.93) | 0.032 | 1.80 (1.07–3.03) | 0.019 | ||
Duration between fever onset and admission (days) | ||||||
0 – 3d | 48 (239) | 48 (2.3) | Ref | Ref | ||
4 – 6d | 1.44 (1.01–2.05) | 0.044 | 1.44 (1.01–2.06) | 0.04 | ||
7–14d | 2.45 (1.58–3.78) | <0.001 | 2.44 (1.57–3.78) | <0.001 | ||
>14d | 1.81 (0.35–9.53) | 0.482 | 1.24 (0.17–9.24) | 0.759 | ||
Duration between rash onset and admission (days) | ||||||
0 –3d | Ref | Ref | ||||
4 –6d | 1.88 (1.25–2.81) | 0.002 | 1.85 (1.24–2.78) | 0.005 | ||
7–14d | 3.84 (2.04–7.23) | <0.001 | 3.70 (1.94–7.05) | <0.001 | ||
>14d | 1.03 (0.06–17.19) | 0.986 | 0.00 (0.00-inf) | 0.629 |
Apart from the two characteristics, using the package epitools v0.5–10.1 available within R statistical software v4.1.3, we were able to re-calculate 15 remaining ORs using the unconditional maximum likelihood estimation (Wald) method, with the p-value calculated using the mid-p method.3,4 Among them, 6 (40%) are significantly different from the original results (more information can be found in the highlighted details in the attached table below). Besides, there is also one typographical error in the calculation of the percentage of children that have an interval of 0–3 days between fever onset and hospital admission.
In this letter, we do not investigate the calculation of the adjusted ORs since the detailed information of the patients involved in the research are not publicly available.
From the provided information, we encourage the authors, reviewers and editors to revisit and/or further elaborate on the methods for the calculation and conclusion of any OR within the paper, and make changes wherever applicable.
Yours sincerely.
Contributors
H.A.N: Conceptualisation, Formal Analysis, Supervision, Writing – Original Draft Preparation; N.T.H.P: Formal Analysis, Validation, Writing – Review & Editing; P.H.P: Supervision, Validation, Writing – Review & Editing; M.H.T: Formal Analysis, Writing – Review & Editing; H.N.V: Formal Analysis, Writing – Review & Editing.
Availability of data and materials
The information analysed within this letter are available in the GitHub repository, https://github.com/hoanganhngo610/recalculate-ORs-measles-Philippines-LRHWP.
Declaration of interests
The authors declare that they have no conflict of interest regarding the publication of this letter to the editor.
Acknowledgments
Funding: No specific grant from funding agencies in the public, commercial or not-for-profit sectors supported the publication of this letter to the editor.
References
- 1.World Health Organization UNICEF and WHO warn of perfect storm of conditions for measles outbreaks, affecting children. https://www.who.int/news/item/27-04-2022-unicef-and-who-warn-of%2d%2dperfect-storm%2d%2dof-conditions-for-measles-outbreaks%2d%2daffecting-children Available online:
- 2.Domai F.M., Agrupis K.A., Han S.M., et al. Measles outbreak in the Philippines: Epidemiological and clinical characteristics of hospitalized children, 2016-2019. Lancet Reg Health West Pacific. 2022;19:100334. doi: 10.1016/j.lanwpc.2021.100334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.R Core Team . R Foundation for Statistical Computing; Vienna, Austria: 2022. R: A language an environment for statistical computing.https://www.R-project.org/ URL. [Google Scholar]
- 4.Aragon T.J. Epitools: epidemiology tools. 2020. https://CRAN.R-project.org/package=epitools R Package version 0.5-10.1. URL.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The information analysed within this letter are available in the GitHub repository, https://github.com/hoanganhngo610/recalculate-ORs-measles-Philippines-LRHWP.