Interpretation of likelihood ratio
Likelihood ratios help in assessing the effect of a diagnostic test on the probability of disease.
- Positive likelihood ratio (effect of a positive test on the probability of disease) is calculated as: Sensitivity/1-Specificity
- Negative likelihood ratio (effect of a negative test on the probability of disease) is calculated as: 1-Sensitivity/specificity
Likelihood ratios >1 show association with disease; whereas, ratios <1 show association with lack of disease.
The table below is an estimate demonstrating the effect of likelihood ratio on probability of disease:
| Likelihood ratio | Change in likelihood of disease after test |
| >10 | Large increase |
| 5 - 10 | Moderate increase |
| 2 – 5 | Small increase |
| 1 – 2 | Minimal increase |
| 1 | No change |
| 0.5 – 1.0 | Minimal decrease |
| 0.2 – 0.5 | Small decrease |
| 0.1 - 0.2 | Moderate decrease |
| <0.1 | Large decrease |
Resistance to fluoroquinolones, beta-lactams and trimethoprim-sulfamethoxazole is escalating. First-line treatment for UTI include nitrofurantoin, fosfomycin and trimethoprim-sulfamethoxazole (when resistance levels are <20%). These antimicrobial agents exhibit minimal collateral damage and resistance. Future improvement in diagnostic assessment would facilitate better differentiation of active infection from colonization and to diagnose infection in patients with baseline urinary symptoms.