實證醫學相關名詞

診斷(Diagnosis):

評估診斷試驗,需考慮可信度(Validity)、有效度(Effectiveness)及應用性(Applicability)

常用指標名詞定義


  • 假陽性:是指健康的人診斷試驗結果為不正常,如同無辜的人
  • 假陰性:是指有病的人診斷試驗結果為正常,如同消遙法外的歹徒

 

將真陽性、假陽性、假陰性、真陰性分別以a, b, c, d來表示

  Disease (+) 生病 Disease (-) 健康  
Test Result(+) 陽性 A 真陽性 B 假陽性 A+B
Test Result(-) 陰性 C 假陰性 D 真陰性 C+D
  A+C+B+D A+C+B+D  
  • Sensitivity (敏感度):為有病者診斷結果為陽性的比率
=真陽性率=真陽性 / 生病 = A / A+C
當高靈敏診斷試驗的結果為陰性,此為未罹患此疾病相當可靠的指標
  • Specificity (特異度):為沒病者診斷結果為陰性的比率
=真陰性率=真陰性 / 健康 = D / B+D
在專一性高的診斷試驗,結果陽性即表有病,因為罕見偽陽性
  • Positive Predictive Value, PPV (陽性預測值):為有病者診斷試驗結果呈現陽性的患者比率
=真陽性 / 陽性試驗結果 = A / A+B
  • Negative Predictive Value, NPV (陰性預測值):為無疾病者診斷試驗結果呈陰性的比率
=真陰性 / 陰性試驗結果 = D / C+D
  • Likelihood Ratios (相似比)
分子:疾病中診斷試驗(陽性或陰性)比率

分母:無疾病中診斷試驗(陽性或陰性)比率

LR(+) = Pr{T+/D+} / Pr{T+/D-} =真陽性率 / 假陽性率=Sensitivity / (1-Specificity) = (A/A+C) / (B/B+D)

LR(-) = Pr{T-/D+} / Pr{T-/D-} =假陰性率 / 真陰性率= (1-Sensitivity) / Specificity = (C/A+C) / (D/B+D)

  • Likelihood Ratios (相似比) 數值所代表的臨床意義

 

Likelihood Ratio Interpretation
>10 Strong evidence to rule in disease
5–10 Moderate evidence to rule in disease
2–5 Weak evidence to rule in disease
0.5–2.0 No significant change in the likelihood
0.2–0.5 Weak evidence to rule out disease
0.1–0.2 Moderate evidence to rule out disease
<0.1 Strong evidence to rule out disease

 


處置(Therapy):

  • 對照組事件發生率 (CER, Control Event Rrate)
  • 實驗組事件發生率 (EER, Experimental Event Rrate)
  • 相對風險比率差 (RRR, Relative Risk Reduction) = |EER – CER| / CER 接受治療組比未接受治療的對照組間,不良結果機率下降之比例, 伴隨95%信賴區間(CI) The proportional reduction in rates of bad outcomes between experimental and control participants in a trial, and accompanied by a 95% confidence interval (CI)
  • 絕對風險比率差 (ARR, Absolute Risk Reduction) = |EER – CER| 治療組與對照組間不良結果機率差的絕對值, 伴隨95%信賴區間(CI) Absolute Risk Reduction (ARR) is the difference in the event rate between control group (CER) and treated group (EER).
  • 需要被治療的病人數目 (NNT, Number Needed to Treat) = 1/ARR 為減少一個不良結果所需治療的病人數目, 伴隨95%信賴區間(CI) The number of patients who need to be treated to prevent one bad outcome, and accompanied by a 95% confidence interval (CI) .
  • 需要被治療的病人數目 (NNH, Number Needed to Harm) 與對照組病患相比,接受實驗性治療導致額一位病人被傷害的病人數目, 伴隨95%信賴區間(CI) , 計算方式與NNT相同 The number of patients who, if they received the experimental treatment, would result in one additional patient being harmed, compared with patients who received the control treatment, and accompanied by a 95% CI.

傷害(Harm):

  • 相對危險性 (Relative Risk, RR) = EER(實驗組事件發生率) / CER(對照組事件發生率) (在隨機試驗與世代研究中) 接受治療病人相對於未接受治療病人的不良事件風險 Relative Risk is the ratio of risk in the treated group (EER) to the risk in the control group (CER). RR is used in randomised trials and cohort studies.
  • 勝算 (Odds) 發生某事件的人數與未發生該事件人數的比值 Odds:a ratio of the number of people incurring an event to the number of people who don’t have an event.
  • 勝算比 (Odds Ratio, OR) (在病例對照研究中) 實驗組中發生疾病的勝算與控制組中發生疾病的勝算比值, 或罹患疾病的病患暴露於某變因的勝算除以控制組暴露的勝算 Odds Ratio is the ratio of the odds of having the target disorder in the experimental group relative to the odds in favour of having the target disorder in the control group or the odds in favour of being exposed in subjects with the target disorder divided by the odds in favour of being exposed in control subjects (without the target disorder).
  • 信賴區間 (Confidence Interval, CI) 有95%的信心確定,群體的正確數值會落在這個數值範圍內 Quantifies the uncertainty in measurement. It is usually reported as a 95% CI which is the range of values within which we can be 95% sure that the true value for the whole population lies.
  • 暴露與不良結果的相關性 RR 或 OR= 1 表示無論有無暴露於假設因子中, 發生不良結果的可能性一樣 RR 或 OR > 1 表示暴露於假設因子中導致不良結果的風險增加 RR 或 OR< 1 表示暴露於假設因子者比未暴露於假設因子者更不可能發生不良結果 病例對照研究(Case-control study)的偏差(bias)較多, 因此當 OR > 4 較有意義. 世代研究(Cohort study)較嚴謹, 但仍會有偏差(bias)存在, RR > 3 時較有意義. 除考慮RR與OR的數值大小, 必須由信賴區間 (Confidence interval, CI)來確認其值地準確度. 當信賴區間越窄, 結果準確度越高.
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