@article{article,
  keywords = {Early diagnosis, Treatment, Pharmacology},
  author = {Novack AC and Cobre ADF and Stremel DP and Ferreira LM and Campos ML and Pontarolo R},
  title = {Development and validation of a new method by MIR-FTIR and chemometrics for the early diagnosis of leprosy and evaluation of the treatment effect},
  abstract = {<p id="sectitle0015"><strong>Objective: </strong>Develop a new method for diagnosing leprosy and monitoring the pharmacological treatment effect of patients.</p>

<p id="sectitle0020"><strong>Material and methods: </strong>Plasma samples from patients diagnosed with leprosy (n\&nbsp;=\&nbsp;211) who had not yet received any pharmacological treatment were collected at a basic health unit in Brazil. After treatment, samples were collected from the same patients (n\&nbsp;=\&nbsp;125). Plasma samples from healthy volunteers were also collected (n\&nbsp;=\&nbsp;179) and used as a control group. All samples were analyzed by Fourier transform mid-infrared spectrophotometry (MIR-FTIR). The spectral data of the samples were subjected to chemometric analysis. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to predict diagnosis and monitor pharmacological treatment.</p>

<p id="sectitle0025"><strong>Results: </strong>The PCA model successfully distinguished among three sample classes: healthy individuals, pre-treatment leprosy patients, and post-treatment leprosy patients. The PLS-DA algorithm accurately classified healthy, treated, and diseased samples, facilitating both reliable diagnosis and treatment monitoring for leprosy. The model achieved a sensitivity of 97\&nbsp;\%{\textendash}100\&nbsp;\%, specificity of 100\&nbsp;\%, and accuracy ranging from 99\&nbsp;\% to 100\&nbsp;\%. Furthermore, when tested on plasma samples from patients with other conditions{\textemdash}renal failure (n\&nbsp;=\&nbsp;1032), hypertriglyceridemia (n\&nbsp;=\&nbsp;100), hypercholesterolemia (n\&nbsp;=\&nbsp;100), and mixed dyslipidemia (n\&nbsp;=\&nbsp;100){\textemdash}the model correctly classified these as negative for leprosy, with diagnostic specificity between 93\&nbsp;\% and 96\&nbsp;\%.</p>

<p id="sectitle0030"><strong>Conclusion:</strong> The MIR-FTIR technique combined with PLS-DA analysis proved to be a highly effective tool for screening leprosy patients and monitoring treatment outcomes. Given its low cost, this method could be easily implemented in laboratories across emerging and low-income countries.</p>
},
  year = {2024},
  journal = {Chemometrics and Intelligent Laboratory Systems},
  volume = {254},
  publisher = {Elsevier BV},
  issn = {0169-7439},
  doi = {10.1016/j.chemolab.2024.105248},
  language = {ENG},
}