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Deletion of the 1p32 region is a major independent prognostic factor in young patients with myeloma: the IFM experience on 1195 patients

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TLDR
The data show that 1p22 and 1p32 deletions are major negative prognostic factors for PFS and OS for patients with MM, and it is suggested that 1 p32 deletion should be tested for all patients at diagnosis.
Abstract
Deletions of the 1p region appear as a pejorative prognostic factor in multiple myeloma patients (especially 1p22 and 1p32 deletions) but there is a lack of data on the real impact of 1p abnormalities on an important and homogeneous group of patients. To address this issue we studied by fluorescence in situ hybridization (FISH) the incidence and prognostic impact of 1p22 and 1p32 deletions in 1195 patients from the IFM (Institut Francophone du Myelome) cell collection. Chromosome 1p deletions were present in 23.3% of the patients (271): 15.1% (176) for 1p22 and 7.3% (85) for 1p32 regions. In univariate analyses, 1p22 and 1p32 appeared as negative prognostic factors for progression-free survival (PFS): 1p22: 19.8 months vs 33.6 months (P<0.001) and 1p32: 14.4 months vs 33.6 months (P<0.001); and overall survival (OS): 1p22: 44.2 months vs 96.8 months (P=0.002) and 1p32: 26.7 months vs 96.8 months (P<0.001). In multivariate analyses, 1p22 and 1p32 deletions still appear as independent negative prognostic factors for PFS and OS. In conclusion, our data show that 1p22 and 1p32 deletions are major negative prognostic factors for PFS and OS for patients with MM. We thus suggest that 1p32 deletion should be tested for all patients at diagnosis.

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Citations
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Journal ArticleDOI

IMWG consensus on risk stratification in multiple myeloma

TL;DR: The International Myeloma Working Group proposes well-defined and easily applicable risk categories based on current available information and suggests the use of this set of prognostic factors as gold standards in all clinical trials and form the basis of subsequent development of more complex prognostic system or better prognostic Factors.
Journal ArticleDOI

Evolutionary biology of high-risk multiple myeloma

TL;DR: This Review discusses end-stage high-risk disease states and how new information is improving the understanding of their evolutionary trajectories, how they may be diagnosed and the biological behaviour that must be addressed if they are to be treated effectively.
Journal ArticleDOI

Interpretation of cytogenetic results in multiple myeloma for clinical practice

TL;DR: A review of how multiple myeloma is classified into specific subtypes based on primary cytogenetic abnormalities is provided to provide a concise overview of how to interpret cytogenetics abnormalities based on the disease stage to aid clinical practice and patient management.
Journal ArticleDOI

Interpreting clinical trial data in multiple myeloma: translating findings to the real-world setting

TL;DR: The complexity of interpreting data across clinical studies in MM, as well as between clinical studies and routine-care analyses, is demonstrated to help clinicians consider all the necessary issues when tailoring individual patients’ treatment approaches.
References
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Journal ArticleDOI

A note on quantifying follow-up in studies of failure time

TL;DR: It is shown that values of median follow-up may differ substantially depending on the method used, and standard analytical methods for survival data, such as the log-rank test 121, the generalized Wilcoxon test, or the proportional hazards model 141, estimate average effects for the observed response times and test those effects for significance.
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