Bridging a translational gap: Using machine learning to improve the prediction of PTSD

BMC Psychiatry

Volumn 15, Issue 1, 2015, Pages

  Karstoft, Karen Inge ^b   Galatzer Levy, Isaac R ^a   Statnikov, Alexander ^a   Li, Zhiguo ^a   Shalev, Arieh Y ^a   Ankri, Yael ^a   Freedman, Sara ^a   Addesky, Rhonda ^a   Israeli Shalev, Yossi ^a   Gilad, Moran ^a   Roitman, Pablo ^a  

^a NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b Research and Knowledge Centre   (Denmark)

Author keywords

Early prediction; Machine learning; Markov boundary feature selection; Posttraumatic Stress Disorder (PTSD); Risk factors; Support vector machines

Indexed keywords

ADULT; AGED; ARTICLE; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; EMERGENCY WARD; HOSPITAL ADMISSION; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; POSTTRAUMATIC STRESS DISORDER; PREDICTION; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; RISK ASSESSMENT; RISK FACTOR; SENSITIVITY AND SPECIFICITY; STATISTICAL PARAMETERS; SUPPORT VECTOR MACHINE; SURVIVOR; SYMPTOM; TARGET INFORMATION EQUIVALENCE ALGORITHM; VALIDATION STUDY; ADAPTIVE BEHAVIOR; ALGORITHM; ARTIFICIAL INTELLIGENCE; COMPLICATION; EARLY DIAGNOSIS; FEMALE; INJURY; MALE; MIDDLE AGED; PATHOPHYSIOLOGY; PHYSIOLOGY; PROGNOSIS; PSYCHOLOGY; STRESS DISORDERS, POST-TRAUMATIC; TRANSLATIONAL RESEARCH;

ADAPTATION, PSYCHOLOGICAL; ADULT; ALGORITHMS; ARTIFICIAL INTELLIGENCE; EARLY DIAGNOSIS; FEMALE; HUMANS; MALE; MIDDLE AGED; PROGNOSIS; RISK ASSESSMENT; RISK FACTORS; ROC CURVE; STRESS DISORDERS, POST-TRAUMATIC; TRANSLATIONAL MEDICAL RESEARCH; WOUNDS AND INJURIES;

EID: 84961554493     PISSN: None     EISSN: 1471244X     Source Type: Journal    
DOI: 10.1186/s12888-015-0399-8     Document Type: Article

References (45)

