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Open AccessJournal ArticleDOI

Risk and Response-Adapted Treatment in Multiple Myeloma

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TLDR
The advent of technologies detecting minimal residual disease gives the opportunity to define the quality of response to treatment with an unpreceded sensitivity and adapt treatment accordingly and even if molecular targeting is still nascent in myeloma, some molecular features are interesting to detect at relapse to determine optimal salvage treatments.
Abstract
Myeloma therapeutic strategies have been adapted to patients' age and comorbidities for a long time. However, although cytogenetics and clinical presentations (plasmablastic cytology; extramedullary disease) are major prognostic factors, until recently, all patients received the same treatment whatever their initial risk. No strong evidence allows us to use a personalized treatment according to one cytogenetic abnormality in newly diagnosed myeloma. Retrospective studies showed a benefit of a double autologous transplant in high-risk cytogenetics according to the International Myeloma Working Group definition (t(4;14), t(14;16) or del(17p)). Moreover, this definition has to be updated since other independent abnormalities, namely gain 1q, del(1p32), and trisomies 5 or 21, as well as TP53 mutations, are also prognostic. Another very strong predictive tool is the response to treatment assessed by the evaluation of minimal residual disease (MRD). We are convinced that the time has come to use it to adapt the strategy to a dynamic risk. Many trials are ongoing to answer many questions: when and how should we adapt the therapy, its intensity and duration. Nevertheless, we also have to take into account the clinical outcome for one patient, especially adverse events affecting his or her quality of life and his or her preferences for continuous/fixed duration treatment.

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Journal ArticleDOI

Advances and Perspectives in the Treatment of B-Cell Malignancies.

TL;DR: B-cell malignancies arise from different stages of B-cell differentiation and constitute a heterogeneous group of cancers including b-cell lymphomas, Bcell leukemias, and plasma cell dyscrasias.
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Prognostic Stratification of Multiple Myeloma Using Clinicogenomic Models: Validation and Performance Analysis of the IAC-50 Model

TL;DR: IAC-50 emerges as a powerful risk stratification model which might be considered forrisk stratification in newly diagnosed myeloma patients, in the context of clinical trials but also in real life.
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The Role of DNA Repair in Genomic Instability of Multiple Myeloma

TL;DR: How unrepaired DNA damage due to aberrant DNA repair response in MM exacerbates genomic instability and chromosomal abnormalities, enabling MM progression and drug resistance is highlighted.
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High Carbohydrate Diet Is Associated with Severe Clinical Indicators, but Not with Nutrition Knowledge Score in Patients with Multiple Myeloma

TL;DR: In this article, the authors assessed nutrition knowledge and diet quality in a group of patients with a diagnosis of multiple myeloma and found that patients with high carbohydrate or low carbohydrate intake showed significant alteration of clinical parameters, such as hemoglobin, uric acid, albumin, total proteins, beta-2 microglobulin, percentage of plasmacytes in the bone marrow and D-dimers, compared to patients in the medium carbohydrate intake tertile.
References
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Journal ArticleDOI

Frailty in Older Adults Evidence for a Phenotype

TL;DR: This study provides a potential standardized definition for frailty in community-dwelling older adults and offers concurrent and predictive validity for the definition, and finds that there is an intermediate stage identifying those at high risk of frailty.
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Signatures of mutational processes in human cancer

Ludmil B. Alexandrov, +84 more
- 22 Aug 2013 - 
TL;DR: It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.
Journal ArticleDOI

A global clinical measure of fitness and frailty in elderly people

TL;DR: The ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools are determined.
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