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Burkitt lymphoma (BL) has unique biological characteristics and clinical course, but lacks standardized prognostic models.
olszewski and others have developed and validated a new prognossis index specific to BL to help with risk stratified, clinical trial interpretation, and targeted development of new treatments.
researchers used a real data set of adult BL patients receiving immunotherapy chemotherapy in the United States between 2009 and 2018 to establish the BL International Prognostic Index (BL-IPI) and identify candidate variables with the strongest prognostic correlation with progressive survival (PFS).
the index was validated in external data set for patients treated in Europe, Canada and Australia between 2004 and 2019.
BL-IPI characteristics in the development queue in 633 BL patients in the development queue, age ≥40 years old, exercise status≥2, serum lactic acid dehydrogenase and 3 times normal upper limit, central nervous system (CNS) burden and other weighting factors have independent prognostic value.
BL-IPI based on the above factors divided adult BL patients into three risk groups: the low risk group (zero risk factor, 18 percent of patients), the medium risk group (one factor, 36 percent of patients) and the high risk group (≥2 factors, 46 per cent of patients), the three risk groups are estimated to have three-year survival rates of 92 per cent, 72 per cent and 53 per cent, respectively, and the three-year total survival rates are estimated to be 96 per cent, 76 per cent and 59 per cent, respectively.
use this index to distinguish patient prognostication and is independent of HIV status, phased or first-line chemotherapy programs.
BL-IPI performance in the validation queue of 457 patients, patient characteristics, BL-IPI grouping relative size and prognostic identification are consistent with the development queue, BL-IPI low, medium and high risk groups of 3 years PFS estimated at 96%, 82% and 63%, respectively.
, BL-IPI has a strong prognostication of survival in adult BL patients, and is suitable for predicting and stratiting clinical trials.
treatment in high-risk groups is not effective and new treatments should be considered.
