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Quantitative decision making for investment in global health intervention trials: Case study of the NEWBORN study on emollient therapy in preterm infants in Kenya.
Stylianou, Annie; Blanks, Keona J H; Gibson, Rachel A; Kendall, Lindsay K; English, Mike; Williams, Sarah; Mehta, Roshni; Clarke, Andrew; Kanyuuru, Lynn; Aluvaala, Jalemba; Darmstadt, Gary L.
Afiliação
  • Stylianou A; GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, Hertfordshire, UK.
  • Blanks KJH; Stanford University, Stanford, California, USA.
  • Gibson RA; GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, Hertfordshire, UK.
  • Kendall LK; GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, Hertfordshire, UK.
  • English M; Oxford Centre for Global Health Research, Nuffield Department of Clinical Medicine, Oxford, UK.
  • Williams S; KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
  • Mehta R; Save the Children UK, London, UK.
  • Clarke A; Save the Children UK, London, UK.
  • Kanyuuru L; Save the Children UK, London, UK.
  • Aluvaala J; Save the Children International, Kenya Country Office, Nairobi, Kenya.
  • Darmstadt GL; KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
J Glob Health ; 12: 04045, 2022 Jun 11.
Article em En | MEDLINE | ID: mdl-35972445
Background: Partners from an NGO, academia, industry and government applied a tool originating in the private sector - Quantitative Decision Making (QDM) - to rigorously assess whether to invest in testing a global health intervention. The proposed NEWBORN study was designed to assess whether topical emollient therapy with sunflower seed oil in infants with very low birthweight <1500 g in Kenya would result in a significant reduction in neonatal mortality compared to standard of care. Methods: The QDM process consisted of prior elicitation, modelling of prior distributions, and simulations to assess Probability of Success (PoS) via assurance calculations. Expert opinion was elicited on the probability that emollient therapy with sunflower seed oil will have any measurable benefit on neonatal mortality based on available evidence. The distribution of effect sizes was modelled and trial data simulated using Statistical Analysis System to obtain the overall assurance which represents the PoS for the planned study. A decision-making framework was then applied to characterise the ability of the study to meet pre-selected decision-making endpoints. Results: There was a 47% chance of a positive outcome (defined as a significant relative reduction in mortality of ≥15%), a 45% chance of a negative outcome (defined as a significant relative reduction in mortality <10%), and an 8% chance of ending in the consider zone (ie, a mortality reduction of 10 to <15%) for infants <1500 g. Conclusions: QDM is a novel tool from industry which has utility for prioritisation of investments in global health, complementing existing tools [eg, Child Health and Nutrition Research Initiative]. Results from application of QDM to the NEWBORN study suggests that it has a high probability of producing clear results. Findings encourage future formation of public-private partnerships for health.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Métodos Terapêuticos e Terapias MTCI: Terapias_biologicas Assunto principal: Recém-Nascido Prematuro / Emolientes Tipo de estudo: Prognostic_studies País/Região como assunto: Africa Idioma: En Revista: J Glob Health Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Métodos Terapêuticos e Terapias MTCI: Terapias_biologicas Assunto principal: Recém-Nascido Prematuro / Emolientes Tipo de estudo: Prognostic_studies País/Região como assunto: Africa Idioma: En Revista: J Glob Health Ano de publicação: 2022 Tipo de documento: Article