Predicting undetectable MRD in newly-diagnosed multiple myeloma

This webpage was designed for predicting undetectable MRD in newly-diagnosed multiple myeloma patients using tumor burden, cytogenetic abnormalities and tumor immune microenvironment biomarkers from a machine learning algorithm. [NEW: The model is now able to impute missing cytogenetic abnormalities and tumor burden (i.e. PC clonality and circulating tumor cells) based on a nearest-neighbor approach. If you are missing these variables, simply type missing]

Please type patients age if you wish to impute variables

Ex. 61; if you do not wish to impute simply type none

del(17p13) and/or t(4;14)

Ex. positive or negative; or missing

Plasma cell clonality

Ex. 0.24 or missing

Absolute number of circulating tumor cells [PB]

Ex. 1.45 or missing

Myeloid Precursors

Ex. 1.63

CD56bright CD27neg NK cells

Ex. 0.23

Eosinophils

Ex. 2.34

CD27neg CD38pos T cells

Ex. 0.35

Mature B cells

Ex. 2.53

Intermediate neutrophils

Ex. 40.6