OncoDataSets: A Comprehensive Collection of Cancer Types and Cancer-related DataSets

Description

This package provides a wide variety of datasets related to cancer types such as melanoma, leukemia, breast, ovarian, and lung cancer, among others.

Details

OncoDataSets: A Comprehensive Collection of Cancer Types and Cancer-related DataSets

A Comprehensive Collection of Cancer Types and Cancer-related DataSets.

Author(s)

Maintainer: Renzo Caceres Rossi arenzocaceresrossi@gmail.com

See Also

Useful links:

• https://github.com/lightbluetitan/oncodatasets

AI for Assessment of Indeterminate Pulmonary Nodules

Description

This dataset, AIPulmonaryNodules_df, is a data frame containing data from a study on the performance of an artificial intelligence (AI) risk stratification tool for assessing Indeterminate Pulmonary Nodules (IPNs) in chest CT scans. The dataset includes information on whether cancer was diagnosed and the AI tool's rating of the probability of cancer (from 0 to 100).

Usage

data(AIPulmonaryNodules_df)

Format

A data frame with 200 observations and 2 variables:

cancer

Cancer diagnosis – whether the nodule is cancerous (1 = cancer, 0 = no cancer) (integer).

rating

AI rating of the probability of cancer, ranging from 0 to 100 (integer).

Details

The dataset name has been kept as 'AIPulmonaryNodules_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package.

Aflatoxin Dosage and Liver Cancer in Lab Animals

Description

This dataset, AflatoxinLiverCancer_df, is a data frame containing data from a study where varying doses of Aflatoxin B1 were administered to lab animals. The dataset records the total number of animals exposed to each dose and the number of animals that developed liver cancer.

Usage

data(AflatoxinLiverCancer_df)

Format

A data frame with 6 observations and 3 variables:

dose

Dose of Aflatoxin B1 administered (integer).

total

Total number of animals exposed to the dose (integer).

tumor

Number of animals that developed liver cancer (integer).

Details

The dataset name has been kept as 'AflatoxinLiverCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the faraway package. Gaylor DW (1987). *Linear nonparametric upper limits for low dose extrapolation*. ASA Proceedings of the Biopharmaceutical Section.

Alcohol Intake and Colorectal Cancer Data

Description

This dataset, AlcoholIntakeCancer_df, is a data frame containing data related to alcohol intake and its association with colorectal cancer risk. The data includes information on alcohol intake levels (dose), the number of cancer cases, person-years of observation, and the relative risk (logrr) along with its standard error (se). The dataset consists of 48 observations with 7 variables.

Usage

data(AlcoholIntakeCancer_df)

Format

A data frame with 48 observations and 7 variables:

id

Identifier for the study (factor).

type

Type of study (factor).

dose

Level of alcohol intake (numeric).

cases

Number of colorectal cancer cases (integer).

peryears

Person-years of observation (numeric).

logrr

Logarithm of the relative risk (numeric).

se

Standard error of the logarithm of the relative risk (numeric).

Details

The dataset name has been kept as 'AlcoholIntakeCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the mixmeta package. Available at: https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041

Cumulative Risk of Women Breast Cancer BRCA1 Mutation

Description

This dataset, BRCA1BreastCancer_df, is a data frame containing data on the cumulative risk of breast cancer in women with the BRCA1 mutation as a function of their age. The dataset includes 11 observations, with each entry representing the cumulative risk at a specific age (in years).

Usage

data(BRCA1BreastCancer_df)

Format

A data frame with 11 observations and 2 variables:

x

Age of the individual in years (numeric).

y

Cumulative risk of breast cancer at that age (numeric).

Details

The dataset name has been kept as 'BRCA1BreastCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the riskyr package.

Cumulative Risk of Women Ovarian Cancer BRCA1 Mutation

Description

This dataset, BRCA1OvarianCancer_df, is a data frame containing data on the cumulative risk of ovarian cancer in women with the BRCA1 mutation as a function of their age. The dataset includes 63 observations, with each entry representing the cumulative risk at a specific age (in years).

Usage

data(BRCA1OvarianCancer_df)

Format

A data frame with 63 observations and 2 variables:

age

Age of the individual in years (numeric).

cumRisk

Cumulative risk of ovarian cancer at that age (numeric).

Details

The dataset name has been kept as 'BRCA1OvarianCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the riskyr package. Based on Figure 2 (p. 2408) of Kuchenbaecker, K. B., Hopper, J. L., Barnes, D. R., Phillips, K. A., Mooij, T. M., Roos-Blom, M. J., ... & BRCA1 and BRCA2 Cohort Consortium (2017). Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA, 317 (23), 2402-2416. doi: 10.1001/jama.2017.7112

Cumulative Risk of Women Breast Cancer BRCA2 Mutation

Description

This dataset, BRCA2BreastCancer_df, is a data frame containing data on the cumulative risk of breast cancer in women with the BRCA2 mutation as a function of their age. The dataset includes 11 observations, with each entry representing the cumulative risk at a specific age (in years).

Usage

data(BRCA2BreastCancer_df)

Format

A data frame with 11 observations and 2 variables:

x

Age of the individual in years (numeric).

y

Cumulative risk of breast cancer at that age (numeric).

Details

The dataset name has been kept as 'BRCA2BreastCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the riskyr package.

Cumulative Risk of Women Ovarian Cancer BRCA2 Mutation

Description

This dataset, BRCA2OvarianCancer_df, is a data frame containing data on the cumulative risk of ovarian cancer in women with the BRCA2 mutation as a function of their age. The dataset includes 63 observations, with each entry representing the cumulative risk at a specific age (in years).

Usage

data(BRCA2OvarianCancer_df)

Format

A data frame with 63 observations and 2 variables:

age

Age of the individual in years (numeric).

cumRisk

Cumulative risk of ovarian cancer at that age (numeric).

Details

The dataset name has been kept as 'BRCA2OvarianCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the riskyr package. Based on Figure 2 (p. 2408) of Kuchenbaecker, K. B., Hopper, J. L., Barnes, D. R., Phillips, K. A., Mooij, T. M., Roos-Blom, M. J., ... & BRCA1 and BRCA2 Cohort Consortium (2017). Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA, 317 (23), 2402–2416. doi: 10.1001/jama.2017.7112

Bladder Cancer Recurrences

Description

This dataset, BladderCancer_df, is a data frame containing data on recurrences of bladder cancer. It is commonly used to demonstrate methodology for recurrent event modelling. The dataset includes information from 340 observations and 7 variables related to bladder cancer recurrences.

Usage

data(BladderCancer_df)

Format

A data frame with 340 observations and 7 variables:

id

Patient identifier (integer).

rx

Treatment received: 1 = thiotepa, 2 = placebo (numeric).

number

Number of recurrences (integer).

size

Size of the recurrence (integer).

stop

Time at which the event or censoring occurred (integer).

event

Event status: 1 = recurrence, 0 = no recurrence or death (numeric).

enum

Event enumeration (integer).

Details

The dataset name has been kept as 'BladderCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the survival package.

