환자-교차 연구(Case-Crossover Design)의 이론과 활용 · 2016. 4. 18. · A case-crossover study design is a method to assess the effect of transient exposures on the risk
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1
서 론
- (Case-crossover design) 1991
Maclure
[1].
, ,
.
.
-
,
.
-
. -
.
본 론
1. 환자-교차 연구 설계의 정의와 개발 배경
(‘A dictionary of epidemiology’4 )
‘ - ’ -
( )
[2].
-
.
. -
1991 [1],
“
?” .
- (“The Onset Study”)
.
.
, ,
(‘healthy-volunteer bias’)
.
,
(‘healthy-day bias’) .
( )
( ,
, , , )
.
,
. ,
,
. , ( )
, ( )
환자-교차 연구(Case-Crossover Design)의 이론과 활용
기모란
을지대학교 의과대학 예방의학교실
지상강좌
2
. ,
. , ‘
’( ) ‘ ’(
)
. (
) ( )
-
[3].
2. 환자-교차 연구 설계의 기본 개념
.
(crossover)
.
-
.
.
- -
. -
, -
. ,
-
.
,
. - ,
, 1
.
-
.
A
Comparison
Physical Activity in Control
Period, One Day Before MI
Physical Activity in HazardPeriod, One Hour Before MI
Hours Prior to MI Onset
25 24 1 Hr 0
MI
B
Comparison
Hours Prior to MI Onset26 1 Hr 0
MI
C
Comparison
MI
Months Prior to MI Onset12 1 Hr 0
Usual Frequency of Exposure During Past Year
Fig.Fig.Fig.Fig. 1.1.1.1. Schematic representation of control selection in case-crossover studies. It is assumed arbitrarily that the physical activity effect on risk of myocardial infarction (MI) lasts 1 hour. A) 1:1 pair-matched interval approach, B) 1:4 pair-matched intervals approach, C) Usual frequency approach
3
- (person-time)
. -
(average incidence rate ratio) .
100 -
100
[1].
- Fig. 1 .
(hazard
period case period) ,
(control period referent
period) , (
) (Fig. 1 A).
-
.
1:M (Fig. 1 B),
1
(Fig. 1 C).
1 2*2
.
1 , 2
,
2 22
.
. 1
1, 0
. (rate ratio) 1/0 2/
22 . 1
22
0/1 2/22 0
(Fig. 2). 2*2
.
. Table 1
1
10 [1].
9
2 .
0:1 ,
(1 730 , 8036
) 730:8036 .
20
1 .
1:0
365:8401 . 10
(Mantel Haenszel estimates)
8401+5116=13517 , 730+36+1820+2920+24
+730+730+365=7355 , 1.8(95% :
Within 1 hour of last physical Activity
Yes No
Myocardial Infarction 1 0
Person - hours 2 22
Rate ratio ∞
n
Within 1 hour of last physical Activity
Myocardial Infarction Yes No
Person - hours 0 1
Rate ratio 2 22
n 0
Fig.Fig.Fig.Fig. 2.2.2.2. Two by two tables of case-crossover studies. Hypothetical data from a patient who reported physical activity 2 hours per day and suffered a myocardial infarction. Up: less than 1 hour after last physical activity, down: more than 1 hour after last physical activity.
4
0.35-9.8) .
3. 환자-교차 연구 설계의 활용
- .
[4], [5],
[6], [7], [8] .
-
[9-13]
30 .
[14-16] .
-
1997 New England Journal of Medicine
(NEJM) Redelmeier Tibshirani
[17].
-
1999 -
[18] [19]
,
[20] 100
.
,
[21].
MMR( , , )
.
MMR
,
.
