Evidence based healthcare special lecture I Final mini-test(Answer)

18th July 2018, 18:30-20:00, D101

1. Please specify the wrong points in explanation and/or method to analyze and suggest how to improve it(if no wrong point, answer so) for each issues underlined below.
(1) In R island with population size of about 4,000 in a developing country. When we see there with Google
Earth, almost equal-sized 40 villages are scattered. Recently the people with high fish and whale intake
are reported to suffer from neural damage symptoms. Due to the possibility of mercury poisoning, (A) 4villages were randomly selected from 40 villages, and in those 4 villages, all 400 residents were recruited tojoin the survey. They were interviewed about the frequency of fish/whale intake, such as [1] none or rarely,[2] monthly, [3] weekly, [4] daily, and the hair mercury concentrations of them were measured. The results(of which raw data are available from http://minato.sip21c.org/fish-Hg-2018.txt; variables are PID as
personal ID number, HairHg as hair mercury concentration, HighHairHg is 1 if HairHg>=5, otherwise 0,and FishIL is one of 4 categories shown above) were summarized below.
Eating fish or whale

Nfrequency

MedianMean ± SDHigh Hg（Hg µg/g hair）(Hg µg/g hair)≥5 µg/g hair

1. None80

3.44

3.55 ± 2.02

27

2. Monthly

90

4.34

4.72 ± 2.89

36

3. Weekly

120

5.45

5.36 ± 2.30

69

4. Daily110
5.97
6.20 ± 2.37
72
There are two approaches to analyze the relationships between fish/whale
intake and mercury exposure. First, the independence between High Hgand eating fish/whale frequency can be analyzed. (B) Fisher's exact test
resulted inand the null hypothesis was rejected, so thatthe relationship between the two variables is statistically significant.
Second, the effect of fish/whale intake on hair mercury concentration canbe analyzed. Welch's one-way ANOVA resulted in F-value of 24.273, firstd.f. of 3, second d.f. of 210.39, and p<0.001. (C) Then pairwise comparisonsof hair Hg levels between all pairs among 4 fish/whale intake frequencies
can be conducted by repeated use of Welch's t-test.

(A) Correct. In such situation, cluster sampling is appropriate.
(B) Correct(C) Due to the problem of multiple comparison causing excess alpha error, we must not repeat t-test.
For this purpose, adjustment for multiple comparison by Holm or FDR method, or Tukey's HSD isneeded. By any of those, except Monthly and Weekly, all pairwise differences are significant (p<0.05).
(2) Based on the result of large scale cohort study, brown rice intake is proved to significantly reduce thebody weight and white rice intake is proved to significantly increase the body weight. Then 5 obese patientschanged their stable food from white rice to brown rice. The changes of body weight (kg) between the 2timings (before intervention and after 6 months) were 70→65, 140→135, 95→85, 95→90, 85→80. The
result of paired t-test was p=0.0008, so that brown rice intake can be judged to have a significant weight
reduction effect as the result the intervention study.
* There are 2 level answers to this question. (Level 1) p=0.003883, but the conclusion is same. (Level 2)
Meals are not only composed of rice. Forced change of staple food may lead to change the amount of meals,
menus of side-dishes, and those may be true cause of weight loss. Thus the design is inappropriate.
(3) The gold standard method A can measure the concentration of biochemical marker for disease X, where
the concentration exceeds a specific threshold value. A cheaper and more rapid new method B wasdeveloped. Validity of B can be confirmed by showing the fact that the Pearson's correlation coefficient
between the measurements by A and B for the sufficient number of X patients and healthy volunteers ismore than 0.8 and that is statistically significant.
Even highly correlated, absolute levels may differ, or systematically biased (eg. in lower ranges, A<B but inhigher ranges, A>B). To check such possibility, Bland-Altman plot is needed.

(4) The 44 chronic hepatitis patients were randomly divided into 2 groups. Treatment group was treated byprednisolone, the other (control group) was just observed. At the end of the study, 11 patients lived intreatment group, 6 lived in control group, but the result of Fisher's exact test was not significant (p=0.215).
The months until death or censoring (lived at the end of the study) were recorded in
http://minato.sip21c.org/hepatitis-2018.txt as time, with flag (1 if died, 0 if still lived) and group (1 fortreatment group, 2 for control group). For all patients (ignoring alive/dead), the mean survival months(109.5 months in treatment group and 64.7 months in control group) were compared by Welch's t-test, thenp=0.013, so that prednisolone has a significant effect of lengthen survival for chronic hepatitis patients.
* There is 2 levels of answers. (Level 1) Appropriate (test statistics and conclusion is not wrong).
(Level 2) Survivors surely lived longer than the recorded time, so that this analysis is inappropriate.
Insted, log-rank test should be used to test the difference of survival considering censoring, p=0.0309.
Conclusion remains unchanged.
2. Please explain the incidence rate of a disease. What type of study design is needed has to be included.
Basically cohort study is needed. During observation, the total number of disease occurrence divided byperson-times. It means the rate of disease occurrence per unit time.
3. Sir Wright developed typhus vaccine and it was used in 6 studies conducted around 1900. In 1904, KarlPearson summarized the results by simply taking average of tetrachoric correlation coefficients of 6studies. The result was 0.193,
which is judged as not enoughstrong to recommend as vaccine byKarl Pearson.
However, if we
consider the death as outcome, andconduct the meta-analysis of odds
ratios, integrated odds ratio is 0.57
(95%CI, 0.48-0.67), which means
the vaccine having the significant
effect to reduce mortality. Please
explain why Pearson made a wrong judge. Why we must not take simple averages of correlation
coefficients?
(This question is difficult) Pearson ignored the differences in sample sizes of 6 studies. One study withrelatively small sample size of experimental group (GarrisonLadysmith) showed very low correlation,
which biased the simple mean.
4. Whether the ability of flash memory is improved by glucose candy or not was investigated for 10healthy volunteers. The result is shown below. Please test whether glucose candy improves flash
memory or not. P-value is needed. You can use computer software or calculator, but manual calculationis possible if you use 97.5% point of t-distribution with d.f. 9 is 2.262 and either of √2=1.414, √3=1.732,
or √5=2.236. *** Note: The values are slightly different from Japanese version ***Scores before glucose candy

8

Scores after glucose candy

9Difference 1637677512879112587669871111

mean 1.2 S.E.√(1.6/9)/√10=0.4/3

Then, t=1.2/(0.4/3)=9 > 2.262. Thus the difference between taking candy is statistically significant.
t.test(c(9,7,5,8,7,9,6,9,8,7),c(8,6,3,7,6,7,5,8,7,6),paired=TRUE) gives the same result,where

5. The RCT (Randomized Controlled Trial) to test new stretch method to improve body flexibility is to beconducted. Outcome measure is the change of standing-posture body anteflexion in centimeter. Basedon previous studies, the conventional stretch method increased 3 cm (standard deviation 2 cm) ofstanding posture body anteflexion measurement. If the new stretch method can increase more than
4cm (as the difference from the conventional method, more than 1 cm) of standing posture body
anteflexion, it can be judged as clinically valuable. Please calculate needed sample size for this RCT for
2-tailed t-test with 5% significance level and 80% power, and assuming the same size of 2 groups.
The result of power.t.test(delta=1, sd=2, sig.level=0.05, power=0.8) is n=63.76…, then sample
size is 64 for each group (EZR, 63 each, PS, 64 each). **(Level 2 answer) This test assess the very shortterm effect of intervention, the same subject can be used as control group after enough washout period. If
paired comparison is done, using PS, the sample size is 33 (using EZR, 34).