Effects of Blood Storage on Prostate Cancer Study

Description

This dataset, BloodStorageProstate_df, is a data frame containing data on 316 men who underwent radical prostatectomy and received a transfusion during or within 30 days of the surgery. The dataset includes demographic, baseline, and prognostic factors, as well as data on the time to biochemical recurrence of prostate cancer, as indicated by prostate serum antigen (PSA) levels. The main exposure of interest was the red blood cell (RBC) storage duration group, and the outcome of interest was time to PSA cancer recurrence.

Usage

data(BloodStorageProstate_df)

Format

A data frame with 316 observations and 20 variables:

RBC.Age.Group

Age group of red blood cells (numeric).

Median.RBC.Age

Median age of red blood cells (numeric).

Age

Patient's age (numeric).

AA

African American status (numeric).

FamHx

Family history of prostate cancer (numeric).

PVol

Prostate volume (numeric).

TVol

Tumor volume (numeric).

T.Stage

Tumor stage (numeric).

bGS

Biopsy grade score (numeric).

BN+

Bone metastasis status (numeric).

OrganConfined

Organ confinement status (numeric).

PreopPSA

Preoperative prostate serum antigen level (numeric).

PreopTherapy

Preoperative therapy received (numeric).

Units

Number of blood transfusion units (numeric).

sGS

Surgical Gleason score (numeric).

AnyAdjTherapy

Any adjuvant therapy received (numeric).

AdjRadTherapy

Adjuvant radiation therapy received (numeric).

Recurrence

Cancer recurrence status (numeric).

Censor

Censoring status (numeric).

TimeToRecurrence

Time to biochemical recurrence in months (numeric).

Details

The dataset name has been kept as 'BloodStorageProstate_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the medicaldata package. Cata et al. (2011). *Blood Storage Duration and Biochemical Recurrence of Cancer after Radical Prostatectomy*. Mayo Clinic Proceedings, 86(2), 120–127.

New Mexico Brain Cancer Cases Data

Description

This dataset, BrainCancerCases_df, is a data frame containing data on brain cancer cases in New Mexico. It includes information about the county, number of cases, year of diagnosis, age group, and sex of the patients. The dataset consists of 1175 observations with 5 variables.

Usage

data(BrainCancerCases_df)

Format

A data frame with 1175 observations and 5 variables:

county

County of diagnosis (Factor with 31 levels).

cases

Number of cases (integer).

year

Year of diagnosis (integer).

agegroup

Age group of patients (integer).

sex

Sex of the patient (integer).

Details

The dataset name has been kept as 'BrainCancerCases_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the rsatscan package, distributed with SaTScan software: https://www.satscan.org

New Mexico Brain Cancer Geography Data

Description

This dataset, BrainCancerGeo_df, is a data frame containing geographic information related to brain cancer cases in New Mexico. It includes data on the county, latitude, and longitude of the regions where brain cancer cases have been reported. The dataset consists of 32 observations with 3 variables.

Usage

data(BrainCancerGeo_df)

Format

A data frame with 32 observations and 3 variables:

county

County where the cases were recorded (Factor with 32 levels).

lat

Latitude of the county (integer).

long

Longitude of the county (integer).

Details

The dataset name has been kept as 'BrainCancerGeo_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the rsatscan package, distributed with SaTScan software: https://www.satscan.org

Breast Cancer Wisconsin (Diagnostic)

Description

This dataset, BreastCancerWI_df, is a data frame containing diagnostic information for 569 patients with breast cancer. The data includes features computed from digitized images of fine needle aspirates (FNA) of breast masses, as well as a diagnosis label indicating whether the mass is malignant or benign.

Usage

data(BreastCancerWI_df)

Format

A data frame with 569 observations and 31 variables:

diagnosis

Diagnosis of the breast mass: malignant or benign (factor with 2 levels).

radius_mean

Mean radius of the mass (numeric).

texture_mean

Mean texture of the mass (numeric).

perimeter_mean

Mean perimeter of the mass (numeric).

area_mean

Mean area of the mass (numeric).

smoothness_mean

Mean smoothness of the mass (numeric).

compactness_mean

Mean compactness of the mass (numeric).

concavity_mean

Mean concavity of the mass (numeric).

concave_points_mean

Mean number of concave points on the mass contour (numeric).

symmetry_mean

Mean symmetry of the mass (numeric).

fractal_dimension_mean

Mean fractal dimension of the mass (numeric).

radius_sd

Standard deviation of the radius (numeric).

texture_sd

Standard deviation of the texture (numeric).

perimeter_sd

Standard deviation of the perimeter (numeric).

area_sd

Standard deviation of the area (numeric).

smoothness_sd

Standard deviation of the smoothness (numeric).

compactness_sd

Standard deviation of the compactness (numeric).

concavity_sd

Standard deviation of the concavity (numeric).

concave_points_sd

Standard deviation of the number of concave points (numeric).

symmetry_sd

Standard deviation of the symmetry (numeric).

fractal_dimension_sd

Standard deviation of the fractal dimension (numeric).

radius_peak

Worst (peak) value of the radius (numeric).

texture_peak

Worst (peak) value of the texture (numeric).

perimeter_peak

Worst (peak) value of the perimeter (numeric).

area_peak

Worst (peak) value of the area (numeric).

smoothness_peak

Worst (peak) value of the smoothness (numeric).

compactness_peak

Worst (peak) value of the compactness (numeric).

concavity_peak

Worst (peak) value of the concavity (numeric).

concave_points_peak

Worst (peak) number of concave points (numeric).

symmetry_peak

Worst (peak) value of the symmetry (numeric).

fractal_dimension_peak

Worst (peak) value of the fractal dimension (numeric).

Details

The dataset name has been kept as 'BreastCancerWI_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The original content has not been modified in any way.

Source

Data taken from the cases package. Original documentation available at: https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic).

Diagnosis of Pancreatic Cancer with CA19-9 Biomarker

Description

This dataset, CA19PancreaticCancer_df, is a data frame containing data from a diagnostic accuracy review on the CA19-9 biomarker used for diagnosing pancreatic cancer. The dataset includes the number of true positives (TP), false positives (FP), false negatives (FN), and true negatives (TN) from various studies.

Usage

data(CA19PancreaticCancer_df)

Format

A data frame with 22 observations and 5 variables:

study

Name or identifier of the study (character).

TP

True positives – the number of correctly identified positive cases (integer).

FP

False positives – the number of cases incorrectly identified as positive (integer).

FN

False negatives – the number of cases incorrectly identified as negative (integer).

TN

True negatives – the number of correctly identified negative cases (integer).

Details

The dataset name has been kept as 'CA19PancreaticCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package.

CASP8 Polymorphism and Breast Cancer Risk

Description

This dataset, CASP8BreastCancer_df, is a data frame containing results from 4 case-control studies examining the association between the CASP8 -652 6N del promoter polymorphism and breast cancer risk. The dataset includes information on the presence or absence of the polymorphism in both cases (breast cancer patients) and controls, with different genotypic combinations analyzed.

Usage

data(CASP8BreastCancer_df)

Format

A data frame with 4 observations and 7 variables:

study

Study identifier (character).

bc.ins.ins

Number of breast cancer cases with the ins/ins genotype (integer).

bc.ins.del

Number of breast cancer cases with the ins/del genotype (integer).

bc.del.del

Number of breast cancer cases with the del/del genotype (integer).

ct.ins.ins

Number of control cases with the ins/ins genotype (integer).

ct.ins.del

Number of control cases with the ins/del genotype (integer).

ct.del.del

Number of control cases with the del/del genotype (integer).

