Reference no: EM131207261
Case Study 1-
In an experiment to determine the efficacy of a proton pump inhibitor (PPI) drug in reducing the frequency of nocturnal gastrointestinal reflux episodes, 12 patients suffering from gastro-eosophageal reflux disease (GERD) were repeatedly treated over a series of 5 day periods with either a placebo, 10mg, 20 mg or 40 mg daily doses of the PPI, with a 7 day washout period between treatment periods. Patients were allocated the 4 treatments in random order. The number of gastric reflux episodes per hour was measured for each patient using 24 hour oesophageal pH monitoring during an initial 5 day pre-treatment baseline period and during each of the 4 treatment periods.
Table 1 shows the change in the number of gastric reflux episodes, for each patient, during each of the 4 treatment periods, relative to the pre-treatment baseline.
Table 1.
|
|
Change in no. reflux episodes / hour
|
|
Patient
|
Placebo
|
10mg
|
20mg
|
40mg
|
|
1
|
-4.53
|
-9.06
|
-6.68
|
-0.9
|
|
2
|
-1.28
|
-12.18
|
-16.33
|
-15.7
|
|
3
|
2.42
|
0.75
|
-0.74
|
-0.58
|
|
4
|
1.39
|
-0.67
|
-1.68
|
-1.55
|
|
5
|
0.17
|
-0.44
|
1.9
|
-8.24
|
|
6
|
0.17
|
-0.9
|
-1.4
|
-1.4
|
|
7
|
12.48
|
-2.48
|
-3.55
|
-4.67
|
|
8
|
-1.36
|
-1.46
|
-1.65
|
-1.55
|
|
9
|
2.41
|
0.12
|
0
|
0
|
|
10
|
-0.77
|
1.41
|
-1.16
|
-2.75
|
|
11
|
2.22
|
-0.04
|
-0.71
|
0.87
|
|
12
|
0.04
|
-0.06
|
0.17
|
-1.88
|
From: Bradstreet, T.E. (1991) "Some Favorite Data Sets from Early Phases of Drug Research." Proceedings of the Section on Statistical Education of the American Statistical Association.
Answer the following questions.
a) State what statistical test was used and explain why you chose the test.
b) Paste in the key results from the statistical test.
c) Is the PPI drug effective at reducing the number reflux episodes and, if so, at which doses? Support your answer using the results from the statistical test.
d) If the drug is effective, is there evidence of a dose-response relationship?
e) Plot a figure (with an appropriate figure legend) illustrating the results of the experiment.
Case Study 2-
In an experiment to determine the pharmacokinetics of a new drug, a 2g dose of the drug was injected into each of a group of 30 subjects (7 elderly (aged ≥ 65 years) males, 7 elderly females, 8 young (aged ≥ 65 years) males, 8 young females).
Table 2 shows the measured plasma concentration of the drug, 12 hours after an intravenous injection of 2g of the drug.
Table 2.
|
Age
|
Sex
|
Plasma Conc.
mg/ml
|
|
Age
|
Sex
|
Plasma Conc.
mg/ml
|
|
Elderly
|
Male
|
22.1
|
|
Young
|
Male
|
15.2
|
|
Elderly
|
Male
|
22.4
|
|
Young
|
Male
|
17.1
|
|
Elderly
|
Male
|
38
|
|
Young
|
Male
|
13.6
|
|
Elderly
|
Male
|
34.6
|
|
Young
|
Male
|
23.6
|
|
Elderly
|
Male
|
30.4
|
|
Young
|
Male
|
23.4
|
|
Elderly
|
Male
|
26.4
|
|
Young
|
Male
|
17.1
|
|
Elderly
|
Male
|
31.5
|
|
Young
|
Male
|
13.2
|
|
Elderly
|
Female
|
28.7
|
|
Young
|
Male
|
16.8
|
|
Elderly
|
Female
|
24.8
|
|
Young
|
Female
|
18.5
|
|
Elderly
|
Female
|
23.2
|
|
Young
|
Female
|
16.4
|
|
Elderly
|
Female
|
24
|
|
Young
|
Female
|
18.1
|
|
Elderly
|
Female
|
18.1
|
|
Young
|
Female
|
16.3
|
|
Elderly
|
Female
|
26.3
|
|
Young
|
Female
|
14
|
|
Elderly
|
Female
|
23.1
|
|
Young
|
Female
|
13.9
|
|
|
|
|
|
Young
|
Female
|
16.5
|
|
|
|
|
|
Young
|
Female
|
9
|
From: Bradstreet, T. E. and Short, T. H. (2001) "Favorite Data Sets from Early Phases of Drug Research - Part 5." Proceedings of the Section on Statistical Education of the American Statistical Association.
