This page was automatically generated by NetLogo 5.0.2.
The applet requires Java 5 or higher. Java must be enabled in your browser settings. Mac users must have Mac OS X 10.4 or higher. Windows and Linux users may obtain the latest Java from Oracle's Java site.
powered by NetLogo
This model has been drawn upon the MSprogressionSimulation model and intends to provide a simplified view on what might happen to disease progression in terms of disability when some medication is introduced. The treatment impact on the patient is represented by means of Quality Adjusted Life Years (QALYs) gain that will be calculated for the time span in years specified by the user.
The second part of the model enables to monitoring the treatment in order to identify suboptimal responses and hence the need to change. Moreover, this is situated in terms of disease (disability) progression as defined by the disability curves and the Multiple Sclerosis Severity Score (MSSS).
Obviously, this is an experimental research model not yet to be used in the daily clinical practice.
The time from onset of the disease to assignment of the DSS scores of 4. 6 and 7 is calculated in terms of the BREMS score, which is derived from the patient characteristics introduced by the user. Then, the patient distribution per year in the different DSS scores (<4, 4, 6 and 7) is presented in two distinct graphical displays. QALYs are calculated in a yearly basis according to the current DSS distribution.
Treatment benefit assessment is based on the impact of relapse free and progression free at two years, as defined by the absolute risk reduction of the different disease-modifying agents, onto the time to assignment of the DSS scores of 4. 6 and 7.
The monitoring component of the system is based on published criteria for identifying patients with suboptimal response, and this component also provides a graphical presentation of the predicted disability progression, derived from the EDSS evolution entered by the user.
The first thing is to press the SETUP button. Then, after selecting the number of years for the prediction (maximum 30 years) and the patient characteristics, the button “go” must be pressed. At this point, the system graphically presents the patient distribution per year in the different DSS scores (<4, 4, 6 and 7). The distribution at the end (e.g. the number of years for the prediction) is presented in a different display by means of “persons” in a different color intensity of blue or pink (males and females, respectively). The BREMS score, the predicted QALYs and the probability of conversion to secondary progressive MS, are also numerically presented.
By selecting one of the disease-modifying agents and pressing the button “assess” the respective QALYs gain for the number of years defined by the user is presented.
Finally, for treatment monitoring the user must enter the respective data in ascending order. An error message will be presented if selected years are not in ascending order. For the yearly data to be processed the “new” button must be pressed after selecting all the data for the current year, including in the last entered year before pressing the “calculate” button. At least two consecutive years are required for treatment monitoring.
If any error occurs, re-start the system by pressing setup and then repeat the all process.
Jacobs LD, Cookfair DL, Rudick RA, et al.; The Multiple Sclerosis Collaborative Research Group (MSCRG): Intramuscular interferon beta-1a for disease progression in relapsing multiple sclerosis. Ann Neurol 1996; 39:285-294.
Johnson KP, Brooks BR, Cohen JA, Ford CC, Goldstein J, Lisak RP, Myers LW, Panitch HS, Rose JW, Schiffer RB; The Copolymer 1 Mul- tiple Sclerosis Study Group: Copolymer 1 reduces relapse rate and improves disability in relapsing-remitting multiple sclerosis: results of a phase III multicenter, double-blind placebo-controlled trial. Neurology 1995; 45: 1268-1276.
Filippini G, Munari L, Incorvaia B, Ebers GC, Polman C, D'Amico R, Rice GP: Interferons in relapsing remitting multiple sclerosis: a systematic review. Lancet 2003; 361: 545-552
PRISMS (Prevention of Relapses and Dis- ability by Interferon beta-1a Subcutaneously in Multiple Sclerosis) Study Group: Randomised double-blind placebo-controlled study of interferon beta-1a in relapsing/remitting multiple sclerosis. Lancet 1998;352: 1498-1504
Polman CH, O'Connor PW, Havrdova E, Hutchinson M, Kappos L, Miller DH, Phillips JT, Lublin FD, Giovannoni G, Wajgt A, Toal M, Lynn F, Panzara MA, Sandrock AW: A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N Engl J Med 2006; 354:899-910.
The IFNB Multiple Sclerosis Study Group, The University of British Columbia MS/MRI Analysis Group: Interferon beta-1b in the treatment of multiple sclerosis: final outcome of the randomized controlled trial. Neurology 1995; 45:1277-1285.
Freedman MS, Hughres B, et al.; Efficacy of diasease-modifying therapies in relapsing remitting multipa sclerosis: A systematic comparison. Eur Neurol 2008; 60:1-11.
Rio J, Comabella M, and Montalban X. Predicting responders to therapies for multiple sclerosis. Nat. Rev. Neurol. 5, 553-560, 2009.
Bashir K, Buchwald L, Coyle PK et al., MS Patient Management: optimizing immunomodulatory therapy for MS patients. Int J MS Care [Suppl. 4]: 3-7, 2002.
Confavreux C., Vukusic S. and Adeleine P., Early clinical predictors and progression of irreversible disability in multiple sclerosis: an amnesic process. Brain (2003), 126, 770-782.
Bergamaschi R., Berzuini C., Romani A., Cosi V., Predicting secondary progression in relapsing-remitting multiple sclerosis: a Bayesian analysis. Journal of the Neurological Sciences 189 (2001) 13-21.
Bergamaschi R. et al., Early prediction of the long term evolution of multiple sclerosis: the Bayesian Risk Estimate for Multiple Sclerosis (BREMS) score. J Neurol Neurosurg Psychiatry 2007;78:757-759
Roxburgh R.H.S.R. et al., Multiple Sclerosis Severity Score Using disability and disease duration to rate disease severity. Neurology 2005; 64: 1144-1151
Achiron A., Barak Y. and Zeev Rotstein Z., Longitudinal disability curves for predicting the course of relapsing / remitting multiple sclerosis. Multiple Sclerosis 2003; 9: 486-491
Mário Veloso MD, Consultant Neurologist