Details

The dataset name has been kept as 'CASP8BreastCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The original content has not been modified in any way.

Source

Data taken from the metadat package. Frank, B., Rigas, S. H., Bermejo, J. L., Wiestler, M., Wagner, K., Hemminki, K., Reed, M. W., Sutter, C., Wappenschmidt, B., Balasubramanian, S. P., Meindl, A., Kiechle, M., Bugert, P., Schmutzler, R. K., Bartram, C. R., Justenhoven, C., Ko, Y.-D., Brüning, T., Brauch, H., Hamann, U., Pharoah, P. P. D., Dunning, A. M., Pooley, K. A., Easton, D. F., Cox, A. & Burwinkel, B. (2008). The CASP8 -652 6N del promoter polymorphism and breast cancer risk: A multicenter study. Breast Cancer Research and Treatment, 111(1), 139-144. https://doi.org/10.1007/s10549-007-9752-z

Lung Cancer by Smoking Status and City

Description

This dataset, CancerSmokeCity_array, is an array containing data on lung cancer rates by smoking status and city. The data includes 32 observations organized by whether the individual smokes, their lung cancer status, and the city. The dimensions of the array are: 2 smoking statuses (smokes, does not smoke), 2 lung cancer statuses (cancer, no cancer), and 8 cities.

Usage

data(CancerSmokeCity_array)

Format

An array with 32 elements, with dimensions:

Smoking

Smoking status (character): 2 categories (smokes, does not smoke).

Lung

Lung cancer status (character): 2 categories (cancer, no cancer).

City

City (character): 8 cities.

Details

The dataset name has been kept as 'CancerSmokeCity_array' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_array' indicates that the dataset is an array. The original content has not been modified in any way.

Source

Data taken from the flatr package. Based on data in Z. Liu, Int. J. Epidemiol., 21: 197–201, 1992.

Mutant p53 Gene and Squamous Cell Carcinoma

Description

This dataset, Carcinoma_p53_df, is a data frame containing data related to the presence of the mutant p53 tumor suppressor gene and its potential role as a prognostic factor in patients with squamous cell carcinoma arising from the oropharynx cavity. The dataset includes unadjusted estimates of log hazard ratios for mutant p53 compared to normal p53 for disease-free and overall survival, along with their associated variances, collected from 6 observational studies. The dataset consists of 6 observations with 5 variables.

Usage

data(Carcinoma_p53_df)

Format

A data frame with 6 observations and 5 variables:

study

Study identifier (integer).

y1

Unadjusted log hazard ratio for disease-free survival (numeric).

y2

Unadjusted log hazard ratio for overall survival (numeric).

V1

Variance of the log hazard ratio for disease-free survival (numeric).

V2

Variance of the log hazard ratio for overall survival (numeric).

Details

The dataset name has been kept as 'Carcinoma_p53_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the mixmeta package. References:

• Jackson D, Riley R, White IR (2011). Multivariate meta-analysis: Potential and promise. Statistics in Medicine. 30 (20);2481–2498.

• Tandon S, Tudur-Smith C, Riley RD, et al. (2010). A systematic review of p53 as a prognostic factor of survival in squamous cell carcinoma of the four main anatomical subsites of the head and neck. Cancer Epidemiology, Biomarkers and Prevention. 19 (2):574–587.

• Sera F, Armstrong B, Blangiardo M, Gasparrini A (2019). An extended mixed-effects framework for meta-analysis. Statistics in Medicine. 2019;38(29):5429–5444.

Cervical Cancer Screening with Smartphones

Description

This dataset, CervicalCancer_df, is a data frame containing data from a study evaluating the diagnostic accuracy of CIN2+ detection using a combined approach with naked-eye and digital VIA (visual inspection with acetic acid) on a Samsung Galaxy J5 smartphone, compared to traditional naked-eye inspection alone.

Usage

data(CervicalCancer_df)

Format

A data frame with 181 observations and 10 variables:

hpv16

Presence of HPV16 (Factor with 2 levels).

hpv1845

Presence of HPV18/45 (Factor with 2 levels).

hpvother

Presence of other HPV strains (Factor with 2 levels).

naked_via

Naked-eye VIA result (Factor with 2 levels).

smart_via

Digital VIA result with smartphone (Factor with 2 levels).

treatment

Treatment received (Factor with 2 levels).

combined_via

Combined naked-eye and digital VIA (Factor with 2 levels).

histology

Histological diagnosis (Factor with 5 levels).

cytology

Cytological diagnosis (Factor with 7 levels).

CIN2plus

CIN2+ status (Factor with 2 levels).

Details

The dataset name has been kept as 'CervicalCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package. Data directly available from https://yareta.unige.ch/archives/ffbeb6d7-b390-4755-987e-8faf85f97c67

Childhood Cancer Data from North Portugal

Description

This dataset, ChildCancer_df, is a data frame containing information on 406 children diagnosed with cancer between January 1, 1999, and December 31, 2003, in the region of North Portugal. The dataset includes complete records on the age at diagnosis, demographic details, and survival information. Due to the interval sampling, the age at diagnosis is doubly truncated by the time from birth to the beginning and end of the study.

Usage

data(ChildCancer_df)

Format

A data frame with 406 observations and 8 variables:

X

Unspecified numerical variable (numeric).

U

Unspecified numerical variable (numeric).

V

Unspecified numerical variable (numeric).

ICCGroup

Cancer group classification (numeric).

Status

Survival status of the child: 1 = alive, 2 = deceased (numeric).

SurvTime

Survival time in days (numeric).

Residence

Residence type of the child: 1 = urban, 2 = rural (numeric).

Sex

Sex of the child: 1 = male, 2 = female (numeric).

Details

The dataset name has been kept as 'ChildCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the DTDA package. The childhood cancer data were gathered from the IPO (Registo Oncológico do Norte) service in North Portugal, kindly provided by Doctor Maria José Bento.

Chemotherapy for Stage B/C Colon Cancer

Description

This dataset, ColonCancerChemo_df, is a data frame containing data from one of the first successful trials of adjuvant chemotherapy for stage B/C colon cancer. The dataset includes information from 1858 observations and 16 variables. Each patient has two records: one for recurrence and one for death.

Usage

data(ColonCancerChemo_df)

Format

A data frame with 1858 observations and 16 variables:

id

Patient identifier (numeric).

study

Study identifier (numeric).

rx

Treatment received: 1 = observation, 2 = levamisole, 3 = levamisole+5-FU (factor).

sex

Sex of the patient: 1 = male, 2 = female (numeric).

age

Age of the patient (numeric).

obstruct

Obstruction of the colon: 1 = yes, 0 = no (numeric).

perfor

Perforation of the colon: 1 = yes, 0 = no (numeric).

adhere

Adherence to nearby organs: 1 = yes, 0 = no (numeric).

nodes

Number of positive lymph nodes detected (numeric).

status

Survival status: 1 = alive, 2 = dead (numeric).

differ

Tumor differentiation: 1 = well, 2 = moderate, 3 = poor (numeric).

extent

Tumor extent: 1 = submucosa, 2 = muscle, 3 = serosa, 4 = contiguous structures (numeric).

surg

Surgical intervention: 0 = short, 1 = long (numeric).

node4

Presence of 4+ positive lymph nodes: 1 = yes, 0 = no (numeric).

time

Follow-up time in days (numeric).

etype

Event type: 1 = recurrence, 2 = death (numeric).

