530
Views
17
CrossRef citations to date
0
Altmetric
Original Research

Applying Machine Learning Models to Predict Medication Nonadherence in Crohn’s Disease Maintenance Therapy

, , , ORCID Icon, , , , & show all
Pages 917-926 | Published online: 03 Jun 2020

References

  • Lichtenstein GR, Loftus EV, Isaacs KL, Regueiro MD, Gerson LB, Sands BE. Correction: ACG clinical guideline: management of Crohn’s disease in adults. Am J Gastroenterol. 2018;113(7):1101. doi:10.1038/s41395-018-0120-x
  • Cramer JA, Roy A, Burrell A, et al. Medication compliance and persistence: terminology and definitions. Value Health. 2008;11(1):44–47. doi:10.1111/j.1524-4733.2007.00213.x
  • Actis GC, Pellicano R. Inflammatory bowel disease: efficient remission maintenance is crucial for cost containment. World J Gastrointest Pharmacol Ther. 2017;8(2):114–119. doi:10.4292/wjgpt.v8.i2.114
  • Jackson CA, Clatworthy J, Robinson A, Horne R. Factors associated with non-adherence to oral medication for inflammatory bowel disease: a systematic review. Am J Gastroenterol. 2010;105(3):525–539. doi:10.1038/ajg.2009.685
  • Sewitch MJ, Abrahamowicz M, Barkun A, et al. Patient nonadherence to medication in inflammatory bowel disease. Am J Gastroenterol. 2003;98(7):1535–1544. doi:10.1111/j.1572-0241.2003.07522.x
  • Woo DH, Kim KO, Kang MK, Lee SH, Jang BI, Kim TN. Predictors and clinical outcomes of follow-up loss in patients with inflammatory bowel disease. J Gastroenterol Hepatol. 2018;33(11):1834–1838. doi:10.1111/jgh.14258
  • Depont F, Berenbaum F, Filippi J, et al. Interventions to improve adherence in patients with immune-mediated inflammatory disorders: a systematic review. PLoS One. 2015;10(12):e0145076. doi:10.1371/journal.pone.0145076
  • Lenti MV, Selinger CP. Medication non-adherence in adult patients affected by inflammatory bowel disease: a critical review and update of the determining factors, consequences and possible interventions. Expert Rev Gastroenterol Hepatol. 2017;11(3):215–226. doi:10.1080/17474124.2017.1284587
  • Khan S, Rupniewska E, Neighbors M, Singer D, Chiarappa J, Obando C. Real-world evidence on adherence, persistence, switching and dose escalation with biologics in adult inflammatory bowel disease in the United States: a systematic review. J Clin Pharm Ther. 2019;44(4):495–507. doi:10.1111/jcpt.12830
  • Bonaz BL, Bernstein CN. Brain-gut interactions in inflammatory bowel disease. Gastroenterology. 2013;144(1):36–49. doi:10.1053/j.gastro.2012.10.003
  • Colonnello V, Agostini A. Disease course, stress, attachment, and mentalization in patients with inflammatory bowel disease. Med Hypotheses. 2020;140:109665. doi:10.1016/j.mehy.2020.109665
  • Almansour NA, Syed HF, Khayat NR, et al. Neural network and support vector machine for the prediction of chronic kidney disease: a comparative study. Comput Biol Med. 2019;109:101–111. doi:10.1016/j.compbiomed.2019.04.017
  • Yu W, Liu T, Valdez R, Gwinn M, Khoury MJ. Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes. BMC Med Inform Decis Mak. 2010;10(1):16. doi:10.1186/1472-6947-10-16
  • Son YJ, Kim HG, Kim EH, Choi S, Lee SK. Application of support vector machine for prediction of medication adherence in heart failure patients. Healthc Inform Res. 2010;16(4):253–259. doi:10.4258/hir.2010.16.4.253
  • Dong Y, Xu L, Fan Y, et al. A novel surgical predictive model for Chinese Crohn’s disease patients. Medicine (Baltimore). 2019;98(46):e17510. doi:10.1097/MD.0000000000017510
  • Peng JC, Ran ZH, Shen J. Seasonal variation in onset and relapse of IBD and a model to predict the frequency of onset, relapse, and severity of IBD based on artificial neural network. Int J Colorectal Dis. 2015;30(9):1267–1273. doi:10.1007/s00384-015-2250-6
  • Waljee AK, Sauder K, Patel A, et al. Machine learning algorithms for objective remission and clinical outcomes with thiopurines. J Crohns Colitis. 2017;11(7):801–810. doi:10.1093/ecco-jcc/jjx014
  • Li Y, Chen B, Gao X, et al. Current diagnosis and management of Crohn’s disease in China: results from a multicenter prospective disease registry. BMC Gastroenterol. 2019;19(1):145. doi:10.1186/s12876-019-1057-2
  • Horne R, Parham R, Driscoll R, Robinson A. Patients’ attitudes to medicines and adherence to maintenance treatment in inflammatory bowel disease. Inflamm Bowel Dis. 2009;15(6):837–844. doi:10.1002/ibd.20846
  • Horne R, Weinman J. Self-regulation and self-management in asthma: exploring the role of illness perceptions and treatment beliefs in explaining non-adherence to preventer medication. Psychol Health. 2002;17(1):17–32. doi:10.1080/08870440290001502
