Table 1 Patient characteristics
From: Deep learning identifies Acute Promyelocytic Leukemia in bone marrow smears
parameter | non-APL AML | APL | Bone marrow donors |
|---|---|---|---|
N | 1 048 | 58 | 236 |
Age, median (IQR) | 57 (49–67) | 50.5 (42.25–58) | 31 (25–39) |
Sex, % | |||
Male | 45.5 | 45.7 | 70 |
Female | 54.5 | 54.3 | 30 |
AML type, % | |||
de novo | 77.5 | 90.5 | / |
sAML | 13.6 | 0 | / |
tAML | 8.9 | 9.5 | / |
ELN2017 risk, % | |||
Favorable | 34.1 | / | / |
intermediate | 44.7 | / | / |
adverse | 21.2 | / | / |
WBC in GPt/l, median (IQR) | 14 (2.7–45.2) | 1.3 (0.7–6.4) | / |
Hb in mmol/l, median (IQR) | 5.8 (5.0–6.8) | 6.3 (5.3–6.9) | / |
Hb in g/dl, median (IQR) | 9.3 (8.1–11.0) | 10.1 (8.5–11.1) | / |
Plt in GPt/l, median (IQR) | 56 (31–103) | 27 (18–57) | / |
PB blasts, median (IQR) | 27 (6–62) | 14.75 (1.3–63) | / |
BM blasts, median (IQR) | 63.5 (41.5–80) | 63 (53.5–76) | / |