Type:	Package
Title:	Datasets from "Modelling Survival Data in Medical Research" by Collett
Version:	0.1.0
Maintainer:	Mark Clements <mark.clements@ki.se>
Description:	Datasets for the book entitled "Modelling Survival Data in Medical Research" by Collett (2023) <doi:10.1201/9781003282525>. The datasets provide extensive examples of time-to-event data.
URL:	https://github.com/mclements/collett
BugReports:	https://github.com/mclements/collett/issues
License:	MIT + file LICENSE
Depends:	R (≥ 3.5.0)
Imports:	utils
Suggests:	survival
Encoding:	UTF-8
RoxygenNote:	7.3.2
LazyData:	true
NeedsCompilation:	no
Packaged:	2025-01-08 16:25:24 UTC; marcle
Author:	Mark Clements [aut, cre]
Repository:	CRAN
Date/Publication:	2025-01-09 14:30:13 UTC

collett: Datasets and Examples from "Modelling Survival Data in Medical Research" by Collett

Description

Datasets and Examples from "Modelling Survival Data in Medical Research" by Collett.

Author(s)

Maintainer: Mark Clements mark.clements@ki.se (ORCID)

See Also

Useful links:

• https://github.com/mclements/collett

• Report bugs at https://github.com/mclements/collett/issues

Datasets

Description

The datasets are based on the official .zip file. A table for the dataset names and file names sorted by file name is here:

And now sorted by the dataset names:

As an alternative to using the R datasets, the collett_data function allows for reading from the original .dat files that are stored in the package.

Usage

collett_data(name)

Arguments

Value

A data-frame

Author(s)

Maintainer: Mark Clements mark.clements@ki.se (ORCID)

Source

https://s3-eu-west-1.amazonaws.com/s3-euw1-ap-pe-ws4-cws-documents.ri-prod/9781032252858/Data%20sets%20from%20Modelling%20Survival%20Data%20in%20Medical%20Research%2C%204th%20edition.zip

See Also

Useful links:

• https://github.com/mclements/collett

• Report bugs at https://github.com/mclements/collett/issues

Examples

head(collett_data("A numerical illustration.dat"))
## which is equivalent to: head(illustration)

Health evaluation and linkage to primary care

Description

A clinical trial for patients in a residential detoxification programme. Patients were randomised to either get a referral to a HELP clinic or not.

Usage

HELP

Format

A data frame with 447 rows and 7 variables:

subject

integer subject id

days

integer time to linkage to primary care in days

status

integer event indicator (0=no linkage, 1=linkage)

age

integer age of patient in years

gender

integer gender of the patient (0=female, 1=male)

housing

integer Homelessness status (0=homeless, 1=housed)

linkage

integer assistance to linking to healthcare (0=no, 1=yes)

Details

Collett (2023) defines this dataset as "help", however that leads to issues with using R's help system. We have changed the dataset name to "HELP". Moreover, the book uses the variables "Time" an d"Help", whereas the dataset includes variables "days" and "linkage", respectively.

Time to discontinuation of the use of an IUD

Description

A very simple dataset showing potential right censoring for time to discontinuation of the use of an IUD.

Usage

IUD

Format

A data frame with 18 rows and 2 variables:

time

integer Time in weeks to discontinuation of the use of an IUD

status

integer Indicator for whether the IUD was discontinued: 0=No, 1=Yes

Details

These data are reported in Table 1.1 (Collett, 2023, page 6).

Chronic active hepatitis

Description

Clinical trial of 44 patients with chronic active hepatitis randomised to either the drug prednisolone or an untreated control group.

Usage

active_hepatitis

Format

A data frame with 44 rows and 3 variables:

treatment

integer treatment (1=prednisolone, 2=control)

time

integer survival time from admission to study (months)

status

integer event indicator (1=event, 0=right censored)

Details

See Collett (2023)

Prognosis for women with breast cancer

Description

For female breast cancer patients from Middlesex Hospital. The dataset includes the result of staining using Helix pomatia agglutinin (HPA).

Usage

bcancer

Format

A data frame with 45 rows and 3 variables:

stain

integer for negative staining (=1) or positive staining (=2)

time

integer time in months for survival

status

integer for status at end of follow-up (0=censored, 1=death)

Details

For details about the study design, see Leathem and Brooks (1987).

The dataset is described in Example 1.2 and Table 1.2 (Collett, 2023, pages 6-7).

