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Schneider S, Dos Reis RCP, Gottselig MMF, Fisch P, Knauth DR, Vigo Á. Clayton copula for survival data with dependent censoring: An application to a tuberculosis treatment adherence data. Stat Med 2023; 42:4057-4081. [PMID: 37720988 DOI: 10.1002/sim.9858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 06/30/2023] [Accepted: 07/10/2023] [Indexed: 09/19/2023]
Abstract
Ignoring the presence of dependent censoring in data analysis can lead to biased estimates, for example, not considering the effect of abandonment of the tuberculosis treatment may influence inferences about the cure probability. In order to assess the relationship between cure and abandonment outcomes, we propose a copula Bayesian approach. Therefore, the main objective of this work is to introduce a Bayesian survival regression model, capable of taking into account the dependent censoring in the adjustment. So, this proposed approach is based on Clayton's copula, to provide the relation between survival and dependent censoring times. In addition, the Weibull and the piecewise exponential marginal distributions are considered in order to fit the times. A simulation study is carried out to perform comparisons between different scenarios of dependence, different specifications of prior distributions, and comparisons with the maximum likelihood inference. Finally, we apply the proposed approach to a tuberculosis treatment adherence dataset of an HIV cohort from Alvorada-RS, Brazil. Results show that cure and abandonment outcomes are negatively correlated, that is, as long as the chance of abandoning the treatment increases, the chance of tuberculosis cure decreases.
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Affiliation(s)
- Silvana Schneider
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Graduate Program in Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Rodrigo Citton P Dos Reis
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Maicon M F Gottselig
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Patrícia Fisch
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Epidemiology Department, Hospital Nossa Senhora da Conceição, Porto Alegre, Rio Grande do Sul, Brazil
| | - Daniela Riva Knauth
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Álvaro Vigo
- Department of Statistics, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Graduate Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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Zeng C, Mitnick CD, Hewison C, Bastard M, Khan P, Seung KJ, Rich ML, Atwood S, Melikyan N, Morchiladze N, Khachatryan N, Khmyz M, Restrepo CG, Salahuddin N, Kazmi E, Dahri AA, Ahmed S, Varaine F, Vilbrun SC, Oyewusi L, Gelin A, Tintaya K, Yeraliyeva LT, Hamid S, Khan U, Huerga H, Franke MF. Concordance of three approaches for operationalizing outcome definitions for multidrug-resistant TB. Int J Tuberc Lung Dis 2023; 27:34-40. [PMID: 36853128 PMCID: PMC9879081 DOI: 10.5588/ijtld.22.0324] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 07/29/2022] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND: The WHO provides standardized outcome definitions for rifampicin-resistant (RR) and multidrug-resistant (MDR) TB. However, operationalizing these definitions can be challenging in some clinical settings, and incorrect classification may generate bias in reporting and research. Outcomes calculated by algorithms can increase standardization and be adapted to suit the research question. We evaluated concordance between clinician-assigned treatment outcomes and outcomes calculated based on one of two standardized algorithms, one which identified failure at its earliest possible recurrence (i.e., failure-dominant algorithm), and one which calculated the outcome based on culture results at the end of treatment, regardless of early occurrence of failure (i.e., success-dominant algorithm).METHODS: Among 2,525 patients enrolled in the multi-country endTB observational study, we calculated the frequencies of concordance using cross-tabulations of clinician-assigned and algorithm-assigned outcomes. We summarized the common discrepancies.RESULTS: Treatment success calculated by algorithms had high concordance with treatment success assigned by clinicians (95.8 and 97.7% for failure-dominant and success-dominant algorithms, respectively). The frequency and pattern of the most common discrepancies varied by country.CONCLUSION: High concordance was found between clinician-assigned and algorithm-assigned outcomes. Heterogeneity in discrepancies across settings suggests that using algorithms to calculate outcomes may minimize bias.