Answer the following questions.
a) State what statistical test was used and explain why you chose the test.
b) Paste in the key results from the statistical test.
c) Does age or gender affect the pharmacokinetics of the drugs? Support your answer using the results from the statistical test.
d) Plot a figure (with an appropriate figure legend) illustrating the results of the experiment.
Case Study 3-
In a study of the effect of aging on DNA methylation, DNA was extracted from blood samples from 65 donors, with ages ranging from 11 to 72 years, and the percentage methylation at a range of CpG sites determined using MS-RDA (methylation-sensitive representational difference analysis).
Table 3 lists the measured percentage methylation at CpG sites on 3 three genes (GPR137, ZIC4, ZDHHC22) and the age of the donor.
Table 3.
|
GPR137
|
|
ZIC4
|
|
ZDHHC22
|
|
Age
(years)
|
Methylation
(%)
|
|
Age
(years)
|
Methylation
(%)
|
|
Age
(years)
|
Methylation
(%)
|
|
11.04
|
89.87
|
|
15.26
|
90.09
|
|
60.18
|
89.59
|
|
14.17
|
89.73
|
|
17.72
|
90.09
|
|
63.21
|
89.74
|
|
22.16
|
89.87
|
|
19.3
|
90.09
|
|
65.71
|
89.74
|
|
25.46
|
89.87
|
|
11.05
|
79.74
|
|
72.14
|
89.44
|
|
36.92
|
90.01
|
|
13.16
|
79.88
|
|
70.54
|
79.62
|
|
46.82
|
89.73
|
|
14.39
|
79.88
|
|
67.5
|
79.62
|
|
12.95
|
79.89
|
|
17.19
|
79.88
|
|
65.89
|
79.62
|
|
14.69
|
80.17
|
|
22.11
|
79.88
|
|
55.89
|
79.62
|
|
16.95
|
80.17
|
|
24.91
|
79.88
|
|
51.61
|
79.77
|
|
19.03
|
80.17
|
|
27.19
|
79.88
|
|
48.39
|
79.62
|
|
21.46
|
80.17
|
|
32.63
|
80.03
|
|
40
|
79.62
|
|
24.94
|
80.17
|
|
34.56
|
80.17
|
|
37.68
|
69.21
|
|
34.14
|
80.31
|
|
36.14
|
80.17
|
|
39.64
|
69.35
|
|
37.27
|
80.31
|
|
38.25
|
80.17
|
|
41.96
|
69.35
|
|
39.88
|
80.31
|
|
40.35
|
80.17
|
|
48.21
|
69.5
|
|
46.65
|
80.03
|
|
14.04
|
69.97
|
|
29.46
|
59.38
|
|
60.37
|
80.03
|
|
21.4
|
69.83
|
|
33.75
|
59.68
|
|
14.17
|
70.04
|
|
27.19
|
69.68
|
|
38.04
|
59.97
|
|
26.85
|
69.76
|
|
29.82
|
69.83
|
|
39.82
|
59.97
|
|
32.93
|
69.9
|
|
33.68
|
70.12
|
|
41.07
|
59.68
|
|
33.62
|
69.9
|
|
38.25
|
69.97
|
|
43.21
|
59.53
|
|
34.32
|
69.76
|
|
39.82
|
69.97
|
|
47.5
|
59.68
|
|
38.14
|
70.04
|
|
41.75
|
69.97
|
|
56.07
|
59.97
|
|
40.05
|
69.76
|
|
43.16
|
69.97
|
|
