SAMURAI (version 1.2.1)

Hpylori: Healing of duodenal ulcers by Helicobacter pylori eradication therapy

Description

Randomized clinical trials comparing duodenal ulcer acute healing among (1) patients on ulcer healing drug + Helicobacter pylori eradication therapy vs. (2) patients ulcer healing drug alone. The event counts represent the numbers of patients not healed.

Usage

data(Hpylori)

Format

A data frame with 33 observations on the following 7 variables.

	study
character	Name of study or principal investigator
year	numeric
Year (optional)	outlook
factor	Denotes whether a study is unpublished, and if so, what outlook it has.
ctrl.n	numeric
The sample size of the control arm.	expt.n
numeric	The sample size of the experimental arm.
ctrl.events	numeric
The number of (undesired) events within the control arm.

Source

Ford AC, Delaney B, Forman D, Moayyedi P. "Eradication therapy for peptic ulcer disease in Helicobacter pylori positive patients." Cochrane Database of Systematic Reviews 2006, Issue 2. Art No.: CD003840. DOI: 10.1002/14651858.CD003840.pub4. Figure 3. Forest plot of comparison: 1 duodenal ulcer acute healing hp eradication + ulcer healing drug vs. ulcer healing drug alone, outcome: 1.1 Proportion not healed.

Details

The outlook of a study can be one of the following: published, very positive, positive, negative, very negative, current effect, no effect, very positive CL, positive CL, negative CL, or very negative CL.

Since the outcome event is undesired, when using the function forestsens(), specify the option higher.is.better=FALSE.

Examples

data(Hpylori)
Hpylori

forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8)

# To fix the random number seed to make the results reproducible.
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8, 
  random.number.seed=106)

# To modify the outlooks of all unpublished studies to, say, "very negative". 
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8, 
  random.number.seed=106, outlook="very negative")

# To modify the outlooks of all unpublished studies to, say, "very negative", 
# and overruling the default relative risk assigned to "very negative".
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8, 
  random.number.seed=106, outlook="very negative", rr.vneg=2.5)

# To generate a forest plot for each of the ten default outlooks 
# defined by forestsens().
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8, 
  random.number.seed=106, all.outlooks=TRUE)