MUM1 Expression versus Hans Algorithm to Predict Prognosis in Indonesian Diffuse Large B-Cell Lymphoma Patients Receiving R-CHOP

Figures & data

Table 1 Clinical and Molecular Characteristics of DLBCL Patients

Variables	No. of Patients (%)
Gender (n=92)
Male	44 (48)
Female	48 (52)
Age (n=92; median 51.5 years, range 18–79 years)
≤60 years	76 (82)
>60 years	16 (18)
IPI (n=67)
Low (score 0–2)	57 (85)
High (score 3–5)	10 (15)
Protein expression (n=92)
CD10 (30% cut-off)	45 (49)
BCL6 (30% cut-off)	59 (64)
MUM1 (30% cut-off)	85 (92)
Ki67 (70% cut-off)	66 (71)
Subtype based on Hans algorithm (n=92)
GCB	46 (50)
Non-GCB	46 (50)
Event within 24 months (n=92)
Yes	44 (48)
No	40 (43)
No information	8 (9)

Figure 1 Kaplan-Meier survival curve of GCB (1) vs non-GCB (0) subtypes (log rank p = 0.08).

Figure 2 Kaplan-Meier survival curves of CD10 at 10% cut-off increments (A) 10% cut-off (log rank p = 0.274) (B) 20% cut-off (log rank p = 0.270) (C) 30% cut-off (log rank p = 0.127) (D) 40% cut-off (log rank p = 0.370) (E) 50% cut-off (log rank p = 0.546) (F) 60% cut-off (log rank p = 0.383) (G) 70% cut-off (log rank p = 0.273) (H) 80% cut-off (log rank p = 0.253) (I) 90% cut-off (log rank p = 0.370).

Figure 3 Kaplan-Meier survival curves of BCL6 at 10% cut-off increments (A) 10% cut-off (log rank p = 0.445) (B) 20% cut-off (log rank p = 0.195) (C) 30% cut-off (log rank p = 0.112) (D) 40% cut-off (log rank p = 0.209) (E) 50% cut-off (log rank p = 0.322) (F) 60% cut-off (log rank p = 0.333) (G) 70% cut-off (log rank p = 0.503) (H) 80% cut-off (log rank p = 0.916) (I) 90% cut-off (log rank p = 0.424).

Figure 4 Kaplan-Meier survival curves of Ki67 at 10% cut-off increments (A) 10% cut-off (B) 20% cut-off (log rank p = 0.392) (C) 30% cut-off (log rank p = 0.392) (D) 40% cut-off (log rank p = 0.871) (E) 50% cut-off (log rank p = 0.582) (F) 60% cut-off (log rank p = 0.177) (G) 70% cut-off (log rank p = 0.793) (H) 80% cut-off (log rank p = 0.741) (I) 90% cut-off (log rank p = 0.976).

Figure 5 Kaplan-Meier survival curves of MUM1 at 10% cut-off increments (A) 10% cut-off (log rank p = 0.216) (B) 20% cut-off (log rank p = 0.618) (C) 30% cut-off (log rank p = 0.396) (D) 40% cut-off (log rank p = 0.251) (E) 50% cut-off (log rank p = 0.035) (F) 60% cut-off (log rank p = 0.003) (G) 70% cut-off (log rank p = 0.000) (H) 80% cut-off (log rank p = 0.000) (I) 90% cut-off (log rank p = 0.000).

Figure 6 Kaplan-Meier survival curves of IPI (high vs low) (n = 67; log rank p = 0.04), age (old = > 60 years) (n = 92; log rank p = 0.014), and gender (n = 92; log rank p = 0.351).

Figure 7 ROC curve from 67 patients; IPI high vs low (AUC = 0.581), age (AUC = 0.631), gender (AUC = 0.557), CD10 (AUC = 0.425), BCL 6 (AUC = 0.43), MUM1 (AUC = 0.802), Ki67 (AUC = 0.523), GCB subtype (AUC =0.431).

Table 2 Prognostic Value of Several Variables for Event Within 24 Months

Variables	Hazard Ratio (95% Confidence Interval)	p
Model 1
GCB (Hans)	0.764 (0.165–3.541)	0.731
CD10 (increment 1%)	1.000 (0.980–1.021)	0.971
BCL6 (increment 1%)	0.995 (0.986–1.004)	0.308
MUM1 (increment 1%)	1.046 (1.024–1.068)	0.000
Ki67 (increment 1%)	0.987 (0.968–1.006)	0.987
Model 2
GCB (Hans)	0.001 (0.00–2.1 X 10^59)	0.923
CD10 (cut off ≥ 30%)	752.5 (0.00–2.7 X 10^65)	0.928
BCL6 (cut off ≥ 30%)	0.673 (0.370–1.227)	0.196
MUM1 (cut off ≥ 70%)	5.81 (2.27–14.85)	0.000
Ki67 (cut off ≥ 30%)	1138.4 (0.00–1.8 X 10^65)	0.923