51.25
|
49.56
|
|
47.87
|
69.9
|
|
27.02
|
59.77
|
|
46.79
|
49.56
|
|
17.99
|
59.91
|
|
33.16
|
59.91
|
|
43.21
|
49.56
|
|
33.45
|
60.2
|
|
37.19
|
59.77
|
|
41.43
|
49.56
|
|
37.79
|
60.06
|
|
40.7
|
59.77
|
|
39.64
|
49.71
|
|
41.44
|
60.06
|
|
43.33
|
59.48
|
|
37.32
|
49.85
|
|
48.21
|
60.2
|
|
46.84
|
59.91
|
|
32.86
|
49.85
|
|
56.03
|
60.2
|
|
48.25
|
59.91
|
|
29.29
|
49.56
|
|
62.98
|
60.2
|
|
30.35
|
50.15
|
|
26.43
|
49.56
|
|
67.15
|
59.91
|
|
34.04
|
50.15
|
|
21.25
|
39.59
|
|
27.02
|
50.07
|
|
40
|
50.29
|
|
25.18
|
39.59
|
|
30.15
|
49.93
|
|
41.4
|
50.29
|
|
26.79
|
39.59
|
|
35.88
|
50.07
|
|
43.86
|
50.15
|
|
36.79
|
39.44
|
|
37.97
|
50.07
|
|
46.84
|
50.15
|
|
43.39
|
39.44
|
|
40.22
|
49.93
|
|
48.6
|
50.15
|
|
25
|
29.62
|
|
41.79
|
49.93
|
|
51.23
|
50.15
|
|
18.93
|
29.62
|
|
43.87
|
49.79
|
|
32.98
|
40.23
|
|
17.14
|
29.77
|
|
48.21
|
49.79
|
|
37.54
|
40.09
|
|
20.36
|
19.65
|
|
50.65
|
49.93
|
|
48.42
|
40.38
|
|
15
|
19.65
|
|
29.98
|
39.66
|
|
56.49
|
40.23
|
|
13.39
|
19.65
|
|
40.05
|
39.51
|
|
60.18
|
40.09
|
|
12.5
|
19.65
|
|
41.61
|
39.37
|
|
50.88
|
30.03
|
|
10.54
|
9.677
|
|
43
|
39.94
|
|
62.98
|
30.03
|
|
13.57
|
9.531
|
|
47.87
|
40.09
|
|
67.19
|
30.03
|
|
|
|
|
65.93
|
39.94
|
|
66.49
|
19.97
|
|
|
|
|
43
|
30.1
|
|
70
|
20.12
|
|
|
|
|
50.99
|
30.1
|
|
67.37
|
10.06
|
|
|
|
|
65.76
|
30.1
|
|
71.93
|
10.06
|
|
|
|
|
72.53
|
19.54
|
|
|
|
|
|
|
|
66.8
|
9.986
|
|
|
|
|
|
|
|
70.27
|
9.843
|
|
|
|
|
|
|
From: Yi S.H. et al (2014) Isolation and identification of age-related DNA methylation markers for forensic age-prediction. Forensic Sci Int Genet. 117-25.
Answer the following questions.
a) State what statistical test(s) were used to analyse the data and explain why you chose the test.
b) Paste in the key results from the statistical test(s).
c) Does age affect methylation at each of the three sites and in what way? Support your answer using the results from the statistical test.
d) Plot a figure (with an appropriate figure legend) illustrating the results of the experiment.
e) Develop a model for predicting age from DNA methylation and state the best fitting equation predicting age from % methylation.
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