R. Hanifah, Nurul Atikah, M. Anwari, M. Naqiyyun, A. Riana, D. Hardiansyah
{"title":"Seleksi Model pada Peptide-receptor Radionuclide Therapy dengan 177Lu-DOTATATE untuk Dosimetri Ginjal","authors":"R. Hanifah, Nurul Atikah, M. Anwari, M. Naqiyyun, A. Riana, D. Hardiansyah","doi":"10.20527/flux.v19i2.12153","DOIUrl":null,"url":null,"abstract":"ABSTRAK- Seleksi model merupakan aspek penting dari analisis data farmakokinetik. Seleksi model dilakukan untuk memperoleh fungsi terbaik yang selanjutnya digunakan dalam perhitungan nilai TIACs pada dosimetri individu. Data yang digunakan pada penelitian ini berupa data biodistribusi radiofarmaka 177 Lu-DOTATATE pada organ ginjal dari 8 pasien PRRT. Setiap data pasien difitting dengan menggunakan beberapa fungsi. Pada setiap fungsi yang diterapkan, dilakukan analisa goodness of fit . Pada setiap fungsi yang memenuhi kriteria goodness of fit dilakukan perhitungan nilai AICc dan nilai pembobotan AICc. Fungsi dengan nilai pembobotan AICc terbesar dipilih menjadi fungsi terbaik. Berdasarkan proses seleksi model yang dilakukan, fungsi 𝑓 2𝑎,1𝑒𝑥 (𝑡) = 𝐴 1 𝑒 ABSTRACT − Model selection is an essential aspect of pharmacokinetic data analysis. Model selection is carried out to obtain the best function, which is then used in calculating TIACs values on individual dosimetry. The data used in this study were the bio-distribution data of radiopharmaceutical 177 Lu-DOTATATE in the kidneys of 8 PRRT patients. Each patient data was fitted using several functions. A goodness of fit analysis was carried out for each function. For each function that meets the goodness of fit criteria, the AICc value and AICc weighting value were calculated. The function with the most significant AICc weighting value was selected. Based on the model selection process, the function 𝑓 2𝑎,1𝑒𝑥 (𝑡) = 𝐴 1 𝑒 −(𝜆 1 +𝜆 𝑝ℎ𝑦𝑠 )𝑡 were best for patients 1,3,4,5,6, and 7. Meanwhile, function 𝑓 2𝑏,2𝑒𝑥 (𝑡) = 𝐴 1 𝑒 −(𝜆 1 +𝜆 𝑝ℎ𝑦𝑠 )𝑡 + (100 − 𝐴 1 ) 𝑒 −(𝜆 𝑝ℎ𝑦𝑠 )𝑡 became the best models for patients 2, and functions 𝑓 1𝑎,1𝑒𝑥 (𝑡) = 𝐴 1 𝑒 −(𝜆 𝑝ℎ𝑦𝑠 )𝑡 became the best models for patient 8.","PeriodicalId":52720,"journal":{"name":"JIF Jurnal Ilmu Fisika","volume":"69 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JIF Jurnal Ilmu Fisika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20527/flux.v19i2.12153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRAK- Seleksi model merupakan aspek penting dari analisis data farmakokinetik. Seleksi model dilakukan untuk memperoleh fungsi terbaik yang selanjutnya digunakan dalam perhitungan nilai TIACs pada dosimetri individu. Data yang digunakan pada penelitian ini berupa data biodistribusi radiofarmaka 177 Lu-DOTATATE pada organ ginjal dari 8 pasien PRRT. Setiap data pasien difitting dengan menggunakan beberapa fungsi. Pada setiap fungsi yang diterapkan, dilakukan analisa goodness of fit . Pada setiap fungsi yang memenuhi kriteria goodness of fit dilakukan perhitungan nilai AICc dan nilai pembobotan AICc. Fungsi dengan nilai pembobotan AICc terbesar dipilih menjadi fungsi terbaik. Berdasarkan proses seleksi model yang dilakukan, fungsi 𝑓 2𝑎,1𝑒𝑥 (𝑡) = 𝐴 1 𝑒 ABSTRACT − Model selection is an essential aspect of pharmacokinetic data analysis. Model selection is carried out to obtain the best function, which is then used in calculating TIACs values on individual dosimetry. The data used in this study were the bio-distribution data of radiopharmaceutical 177 Lu-DOTATATE in the kidneys of 8 PRRT patients. Each patient data was fitted using several functions. A goodness of fit analysis was carried out for each function. For each function that meets the goodness of fit criteria, the AICc value and AICc weighting value were calculated. The function with the most significant AICc weighting value was selected. Based on the model selection process, the function 𝑓 2𝑎,1𝑒𝑥 (𝑡) = 𝐴 1 𝑒 −(𝜆 1 +𝜆 𝑝ℎ𝑦𝑠 )𝑡 were best for patients 1,3,4,5,6, and 7. Meanwhile, function 𝑓 2𝑏,2𝑒𝑥 (𝑡) = 𝐴 1 𝑒 −(𝜆 1 +𝜆 𝑝ℎ𝑦𝑠 )𝑡 + (100 − 𝐴 1 ) 𝑒 −(𝜆 𝑝ℎ𝑦𝑠 )𝑡 became the best models for patients 2, and functions 𝑓 1𝑎,1𝑒𝑥 (𝑡) = 𝐴 1 𝑒 −(𝜆 𝑝ℎ𝑦𝑠 )𝑡 became the best models for patient 8.