Moving forward through the in silico modeling of multiple sclerosis: Treatment layer implementation and validation

Maleki, Avisa; Crispino, Elena; Italia, Serena Anna; Salvatore, Valentina Di; Chiacchio, Maria Assunta; Sips, F.L.P.; Bursi, Roberta; Russo, Giulia; Maimone, Davide; Pappalardo, Francesco

doi:10.1016/j.csbj.2023.05.020

Cited by 5 publications

(10 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Limitations were observed due to incomplete reporting of baseline characteristics and issues with blinding. Among the six quasi-experimental studies evaluated, five (83.33%) 13 , 15 , 16 , 18 , 21 achieved at least six positive responses, indicating an acceptable quality, while one study (16.67%) 19 fell slightly below this threshold with five positive responses. The primary challenges in these quasi-experimental studies were due to the lack of control groups, inadequate baseline comparisons, and limited follow-up reporting.…”

Section: Resultsmentioning

confidence: 96%

“…Six studies 15 , 16 , 18 – 20 , 22 focused on the precision of individual therapy effects using digital twins, demonstrating a 70% effectiveness rate (7 out of 10 outcomes), as detailed in Fig. 3c .…”

Section: Resultsmentioning

confidence: 99%

“…The intervention led to a 16% decrease in average pain intensity and an additional median pain-free duration of 23 hours, extending from 72 hours in cancer patients. Another quasi-experimental study 18 created 3000 virtual patients with multiple sclerosis to assess the impact of Ocrelizumab. Findings indicated Ocrelizumab can resulted in a reduction in relapses (0.191 [0.143, 0.239]) and lymphopenic adverse events (83.73% vs .…”

Section: Resultsmentioning

confidence: 99%

“…Further scrutiny resulted in the exclusion of one study (1/17, 5.88%) lacking healthrelated outcomes and four studies (4/17, 23.53%) with overlapping data. Ultimately, 12 (12/17, 70.59%) original studies [13][14][15][16][17][18][19][20][21][22][23][24] were included in the systematic review. Supplementary Table 1 provides a summary of the reasons for exclusion at the full-text reading phase.…”

Section: Search Resultsmentioning

confidence: 99%

“…The studies included in this systematic review were published between 2021 (2/12, 16.67%) 23,24 and 2023 (8/12, 66.67%) [13][14][15][16][17][18][19][20] . Originating from diverse regions, 4/12 studies (33.33%) were from Asia 13,14,21,24 , 5/12 (41.67%) from America 15,17,19,20,22 , and 3/12 (25.00%) from Europe 16,18,23 .…”

Section: Study Characteristicsmentioning

confidence: 99%

See 4 more Smart Citations

The effectiveness of digital twins in promoting precision health across the entire population: a systematic review

Shen,

Chen,

Ding

2024

npj Digit. Med.

View full text Add to dashboard Cite

Digital twins represent a promising technology within the domain of precision healthcare, offering significant prospects for individualized medical interventions. Existing systematic reviews, however, mainly focus on the technological dimensions of digital twins, with a limited exploration of their impact on health-related outcomes. Therefore, this systematic review aims to explore the efficacy of digital twins in improving precision healthcare at the population level. The literature search for this study encompassed PubMed, Embase, Web of Science, Cochrane Library, CINAHL, SinoMed, CNKI, and Wanfang Database to retrieve potentially relevant records. Patient health-related outcomes were synthesized employing quantitative content analysis, whereas the Joanna Briggs Institute (JBI) scales were used to evaluate the quality and potential bias inherent in each selected study. Following established inclusion and exclusion criteria, 12 studies were screened from an initial 1321 records for further analysis. These studies included patients with various conditions, including cancers, type 2 diabetes, multiple sclerosis, heart failure, qi deficiency, post-hepatectomy liver failure, and dental issues. The review coded three types of interventions: personalized health management, precision individual therapy effects, and predicting individual risk, leading to a total of 45 outcomes being measured. The collective effectiveness of these outcomes at the population level was calculated at 80% (36 out of 45). No studies exhibited unacceptable differences in quality. Overall, employing digital twins in precision health demonstrates practical advantages, warranting its expanded use to facilitate the transition from the development phase to broad application.PROSPERO registry: CRD42024507256.

show abstract