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Table 3 Performance metrics for determining breast cancer recurrence using pre-specified variable algorithm and conditional tree algorithms

From: Evaluation of algorithms using administrative health and structured electronic medical record data to determine breast and colorectal cancer recurrence in a Canadian province

 

Pre-defined variable algorithm, % (95% CIc)

Conditional tree algorithm, % (95% CI)

Training cohort (N = 933)

Validation cohort (N = 1811)

Training cohort (N = 933)

Validation cohort (N = 1811)

 

Unweighted

Weighted

 

Unweighted

Weighted

Sensitivity

83.3 (77.9–88.2)

83.2 (77.2–88.6)

81.1 (77.4–84.8)

78.0 (72.0–83.9)

73.7 (67.1–79.7)

68.5 (64.6–72.4)

Specificity

89.7 (85.0–93.6)

92.5 (88.1–95.8)

93.2 (90.6–95.4)

95.7 (92.5–98.4)

96.4 (93.4–98.8)

97.0 (95.4–98.5)

PPVa

66.8 (57.9–76.7)

64.7 (54.0–76.8)

61.4 (53.7–70.2)

81.9 (72.0–92.4)

73.7 (63.5–91.1)

75.4 (66.3–85.7)

NPVb

96.0 (94.2–96.9)

97.1 (96.1–98.0)

97.4 (96.8–97.9)

94.6 (93.2–96.0)

96.4 (94.7–96.7)

95.8 (95.3–96.3)

Correct classification

88.4 (84.5–91.9)

91.1 (87.6–94.2)

91.8 (89.4–93.8)

92.2 (89.5–94.6)

93.1 (90.3–95.6)

93.6 (92.1–94.9)

Scaled Brier

0.27 (0.03–0.49)

0.27 (−0.03–0.53)

0.21 (−0.01–0.40)

0.51 (34.2–66.4)

0.44 (0.20–0.64)

0.39 (0.24–0.51)

  1. aPositive predictive value
  2. bNegative predictive value
  3. cConfidence interval