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Table 1 Numerical illustration for calculating RPB of hypothetical binary markers using data of three cancers as examples

From: Quantification of population benefit in evaluation of biomarkers: practical implications for disease detection and prevention

Biomarker/exposure characteristics Ratio of population benefit (RPB) Net benefit (NB)
OR Prevalence (%) PAR% Sen. Spe. RPB RPB RPB NB NB NB
(EA, f 0.03) (Breast ca, f 0.06) (Ovarian ca, f 0.15) (EA, f 0.03) (Breast ca, f 0.06) (Ovarian ca, f 0.15)
1.5 0.1 0.05 0.001 0.999 -0.000 -0.001 -0.001 -0.000 -0.000 -0.000
2 0.1 0.10 0.002 0.999 -0.000 -0.001 -0.001 -0.000 -0.000 -0.000
4 0.1 0.29 0.004 0.999 0.000 -0.000 -0.001 0.000 -0.000 -0.000
10 0.1 0.81 0.009 0.999 0.002 0.001 -0.000 0.000 0.000 -0.000
20 0.1 1.56 0.017 0.999 0.004 0.002 0.000 0.000 0.000 0.000
50 0.1 3.19 0.033 0.999 0.008 0.004 0.001 0.000 0.000 0.000
1.5 1 0.49 0.015 0.990 -0.004 -0.006 -0.008 -0.000 -0.000 -0.001
2 1 0.97 0.020 0.990 -0.002 -0.006 -0.008 0.000 -0.000 -0.001
4 1 2.81 0.038 0.990 0.002 -0.003 -0.007 0.000 -0.000 -0.001
10 1 7.61 0.085 0.991 0.015 0.004 -0.003 0.001 0.000 -0.001
20 1 13.93 0.148 0.991 0.031 0.014 0.001 0.001 0.001 0.000
50 1 26.33 0.271 0.993 0.063 0.033 0.010 0.002 0.002 0.002
1.5 10 4.70 0.142 0.900 -0.039 -0.065 -0.084 -0.002 -0.004 -0.013
2 10 8.94 0.180 0.901 -0.029 -0.059 -0.082 -0.001 -0.004 -0.013
4 10 22.54 0.303 0.902 0.003 -0.040 -0.073 0.000 -0.003 -0.012
10 10 46.05 0.514 0.904 0.058 -0.008 -0.057 0.002 -0.001 -0.009
20 10 63.92 0.675 0.906 0.100 0.017 -0.046 0.004 0.001 -0.007
50 10 81.79 0.836 0.907 0.141 0.041 -0.034 0.006 0.003 -0.005
1.5 30 12.90 0.390 0.701 -0.125 -0.200 -0.256 -0.005 -0.014 -0.041
2 30 22.80 0.460 0.702 -0.107 -0.189 -0.251 -0.004 -0.013 -0.040
4 30 46.84 0.628 0.703 -0.064 -0.163 -0.238 -0.003 -0.011 -0.038
10 30 72.43 0.807 0.705 -0.017 -0.136 -0.225 -0.001 -0.009 -0.036
20 30 84.69 0.893 0.706 0.005 -0.123 -0.219 0.000 -0.009 -0.035
50 30 93.44 0.954 0.707 0.021 -0.114 -0.215 0.001 -0.008 -0.034
1.5 70 25.71 0.777 0.301 -0.327 -0.486 -0.606 -0.013 -0.034 -0.096
2 70 40.89 0.823 0.301 -0.316 -0.480 -0.603 -0.013 -0.033 -0.096
4 70 67.46 0.902 0.302 -0.295 -0.467 -0.597 -0.012 -0.032 -0.095
10 70 86.14 0.958 0.303 -0.280 -0.459 -0.593 -0.011 -0.032 -0.094
20 70 92.92 0.979 0.303 -0.275 -0.456 -0.591 -0.011 -0.032 -0.094
50 70 97.13 0.991 0.303 -0.272 -0.454 -0.591 -0.011 -0.031 -0.094
  1. ca= cancer. EA= esophageal adenocarcinoma. f= loss adjustment factor of quality-adjusted life year. NB= net benefit. OR= odds ratio.
  2. The table shows numerical relationship between Odds ratio, Marker prevalence, PAR% of binary markers and their RPB based on the cancer data of three studies. NB were also calculated.
  3. The table assumes 1% disease prevalence in general population. For PAR%, sensitivity and specificity similar patterns are observed with other disease prevalence values less than about 10%. Disease prevalence affects RPB more directly (see text).