Urabe
SubjectLast time Usual
Observed Odds*
Expected Odds*
before MI frequency
1 9 hours 2 /day 0:1 730:8,036
2 20 minutes 1 /day 1:0 365:8,401
3 3 hours 3 /month 0:1 36:8,736
4 22 hours 5 /day 0:1 1,820:6,946
5 6 hours 8 /day 0:1 2,920:5,846
6 7 hours 2 /month 0:1 24:8,742
7 12 hours 2 /day 0:1 730:8,036
8 5 hours 2 /day 0:1 730:8,036
9 <1 hour 10 /day 1:0 3,650:5,116
10 24 hours 1 /day 0:1 365:8,401
Mantel-Haenszel estimate
of relative risk
Numerator:
Denominator:
Ratio
13,517
7,355
= 1.8
(95 % confidence interval) (0.35-9.8)
* The observe odds (1:0 or 0:1) are the odds that exposure was less than one hour before onset of myocardial infarction. The expected odds
are the odds that a random event during the past year would have fallen within one hour after an episode of exposure. The effect-period
after the hypothesized trigger is here assumed to be one hour long, with a minimum induction time of zero.
Table Table Table Table 1.1.1.1. Case-crossover study of the Myocardial Infarction (MI) onset data from The Onset Study (1).
5
am 9 Hoshino
.
, Urabe am
9 Hoshino
.
Fig. 3
2*2 .
,
a . b, c,
d .
a+b . c
d .
( MMR 90%
.) c, d
( , )
.
.
-
.
-
Fig. 4 . 1
0-42
, 43-365
. 6
.
-
MMR
12-15 . -
(time trend)
.
MMR
,
Illness or Syndrome
Yes No
Vaccination
Yes a b
No c d
Fig.Fig.Fig.Fig. 3.3.3.3. Two by two table for vaccine adverse events studies.
Comparison
MMR vaccination in controlperiod during past year
MMR vaccination in hazardperiod before Meningitis
Meningitis
365d 42d 0
Duration of time prior toMeningitis onset, day
Fig.Fig.Fig.Fig. 4.4.4.4. Case-crossover study design for MMR vaccination and aseptic meningitis [23].
6
. , (age-depe-
ndent) (time-dependent)
.
, .
3
,
.
Farrington
[23].
- MMR
,
2.17(95% : 1.22-3.85) .
Urabe am 9 Hoshino MMR
5.54 (95% : 2.60-11.8)
. Jeryl Lyn Rubini
MMR
0.60 (95% : 0.18-1.97)
.
, 1998 1 3
441 37
.
8.4% .
Urabe am 9
Hoshino MMR
. Jeryl
Lynn MMR .
4. 환자-교차 설계 적용시 고려해야 할 기준
-
( )
,
.
( )
.
, ,
,
- .
, .
- .
(Acute hemorrhagic
fever with renal syndrome)
7-34 , 35-60
[24]. MMR
, 1-42
, 42-365
MMR [22].
‘ ’, ‘ ’, ‘ ’
1-2
. ‘
’
,
[3].
-
( ) .
.
, 3 [22]
MMR
.
365 , 366-730
.
7
- - -
(case-time-control) [25].
,
- .
.
, 30
. 1
15 [3].
, -
.
-
.
, ,
-
.
-
- .
(pilot study) .
,
,
( ,
) .
.
-
. , ,
[17]. MMR
,
( ) [22].
5. 환자-교차 설계시 통계 분석
, -
- .
-
.
,
.
,
,
. 2*2
(concordance pair)
.
.
-
(overmatching) .
-
[3]. - 1:4
, -
(
)
.
, 1
.
- 1:4
35% ,
100 40%
[26].
8
-
- . 2*2
Fig. 2 -
(aiNoi/Ti) / (biN1i/Ti) .
(subgroup analysis) ,
(homogeneity test)
. (condit-
ional logistic regression analysis) . MMR
(person-years)
[27].
-
.
6. 환자-교차 연구 설계의 제한점
- -
. 1) .
-
. 2)
(carry-over effect)
. , -
. 3)
. ,
. 4)
.
