Personalized medicine. Closing the gap between knowledge and clinical practice

Anaya, Juan Manuel; Duarte-Rey, Carolina; Sarmiento-Monroy, Juan Camilo; Bardey, David; Castiblanco, John; Rojas-Villarraga, Adriana

doi:10.1016/j.autrev.2016.06.005

Cited by 50 publications

(35 citation statements)

References 131 publications

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“…Such data should allow the implementation of personalized medicine, in which the accurate selection of individuals for each therapy will lead to a personalized treatment, and probably the prediction and prevention of clinical outcomes. Mounting evidence supports the utility of these tools in the near future (75,76).…”

Section: Discussionmentioning

confidence: 97%

Comparison of Plasma Cytokine Levels before and after Treatment with Rituximab in Patients with Rheumatoid Arthritis and Systemic Lupus Erythematosus-Associated Polyautoimmunity

Barahona-Correa¹,

Cortés²,

Uribe³

et al. 2018

UNIV.MED.

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Introduction: Coexistence of more than one autoimmune disease (AD) in a single patient is known as polyautoimmunity, and may be seen in up to 35% of patients with ADs. The elimination of B-cells using Rituximab (RTX) improves clinical status in different ADs. The role of cytokine production by B-cells is unclear in systemic lupus erythematosus (SLE) and polyautoimmunity. Methods: As an exploratory study, plasma from 11 patients with either rheumatoid arthritis (RA) or SLE-associated polyautoimmunity was assessed prior and 6 months after therapy with RTX. Eight healthy individuals were used as controls. Cytokine levels were measured using ELISA (IFN-α and TGF-β1) or Cytometric Bead Array (TNF-α, IL-1β, IL-6, IL-8, IL-10, and IL-12p70). Results: Prior to RTX, IL-6 was only elevated in RA and IL-8 was elevated in both RA and SLE-associated polyautoimmunity, compared with controls. After RTX, significant decreases of IL-6 in RA and IL-8 in SLE-associated polyautoimmunity were observed. Levels of other cytokines measured were either similar (IFN-α, TGF β1) or below the detection limit (TNF-α, IL-1β, IL-10, IL-12p70) for both patients and controls. Conclusion:Our data highlight the importance of B-cell cytokine secretion in RA and SLE-associated polyautoimmunity, and suggest a differential role in each pathology. A significant increase of IL-8 prior to RTX in both groups, and a significant decrease after therapy only in SLE-associated polyautoimmunity support the potential of IL-8 as a therapeutic target. The heterogeneity of the polyautoimmunity patient population highlights the importance of the selection of specific subsets in future research.

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Section: Discussionmentioning

confidence: 97%

Comparison of Plasma Cytokine Levels before and after Treatment with Rituximab in Patients with Rheumatoid Arthritis and Systemic Lupus Erythematosus-Associated Polyautoimmunity

Barahona-Correa¹,

Cortés²,

Uribe³

et al. 2018

UNIV.MED.

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“…In fact, the personalised medicine is an emerging practice of medicine that uses the patients' phenotype to guide decisions made in regard to the diagnosis, prevention and treatment of diseases [170]. Biomarkers profiling may be useful for tailoring the right therapeutic strategy for the right patient at the right time, and/or to onset of a specific complications [171,172].…”

Section: Discussionmentioning

confidence: 99%

Guidelines for biomarkers in autoimmune rheumatic diseases - evidence based analysis

Giacomelli

Afeltra

Alunno

et al. 2019

Autoimmunity Reviews

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Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement activation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing these patients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised and tailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world practice. In this context, the need for biomarkers facilitating early diagnosis and profiling those individuals at the highest risk for a poor outcome has become of crucial interest. A biomarker generally refers to a measured characteristic which may be used as an indicator of some biological state or condition. Three different types of medical biomarkers has been suggested: i. mechanistic markers; ii. clinical disease markers; iii. therapeutic markers. A combination of biomarkers from these different groups could be used for an ideal more accurate diagnosis and treatment. However, although a growing body of evidence is focused on improving biomarkers, a significant amount of this information is not integrated on standard clinical care. The overarching aim of this work was to clarify the meaning of specific biomarkers during autoimmune diseases; their possible role in confirming diagnosis, predicting outcome and suggesting specific treatments.

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“…There are extensive data on the impact that inadequate education and training can exert on the proper implementation of precision medicine. 64,65 It has been proposed that to realize the translation of precision medicine concepts and instruments into clinical care, specific training packages should be implemented at undergraduate and graduate levels. 66 Furthermore, a specific set of skills are needed in healthcare providers involved in precision medicine implementation.…”

Section: Barriers To Precision Medicine In Psychiatrymentioning

confidence: 99%

<p>Challenges and Future Prospects of Precision Medicine in Psychiatry</p>

Manchia¹,

Pisanu²,

Squassina³

et al. 2020

PGPM

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Precision medicine is increasingly recognized as a promising approach to improve disease treatment, taking into consideration the individual clinical and biological characteristics shared by specific subgroups of patients. In specific fields such as oncology and hematology, precision medicine has already started to be implemented in the clinical setting and molecular testing is routinely used to select treatments with higher efficacy and reduced adverse effects. The application of precision medicine in psychiatry is still in its early phases. However, there are already examples of predictive models based on clinical data or combinations of clinical, neuroimaging and biological data. While the power of single clinical predictors would remain inadequate if analyzed only with traditional statistical approaches, these predictors are now increasingly used to impute machine learning models that can have adequate accuracy even in the presence of relatively small sample size. These models have started to be applied to disentangle relevant clinical questions that could lead to a more effective management of psychiatric disorders, such as prediction of response to the mood stabilizer lithium, resistance to antidepressants in major depressive disorder or stratification of the risk and outcome prediction in schizophrenia. In this narrative review, we summarized the most important findings in precision medicine in psychiatry based on studies that constructed machine learning models using clinical, neuroimaging and/or biological data. Limitations and barriers to the implementation of precision psychiatry in the clinical setting, as well as possible solutions and future perspectives, will be presented.

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Personalized medicine. Closing the gap between knowledge and clinical practice

Cited by 50 publications

References 131 publications

Comparison of Plasma Cytokine Levels before and after Treatment with Rituximab in Patients with Rheumatoid Arthritis and Systemic Lupus Erythematosus-Associated Polyautoimmunity

Comparison of Plasma Cytokine Levels before and after Treatment with Rituximab in Patients with Rheumatoid Arthritis and Systemic Lupus Erythematosus-Associated Polyautoimmunity

Guidelines for biomarkers in autoimmune rheumatic diseases - evidence based analysis

<p>Challenges and Future Prospects of Precision Medicine in Psychiatry</p>

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