Table 2 Cox regression models for the associations between tumour necrosis percentage and survival in Cohorts 1 and 2.

From: Immunological and prognostic significance of tumour necrosis in colorectal cancer

 

Cancer-specific survival

Overall survival

Tumour necrosis percentage

No. of cases

No. of events

Univariable HR (95% CI)

Multivariable HR (95% CI)

No. of events

Univariable HR (95% CI)

Multivariable HR (95% CI)

Cohort 1

  <3%

100

15

1 (referent)

1 (referent)

42

1 (referent)

1 (referent)

  3–9.9%

577

145

1.73 (1.01–2.94)

1.76 (1.02–3.04)

278

1.19 (0.87–1.65)

1.19 (0.85–1.66)

  10–39.9%

327

107

2.45 (1.43–4.20)

2.35 (1.34–4.11)

173

1.41 (1.01–1.97)

1.44 (1.02–2.04)

  ≥40%

59

28

4.24 (2.27–7.94)

3.22 (1.68–6.17)

37

1.96 (1.26–3.05)

1.88 (1.19–2.97)

  Ptrend

  

<0.0001

<0.0001

 

0.0010

0.0011

Cohort 2

  <3%

61

7

1 (referent)

1 (referent)

22

1 (referent)

1 (referent)

  3–9.9%

105

20

1.67 (0.71–3.94)

1.80 (0.71–4.60)

43

1.13 (0.68–1.89)

1.08 (0.62–1.88)

  10–39.9%

87

32

3.70 (1.63–8.39)

1.85 (0.75–4.55)

47

1.78 (1.07–2.94)

1.10 (0.62–1.96)

  ≥40%

31

17

7.53 (3.12–18.18)

3.39 (1.28–8.96)

21

3.14 (1.72–5.71)

1.70 (0.86–3.36)

  Ptrend

  

<0.0001

0.018

 

<0.0001

0.19

  1. HR hazard ratio, CI confidence interval.
  2. Multivariable Cox regression models were adjusted for age (<65, 65–75, >75), sex (male, female), T (1–2, 3–4), N (0, 1–2), M (0, 1), tumour location (proximal colon, distal colon, rectum), year of operation (Cohort 1: 2000–2005, 2006–2010, 2011–2015; Cohort 2: 2006- Jan. 2010, Feb. 2010–2014), lymphatic or venous invasion (no, yes), grade (low-grade, high grade), MMR status (proficient, deficient), and BRAF status (wild-type, mutant). We excluded patients who died 30 days or less after having surgery (N = 37, in Cohort 1 and N = 3 in Cohort 2). Ptrend values were calculated by using the four ordinal categories of tumour necrosis percentage as a continuous variable in univariable and multivariable Cox proportional hazard regression models.