Множественная миелома: моделирование сценариев терапии с использованием метода Монте-Карло

Author:

Лучинин Александр СергеевичORCID,Семенова А. А.ORCID,Семочкин С. В.ORCID

Abstract

AIM. To develop an information and retrieval system for hematologists which would enable effective decision making in multiple myeloma (MM) treatment through simulation and prediction of response to therapy considering a patient’s clinical profile-related characteristics and based on the analysis of data from public science sources. MATERIALS & METHODS. The analysis included 145 therapeutic options and 56,217 MM patients enrolled in 311 clinical studies, the results of which were published in the medical literature from 2003 to 2024. To simulate therapy scenarios, the Monte Carlo method was used for calculating the probability of achieving very good and even better partial response in patients with different characteristics that define not only their clinical profile but also the chemotherapy variants. RESULTS. This study introduces an interactive online application called М-BОТ (available at oncotriage.ru) enabling to predict response to therapy under certain specified conditions and to visualize the result as real-time ranking of therapeutic options via the user interface. Apart from a patient’s clinical profile-related characteristics underlying MM treatment decision making, it is possible to select trials by their types and numbers of patients enrolled. CONCLUSION. The therapy recommendations resulted from simulation of different MM therapy scenarios with the use of the Monte Carlo method considerably extend the potential for rapid retrieval of reliable science information which would confirm the optimal choice of a therapeutic option in the given clinical setting. In future, this approach can be regarded as a basis for building up a support system in individual and consensus decision making. It will allow for predicting the efficacy of multi-stage MM treatment strategies with several therapy lines and their safety as well.

Publisher

Practical Medicine Publishing House

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3