References

Leathem AJ, Brooks S. Predictive value of lectin binding on breast-cancer recurrence and survival. The Lancet. 1987 May 9;329(8541):1054-6. doi:10.1016/S0140-6736(87)90482-X

Examples

library(survival)
plot(survfit(Surv(time,status)~stain, data=bcancer), col=1:2, xlab="Survival time (months)",
ylab="Survival")
legend("topright", legend=c("Negative staining","Positive staining"), col=1:2, lty=1,
bty="n")

Recurrence of bladder cancer

Description

Placebo controlled trial of bladder cancer patients randomised to thiopeta or to placebo

Usage

bladder

Format

A data frame with 86 rows and 6 variables:

patient

integer patient number (1-86)

time

integer survival time in months

status

integer status of patient (0=censored, 1=recurrence)

treat

integer treatment group (1=placebo, 2=thiotepa)

init

integer initial number of tumours

size

integer diameter of larger initial tumour in cm

Details

See Collett (2023)

Bone marrow transplantation

Description

A study of 37 patients with leukaemia in complete remission who received a non-depleted allogenic bone marrow transplant.

Usage

bone_marrow

Format

A data frame with 37 rows and 9 variables:

patient

integer patient number (1-37)

time

integer survival time in days

status

integer status of patient (0=alive, 1=dead)

rage

integer age of patient in years

dage

integer age of donor in years

type

integer type of leukaemia (1=AML, 2=ALL, 3=CML)

preg

integer Donor pregnancy (0=no, 1=yes)

index

double index of cell-lymphocyte reactions

gvhd

integer graft-versus-host disease (0=no, 1=yes)

Details

See Collett (2023)

Patient outcome following bone marrow transplantation

Description

Patient outcome following bone marrow transplantation

Usage

bone_marrow_tx

Format

A data frame with 2204 rows and 9 variables:

id

integer patient id

leukaemia

character type of leukaemia (CML,ALL,AML)

age

character age group of patient in years (<=20, 21-40, >40))

match

integer indicator for whether there was a donor gender match (0=no, 1=yes)

tcell

integer indicator for whether there was T-cell depletion (1=yes, n=no)

ptime

integer time to platelet recovery (days)

pcens

integer event indicator for platelet recovery (1=event, 0=censored)

rdtime

integer time to relapse of death (days)

rdcens

integer event indicator for relapse or death (1=event, 0=censored)

Details

See Collett (2023)

Recurrence free survival in breast cancer patients

Description

Recurrence free survival in breast cancer patients

Usage

breast_rfs

Format

A data frame with 686 rows and 11 variables:

id

integer patient id

treat

integer hormonal treatment (0=no tamoxifen, 1=tamoxifen)

age

integer patient age (years)

men

integer menopausal status (1=premenopausal, 2=postmenopausal)

size

integer tumour size (mm)

grade

integer tumour grade (1,2,3)

nodes

integer number of positive pymph nodes

prog

integer progesterone receptor status (femtomoles)

oest

integer oestrogen receptor status (femtomoles)

time

integer recurrence-free survival time (days)

status

integer event indicator (0=censored, 1=relapse or death)

Details

See Collett (2023)

Infection in patients on dialysis

Description

Time from dialysis to infection for patients with diseases of the kidney.

Usage

dialysis

Format

A data frame with 13 rows and 5 variables:

patient

integer patient id

time

integer time to infection (days)

status

integer event indicator (0=censored, 1=infection)

age

integer age in years

sex

integer sex of the patient (1=male, 2=female)

Details

See Collett (2023)

Survival of black ducks

Description

Black ducks, Anas rubripes, were followed the US Fish and Wildlife Service.

Usage

ducks

Format

A data frame with 50 rows and 6 variables:

duck

integer duck indicator

time

integer survival time in days

status

integer status of bird (0=alive or missing, 1=dead)

age

integer age group (0=hatch-year bird, 1=bird aged >= 1 year)

weight

integer weight of bird in g

length

integer length of wing in mm

Details

See Collett (2023)

Survival of patients with gastric cancer

Description

Survival of patients with gastric cancer

Usage

gcancer

Format

A data frame with 90 rows and 4 variables:

patient

integer patient id

time

integer survival time in days

status

integer event indicator (0=censored, 1=dead)

treat

integer treatment arm (0=chemotherapy alone, 1=chemotherapy and radiotherapy)

Details

See Collett (2023)

Chronic granulomatous disease

Description

Trial comparing interferon with a placebo.

