Corrigendum to “Optimising outcomes for adults with Cystic Fibrosis taking CFTR modulators by individualising care: Personalised data linkage to understand treatment optimisation (PLUTO), a novel clinical framework” [Respirat. Med. 239 (2025)] - 24/04/25
, Alan Anderson c, Tracy Barnett d, Stephen J. Bourke c, Sarah Cameron a, Stephen J. Chapman e, Jocelyn Choyce f, Thom Daniels g, h, Tracey Daniels i, Sophie Dawson j, Simon Doe c, Michael Dooney k, Carlos Echevarria c, e, Penny Galey l, Giles Fitch k, Lana YH. Lai m, Julia A. Nightingale g, Michelle Thomas n, Rachael Thompson a, Joanna Whitehouse f, Louise Warnock e, David Waine n, Nick Withers o, Zhe Hui Hoo a, Martin J. Wildman a, bAbstract |
Cystic Fibrosis (CF) is a life-limiting, inherited condition in which a novel class of oral medicine, CFTR modulators, has revolutionised symptoms and health indicators, providing an opportunity to evaluate traditional treatment regimens with the hope of reducing burden. Additionally, there is cautious optimism that life expectancy for people with CF born today could ultimately compare to that of the general population. Given this potential, there is a need and requirement to optimise treatment to balance burden with the best clinical outcomes for each person with CF in an individualised manner. Personalised data-Linkage to Understand Treatment Optimisation (PLUTO) is a clinical framework, developed within the 14-Centre UK CFHealthHub Learning Health System collaborative, designed for use at an individual level for people with CF taking CFTR modulators. The PLUTO framework encourages use of two routinely collected clinical outcome measure (FEV1 and BMI) to determine health status. Where FEV1 or BMI trends suggest that optimal health outcomes are not being achieved for a person with CF, PLUTO supports consideration of adherence to both CFTR modulators and inhaled therapy to help guide the next steps. PLUTO is designed to support people with CF and their clinical teams to individualise care and optimise outcomes for those taking CFTR modulators, using data available in routine clinical encounters.
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