fhcrcData: List tables for the simulation

In mclements/prostata: Prostate Cancer Microsimulation for Sweden

List tables for the simulation

Description

DATASET_DESCRIPTION all_cause_mortality

Usage

fhcrcData

Format

A data frame with 12120 rows and 4 variables:

BirthCohort

integer COLUMN_DESCRIPTION

Age

integer COLUMN_DESCRIPTION

AnnualMortality

double COLUMN_DESCRIPTION

Survival

double COLUMN_DESCRIPTION

biopsy_frequency

A data frame with 3 rows and 7 variables:

PSA.beg

integer COLUMN_DESCRIPTION

PSA.end

integer COLUMN_DESCRIPTION

X55.59

double COLUMN_DESCRIPTION

X60.64

double COLUMN_DESCRIPTION

X65.69

double COLUMN_DESCRIPTION

X70.74

double COLUMN_DESCRIPTION

X75.79

double COLUMN_DESCRIPTION

biopsy_sensitivity

A data frame with 14 rows and 2 variables:

Year

integer COLUMN_DESCRIPTION

Sensitivity

double COLUMN_DESCRIPTION

neg_biopsy_to_psa

A data frame with 4 rows and 3 variables. Describing the time to the next PSA test following a negative biopsy. Modelled as a competing risk with a biopsy. Informed by the Stockholm PSA and Biopsy Register (SPBR).:

age

integer with age groups

meanlog

double for the mean of a log-normal time to a PSA test following a negative biopsy.

sdlog

double for the standard deviation of a log-normal.

neg_biopsy_to_biopsy

A data frame with 4 rows and 3 variables. Describing the time to the next biopsy following a negative biopsy. Modelled as a competing risk with a PSA test. Informed by the Stockholm PSA and Biopsy Register (SPBR).:

age

integer with age groups

meanlog

double describing the mean of a log-normal

sdlog

double describing the standard deviation of a log-normal

cure_m_CM_to_RP

A data frame with 4 rows and 4 variables. Cure model giving the probability of not having a radical prostatectomy following assignment to conservative management (active surveillance & watchfull waiting). Log-normal distribution of the time to radical prostatectomy for those that do have that. A future extension would be to model active surveillance and watchfull waiting separately:

age

double with age groups

pnever

double probability of not having a radical prostatectomy

meanlog

double mean of log-normal time to radical prostatectomy

sdlog

double standard deviation of log-normal time to radical prostatectomy

cure_m_CM_to_RT

A data frame with 4 rows and 4 variables. Cure model giving the probability of not having a radiation therapy following assignment to conservative management (active surveillance & watchfull waiting). Log-normal distribution of the time to radiation therapy for those that do have that. A future extension would be to model active surveillance and watchfull waiting separately:

age

double with age groups

pnever

double probability of not having a radical prostatectomy

meanlog

double mean of log-normal time to radiation therapy

sdlog

double standard deviation of log-normal time to radiation therapy

A data frame with 4 rows and 3 variables. Describing the time to the next biopsy following a negative biopsy. Modelled as a competing risk with a PSA test. Informed by the Stockholm PSA and Biopsy Register (SPBR).:

age

integer with age groups

meanlog

double describing the mean of a log-normal

sdlog

double describing the standard deviation of a log-normal

dre

A data frame with 4 rows and 4 variables:

psa.low

integer COLUMN_DESCRIPTION

psa.high

double COLUMN_DESCRIPTION

sensitivity

double COLUMN_DESCRIPTION

specificity

double COLUMN_DESCRIPTION

prob_grade7

A data frame with 51 rows and 2 variables:

slope

double COLUMN_DESCRIPTION

Pr.grade.7.

double COLUMN_DESCRIPTION

pradt

A data frame with 8208 rows and 6 variables:

Tx

integer COLUMN_DESCRIPTION

Age

integer COLUMN_DESCRIPTION

DxY

integer COLUMN_DESCRIPTION

Grade

integer COLUMN_DESCRIPTION

NoADT

double COLUMN_DESCRIPTION

ADT

double COLUMN_DESCRIPTION

prtx

A data frame with 2664 rows and 6 variables:

Age

integer COLUMN_DESCRIPTION

DxY

integer COLUMN_DESCRIPTION

G

integer COLUMN_DESCRIPTION

CM

double COLUMN_DESCRIPTION

RP

double COLUMN_DESCRIPTION

RT

double COLUMN_DESCRIPTION

survival_dist

A data frame with 42 rows and 3 variables:

Grade

integer COLUMN_DESCRIPTION

Time

integer COLUMN_DESCRIPTION

Survival

double COLUMN_DESCRIPTION

survival_local

A data frame with 294 rows and 5 variables:

AgeLow

integer COLUMN_DESCRIPTION

AgeHigh

integer COLUMN_DESCRIPTION

Grade

integer COLUMN_DESCRIPTION

Time

integer COLUMN_DESCRIPTION

Survival

double COLUMN_DESCRIPTION

prob_earlystage

A data frame with 84 rows and 6 variables:

BeginAge

integer COLUMN_DESCRIPTION

EndAge

integer COLUMN_DESCRIPTION

BeginPSA

integer COLUMN_DESCRIPTION

EndPSA

integer COLUMN_DESCRIPTION

Grade

integer COLUMN_DESCRIPTION

Prob

double COLUMN_DESCRIPTION

mclements/prostata documentation built on Feb. 1, 2023, 1:20 p.m.