Usage

granulomatous

Format

A data frame with 128 rows and 12 variables:

patient

integer patient number (1-128)

time

integer time to first infection (days)

status

integer status of patient (0=censored, 1=infection)

centre

integer treatment centre; see Collett (2023, page 504)

treat

integer treatment group (0=placebo, 1=interferon)

age

integer age in years

sex

integer sex (1=male, 2=female)

height

double height in cm

weight

double weight in kg

pattern

integer pattern of inheritance (1=X-linked, 2=autosomal recessive)

cort

integer use of corticosteroids at trial entry (1=used, 2=not used)

anti

integer Use of antibiotics at trial entry (1=used, 2=not used)

Details

See Collett (2023)

A numerical illustration

Description

Artificial data on patient survival classified according to factors a and b

Usage

illustration

Format

A data frame with 37 rows and 4 variables:

a

integer factor a

b

integer factor b

time

integer event time

status

integer event status (1=event, 0=right censored)

Details

See Collett (2023).

Treatment of hypernephroma

Description

This study was undertaken at the University of Oklahoma Health Sciences Center to investigate survival among 36 patients with a kidney tumour (hypernephroma). Standard tangent included chemotherapy and immunotherapy, with some patients also having a nephrectomy, or surgical removal of the kidney. For further details, see Lee and Wang (2013).

Usage

kidney

Format

A data frame with 36 rows and 4 variables:

nephrectomy

integer indicator for nephrectomy (0=No; 1=Yes)

age

integer age group (1=<60; 2=60-70; 3=>70

time

integer for the follow-up time in months

status

integer for status at the end of follow-up (1=died; 0=censored)

References

Lee ET, Wang J. Statistical Methods for Survival Data Analysis. New York, NY: John Wiley & Sons; 2013, fourth edition. https://www.wiley.com/en-sg/Statistical+Methods+for+Survival+Data+Analysis%252C+4th+Edition-p-9781118095027

Comparisons between kidney transplant centres

Description

Transplant survival rates by recipients of organs from deceased donors. No event was defined as being alive with a functioning graft at the last known follow-up.

Usage

kidneytx

Format

A data frame with 1439 rows and 9 variables:

patient

integer patient id

centre

integer transplant centre (1-8)

tsurv

integer transplant survival time (days)

tcens

integer event indicator (0=censored, 1=transplant failure)

dage

integer donor age (years)

dtype

integer donor type (0=deceased following brain death, 1=circulatory death)

rage

integer recipient age (years)

diab

integer diabetic status (0=absent, 1=present)

cit

double cold ischaemic time (hours)

Details

See Collett (2023). Thirty-five patients had tsurv==0 (that is, the transplanted kidney did not function).

Data from a cirrhosis study (lbr data)

Description

DATASET_DESCRIPTION

Usage

lbrdata0

Format

A data frame with 42 rows and 3 variables:

patient

integer patient id

time

integer date of measurement (days)

lbr

double log bilirubin level

Details

See Collett (2023)

Bone marrow transplantation in the treatment of leukaemia

Description

Bone marrow transplantation in the treatment of leukaemia

Usage

leukaemia

Format

A data frame with 23 rows and 8 variables:

patient

integer patient id

time

integer survival time in days

status

integer event indicator (0=alive, 1=dead)

group

integer disease group (1=ALL, 2=low-risk AML, 3=high-risk AML)

page

integer age of patient in years

dage

integer age of donor in years

precovery

integer platelet recovery indicator (0=no, 1=yes)

ptime

character time in days to return of platelets to normal level (if precovery=1)

Details

See Collett (2023). Note that ptime will need conversion:).

Survival of liver transplant recipients

Description

Survival of liver transplant recipients

Usage

liver

Format

A data frame with 1761 rows and 7 variables:

patient

integer patient id

age

integer patient age in years

gender

integer patient gender (1=male, 2=female)

disease

integer primary disease (1=PBC, 2=PSC, 3=ALD)

time

integer time to event (days)

status

integer cof>0

cof

integer cause of graft failure (0=functioning graft, 1=rejection, 2=thrombosis, 3=recurrent disease, 4=other)

Details

See Collett (2023)

Data from a cirrhosis study (in counting process format)

Description

Artificial data

Usage

liver_counting

Format

A data frame with 54 rows and 7 variables:

patient

integer patient id

start

integer start time (days)

stop

integer stop time (days)

status

integer event indicator (0=censored, 1=uncensored)

treat

integer treatment group (0=placebo, 1=Liverol)

age

integer age of the patient at start of study (years)

lbrt

double logarithm of bilirubin level

Details

See Collett (2023). Note that the variable for log of bilirubin differs to that for "liverbase".

Data from a cirrhosis study (baseline)

Description

Articial data

Usage

liverbase

Format

A data frame with 12 rows and 6 variables:

patient

integer patient id

time

integer survival time in days

status

integer event indicator (0=censored, 1=uncensored)

age

integer age of the patient (years)

treat

integer treatment group (0=placebo, 1=Liverol)

lbr

double logarithm of bilirubin level

Details

See Collett (2023)

Time to death while waiting for a liver transplant

Description

Investigate the time on the liver transplantation list.