1. Brewin CR, Andrews B, Valentine JD. Meta-analysis of risk factors for posttraumatic stress disorder in trauma-exposed adults. J Consult Clin Psychol. 2000;68(5):748-66.
2. Ozer EJ, Best SR, Lipsey TL, Weiss DS. Predictors of posttraumatic stress disorder and symptoms in adults: A meta-analysis. Psychol Bull. 2003;129(1):52-73.
3. Kessler RC, Sonnega A, Bromet E, Hughes M, Nelson C. Post-traumatic stress disorder in the National Comorbidity Survey. Arch Gen Psychiatry. 1995;52:1048-60.
4. Marmar CR, Weiss DS, Schlenger WE, et al. Peritraumatic dissociation and posttraumatic stress in male Vietnam theater veterans. Am J Psychiatry. 1994;151(6):902-7.
5. Shalev AY, Peri T, Canetti L, Schreiber S. Predictors of PTSD in injured trauma survivors: a prospective study. Am J Psychiatry. 1996;153(2):219-25.
6. Forbes D, Creamer M, Biddle D. The validity of the PTSD checklist as a measure of symptomatic change in combat-related PTSD. Behav Res Ther. 2001;39(8):977-86.
7. Bryant RA, Harvey AG, Guthrie RM, Moulds ML. A prospective study of psychophysiological arousal, acute stress disorder, and posttraumatic stress disorder. J Abnorm Psychol. 2000;109(2):341-4.
8. Difede J, Barocas D. Acute intrusive and avoidant PTSD symptoms as predictors of chronic PTSD following burn injury. J Trauma Stress. 1999;12(2):363-9.
9. Kleim B, Ehlers A, Glucksman E. Early predictors of chronic post-traumatic stress disorder in assault survivors. Psychol Med. 2007;37(10):1457-67.
10. Mellman TA, David D, Bustamante V, Fins AI, Esposito K. Predictors of post-traumatic stress disorder following severe injury. Depress Anxiety. 2001;14(4):226-31.
11. Shalev AY, Peri T, Brandes D, Freedman S, Orr SP, Pitman RK. Auditory startle response in trauma survivors with posttraumatic stress disorder: a prospective study. Am J Psychiatry. 2000;157(2):255-61.
12. Segman RH, Shefi N, Goltser-Dubner T, Friedman N, Kaminski N, Shalev AY. Peripheral blood mononuclear cell gene expression profiles identify emergent post-traumatic stress disorder among trauma survivors. Mol Psychiatry. 2005;10(5):500. -513, 425.
13. Koenen KC, Stellman JM, Stellman SD, Sommer Jr JF. Risk factors for course of posttraumatic stress disorder among Vietnam veterans: a 14-year follow-up of American Legionnaires. J Consult Clin Psych. 2003;71(6):980-6.
14. Shalev AY, Segman RH. Commentary: biological findings in PTSD - too much or too little? Prog Brain Res. 2008;167:187-99.
15. Orrù G, Pettersson-Yeo W, Marquand AF, Sartori G, Mechelli A. Using support vector machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review. Neurosci Biobehav Rev. 2012;36(4):1140-52.
16. Norman SB, Stein MB, Dimsdale JE, Hoyt DB. Pain in the aftermath of trauma is a risk factor for post-traumatic stress disorder. Psychol Med. 2008;38(4):533-42.
17. Bryan CJ, Clemans TA. Repetitive traumatic brain injury, psychological symptoms, and suicide risk in a clinical sample of deployed military personnel. JAMA Psychiatry (Chicago, Ill). 2013;70(7):686-91.
18. Haagsma JA, Ringburg AN, van Lieshout EM, van Beeck EF, Patka P, Schipper IB. Prevalence rate, predictors and long-term course of probable posttraumatic stress disorder after major trauma: a prospective cohort study. BMC Psychiatry. 2012;12:236.
19. Bienvenu OJ, Gellar J, Althouse BM, Colantuoni E, Sricharoenchai T, Mendez-Tellez PA, et al. Post-traumatic stress disorder symptoms after acute lung injury: a 2-year prospective longitudinal study. Psychol Med. 2013;43(12):2657-71.
20. Statnikov A, Lytkin NI, Lemeire J, Aliferis CF. Algorithms for Discovery of Multiple Markov Boundaries. J Mach Learn Res. 2013;14:499-566.
21. Breiman L. Statistical modeling: the two cultures. Stat Sci. 2001;16(3):199-215.
22. Statnikov A, Aliferis CF. Analysis and computational dissection of molecular signature multiplicity. PLoS Comput Biol. 2010;6(5):e1000790.
23. Galatzer-Levy IR, Karstoft KI, Statnikov A, Shalev AY. Quantitative forecasting of PTSD from early trauma responses: a Machine Learning application. J Psychiatr Res. 2014;59:68-76.