  • Severs M, Mangen MJ, Fidder HH, et al. Clinical predictors of future nonadherence in inflammatory bowel disease. Inflamm Bowel Dis. 2017;23(9):1568–1576. doi:10.1097/MIB.0000000000001201
  • Ribaldone DG, Vernero M, Saracco GM, et al. The adherence to the therapy in inflammatory bowel disease: beyond the number of the tablets. Scand J Gastroenterol. 2018;53(2):141–146. doi:10.1080/00365521.2017.1405070
  • Karve S, Cleves MA, Helm M, Hudson TJ, West DS, Martin BC. Good and poor adherence: optimal cut-point for adherence measures using administrative claims data. Curr Med Res Opin. 2009;25(9):2303–2310. doi:10.1185/03007990903126833
  • Severs M, Zuithoff PN, Mangen MJ, et al. Assessing self-reported medication adherence in inflammatory bowel disease: a comparison of tools. Inflamm Bowel Dis. 2016;22(9):2158–2164. doi:10.1097/MIB.0000000000000853
  • Tiao DK, Chan W, Jeganathan J, et al. Inflammatory bowel disease pharmacist adherence counseling improves medication adherence in Crohn’s disease and ulcerative colitis. Inflamm Bowel Dis. 2017;23(8):1257–1261. doi:10.1097/MIB.0000000000001194
  • Horne R, Weinman J, Hankins M. The beliefs about medicines questionnaire: the development and evaluation of a new method for assessing the cognitive representation of medication. Psychol Health. 1999;14(1):1–24. doi:10.1080/08870449908407311
  • Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–370. doi:10.1111/j.1600-0447.1983.tb09716.x
  • Strobl C, Boulesteix AL, Zeileis A, Hothorn T. Bias in random forest variable importance measures: illustrations, sources and a solution. BMC Bioinformatics. 2007;8(1):25. doi:10.1186/1471-2105-8-25
  • Predictor importance estimates by permutation of out-of-bag predictor observations for random forest of classification trees. Available from: https://www.mathworks.com/help/stats/classificationbaggedensemble.oobpermutedpredictorimportance.html#bvgfu5_. Accessed May 15, 2020.
  • Stoltzfus JC. Logistic regression: a brief primer. Acad Emerg Med. 2011;18(10):1099–1104. doi:10.1111/j.1553-2712.2011.01185.x
  • Lippmann R. An introduction to computing with neural nets. IEEE ASSP Mag. 1987;4(2):4–22. doi:10.1109/MASSP.1987.1165576
  • Yang C, Odvody GN, Fernandez CJ, Landivar JA, Minzenmayer RR, Nichols RL. Evaluating unsupervised and supervised image classification methods for mapping cotton root rot. Precis Agric. 2015;16(2):201–215. doi:10.1007/s11119-014-9370-9
  • Huang J, Ling CX. Using AUC and accuracy in evaluating learning algorithms. IEEE Trans Knowl Data Eng. 2005;17(3):299–310. doi:10.1109/TKDE.2005.50
  • Neuendorf R, Harding A, Stello N, Hanes D, Wahbeh H. Depression and anxiety in patients with inflammatory bowel disease: a systematic review. J Psychosom Res. 2016;87:70–80. doi:10.1016/j.jpsychores.2016.06.001
  • Swets JA. Measuring the accuracy of diagnostic systems. Science. 1988;240(4857):1285–1293. doi:10.1126/science.3287615
  • Tabibian A, Tabibian JH, Beckman LJ, Raffals LL, Papadakis KA, Kane SV. Predictors of health-related quality of life and adherence in Crohn’s disease and ulcerative colitis: implications for clinical management. Dig Dis Sci. 2015;60(5):1366–1374. doi:10.1007/s10620-014-3471-1
  • Varni JW, Shulman RJ, Self MM, et al. Perceived medication adherence barriers mediating effects between gastrointestinal symptoms and health-related quality of life in pediatric inflammatory bowel disease. Qual Life Res. 2018;27(1):195–204. doi:10.1007/s11136-017-1702-6
  • Coenen S, Weyts E, Ballet V, et al. Identifying predictors of low adherence in patients with inflammatory bowel disease. Eur J Gastroenterol Hepatol. 2016;28(5):503–507. doi:10.1097/MEG.0000000000000570
  • Gaines LS, Slaughter JC, Horst SN, et al. Association between affective-cognitive symptoms of depression and exacerbation of Crohn’s disease. Am J Gastroenterol. 2016;111(6):864–870. doi:10.1038/ajg.2016.98
  • Michetti P, Weinman J, Mrowietz U, et al. Impact of treatment-related beliefs on medication adherence in immune-mediated inflammatory diseases: results of the Global ALIGN Study. Adv Ther. 2017;34(1):91–108. doi:10.1007/s12325-016-0441-3
  • Bruna-Barranco I, Lue A, Gargallo-Puyuelo CJ, et al. Young age and tobacco use are predictors of lower medication adherence in inflammatory bowel disease. Eur J Gastroenterol Hepatol. 2019;31(8):948–953. doi:10.1097/MEG.0000000000001436
  • Agostini A, Scaioli E, Belluzzi A, Campieri M. Attachment and mentalizing abilities in patients with inflammatory bowel disease. Gastroenterol Res Pract. 2019;2019:7847123. doi:10.1155/2019/7847123