資料的評讀(II)
診斷與篩檢
神經內科 王志弘
診斷的過程
1.Initiation of diagnosis hypothesis
初步診斷
我想這病人可能有 。。。
2.Refinement of the diagnostic causes
修正診斷
他可能不是X 或 Y ，但到底是何種感染呢？
Narrowing the possibilities
3.Defining the final diagnosis
最終診斷
我們應該再做個［XX 切片］確定，再來治療
初步診斷
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目前有上萬種的診斷疾病
如果我們不認識這個疾病，我們就不可能考慮到
這個診斷
關於疾病發生比例的文獻，讓我們了解各種診斷
的可能性（pretest probability）
修正診斷
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根據
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Symptoms, 症狀
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Signs, 徵象
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Laboratory tests, 實驗室檢查
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Imaging, 影像檢查
診斷性試驗的實證
Evidence about “diagnostic tests”
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Is this evidence about the accuracy of
diagnostic test valid?
Is this (valid) evidence show that the test is
useful at all?
How can I apply this valid, accurate
diagnostic test to a specific patient?
文獻評讀
治療性
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●
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Validity (closeness to
the truth)
Impact (size of the
effect)
診斷性
●
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Applicability
(usefulness in our
clinical practice)
●
Is this evidence about
the accuracy of
diagnostic test valid?
Is this (valid)
evidence show that
the test is useful at
all?
How can I apply this
valid, accurate
Valid
Useful
Apply
什麼是『正常』
BNP vs
LV dysfunction
Is this evidence about the
accuracy of a diagnostic test
valid?
Validity about Diagnostic Tests
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●
Diagnostic Test in
Question
Reference (gold)
standard
常見的 GOLD STANDARDS
1. 外科或是病理標本
2. 血液培養的菌株
3. 風溼熱， Jones Criteria
4. DSM IV (精神疾病)
5. X 光
6. 長期追蹤
代表性
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該檢查是否在適當的病患族群中被評估過（尤其
是那些在臨床上會使用此一檢查的對象）
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Representative
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common presentation of the target disorder
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confusing presentations
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include patients, with mild and severe, early and
late, treated and untreated cases.
確定性
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無 論 檢 查 結 果 如 何 ， 參 考 標 準 （ reference
standard）是否經過確認
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如何達到確定診斷?
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另一個參考標準
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長期追蹤
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確定不會延誤治療
測量
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Independent and blind measurement
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Psychiatric disorders
Is this (valid)
evidence show that
the test is useful at
all?
Sensitivity,
Specificity,
Likelihood ratios
整體盛行率
Prevalence
= ( a + c) / ( a + b + c +d ) = 809 / 2579 = 31%
Pre-test probability
Positive predictive value
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陽性預測值= a / (a + b) = 731 / 1001 = 73%
檢查陽性（ferritin < 65）的人當中，真正有病~
（缺鐵性貧血）的人的比例
Negative predictive value
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陰性預測值= d / (c + d) = 1500 / 1578 = 95%
檢查陰性（ferritin > 65）的人當中，真正沒有病
~（缺鐵性貧血）的人的比例
Positive vs
Negative Predictive Value
Pre-test probability: 測前機率
Post-test probability: 測後機率
根據前兩張slide：
– Positive predictive value: 73%
– Negative predictive value: 95%
假設抽血檢查前病人(有病)的測前機率：50%
如果陽性反應 測後機率：73%
如果陰性反應 測後機率： 1-95% = 5%
Sensitivity
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敏感度= a / (a + c) = 731 / 809 = 90%
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真正有病的人當中，檢查有問題（陽性）的比例
Specificity
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特異度= d / (b + d) = 1500 / 1700 = 85%
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真正沒病的人當中，檢查沒問題（陰性）的比例
Likelihood Ratio
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可能性比率
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陽性結果的可能性比率
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LR+ = (出現目標疾病的病人中，檢查結果為陽
性的可能性） / (沒有出現目標疾病的病人中，檢
查結果為陽性的可能性）
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= 敏感度 / (1- 特異度)
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= 90% / (1-85%) = 6
Likelihood Ratio
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陰性結果的可能性比率
LR- = (出現目標疾病的病人中，檢查結果為陰性
的可能性） / (沒有出現目標疾病的病人中，檢查
結果為陰性的可能性）
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= (1-敏感度) / 特異度
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= (1-90%) / 85% = 0.12
勝算 vs 機率
• Odds vs Probability
• 假設有病與沒病的機率分別是 31%，69%
• 則有病的勝算為：31%/69% = 0.45
• Study pre-test odds = prevalence / (1prevalence)
Post-test Odds
測後勝算
• LR+ = (出現目標疾病的病人中，檢查結果為陽
性的可能性） / (沒有出現目標疾病的病人中，檢
查結果為陽性的可能性）
• LR+(ferritin)= sensitivity/(1-specificity) =
90%/15%=6
• 測後勝算(陽性反應)
• = 測前勝算 * LR+ =1 * 6 = 6
• 測後勝算(陰性反應) = 測前勝算 * LR-
Post-test Odds vs Probability
• 測後機率 = 測後勝算 / (測後勝算+1)
• Study pre-test odds = 0.45
• Study post-test odds = 0.45 *6 = 2.7
• Study post-test probability = 2.7 /(2.7+1) = 73%
Post-test Odds , Probability (陰性)
• 測後機率 = 測後勝算 / (測後勝算+1)
• Study pre-test odds = 0.45
• Study post-test odds = 0.45 *0.12 = 0.054
• Study post-test probability(有病) = 0.054/(0.054+1) =
5%
• 測後沒病機率 = 1-5% = 95%  negative predictive
value
個人化調整
病患測後勝算
= 研究測後勝算 * (病患測前勝算/研究測前勝算)
檢查是否有用
Sensitivity 敏感度, Specificity 特異度
兩者相加減掉100% (Youden Index)
至少要大於 0, 最好要大於 50%, 理想值是 100%
Rule in / Rule out
SnNout:
– high sensitivity, negative result rule out the diagnosis
SpPin:
– high specificity, positive result rule in the diagnosis
LR+ = sensitivity / (1-specificity)
LR- = (1-sensitivity) /specificity
D-dimer vs Deep Vein Thrombosis
Sensitivity: 97.7% Specificity: 46%
Ferritin vs Iron deficiency anemia
Sensitivity: 90%, specificity: 85%
How can I apply
this valid,
accurate
diagnostic test to
a specific
patient?
Is the diagnostic tests
Available
Affordable
Accurate
Precise
In our setting
Patients Pre-Test Probability
• From personal experience, prevalence
statistics, practice database, primary
studies
• The study patients similar to our own ?
• If the disease probability changes after the
evidence
Results Affect our management?
1. Move us across a test-treatment threshold
2. Our patient willing to carry it out
3. The consequence of the test help the
patient reach his/her goal
Multilevel likelihood ratios
Multiple Tests
Prediction rule
SCREENING
Screening
Case-finding
Early diagnosis of presymptomatic disease
among well individual in
public
Early diagnosis of presymptomatic disease
among patients who came
to us for other unrelated
diseases
Harm of Early Diagnosis
• Label: high risk for developing some disease
• False positive screening test
• Early diagnosis may not make
people live longer, but it surely
makes all of them “sick” longer.
Screening 有效嗎?
通常願意來接受篩檢的人，對醫囑的遵從性較高
 自然預後較好
早期診斷通常會找到進展較慢的疾病
Diagnostic test
診斷不是用來發現絕對的事實
是用來減少臨床診斷的不確定性