Details

The dataset name has been kept as 'ColonCancerChemo_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the survival package.

PubMed Data of miRNAs in Colorectal Cancer

Description

This dataset, ColorectalMiRNAs_tbl_df, is a tibble containing information from PubMed abstracts related to microRNAs (miRNAs) in colorectal cancer. The data provides key details such as publication metadata, article abstracts, and associated miRNAs. The dataset consists of 508 observations with 8 variables.

Usage

data(ColorectalMiRNAs_tbl_df)

Format

A tibble with 508 observations and 8 variables:

PMID

PubMed Identifier (numeric).

Year

Publication year of the article (numeric).

Title

Title of the PubMed article (character).

Abstract

Abstract of the article (character).

Language

Language of the article (character).

Type

Type of publication, e.g., review, study (character).

Topic

Research topic related to colorectal cancer and miRNAs (character).

miRNA

Specific microRNAs mentioned in the publication (character).

Details

The dataset name has been kept as 'ColorectalMiRNAs_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_tbl_df' indicates that the dataset is a tibble, which is an enhanced version of a data frame in R. The original content has not been modified in any way.

Source

Data taken from the miRetrieve package. More information is available at: https://pubmed.ncbi.nlm.nih.gov/

Histology Grade and Risk Factors for Endometrial Cancer

Description

This dataset, EndometrialCancer_df, is a data frame containing information on histology grades and associated risk factors for 79 cases of endometrial cancer. The dataset provides variables related to histological grades, pathological indices, and other clinical measures. The dataset consists of 79 observations with 4 variables.

Usage

data(EndometrialCancer_df)

Format

A data frame with 79 observations and 4 variables:

NV

Nuclear volume (integer).

PI

Pathological index (integer).

EH

Endometrial hyperplasia (numeric).

HG

Histology grade (integer).

Details

The dataset name has been kept as 'EndometrialCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the enrichwith package. The dataset was first analyzed in Heinze and Schemper (2002) and originally provided by Dr. E. Asseryanis from the Medical University of Vienna. The data was downloaded in .dat format from https://users.stat.ufl.edu/~aa/glm/data/, which provides datasets used in Agresti (2015).

Head and Neck Squamous-Cell Carcinoma Treatment

Description

This dataset, HeadNeckCarcinoma_df, is a data frame containing results from 65 trials examining mortality risk in patients with nonmetastatic head and neck squamous-cell carcinoma receiving either locoregional treatment plus chemotherapy versus locoregional treatment alone. The dataset provides the observed minus expected number of deaths and corresponding variances in the locoregional treatment plus chemotherapy group.

Usage

data(HeadNeckCarcinoma_df)

Format

A data frame with 65 observations and 5 variables:

id

Trial identifier (numeric).

trial

Name of the trial (character).

OmE

Observed minus expected number of deaths (numeric).

V

Variance of the observed minus expected deaths (numeric).

grp

Treatment group (integer).

Details

The dataset name has been kept as 'HeadNeckCarcinoma_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the metadat package. Pignon, J. P., Bourhis, J., Domenge, C., & Designe, L. (2000). Chemotherapy added to locoregional treatment for head and neck squamous-cell carcinoma: Three meta-analyses of updated individual data. Lancet, 355(9208), 949-955. https://doi.org/10.1016/S0140-6736(00)90011-4

ICGC Liver Cancer Data from Japan

Description

This dataset, ICGCLiver_df, is a data frame containing liver cancer data from Japan, released by the ICGC database. The dataset includes survival time, event status, and expression levels for four genes (ANLN, CENPA, GPR182, and BCO2).

Usage

data(ICGCLiver_df)

Format

A data frame with 232 observations and 6 variables:

time

Survival time (numeric).

status

Event status (1 = event occurred, 0 = censored) (integer).

ANLN

Expression level of the ANLN gene (numeric).

CENPA

Expression level of the CENPA gene (numeric).

GPR182

Expression level of the GPR182 gene (numeric).

BCO2

Expression level of the BCO2 gene (numeric).

Details

The dataset name has been kept as 'ICGCLiver_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the ggrisk package. ICGC (International Cancer Genome Consortium) database. Liver cancer data from Japan.

North Humberside Leukemia and Lymphoma Cases

Description

This dataset, LeukemiaLymphomaCases_df, is a data frame containing information on the number of leukemia and lymphoma cases reported in different locations within North Humberside. The dataset includes the location ID and the number of cases for each location.

Usage

data(LeukemiaLymphomaCases_df)

Format

A data frame with 191 observations and 2 variables:

locationid

Location ID (integer).

numcases

Number of leukemia and lymphoma cases (integer).

Details

The dataset name has been kept as 'LeukemiaLymphomaCases_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the rsatscan package, distributed with SaTScan software: https://www.satscan.org

North Humberside Leukemia and Lymphoma Control Cases

Description

This dataset, LeukemiaLymphomaControl_df, is a data frame containing information on the number of control cases for leukemia and lymphoma reported in different locations within North Humberside. The dataset includes the location ID and the number of control cases for each location.

Usage

data(LeukemiaLymphomaControl_df)

Format

A data frame with 191 observations and 2 variables:

locationid

Location ID (integer).

numcontrols

Number of control cases (integer).

Details

The dataset name has been kept as 'LeukemiaLymphomaControl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the rsatscan package, distributed with SaTScan software: https://www.satscan.org

North Humberside Leukemia and Lymphoma Geographic Data

Description

This dataset, LeukemiaLymphomaGeo_df, is a data frame containing the geographical coordinates (x and y) for locations in North Humberside related to leukemia and lymphoma cases. It includes the location ID and the coordinates for each of the 191 locations.

Usage

data(LeukemiaLymphomaGeo_df)

Format

A data frame with 191 observations and 3 variables:

locationid

Location ID (integer).

x-coordinate

X-coordinate (integer).

y-coordinate

Y-coordinate (integer).

Details

The dataset name has been kept as 'LeukemiaLymphomaGeo_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the rsatscan package, distributed with SaTScan software: https://www.satscan.org

Impact of 6-MP on Acute Leukemia Remission Duration

Description

This dataset, LeukemiaRemission_df, is a data frame containing data on the duration of remission for acute leukemia patients who were randomly assigned to maintenance therapy with 6-mercaptopurine (6-MP), an active antileukemic compound, or a placebo. The dataset includes the sex, white blood cell (WBC) count, time to relapse, event status, and treatment group for the patients.

Usage

data(LeukemiaRemission_df)

Format

A data frame with 42 observations and 5 variables:

sex

Sex of the patient (integer).

wbc

White blood cell (WBC) count (numeric).

time

Time to relapse (integer).

event

Event status (Factor with 2 levels: 1 = relapse, 0 = no relapse).

grp

Treatment group (Factor with 2 levels: 1 = 6-MP, 0 = placebo).

Details

The dataset name has been kept as 'LeukemiaRemission_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package. Kleinbaum, D.G. and Klein, M., 1996. Survival Analysis: A Self-Learning Text. Springer.

