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- W4313011077 abstract "<b>Background:</b> Estimating the probability of an asthma patient’s response to long-acting beta-2 adrenergic receptor agonists (LABA) from only a few lung function measurements would help clinicians avoid unnecessary drug prescription, contributing to personalized treatment and reduced costs. <b>Aims and objectives:</b> To develop a computational methodology capable of generating estimates of the probability of LABA-responsiveness and assess its accuracy using cohort data. <b>Methods:</b> Using fluctuation-based clustering (Delgado-Eckert E. et al. Thorax 2018; 73.2:107-115) we retrospectively analysed time series of PEF measurements recorded by 79 mild-to-moderate asthmatic adults during the placebo phase of a study aimed at characterizing the effects of salmeterol and salbutamol treatment (described in Thamrin C. et al. Eur Respir J 2009; 33:486–493). This yielded three clusters of patients: 1, composed mainly of salmeterol responders; 2, mainly non-responders; 3, a mixed group. We randomly removed 99% of the data from each time series, using these stripped-down versions as proxies for new patients’ data. Using Softmax Regression, we calculated the probability that a patient would be assigned to one of the three clusters. Based on the proportion of responders in each cluster, we calculated the salmeterol-responsiveness probability of a given “new” patient. We used a Receiver Operating Characteristic (ROC) curve to assess the probability’s classification performance. <b>Results:</b> The LABA-responsiveness probability ROC curve had a mean area under the curve of 0.7. <b>Conclusion:</b> Our method yields LABA-responsiveness probability estimates with good discriminatory power." @default.
- W4313011077 created "2023-01-05" @default.
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- W4313011077 date "2022-09-04" @default.
- W4313011077 modified "2023-09-27" @default.
- W4313011077 title "Using clusters of asthmatic patients to quantitatively estimate, prior to initiating treatment, the likelihood of β2-agonist response in asthma patients" @default.
- W4313011077 doi "https://doi.org/10.1183/13993003.congress-2022.3699" @default.
- W4313011077 hasPublicationYear "2022" @default.
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