generated from mbg-unsw/neweywest
-
Notifications
You must be signed in to change notification settings - Fork 0
/
pnuc.bib
89 lines (82 loc) · 5.2 KB
/
pnuc.bib
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
@article{webster-clark_initiator_2020,
title = {Initiator {Types} and the {Causal} {Question} of the {Prevalent} {New}-{User} {Design}: {A} {Simulation} {Study}},
shorttitle = {Initiator {Types} and the {Causal} {Question} of the {Prevalent} {New}-{User} {Design}},
url = {https://academic.oup.com/aje/article/190/7/1341/6043913},
doi = {10.1093/aje/kwaa283},
journal = {American Journal of Epidemiology},
author = {Webster-Clark, Michael and Ross, Rachael K and Lund, Jennifer L},
year = {2021},
pages = {1341--1348},
volume = {190},
number = {7},
}
@article{suissa_prevalent_2017,
title = {Prevalent new-user cohort designs for comparative drug effect studies by time-conditional propensity scores},
volume = {26},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pds.4107},
doi = {10.1002/pds.4107},
number = {4},
urldate = {2021-06-16},
journal = {Pharmacoepidemiology and Drug Safety},
author = {Suissa, Samy and Moodie, Erica E. M. and Dell'Aniello, Sophie},
year = {2017},
keywords = {cohort studies, comparative effectiveness, database research, drug safety, epidemiologic design, pharmacoepidemiology},
pages = {459--468},
}
@article{tran_comparing_2021,
title = {Comparing {New}-{User} {Cohort} {Designs}: {The} {Example} of {Proton} {Pump} {Inhibitor} {Effectiveness} in {Idiopathic} {Pulmonary} {Fibrosis}},
volume = {190},
shorttitle = {Comparing {New}-{User} {Cohort} {Designs}},
url = {https://doi.org/10.1093/aje/kwaa242},
doi = {10.1093/aje/kwaa242},
abstract = {The prevalent new-user cohort design is useful for assessing the effectiveness of a medication in the absence of an active comparator. Alternative approaches, particularly in the presence of informative censoring, include a variant of this design based on never users of the study drug and the marginal structural Cox model approach. We compared these approaches in assessing the effectiveness of proton pump inhibitors (PPIs) in reducing mortality among patients with idiopathic pulmonary fibrosis (IPF) using a cohort of IPF patients identified in the United Kingdom’s Clinical Practice Research Datalink and diagnosed between 2003 and 2016. The cohort included 2,944 IPF patients, 1,916 of whom initiated use of PPIs during follow-up. There were 2,136 deaths (mortality rate = 25.8 per 100 person-years). Using the conventional prevalent new-user design, we found a hazard ratio for death associated with PPI use compared with nonuse of 1.07 (95\% confidence interval (CI): 0.94, 1.22). The variant of the prevalent new-user design comparing PPI users with never users found a hazard ratio of 0.82 (95\% CI: 0.73, 0.91), while the marginal structural Cox model found a hazard ratio of 1.08 (95\% CI: 0.85, 1.38). The marginal structural model and the conventional prevalent new-user design, both accounting for informative censoring, produced similar results. However, the prevalent new-user design variant based on never users introduced selection bias and should be avoided.},
number = {5},
urldate = {2021-05-09},
journal = {American Journal of Epidemiology},
author = {Tran, Tanja and Suissa, Samy},
year = {2021},
pages = {928--938},
}
@article{tazare_prevalent_2022,
title = {Prevalent new user designs: a literature review of current implementation practice},
shorttitle = {Prevalent new user designs},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pds.5656},
doi = {10.1002/pds.5656},
urldate = {2023-06-22},
year = {2022},
journal = {Pharmacoepidemiology and Drug Safety},
author = {Tazare, John and Gibbons, Daniel C. and Bokern, Marleen and Williamson, Elizabeth J. and Gillespie, Iain A. and Cunnington, Marianne and Logie, John and Douglas, Ian J.},
}
@article{webster-clark_alternative_2022,
title = {Alternative analytic and matching approaches for the prevalent new-user design: {A} simulation study},
volume = {31},
shorttitle = {Alternative analytic and matching approaches for the prevalent new-user design},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pds.5446},
doi = {10.1002/pds.5446},
number = {7},
urldate = {2024-01-02},
journal = {Pharmacoepidemiology and Drug Safety},
author = {Webster-Clark, Michael and Mavros, Panagiotis and Garry, Elizabeth M. and St{\"u}rmer, Til and Shmuel, Shahar and Young, Jessica and Girman, Cynthia},
year = {2022},
pages = {796--803},
}
@article{wintzell_selection_2022,
title = {Selection of {Comparator} {Group} in {Observational} {Drug} {Safety} {Studies}: {Alternatives} to the {Active} {Comparator} {New} {User} {Design}},
volume = {33},
shorttitle = {Selection of {Comparator} {Group} in {Observational} {Drug} {Safety} {Studies}},
url = {https://journals.lww.com/epidem/fulltext/2022/09000/selection_of_comparator_group_in_observational.14.aspx},
doi = {10.1097/EDE.0000000000001521},
number = {5},
urldate = {2024-01-15},
journal = {Epidemiology},
author = {Wintzell, Viktor and Svanstr{\"o}m, Henrik and Pasternak, Björn},
year = {2022},
pages = {707},
}
@misc{webster-clark_presentation_2020,
title = {The prevalent new user design: establishing the estimand and sources of bias},
url = {https://pharmacoepi.unc.edu/wp-content/uploads/sites/6788/2020/12/Webster-Clark_Michael_PNU.pdf},
author = {Webster-Clark, Michael},
year = {2020},
note = {Accessed: 2024-01-15},
}