Leukemia Remission Survival Times Placebo-Controlled RCT

Description

This dataset, LeukemiaSurvival_df, is a data frame containing remission survival times of 42 leukemia patients enrolled in a placebo-controlled randomized controlled trial (RCT). The dataset includes information on the time to remission, patient status, sex, white blood cell count (log-transformed), and treatment regimen.

Usage

data(LeukemiaSurvival_df)

Format

A data frame with 42 observations and 5 variables:

time

Time to remission in days (integer).

status

Patient status (1 for event, 0 for censored) (integer).

sex

Gender of the patient (numeric, 1 for male, 2 for female).

logWBC

Log-transformed white blood cell count (numeric).

rx

Treatment regimen (numeric, coded treatment type).

Details

The dataset name has been kept as 'LeukemiaSurvival_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the autoReg package.

Passive Smoking's Lung Cancer Threat in Women

Description

This dataset, LungCancerETS_df, is a data frame containing results from 37 studies on the risk of lung cancer in women exposed to environmental tobacco smoke (ETS) from their smoking spouse. The dataset includes data from both cohort and case-control studies, focusing on women who are lifelong nonsmokers but have been exposed to ETS.

Usage

data(LungCancerETS_df)

Format

A data frame with 37 observations and 11 variables:

study

Study identifier (integer).

author

Author(s) of the study (character).

year

Year of publication (integer).

country

Country where the study was conducted (character).

design

Design of the study (e.g., cohort or case-control) (character).

cases

Number of cases in the study (integer).

or

Odds ratio estimate (numeric).

or.lb

Lower bound of the odds ratio confidence interval (numeric).

or.ub

Upper bound of the odds ratio confidence interval (numeric).

yi

Effect size estimate (numeric).

vi

Variance of the effect size estimate (numeric).

Details

The dataset name has been kept as 'LungCancerETS_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the metadat package. Hackshaw, A. K., Law, M. R., & Wald, N. J. (1997). The accumulated evidence on lung cancer and environmental tobacco smoke. British Medical Journal, 315(7114), 980-988. https://doi.org/10.1136/bmj.315.7114.980 Hackshaw, A. K. (1998). Lung cancer and passive smoking. Statistical Methods in Medical Research, 7(2), 119-136. https://doi.org/10.1177/096228029800700203

Incidental or Screen-Detected Lung Nodules

Description

This dataset, LungNodulesDetected_df, is a data frame containing data on incidental or screen-detected lung nodules. The data includes information such as patient demographics, smoking status, nodule characteristics, and whether the nodule is malignant. The dataset was collected from patients with pulmonary nodules of up to 15mm detected on routine CT chest scans, aged 18 years or older, from 3 academic centers in the UK.

Usage

data(LungNodulesDetected_df)

Format

A data frame with 999 observations and 8 variables:

sex

Gender of the patient, represented as a factor with 2 levels (Male, Female).

age

Age of the patient (numeric).

num.annotated

Number of annotated nodules (numeric).

location

Location of the nodule, represented as a factor with 6 levels.

spiculate

Whether the nodule is spiculated, represented as a factor with 2 levels (Yes, No).

smoke.status

Smoking status of the patient, represented as a factor with 5 levels.

diameter

Diameter of the nodule (numeric).

malignant

Malignancy status of the nodule (numeric).

Details

The dataset name has been kept as 'LungNodulesDetected_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package. The dataset was collected from patients with pulmonary nodules detected on CT chest scans, aged 18 years or older, from 3 academic centers in the UK.

Mouse Cancer Data

Description

This dataset, MaleMiceCancer_df, is a data frame containing data on the occurrence of cancer in male mice. The dataset records the number of days until the occurrence of cancer under different treatment conditions. It includes 181 observations and 4 variables.

Usage

data(MaleMiceCancer_df)

Format

A data frame with 181 observations and 4 variables:

trt

Treatment group: 1 = treatment, 2 = control (factor).

days

Number of days until the occurrence of cancer (numeric).

outcome

Cancer outcome: levels include 'none', 'localized', 'metastatic', and 'other' (factor).

id

Mouse identifier (integer).

Details

The dataset name has been kept as 'MaleMiceCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the survival package.

Survival from Malignant Melanoma

Description

This dataset, Melanoma_df, is a data frame containing information about 205 patients with malignant melanoma (a type of skin cancer) who underwent a radical operation at Odense University Hospital, Denmark, between 1962 and 1977. Patients were followed up until the end of 1977. By that time, 134 patients were still alive, and 71 had died (57 due to cancer and 14 from other causes). This dataset provides detailed clinical and demographic information for studying malignant melanoma outcomes.

Usage

data(Melanoma_df)

Format

A data frame with 205 observations and 7 variables:

time

Follow-up time in days (integer).

status

Patient's status at the end of the study: 1 = alive, 2 = dead from cancer, 3 = dead from other causes (integer).

sex

Sex of the patient: 1 = male, 2 = female (integer).

age

Age of the patient at the time of surgery (integer).

year

Year of surgery (integer).

thickness

Tumor thickness in millimeters (numeric).

ulcer

Presence of ulceration: 1 = no, 2 = yes (integer).

Details

The dataset name has been kept as 'Melanoma_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the MASS package. Original study conducted at Odense University Hospital, Denmark.

Mice Deaths from Radiation

Description

This dataset, MiceDeathRadiation_df, is a data frame containing data on deaths of RFM male mice exposed to 300 rads of x-radiation at 5–6 weeks of age. The dataset records the causes of death, which include thymic lymphoma, reticulum cell sarcoma, and other causes. Additionally, it distinguishes between mice kept in a conventional environment and those in a germ-free environment.

Usage

data(MiceDeathRadiation_df)

Format

A data frame with 177 observations and 4 variables:

type

Type of environment (factor with 2 levels: conventional or germ-free).

cause

Cause of death (factor with 3 levels: thymic lymphoma, reticulum cell sarcoma, or other).

status

Survival status (numeric).

y

Time to death in days (numeric).

Details

The dataset name has been kept as 'MiceDeathRadiation_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the SMPracticals package.

NCCTG Lung Cancer Data

Description

This dataset, NCCTGLungCancer_df, is a data frame containing data on survival in patients with advanced lung cancer from the North Central Cancer Treatment Group (NCCTG). The data includes 228 observations and 10 variables related to clinical and performance score data for lung cancer patients.

Usage

data(NCCTGLungCancer_df)

Format

A data frame with 228 observations and 10 variables:

inst

Institution code (numeric).

time

Survival time in days (numeric).

status

Survival status: 1 = dead, 2 = alive (numeric).

age

Age of the patient (numeric).

sex

Sex of the patient: 1 = male, 2 = female (numeric).

ph.ecog

ECOG performance score (numeric).

ph.karno

Karnofsky performance score (numeric).

pat.karno

Patient's Karnofsky performance score (numeric).

meal.cal

Daily calorie intake (numeric).

wt.loss

Weight loss in kilograms (numeric).

Details

The dataset name has been kept as 'NCCTGLungCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the nftbart package. Based on survival data from patients with advanced lung cancer from the North Central Cancer Treatment Group (NCCTG). Performance scores rate how well the patient can perform usual daily activities.