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Affiliation(s)
- C Zeng
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
| | - C D Mitnick
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA, Partners In Health (PIH), Boston, MA, USA, Division of Global Health Equity, Brigham and Women´s Hospital, Boston, MA, USA
| | - C Hewison
- Medical Department, Médecins Sans Frontières (MSF), Paris, France
| | - M Bastard
- Field Epidemiology Department, Epicentre, Paris, France
| | - P Khan
- Interactive Research and Development Global, Singapore, Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - K J Seung
- Partners In Health (PIH), Boston, MA, USA, Division of Global Health Equity, Brigham and Women´s Hospital, Boston, MA, USA
| | - M L Rich
- Partners In Health (PIH), Boston, MA, USA, Division of Global Health Equity, Brigham and Women´s Hospital, Boston, MA, USA
| | - S Atwood
- Division of Global Health Equity, Brigham and Women´s Hospital, Boston, MA, USA
| | - N Melikyan
- Field Epidemiology Department, Epicentre, Paris, France
| | | | | | | | | | - N Salahuddin
- Indus Hospital & Health Network (IHHN), Karachi, Pakistan
| | - E Kazmi
- Center for Disease Control and Prevention, Directorate General Health Services, Sindh, Pakistan
| | - A A Dahri
- Center for Disease Control and Prevention, Directorate General Health Services, Sindh, Pakistan
| | - S Ahmed
- Interactive Research and Development, Karachi, Pakistan
| | - F Varaine
- Medical Department, Médecins Sans Frontières (MSF), Paris, France
| | - S C Vilbrun
- Haitian Group for the Study of Kaposi´s Sarcoma and Opportunistic Infections (GHESKIO), Port-au-Prince, Haiti
| | | | - A Gelin
- Zanmi Lasante, Port-au-Prince, Haiti
| | - K Tintaya
- PIH/Socios En Salud Sucursal Peru, Lima, Peru
| | - L T Yeraliyeva
- National Scientific Center of Phthisiopulmonology of the Ministry of Health of the Republic of Kazakhstan, Kazakhstan
| | - S Hamid
- Bishoftu General Hospital, Bishoftu, Ethiopia
| | - U Khan
- Interactive Research and Development Global, Singapore
| | - H Huerga
- Field Epidemiology Department, Epicentre, Paris, France
| | - M F Franke
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
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Ngari MM, Schmitz S, Maronga C, Mramba LK, Vaillant M. A systematic review of the quality of conduct and reporting of survival analyses of tuberculosis outcomes in Africa. BMC Med Res Methodol 2021; 21:89. [PMID: 33906605 PMCID: PMC8080365 DOI: 10.1186/s12874-021-01280-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 04/12/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Survival analyses methods (SAMs) are central to analysing time-to-event outcomes. Appropriate application and reporting of such methods are important to ensure correct interpretation of the data. In this study, we systematically review the application and reporting of SAMs in studies of tuberculosis (TB) patients in Africa. It is the first review to assess the application and reporting of SAMs in this context. METHODS Systematic review of studies involving TB patients from Africa published between January 2010 and April 2020 in English language. Studies were eligible if they reported use of SAMs. Application and reporting of SAMs were evaluated based on seven author-defined criteria. RESULTS Seventy-six studies were included with patient numbers ranging from 56 to 182,890. Forty-three (57%) studies involved a statistician/epidemiologist. The number of published papers per year applying SAMs increased from two in 2010 to 18 in 2019 (P = 0.004). Sample size estimation was not reported by 67 (88%) studies. A total of 22 (29%) studies did not report summary follow-up time. The survival function was commonly presented using Kaplan-Meier survival curves (n = 51, (67%) studies) and group comparisons were performed using log-rank tests (n = 44, (58%) studies). Sixty seven (91%), 3 (4.1%) and 4 (5.4%) studies reported Cox proportional hazard, competing risk and parametric survival regression models, respectively. A total of 37 (49%) studies had hierarchical clustering, of which 28 (76%) did not adjust for the clustering in the analysis. Reporting was adequate among 4.0, 1.3 and 6.6% studies for sample size estimation, plotting of survival curves and test of survival regression underlying assumptions, respectively. Forty-five (59%), 52 (68%) and 73 (96%) studies adequately reported comparison of survival curves, follow-up time and measures of effect, respectively. CONCLUSION The quality of reporting survival analyses remains inadequate despite its increasing application. Because similar reporting deficiencies may be common in other diseases in low- and middle-income countries, reporting guidelines, additional training, and more capacity building are needed along with more vigilance by reviewers and journal editors.
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Affiliation(s)
- Moses M Ngari
- KEMRI/Wellcome Trust Research Programme, P.O Box 230, Kilifi, 80108, Kenya.
- The Childhood Acute Illness & Nutrition Network (CHAIN), Nairobi, Kenya.
- Competence Center for Methodology and Statistics, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg.
| | - Susanne Schmitz
- Competence Center for Methodology and Statistics, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Christopher Maronga
- KEMRI/Wellcome Trust Research Programme, P.O Box 230, Kilifi, 80108, Kenya
- The Childhood Acute Illness & Nutrition Network (CHAIN), Nairobi, Kenya
| | - Lazarus K Mramba
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas, USA
| | - Michel Vaillant
- Competence Center for Methodology and Statistics, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
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