Usage

livertx

Format

A data frame with 281 rows and 7 variables:

patient

integer patient id

time

integer time on the list

status

integer event indicator (0=censored, including having a transplant, 1=died on the list)

age

integer patient age in years

gender

integer patient gender (1=male, 0=female)

bmi

double body mass index (kg/m^2)

ukeld

integer UK endstage liver disease score

Details

See Collett (2023). A higher UKELD is associated with worse disease severity.

Survival of patients registered for a lung transplant

Description

Survival of patients registered for a lung transplant

Usage

lung

Format

A data frame with 196 rows and 7 variables:

patient

integer patient id

time

integer time from registration to the earlist of removal from list, last known follow-up date, 30 April 2012, or death (days)

status

integer event indicator (0=censored, 1=dead)

age

integer age in years

gender

integer gender (1=male, 2=female)

bmi

double body mass index

disease

integer disease (1=COPD, 2=fibrosis, 3=suppurative, 4=other)

Details

See Collett (2023)

Recurrence of mammary tumours in female rats

Description

This is an animal experiment to compare the use of retinyl acetate (related to vitamin A) across the study (treatment) to treatment with retinyl acetate to 60 days and then no further treatment (control). The female rats all had mammary tumours.

Usage

mammary

Format

A data frame with 254 rows and 4 variables:

rat

integer id for each rat

treatment

integer treatment arm indicator (1=treatment, 0=control)

time

double follow-up time (days)

status

integer recurrence indicator (0=no, 1=yes)

Details

See Collett (2023)

Survival times of patients with melanoma

Description

Comparing two immunotherapy treatments for patients with melanoma

Usage

melanoma

Format

A data frame with 30 rows and 4 variables:

age

integer age group (1=21-44, 2=41-60, 3=61+)

treatment

integer treatment arm (1=BCG, 2=C. parvum)

time

integer survival time (months)

status

integer event indicator (0=censored, 1=dead)

Details

See Collett (2023)

Survival of laboratory mice

Description

Laboratory study of survival for two groups of mice exposed to radiation.

Usage

mice

Format

A data frame with 181 rows and 3 variables:

environment

integer type of environment (1=standard, 2=germ-free)

causeofdeath

integer cause of death (1=thymic lymphoma, 2=reticulum cell sarcoma, 3=other causes)

time

integer survival time (days)

Details

See Collett (2023). Note that are no censored event times.

Survival of multiple myeloma patients

Description

Patients diagnosed with multiple myeloma who were diagnosed and treated with alkylating agents at West Virginia University Medical Center for ages 50-80 years.

Usage

myeloma

Format

A data frame with 48 rows and 10 variables:

patient

integer for a patient identifier

time

integer survival time in months

status

integer for status at follow-up (0=Alive, 1=Dead)

age

integer age at diagnosis in years

sex

integer for sex of the patient (1=male, 2=female)

bun

integer level of blood urea nitrogen at diagnosis (unit assumed to be mg/dL based on the normal range for adults reported by https://en.wikipedia.org/wiki/Blood_urea_nitrogen)

ca

integer serum calcium at diagnosis in mg/dL

hb

double for serum hemoglobin level at diagnosis in g/dL (equivalently, grams per 100 mL)

pcells

integer percent of plasma cells in the bone marrow at diagnosis

protein

integer indicator for whether or not the Bence-Jones protein was present in the urine at diagnosis (0=absent, 1=present)

Details

Krall et al (1975) did not provide the units for all of these measurements. In their analyses, they used some data transformations: log(bun). Collett (2023) converted data from Krall et al (1975): BUN is reported by Krall and colleagues as X1=log(BUN), however the log base and unit is unclear; Krall and colleagues reported for 65 individuals, including those younger than 50 and older than 80.

References

Krall JM, Uthoff VA, Harley JB. A step-up procedure for selecting variables associated with survival. Biometrics. 1975 Mar 1:49-57. doi:10.2307/2529709

Examples

## To be completed.

Chemotherapy in ovarian cancer patients

Description

Trial for treatment of ovarian cancer patients comparing cyclophosphamide alone with cyclophosphamide combined with adriamycin.