Nodal Involvement in Prostate Cancer

Description

This dataset, NodalProstate_df, is a data frame containing data on 53 patients diagnosed with prostate cancer. The dataset records several clinical and diagnostic factors to assess nodal involvement without surgery. Nodal involvement is a critical factor in determining the treatment strategy for prostate cancer patients.

Usage

data(NodalProstate_df)

Format

A data frame with 53 observations and 7 variables:

m

Estimated probability of nodal involvement (numeric).

r

Predicted nodal involvement risk (numeric).

aged

Age group of the patient (factor with 2 levels).

stage

Cancer stage (factor with 2 levels).

grade

Tumor grade (factor with 2 levels).

xray

X-ray result (factor with 2 levels).

acid

Acid phosphatase test result (factor with 2 levels).

Details

The dataset name has been kept as 'NodalProstate_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the SMPracticals package.

Ovarian Cancer Survival Data

Description

This dataset, OvarianCancer_df, is a data frame containing survival data from a randomized trial comparing two treatments for ovarian cancer. It includes 26 observations and 6 variables related to patient demographics, treatment, and survival outcomes.

Usage

data(OvarianCancer_df)

Format

A data frame with 26 observations and 6 variables:

futime

Follow-up time in days (numeric).

fustat

Survival status: 1 = deceased, 0 = alive (numeric).

age

Age of the patient in years (numeric).

resid.ds

Residual disease: size of the largest residual tumor in centimeters (numeric).

rx

Treatment group: 1 = standard treatment, 2 = experimental treatment (numeric).

ecog.ps

ECOG performance status score: 0 = fully active, 1 = restricted activity, 2 = unable to carry out work activities (numeric).

Details

The dataset name has been kept as 'OvarianCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the survival package.

Factors associated with prostate specific antigen

Description

This dataset, PSAProstateCancer_df, is a data frame containing data from a study by Stamey et al. (1989) to examine the association between prostate specific antigen (PSA) and several clinical measures in men about to receive a radical prostatectomy. The dataset includes 97 observations and 9 variables, each representing a factor potentially associated with PSA.

Usage

data(PSAProstateCancer_df)

Format

A data frame with 97 observations and 9 variables:

lcavol

Logarithm of cancer volume (numeric).

lweight

Logarithm of prostate weight (numeric).

age

Age of the patient in years (integer).

lbph

Logarithm of benign prostatic hyperplasia (numeric).

svi

Seminal vesicle invasion (integer).

lcp

Logarithm of cancer perineural invasion (numeric).

gleason

Gleason score (integer).

pgg45

Percentage of cancerous tissue with Gleason score 4 or 5 (integer).

lpsa

Logarithm of prostate specific antigen (PSA) (numeric).

Details

The dataset name has been kept as 'PSAProstateCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the ncvreg package. Based on data from Stamey et al. (1989), which examined the association between prostate specific antigen (PSA) and several clinical measures potentially associated with PSA in men about to receive a radical prostatectomy.

PubMed Data of miRNAs in Pancreatic Cancer

Description

This dataset, PancreaticMiRNAs_tbl_df, is a tibble containing information from PubMed abstracts related to microRNAs (miRNAs) in pancreatic cancer. The data provides key details such as publication metadata, article abstracts, and associated miRNAs. The dataset consists of 381 observations with 8 variables.

Usage

data(PancreaticMiRNAs_tbl_df)

Format

A tibble with 381 observations and 8 variables:

PMID

PubMed Identifier (numeric).

Year

Publication year of the article (numeric).

Title

Title of the PubMed article (character).

Abstract

Abstract of the article (character).

Language

Language of the article (character).

Type

Type of publication, e.g., review, study (character).

Topic

Research topic related to pancreatic cancer and miRNAs (character).

miRNA

Specific microRNAs mentioned in the publication (character).

Details

The dataset name has been kept as 'PancreaticMiRNAs_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_tbl_df' indicates that the dataset is a tibble, which is an enhanced version of a data frame in R. The original content has not been modified in any way.

Source

Data taken from the miRetrieve package. More information is available at: https://pubmed.ncbi.nlm.nih.gov/

DNA Methylation Data from Patients Prostate Cancer

Description

This dataset, ProstateMethylation_df, is a data frame containing pre-processed beta methylation values collected from two sample types (benign and tumor tissue) of 4 patients diagnosed with prostate cancer. The dataset can be used for analyses of methylation patterns in benign versus tumor tissues in prostate cancer cases.

Usage

data(ProstateMethylation_df)

Format

A data frame with 5067 observations and 9 variables:

IlmnID

Unique identifier for the methylation probe (character).

FFPE_benign_1

Beta methylation value for benign tissue, patient 1 (numeric).

FFPE_benign_2

Beta methylation value for benign tissue, patient 2 (numeric).

FFPE_benign_3

Beta methylation value for benign tissue, patient 3 (numeric).

FFPE_benign_4

Beta methylation value for benign tissue, patient 4 (numeric).

FFPE_tumour_1

Beta methylation value for tumor tissue, patient 1 (numeric).

FFPE_tumour_2

Beta methylation value for tumor tissue, patient 2 (numeric).

FFPE_tumour_3

Beta methylation value for tumor tissue, patient 3 (numeric).

FFPE_tumour_4

Beta methylation value for tumor tissue, patient 4 (numeric).

Details

The dataset name has been kept as ProstateMethylation_df to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the betaclust package.

Prostate Cancer Surgery Study

Description

This dataset, ProstateSurgery_df, is a data frame containing data from a study on 97 men with prostate cancer who were scheduled to undergo radical prostatectomy. The dataset includes clinical and pathological variables associated with prostate cancer.

Usage

data(ProstateSurgery_df)

Format

A data frame with 97 observations and 9 variables:

lcavol

Logarithm of cancer volume (numeric).

lweight

Logarithm of prostate weight (numeric).

age

Patient's age in years (integer).

lbph

Logarithm of the amount of benign prostatic hyperplasia (numeric).

svi

Seminal vesicle invasion (binary: 0 = No, 1 = Yes; integer).

lcp

Logarithm of capsular penetration (numeric).

gleason

Gleason score (integer).

pgg45

Percentage of Gleason scores 4 or 5 (integer).

lpsa

Logarithm of prostate-specific antigen (PSA) level (numeric).

Details

The dataset name has been kept as 'ProstateSurgery_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the faraway package.

Prostate Cancer Survival Data

Description

This dataset, ProstateSurvival_df, is a data frame containing survival times for two competing causes: time from prostate cancer diagnosis to death from prostate cancer, and time from prostate cancer diagnosis to death from other causes. The data set also contains information on several risk factors. The data in this data set are simulated from detailed competing risk survival curves and counts of numbers of patients per group presented in Lu-Yao et al. (2009).

Usage

data(ProstateSurvival_df)

Format

A data frame with 14,294 observations and 5 variables:

grade

Cancer grade categorized into 2 levels (factor).

stage

Cancer stage categorized into 3 levels (factor).

ageGroup

Age group categorized into 4 levels (factor).

survTime

Survival time in months from prostate cancer diagnosis (integer).

status

Event status: 1 for death from prostate cancer, 2 for death from other causes, 0 for censored (integer).