-
- (recall
bias) .
(selection bias) . -
. -
.
(time trend)
(24 , ),
.
[21].
- (bidirectional case-crossover
designs)
.
결 론
(case-only study) -
.
. -
.
.
ai bi
N1i N0i
Ti
Fig.Fig.Fig.Fig. 5.5.5.5. Notations for Mantel-Haenszel estimates in case-crossover studies. Mantel-Haenszel Estimates = (ai Noi/Ti) / (bi N1i/Ti)
9
.
.
-
, -
.
참고문헌
1. Maclure M. The case-crossover design: a method
for studying transient effects on the risk of acute
events. Am J Epidemiol 1991;133(2):144-53.
2. Last JM, Spasoff RA, Harris SS, Thuriaux MC,
International Epidemiological Association. A
dictionary of epidemiology. 4th ed. Oxford ; New
York: Oxford University Press; 2001.
3. Maclure M, Mittleman MA. Should we use a
case-crossover design? Annu Rev Public Health
2000;21:193-221.
4. Mittleman MA, Maclure M, Tofler GH, Sherwood
JB, Goldberg RJ, Muller JE. Triggering of acute
myocardial infarction by heavy physical exertion.
Protection against triggering by regular exertion.
Determinants of Myocardial Infarction Onset
Study Investigators. N Engl J Med 1993;329(23)
:1677-83.
5. Mittleman MA, Maclure M, Sherwood JB, Mulry
RP, Tofler GH, Jacobs SC, et al. Triggering of
acute myocardial infarction onset by episodes of
anger. Determinants of Myocardial Infarction
Onset Study Investigators. Circulation 1995;92(7):
1720-5.
6. Muller JE, Mittleman MA, Maclure M, Sherwood
JB, Tofler GH. Triggering myocardial infarction
by sexual activity. Low absolute risk and prev-
ention by regular physical exertion. Determinants
of Myocardial Infarction Onset Study Investig-
ators. Jama 1996;275(18):1405-9.
7. Mittleman MA, Mintzer D, Maclure M, Tofler GH,
Sherwood JB, Muller JE. Triggering of myocardial
infarction by cocaine. Circulation 1999;99(21):
2737-41.
8. Mittleman MA, Lewis RA, Maclure M, Sherwood
JB, Muller JE. Triggering myocardial infarction by
marijuana. Circulation 2001;103(23):2805-9.
9. Vinson DC, Maclure M, Reidinger C, Smith GS.
A population-based case-crossover and case-control
study of alcohol and the risk of injury. J Stud
Alcohol 2003;64(3):358-66.
10. Roberts I, Marshall R, Lee-Joe T. The urban traffic
environment and the risk of child pedestrian injury:
a case-crossover approach. Epidemiology 1995;6
(2):169-71.
11. Petridou E, Mittleman MA, Trohanis D, Dessypris
N, Karpathios T, Trichopoulos D. Transient exposures
and the risk of childhood injury: a case-crossover
study in Greece. Epidemiology 1998;9(6):622-5.
12. Cherpitel CJ, Ye Y. Alcohol-attributable fraction
for injury in the U.S. general population: data from
the 2005 National Alcohol Survey. J Stud Alcohol
Drugs 2008;69(4):535-8.
13. Vegso S, Cantley L, Slade M, Taiwo O, Sircar K,
Rabinowitz P, et al. Extended work hours and risk
of acute occupational injury: A case-crossover
study of workers in manufacturing. Am J Ind Med
2007;50(8):597-603.
14. Barbone F, McMahon AD, Davey PG, Morris AD,
Reid IC, McDevitt DG, et al. Association of
road-traffic accidents with benzodiazepine use.
Lancet 1998;352(9137):1331-6.
15. Viboud C, Boelle PY, Kelly J, Auquier A, Schlin-
gmann J, Roujeau JC, et al. Comparison of the
statistical efficiency of case-crossover and case-