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Table 3 Performance of the revised ABSST total score at various cut-points* predicting Clinician’s Urologist Referral

From: Development of a short form and scoring algorithm from the validated actionable bladder symptom screening tool

Cut-Point± Odds Sensitivity2 Specificity3 Positive Negative % Warranting c-statistic7
  ratio1      referral6  
     Predictive value (%)4 Predictive value (%)5   
>= 21   . 2.04 100.00 100.0 68.0 68.2 0.510
>= 9 55.53 69.39 96.08 89.5 86.7 87.4 0.827
>= 6 81.43 85.71 93.14 85.7 93.1 90.7 0.894
>= 4 33.54 93.88 68.63 59.0 95.9 76.8 0.813
>= 1 8.28 97.96 14.71 35.6 93.8 41.7 0.563
  1. * Only quartiles and key cut points are displayed in the table.
  2. The cut point is defined as different total raw scores on the ABSST ranging from 0 to 24.
  3. 1 The odds ratio was defined as those MS patients more likely to be referred to a urologist than not. Values > 1 indicated that the patient is that many more times (for example 8.28) likely to be referred to a urologist.
  4. 2 The sensitivity refers to those results that are true results (e.g. would refer to a urologist). Minimum criteria was ≥0.75.
  5. 3 Specificity refers to those results that are truly negative results (e.g. would NOT refer to a urologist). Minimum criteria was ≥0.80.
  6. 4 PPV refers to proportion of positive test results that are true positives (e.g. proportion of patients who would warrant a referral to a urologist). Values closer to 100% approximates higher proportion of true positives.
  7. 5 NPV refers to the proportion of negative results that are true negatives (e.g. the proportion of patients who would NOT warrant a referral to a urologist are not referred). Values closer to 100% approximates higher proportions of true negatives.
  8. 6 The percent of classified patients is the percentage of patients who are warranted to be referred to a urologist or not.
  9. 7 The c-statistic is the area under the ROC curve. Values closer to 1 approximate a perfect model.