Details

The dataset name has been kept as 'ProstateSurvival_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the asaur package. Simulated data based on competing risk survival curves and patient counts presented in Lu-Yao et al. (2009): *Outcomes of localized prostate cancer following conservative management*. Journal of the American Medical Association, 302, 1202–1209.

Radiation Dose Effects on Chromosomal Abnormality

Description

This dataset, RadiationEffects_df, is a data frame containing data from an experiment conducted to examine the effects of gamma radiation on the number of chromosomal abnormalities observed. The data explores the relationships between radiation dose, dose rate, and chromosomal changes.

Usage

data(RadiationEffects_df)

Format

A data frame with 27 observations and 4 variables:

cells

Number of cells observed (integer).

ca

Number of chromosomal abnormalities (integer).

doseamt

Amount of gamma radiation dose (numeric).

doserate

Rate of gamma radiation dose (numeric).

Details

The dataset name has been kept as 'RadiationEffects_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the faraway package. Based on the study by Purott R. and Reeder E. (1976): *The effect of changes in dose rate on the yield of chromosome aberrations in human lymphocytes exposed to gamma radiation*. Mutation Research, 35, 437–444.

Rotterdam Breast Cancer Data

Description

This dataset, RotterdamBreastCancer_df, is a data frame containing data on 2982 patients with primary breast cancer. The data was collected as part of the Rotterdam tumor bank and was used in Royston and Altman (2013) for survival analysis and prognostic model evaluation.

Usage

data(RotterdamBreastCancer_df)

Format

A data frame with 2982 observations and 15 variables:

pid

Patient ID (integer).

year

Year of diagnosis (integer).

age

Age at diagnosis in years (integer).

meno

Menopausal status: 1 = premenopausal, 2 = postmenopausal (integer).

size

Tumor size categorized into three levels (factor).

grade

Tumor grade: 1 = low, 2 = intermediate, 3 = high (integer).

nodes

Number of lymph nodes involved (integer).

pgr

Progesterone receptor status (integer).

er

Estrogen receptor status (integer).

hormon

Hormonal therapy: 1 = yes, 0 = no (integer).

chemo

Chemotherapy: 1 = yes, 0 = no (integer).

rtime

Time to recurrence in days (numeric).

recur

Recurrence status: 1 = recurrence, 0 = no recurrence (integer).

dtime

Time to death in days (numeric).

death

Death status: 1 = deceased, 0 = alive (integer).

Details

The dataset name has been kept as 'RotterdamBreastCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the survival package. Based on records from the Rotterdam tumor bank and used in Royston and Altman (2013) for survival analysis.

Simulated Data from Skin Cancer Chemoprevention Trial

Description

This dataset, SkinCancerChemo_df, is a data frame containing simulated data mimicking the Skin Cancer Chemoprevention Trial as used in Chiou et al. (2017). It records tumor recurrence in patients who were part of the trial, which includes information on patient demographics, prior tumors, and the treatment they received. The dataset consists of 894 observations with 7 variables.

Usage

data(SkinCancerChemo_df)

Format

A data frame with 894 observations and 7 variables:

id

Patient ID (numeric).

time

Time to event or censoring (numeric).

count

Number of tumor recurrences (numeric).

age

Age of the patient at the start of the trial (numeric).

male

Gender of the patient (1 = male, 0 = female) (numeric).

dfmo

Indicates whether the patient received DFMO treatment (1 = yes, 0 = no) (numeric).

priorTumor

Number of prior tumors before the trial (numeric).

Details

The dataset name has been kept as 'SkinCancerChemo_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the spef package. This simulated dataset is based on the study by Chiou et al. (2017): *Marginal and conditional cumulative incidence functions in the presence of dependent censoring*. Biometrics, 73(2), 385–394.

Small Cell Lung Cancer Data

Description

This dataset, SmallCellLung_tbl_df, is a tibble containing information on the entry age and survival time of 121 patients diagnosed with small cell lung cancer (SCLC) under two different treatment regimens. The dataset provides key insights for survival analysis and treatment comparisons in patients with SCLC.

Usage

data(SmallCellLung_tbl_df)

Format

A tibble with 121 observations and 3 variables:

treatment

Treatment group of the patient (factor with 2 levels).

age

Entry age of the patient at the start of treatment (integer).

survival

Survival time of the patient in days (integer).

Details

The dataset name has been kept as 'SmallCellLung_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the BSDA package. Originally published in: Ying, Z., Jung, S., Wei, L. 1995. Survival Analysis with Median Regression Models.

Years of Smoking and Lung Cancer Deaths in Men

Description

This dataset, SmokingLungCancer_df, is a data frame containing data on man-years of risk and observed number of lung cancer deaths among men. The data includes information about the years of smoking, pack-years, number of cigarettes smoked per day, and the number of deaths due to lung cancer.

Usage

data(SmokingLungCancer_df)

Format

A data frame with 63 observations and 4 variables:

yrs_smk

Years of smoking, represented as a factor with 9 levels.

pys

Pack-years of smoking (numeric).

num_cigs

Number of cigarettes smoked per day, represented as a factor with 7 levels.

deaths

Number of deaths due to lung cancer (numeric).

Details

The dataset name has been kept as 'SmokingLungCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package. Data originally from Table 24-4, page 702 of Kleinbaum et al (1988).

Suspected Cancer (SCAN) Pathway

Description

This dataset, SuspectedCancer_df, is a data frame containing blood test results from individuals presenting with non-specific symptoms of cancer. The data was collected as part of the Suspected CANcer (SCAN) pathway, which evaluates a new standard of care for patients in primary care settings.

Usage

data(SuspectedCancer_df)

Format

A data frame with 750 observations and 8 variables:

age

Age of the individual (numeric).

comorbidity

Comorbidity index (numeric).

haemoglobin

Haemoglobin level (numeric).

albumin

Albumin level (numeric).

alaninetrans

Alanine aminotransferase level (numeric).

whitebloodcell

White blood cell count (numeric).

bilirubin

Bilirubin level (numeric).

calcium

Calcium level (numeric).

Details

The dataset name has been kept as 'SuspectedCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package. Nicholson BD, Oke JL, Friedemann Smith C, et al. The Suspected CANcer (SCAN) pathway: protocol for evaluating a new standard of care for patients with non-specific symptoms of cancer. BMJ Open 2018;8:e018168.

Lung Cancer Deaths among UK Physicians

Description

This dataset, UKLungCancerDeaths_df, is a data frame containing the number of deaths due to lung cancer among British male physicians. The data is categorized by years of smoking and cigarette consumption and was originally used in Frome (1983) to analyze rates using Poisson regression models.

Usage

data(UKLungCancerDeaths_df)

Format

A data frame with 63 observations and 4 variables:

years.smok

Years of smoking categorized into 9 levels (factor).

cigarettes

Cigarette consumption categorized into 7 levels (factor).

Time

Exposure time in person-years (numeric).

y

Number of lung cancer deaths (numeric).

Details

The dataset name has been kept as 'UKLungCancerDeaths_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the SMPracticals package. Based on the study by Frome, E. L. (1983): *The analysis of rates using Poisson regression models*. Biometrics, 39, 665–674.