24. Boser BE, Guyon IM, Vapnik VN. A training algorithm for optimal margin classifiers. In: Proceedings of the fifth annual workshop on Computational learning theory (COLT '92). New York, NY, USA: ACM; 1992. 144-152. doi:10.1145/130385.130401.
25. Galatzer-Levy IR, Ankri Y, Freedman S, Israeli-Shalev Y, Roitman P, Gilad M, et al. Early. PTSD Symptom Trajectories: Persistence, Recovery, and Response to Treatment: Results from the Jerusalem Trauma Outreach and Prevention Study (J-TOPS). PLoS One. 2013;8(8):e70084.
26. Shalev AY, Ankri Y, Israeli-Shalev Y, Peleg T, Adessky R, Freedman S. Prevention of posttraumatic stress disorder by early treatment: results from the Jerusalem Trauma Outreach And Prevention study. Arch Gen Psychiatry. 2012;69(2):166-76.
27. Shalev AY, Ankri YL, Peleg T, Israeli-Shalev Y, Freedman S. Barriers to receiving early care for PTSD: results from the Jerusalem trauma outreach and prevention study. Psychiatr Serv. 2011;62(7):765-73.
28. Foa EB, Tolin DF. Comparison of the PTSD Symptom Scale-Interview Version and the Clinician-Administered PTSD scale. J Trauma Stress. 2000;13(2):181-91.
29. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32(6):959-76.
30. Bryant RA, Moulds ML, Guthrie RM. Acute Stress Disorder Scale: a self-report measure of acute stress disorder. Psychol Assess. 2000;12(1):61-8.
31. Guy W. Clinical global impression scale. The ECDEU Assessment Manual for Psychopharmacology-Revised Volume DHEW Publ No ADM 76. 1976;338:218-22.
32. Foa EB, Ehlers A, Clark DM, Tolin DF, Orsillo SM. The Posttraumatic Cognitions Inventory (PTCI): Development and validation. Psychol Assess. 1999;11(3):303-14.
33. Lazarus RS, Folkman S. Stress, Appraisal, and Coping. New York: Springer; 1984.
34. Bryant RA, O'Donnell ML, Creamer M, McFarlane AC, Silove D: A Multisite Analysis of the Fluctuating Course of Posttraumatic Stress Disorder. JAMA psychiatry (Chicago, Ill.). Jun 19 2013:1-8
35. Statnikov A, Tsamardinos I, Brown LE, Aliferis CF. Causal Explorer: A Matlab Library of Algorithms for Causal Discovery and Variable Selection for Classification. In: Guyon IM, Aliferis CF, Cooper GF, editors. Challenges in Machine Learning Volume 2: Causation and Prediction Challenge. Bookline, Massachusetts: Microtome Publishing; 2010. p. 267-78.
36. Chang C-C, Lin C-J, LIBSVM. A library for support vector machines. ACM Trans Intell Syst Technol. 2011;2(3):1-27.
37. Bradley AP. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recogn. 1997;30(7):15.
38. Shalev AY, Freedman S. PTSD following terrorist attacks: a prospective evaluation. Am J Psychiatry. 2005;162(6):1188-91.
39. Freedman SA, Brandes D, Peri T, Shalev A. Predictors of chronic post-traumatic stress disorder. A prospective study. Br J Psychiatry. 1999;174:353-9.
40. Breslau N, Chilcoat HD, Kessler RC, Davis GC. Previous exposure to trauma and PTSD effects of subsequent trauma: results from the Detroit Area Survey of Trauma. Am J Psychiatry. 1999;156(6):902-7.
41. Koenen KC, Harley R, Lyons MJ, Wolfe J, Simpson JC, Goldberg J, et al. A twin registry study of familial and individual risk factors for trauma exposure and posttraumatic stress disorder. J Nerv Ment Dis. 2002;190(4):209-18.
42. Shalev AY, Videlock EJ, Peleg T, Segman R, Pitman RK, Yehuda R. Stress hormones and post-traumatic stress disorder in civilian trauma victims: a longitudinal study. Part I: HPA axis responses. Int J Neuropsychopharmacol. 2008;11(03):365-72.
43. Binder EB, Bradley RG, Liu W, Epstein MP, Deveau TC, Mercer KB, et al. Association of fkbp5 polymorphisms and childhood abuse with risk of posttraumatic stress disorder symptoms in adults. JAMA. 2008;299(11):1291-305.
44. Boscarino JA, Erlich PM, Hoffman SN, Zhang X. Higher FKBP5, COMT, CHRNA5, and CRHR1 allele burdens are associated with PTSD and interact with trauma exposure: implications for neuropsychiatric research and treatment. Neuropsychiatr Dis Treat. 2012;8:131-9.
45. Visweswaran S, Angus DC, Hsieh M, Weissfeld L, Yealy D, Cooper GF. Learning patient-specific predictive models from clinical data. J Biomed Inform. 2010;43(5):669-85.