Usage

ovarian

Format

A data frame with 26 rows and 7 variables:

patient

integer identifer

time

integer survival time from randomisation in days

status

integer event indicator (0=right censored, 1=event)

treat

integer treatment (1=single, 2=combined)

age

integer age of patients in years

rdisease

integer extent of residual disease (1=incomplete, 2=complete)

perf

integer performance status (1=good, 2=poor)

Details

See Collett (2023)

Comparison of two treatments for prostatic cancer

Description

Randomised controlled trial from the Veteran's Administration Cooperative Urological Research Group. Includes patients who had stage III cancers and were randomised to placebo or daily oral treatment with 1.0 mg of diethylstilbesterol (DES).

Usage

prostatic

Format

A data frame with 38 rows and 8 variables:

patient

integer patient identifier

treatment

integer treatment indicator (1=placebo; 2=daily treatment with 1.0 mg of diethylstilbesterol (DES))

time

integ er survival time from trial entry to end of follow-up in months

status

integer for follow-up status (0=alive or died from other causes, 1=died from prostate cancer

age

integer age at trial entry in years

shb

double serum hemoglobin at trial entry in g/dL

size

integer size of the primary tumour in cm^3

index

integer Gleason index based on histopathology

Details

TBC.

References

Andrews DF, Herzberg AM. Data: a collection of problems from many fields for the student and research worker. Springer Series in Statistics; Springer New York, NY; 1985. doi:10.1007/978-1-4612-5098-2

Pulmonary metastasis

Description

A very simple dataset with no censoring

Usage

pulmonary

Format

A data frame with 11 rows and 1 variables:

time

integer survival time from pulmonary metastasis to death in months

Details

See Collett (2023)

Clinical trial of tamoxifen in breast cancer patients

Description

Clinical trial for breast cancer patients comparing combined tamoxifen and radiotherapy with tamoxifen alone.

Usage

tamoxifen

Format

A data frame with 641 rows and 18 variables:

id

integer patient identifier

treat

integer treatment group (0=tamoxifen+radiotherapy, 1=tamoxifen)

age

integer patient age at study entry (years)

size

double tumour size (cm)

hist

integer tumour histology (1=ductal, 2=lobular, 3=medullary, 4=mixed, 5=other)

hr

integer hormone receptor level (0=negative, 1=positive)

hb

integer Haemoglobin level (g/l)

andis

integer axillary relapse (0=no, 1=yes)

lsurv

integer time to local relapse or last follow-up (days)

ls

integer local relapse (0=no, 1=yes))

asurv

integer time to axillary relapse or last follow-up (days)

as

integer axillary relapse (0=no, 1=yes)

dsurv

integer Time to distant relapse or last follow-up (days)

ds

integer distant relapse (0=no, 1=yes)

msurv

integer time to second malignancy or last follow-up (days)

ms

integer second malignancy (0=no, 1=yes)

tsurv

integer time from randomisation to death or last follow-up (days)

ts

integer status at last follw-up (0=alive, 1=dead)

Details

See Collett (2023)

Survival following kidney transplantation

Description

Survival following kidney transplantation

Usage

tplant

Format

A data frame with 434 rows and 7 variables:

patient

integer patient id

donor

integer donoe id

time

integer survival time in days

status

integer event indicator (0=censored, 1=graft failure or death with a functioning graft)

age

integer patient age (years)

diabetes

integer diabetes status (0=absent, 1=present)

cit

double cold ischaemic time, the time in hours between retrieval of the kidney from the donor and the transplantation

Details

See Collett (2023)

Recurrence of an ulcer

Description

A double-blind trial comparing two treatments for ulcers. Data from Belgium.

Usage

ulcer

Format

A data frame with 43 rows and 6 variables:

patient

integer patient id

age

integer age at the end of the trial in years

duration

integer duration of verified disease (1: <5 years, 2: >=5 years

treatment

integer treatment arm (1=A,2=B)

time

integer time since last visit (months)

result

integer result of the last visit (1=no ulcer detected, 2=ulcer detected)

Details

See Collett (2023)

Survival following aortic valve replacement

Description

Patients following an aortic valve replacement are measured for left ventricular mass index (LVMI).

Usage

valve

Format

A data frame with 988 rows and 11 variables:

id

integer patient id

futime

double total follow-up time from date of surgery (years)

status

integer event indicator (0=censored, 1=death)

time

double time of LVMI measurement after surgery (years)

lvmi

double standardised LVMI

age

integer age of patient in years

sex

integer sex of patient (0=male, 1=female)

redo

integer previous cardiac surgery (0=no, 1=yes)

emerg

integer operative urgency (0=elective, 1=urgent or emergency)

dm

integer preoperative diabetes mellitus (0=no, 1=yes)

type

integer type of valve (1=human tissue, 2=porcine tissue)

Details

See Collett (2023)