US Cancer Incidence, Mortality, and Survival Changes

Description

This dataset, USCancerStats_df, is a data frame containing cancer statistics for 20 solid tumor types, including incidence, mortality, and survival data. The dataset reports the absolute difference in 5-year survival between 1989-1995 and 1950-1954, as well as the percentage change in mortality and incidence from 1950 to 1996.

Usage

data(USCancerStats_df)

Format

A data frame with 20 observations and 4 variables:

site

Tumor site (character).

survival

Absolute difference in 5-year survival (numeric).

mortality

Percentage change in mortality (numeric).

incidence

Percentage change in incidence (numeric).

Details

The dataset name has been kept as 'USCancerStats_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the R4HCR package.

US Mortality Rates by Cause (Cancer) and Gender

Description

This dataset, USMortalityCancer_df, is a data frame containing mortality rates across all ages in the USA (Nation-wide) by cause of death, sex, and rural/urban status, recorded from 2011 to 2013. It includes national aggregate rates and region-wise rates for each administrative region under the Department of Health and Human Services (HHS). The dataset consists of 40 observations with 5 variables.

Usage

data(USMortalityCancer_df)

Format

A data frame with 40 observations and 5 variables:

Status

Rural or urban status (factor with 2 levels).

Sex

Gender of the individual (factor with 2 levels).

Cause

Cause of death (factor with 10 levels).

Rate

Mortality rate (numeric).

SE

Standard error of the mortality rate (numeric).

Details

The dataset name has been kept as 'USMortalityCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the lattice package. This dataset is based on the study by the Rural Health Reform Policy Research Center: *Exploring Rural and Urban Mortality Differences*, August 2015, Bethesda, MD. Available at https://ruralhealth.und.edu/projects/health-reform-policy-research-center/rural-urban-mortality.

US Region Mortality Rates by Cause (Cancer) and Gender

Description

This dataset, USRegionalMortality_df, is a data frame containing mortality rates across all ages in the USA, recorded region-wise by cause of death, sex, and rural/urban status for the years 2011–2013. It includes region-wide rates for each administrative region under the Department of Health and Human Services (HHS). The dataset consists of 400 observations with 6 variables.

Usage

data(USRegionalMortality_df)

Format

A data frame with 400 observations and 6 variables:

Region

Administrative region under the Department of Health and Human Services (HHS) (factor with 10 levels).

Status

Rural or urban status (factor with 2 levels).

Sex

Gender of the individual (factor with 2 levels).

Cause

Cause of death (factor with 10 levels).

Rate

Mortality rate (numeric).

SE

Standard error of the mortality rate (numeric).

Details

The dataset name has been kept as 'USRegionalMortality_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the lattice package. This dataset is based on the study by the Rural Health Reform Policy Research Center: *Exploring Rural and Urban Mortality Differences*, August 2015, Bethesda, MD. Available at https://ruralhealth.und.edu/projects/health-reform-policy-research-center/rural-urban-mortality.

VA Lung Cancer Data Set

Description

This dataset, VALungCancer_list, is a list containing two components: 'X' and 'y'. The data comes from a randomized trial of two treatment regimens for lung cancer. The 'X' component contains the covariates, and the 'y' component contains the survival time data. This dataset is typically used in survival analysis.

Usage

data(VALungCancer_list)

Format

A list with 2 components:

X

A numeric matrix with 1137 rows and 19 columns, representing the covariates.

y

A numeric matrix with 1137 rows and 12 columns, representing the survival time data. The columns include 'time' for the survival time and other variables related to survival analysis.

Details

The dataset name has been kept as 'VALungCancer_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_list' indicates that the dataset is a list. The original content has not been modified in any way.

Source

Data taken from the ncvreg package. Based on data from a randomized trial of two treatment regimens for lung cancer, as presented in the classic textbook by Kalbfleisch and Prentice.

Effect of Vinylidene Fluoride on Liver Cancer

Description

This dataset, VinylideneLiverCancer_df, is a data frame containing data from an experiment to investigate whether vinylidene fluoride induces liver damage. The dataset records the levels of three serum enzymes (SDH, SGOT, SGPT) under four different dosages of vinylidene fluoride. Increased serum enzyme levels are indicative of liver damage. Real data which are available on page 10 of Silvapulle and Sen (2005) and in a report prepared by Litton Bionetics Inc in 1984. These data were used in an experiment to find out whether vinylidene fluoride gives rise to liver damage.

Usage

data(VinylideneLiverCancer_df)

Format

A data frame with 40 observations and 4 variables:

SDH

Serum enzyme SDH levels (integer).

SGOT

Serum enzyme SGOT levels (integer).

SGPT

Serum enzyme SGPT levels (integer).

dose

Dose of vinylidene fluoride administered (factor with 4 levels).

Details

The dataset name has been kept as 'VinylideneLiverCancer_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix '_df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the goric package. Silvapulle MJ and Sen PK (2005). *Constrained Statistical Inference: Order, Inequality, and Shape Restrictions*. Wiley. Litton Bionetics Inc (1984). Report on the effects of vinylidene fluoride on liver enzymes in Fischer-344 rats.

Women with Breast Cancer Study

Description

This dataset, WBreastCancer_tbl_df, is a tibble containing data from a study among women with breast cancer. The dataset includes clinical and demographic variables for 1207 patients, providing valuable insights for breast cancer research and analysis.

Usage

data(WBreastCancer_tbl_df)

Format

A tibble with 1207 observations and 9 variables:

id

Unique identifier for each patient (numeric).

time

Time to the event or censoring (numeric).

status

Event status: 1 if the event occurred, 0 if censored (numeric).

er

Estrogen receptor status (numeric).

age

Age of the patient at the time of diagnosis (numeric).

histgrad

Histological grade of the tumor (numeric).

ln_yesno

Presence of lymph nodes: 1 if positive, 0 if negative (numeric).

pathsd

Pathological stage of the disease (numeric).

pr

Progesterone receptor status (numeric).

Details

The dataset name has been kept as 'WBreastCancer_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The original content has not been modified in any way.

Source

Data taken from the psfmi package.

Cancer in Dogs and Exposure to 2,4-D Herbicide

Description

This dataset, cancer_in_dogs_tbl_df, is a tibble containing information from a study conducted in 1994. The study aimed to determine whether there is an increased risk of cancer in dogs exposed to the herbicide 2,4-Dichlorophenoxyacetic acid (2,4-D). It includes data from 491 dogs diagnosed with cancer (case group) and 945 dogs without cancer (control group).

Usage

data(cancer_in_dogs_tbl_df)

Format

A tibble with 1,436 observations and 2 variables:

order

Indicates whether the dog belongs to the "case" group (with cancer) or the "control" group (without cancer) (factor with 2 levels).

response

Indicates the dog's exposure to the herbicide 2,4-D, with levels such as "exposed" or "not exposed" (factor with 2 levels).

Details

The dataset name has been kept as 'cancer_in_dogs_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the OncoDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the openintro package. Original study: Hayes HM, Tarone RE, Cantor KP, Jessen CR, McCurnin DM, and Richardson RC. 1991. Case-Control Study of Canine Malignant Lymphoma: Positive Association With Dog Owner's Use of 2,4-Dichlorophenoxyacetic Acid Herbicides. *Journal of the National Cancer Institute*, 83(17):1226-1231.