Wolfgang Gaebel1, Mathias Riesbeck2. 1. Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany. Electronic address: wolfgang.gaebel@uni-duesseldorf.de. 2. Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany.
Abstract
OBJECTIVE: Despite the availability of effective long-term treatment strategies in schizophrenia, relapse is still common. Relapse prevention is one of the major treatment objectives, because relapse represents burden and costs for patients, their environment, and society and seems to increase illness progression at the biological level. Valid predictors for relapse are urgently needed to enable more individualized recommendations and treatment decisions to be made. METHODS: Mainly recent evidence regarding predictors and early warning signs of relapse in schizophrenia was reviewed. In addition, data from the first-episode (long-term) study (FES; Gaebel et al., 2007, 2011) performed within the German Research Network on Schizophrenia were analyzed. RESULTS: On the basis of FES data, premorbid adjustment, residual symptoms and some side effects are significant predictors. Although a broad spectrum of potential parameters has been investigated in several other studies, only a few and rather general valid predictors were identified consistently. Data of the FES also indicated that predictive power could be enhanced by considering interacting conjunctions, as suggested by the Vulnerability-Stress-Coping model. Prospective studies, however, are rare. In addition, prodromal symptoms as course-related characteristics likewise investigated in the FES add substantially to early recognition of relapse and may serve as early warning signs, but prognosis nevertheless remains a challenge. CONCLUSIONS: Comprehensive and well-designed studies are needed to identify and confirm valid predictors for relapse in schizophrenia. In this respect, broadly accepted and specifically defined criteria for relapse would greatly facilitate comparison of results across studies.
OBJECTIVE: Despite the availability of effective long-term treatment strategies in schizophrenia, relapse is still common. Relapse prevention is one of the major treatment objectives, because relapse represents burden and costs for patients, their environment, and society and seems to increase illness progression at the biological level. Valid predictors for relapse are urgently needed to enable more individualized recommendations and treatment decisions to be made. METHODS: Mainly recent evidence regarding predictors and early warning signs of relapse in schizophrenia was reviewed. In addition, data from the first-episode (long-term) study (FES; Gaebel et al., 2007, 2011) performed within the German Research Network on Schizophrenia were analyzed. RESULTS: On the basis of FES data, premorbid adjustment, residual symptoms and some side effects are significant predictors. Although a broad spectrum of potential parameters has been investigated in several other studies, only a few and rather general valid predictors were identified consistently. Data of the FES also indicated that predictive power could be enhanced by considering interacting conjunctions, as suggested by the Vulnerability-Stress-Coping model. Prospective studies, however, are rare. In addition, prodromal symptoms as course-related characteristics likewise investigated in the FES add substantially to early recognition of relapse and may serve as early warning signs, but prognosis nevertheless remains a challenge. CONCLUSIONS: Comprehensive and well-designed studies are needed to identify and confirm valid predictors for relapse in schizophrenia. In this respect, broadly accepted and specifically defined criteria for relapse would greatly facilitate comparison of results across studies.
Authors: Marc De Hert; Jan Sermon; Paul Geerts; Kristof Vansteelandt; Joseph Peuskens; Johan Detraux Journal: CNS Drugs Date: 2015-08 Impact factor: 5.749
Authors: Andrew I Gumley; Simon Bradstreet; John Ainsworth; Stephanie Allan; Mario Alvarez-Jimenez; Maximillian Birchwood; Andrew Briggs; Sandra Bucci; Sue Cotton; Lidia Engel; Paul French; Reeva Lederman; Shôn Lewis; Matthew Machin; Graeme MacLennan; Hamish McLeod; Nicola McMeekin; Cathy Mihalopoulos; Emma Morton; John Norrie; Frank Reilly; Matthias Schwannauer; Swaran P Singh; Suresh Sundram; Andrew Thompson; Chris Williams; Alison Yung; Lorna Aucott; John Farhall; John Gleeson Journal: Health Technol Assess Date: 2022-05 Impact factor: 4.106
Authors: Dan W Joyce; Angie A Kehagia; Derek K Tracy; Jessica Proctor; Sukhwinder S Shergill Journal: J Transl Med Date: 2017-01-18 Impact factor: 5.531
Authors: Tak Lam Lo; Matthew Warden; Yanling He; Tianmei Si; Seshadri Kalyanasundaram; Manickam Thirunavukarasu; Nurmiati Amir; Ahmad Hatim; Tomas Bautista; Cheng Lee; Robin Emsley; Jose Olivares; Yen Kuang Yang; Ronnachai Kongsakon; David Castle Journal: Asia Pac Psychiatry Date: 2016-06 Impact factor: 2.538