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Cheung YB, Ma X, Lam KF, Yung CF, Milligan P. Estimation of trajectory of protective efficacy in infectious disease prevention trials using recurrent event times. Stat Med 2024; 43:1759-1773. [PMID: 38396234 DOI: 10.1002/sim.10049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 12/20/2023] [Accepted: 02/14/2024] [Indexed: 02/25/2024]
Abstract
In studies of infectious disease prevention, the level of protective efficacy of medicinal products such as vaccines and prophylactic drugs tends to vary over time. Many products require administration of multiple doses at scheduled times, as opposed to one-off or continual intervention. Accurate information on the trajectory of the level of protective efficacy over time facilitates informed clinical recommendations and implementation strategies, for example, with respect to the timing of administration of the doses. Based on concepts from pharmacokinetic and pharmacodynamic modeling, we propose a non-linear function for modeling the trajectory after each dose. The cumulative effect of multiple doses of the products is captured by an additive series of the function. The model has the advantages of parsimony and interpretability, while remaining flexible in capturing features of the trajectories. We incorporate this series into the Andersen-Gill model for analysis of recurrent event time data and compare it with alternative parametric and non-parametric functions. We use data on clinical malaria disease episodes from a trial of four doses of an anti-malarial drug combination for chemoprevention to illustrate, and evaluate the performance of the methods using simulation. The proposed method out-performed the alternatives in the analysis of real data in terms of Akaike and Bayesian Information Criterion. It also accurately captured the features of the protective efficacy trajectory such as the area under curve in simulations. The proposed method has strong potential to enhance the evaluation of disease prevention measures and improve their implementation strategies.
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Affiliation(s)
- Yin Bun Cheung
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
- Programme in Health Services & Systems Research, Duke-NUS Medical School, Singapore, Singapore
- Tampere Center for Child, Adolescent and Maternal Health Research, Tampere University, Tampere, Finland
| | - Xiangmei Ma
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
| | - K F Lam
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
- Department of Statistics and Actuarial Science, University of Hong Kong, Hong Kong, China
| | - Chee Fu Yung
- Infectious Disease Service, KK Women's and Children's Hospital, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Academic Medicine Department, Duke-NUS Medical School, Singapore, Singapore
| | - Paul Milligan
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
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Cheung YB, Ma X, Lam KF, Yung CF, Milligan P. Modelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies. J Biopharm Stat 2023; 33:220-233. [PMID: 35946934 DOI: 10.1080/10543406.2022.2108826] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Abstract
Protective efficacy of vaccines and pharmaceutical products for prevention of infectious diseases usually vary over time. Information on the trajectory of the level of protection is valuable. We consider a parsimonious, non-linear and non-monotonic function for modelling time-varying intervention effects and compare it with several alternatives. The cumulative effects of multiple doses of intervention over time can be captured by an additive series of the function. We apply it to the Andersen-Gill model for analysis of recurrent time-to-event data. We re-analyze data from a trial of intermittent preventive treatment for malaria to illustrate and evaluate the method by simulation.
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Affiliation(s)
- Yin Bun Cheung
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore.,Programme in Health Services & Systems Research, Duke-NUS Medical School, Singapore.,Tampere Center for Child, Adolescent and Maternal Health Research, Tampere University, Tampere, Finland
| | - Xiangmei Ma
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore
| | - K F Lam
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore.,Department of Statistics and Actuarial Science, University of Hong Kong, Hong Kong, Pok Fu Lam, China
| | - Chee Fu Yung
- Infectious Disease Service, KK Women's and Children's Hospital, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.,Academic Medicine Department, Duke-NUS Medical School, Singapore
| | - Paul Milligan
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
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Cairns M, Barry A, Zongo I, Sagara I, Yerbanga SR, Diarra M, Zoungrana C, Issiaka D, Sienou AA, Tapily A, Sanogo K, Kaya M, Traore S, Diarra K, Yalcouye H, Sidibe Y, Haro A, Thera I, Snell P, Grant J, Tinto H, Milligan P, Chandramohan D, Greenwood B, Dicko A, Ouedraogo JB. The duration of protection against clinical malaria provided by the combination of seasonal RTS,S/AS01 E vaccination and seasonal malaria chemoprevention versus either intervention given alone. BMC Med 2022; 20:352. [PMID: 36203149 PMCID: PMC9540742 DOI: 10.1186/s12916-022-02536-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 08/18/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND A recent trial of 5920 children in Burkina Faso and Mali showed that the combination of seasonal vaccination with the RTS,S/AS01E malaria vaccine (primary series and two seasonal boosters) and seasonal malaria chemoprevention (four monthly cycles per year) was markedly more effective than either intervention given alone in preventing clinical malaria, severe malaria, and deaths from malaria. METHODS In order to help optimise the timing of these two interventions, trial data were reanalysed to estimate the duration of protection against clinical malaria provided by RTS,S/AS01E when deployed seasonally, by comparing the group who received the combination of SMC and RTS,S/AS01E with the group who received SMC alone. The duration of protection from SMC was also estimated comparing the combined intervention group with the group who received RTS,S/AS01E alone. Three methods were used: Piecewise Cox regression, Flexible parametric survival models and Smoothed Schoenfeld residuals from Cox models, stratifying on the study area and using robust standard errors to control for within-child clustering of multiple episodes. RESULTS The overall protective efficacy from RTS,S/AS01E over 6 months was at least 60% following the primary series and the two seasonal booster doses and remained at a high level over the full malaria transmission season. Beyond 6 months, protective efficacy appeared to wane more rapidly, but the uncertainty around the estimates increases due to the lower number of cases during this period (coinciding with the onset of the dry season). Protection from SMC exceeded 90% in the first 2-3 weeks post-administration after several cycles, but was not 100%, even immediately post-administration. Efficacy begins to decline from approximately day 21 and then declines more sharply after day 28, indicating the importance of preserving the delivery interval for SMC cycles at a maximum of four weeks. CONCLUSIONS The efficacy of both interventions was highest immediately post-administration. Understanding differences between these interventions in their peak efficacy and how rapidly efficacy declines over time will help to optimise the scheduling of SMC, malaria vaccination and the combination in areas of seasonal transmission with differing epidemiology, and using different vaccine delivery systems. TRIAL REGISTRATION The RTS,S-SMC trial in which these data were collected was registered at clinicaltrials.gov: NCT03143218.
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Affiliation(s)
- Matthew Cairns
- International Statistics and Epidemiology Group, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | - Amadou Barry
- Malaria Research and Training Centre, Bamako, Mali
| | - Issaka Zongo
- Institut de Recherche en Sciences de la Santé, Bobo Dioulasso, Burkina Faso
| | | | - Serge R Yerbanga
- Institut de Recherche en Sciences de la Santé, Bobo Dioulasso, Burkina Faso
| | | | - Charles Zoungrana
- Institut de Recherche en Sciences de la Santé, Bobo Dioulasso, Burkina Faso
| | | | - Abdoul Aziz Sienou
- Institut de Recherche en Sciences de la Santé, Bobo Dioulasso, Burkina Faso
| | | | | | | | | | | | | | | | - Alassane Haro
- Institut de Recherche en Sciences de la Santé, Bobo Dioulasso, Burkina Faso
| | | | - Paul Snell
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Jane Grant
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Halidou Tinto
- Institut de Recherche en Sciences de la Santé, Bobo Dioulasso, Burkina Faso
| | - Paul Milligan
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Daniel Chandramohan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Brian Greenwood
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
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