CLL-data {RPointCloud}

Chronic Lymphocytic Leukemia Clinical Data

Description

Contains 29 columns of deidentified clinical data on 266 patients with chronic lymphocytic leukemia (CLL).

Usage

data(CLL)

Format

Note that there are three distinct objects included in the data set: clinical, daisydist, and ripDiag.

clinical

A numerical data matrix with 266 rows (patients) amd 29 columns (clinical features). Patients were newly diagnosed with CLL and previously untreated at the time the clinical measurements were recorded.

daisydist

A distance matrix, stored as a dist object, recording pairwise distances between the 266 CLL patients. Distances were computed using the daisy function of Kaufmann and Rooseeuw, as implemented in the cluster R package.

ripDiag

This object is a "Rips diagram". It was produced by running the the ripsDiag function from the TDA R package on the daisydist distance matrix.

Author(s)

Kevin R. Coombes [e-mail], Caitlin E. Coombes [e-mail], Jake Reed [e-mail]

Source

Data were collected in the clinic of Dr. Michael Keating at the University of Texas M.D. Anderson Cancer Center to accompany patient samples sent to the laboratory of Dr. Lynne Abruzzo. Various subsets of the data have been reported previously; see the references for some publications. Computation of the daisy distance was performed by Caitlin E. Coombes, whose Master's Thesis also showed that this was the most appropriate method when dealing with heterogeneous clinical data of mixed type. Computation of the topological data analysis (TDA) using the Rips diagram was performed by Jake Reed.

References

Schweighofer CD, Coombes KR, Barron LL, Diao L, Newman RJ, Ferrajoli A, O'Brien S, Wierda WG, Luthra R, Medeiros LJ, Keating MJ, Abruzzo LV. A two-gene signature, SKI and SLAMF1, predicts time-to-treatment in previously untreated patients with chronic lymphocytic leukemia. PLoS One. 2011;6(12):e28277. doi: 10.1371/journal.pone.0028277.

Duzkale H, Schweighofer CD, Coombes KR, Barron LL, Ferrajoli A, O'Brien S, Wierda WG, Pfeifer J, Majewski T, Czerniak BA, Jorgensen JL, Medeiros LJ, Freireich EJ, Keating MJ, Abruzzo LV. LDOC1 mRNA is differentially expressed in chronic lymphocytic leukemia and predicts overall survival in untreated patients. Blood. 2011 Apr 14;117(15):4076-84. doi: 10.1182/blood-2010-09-304881.

Schweighofer CD, Coombes KR, Majewski T, Barron LL, Lerner S, Sargent RL, O'Brien S, Ferrajoli A, Wierda WG, Czerniak BA, Medeiros LJ, Keating MJ, Abruzzo LV. Genomic variation by whole-genome SNP mapping arrays predicts time-to-event outcome in patients with chronic lymphocytic leukemia: a comparison of CLL and HapMap genotypes. J Mol Diagn. 2013 Mar;15(2):196-209. doi: 10.1016/j.jmoldx.2012.09.006.

Herling CD, Coombes KR, Benner A, Bloehdorn J, Barron LL, Abrams ZB, Majewski T, Bondaruk JE, Bahlo J, Fischer K, Hallek M, Stilgenbauer S, Czerniak BA, Oakes CC, Ferrajoli A, Keating MJ, Abruzzo LV. Time-to-progression after front-line fludarabine, cyclophosphamide, and rituximab chemoimmunotherapy for chronic lymphocytic leukaemia: a retrospective, multicohort study. Lancet Oncol. 2019 Nov;20(11):1576-1586. doi: 10.1016/S1470-2045(19)30503-0.

Coombes CE, Abrams ZB, Li S, Abruzzo LV, Coombes KR. Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia. J Am Med Inform Assoc. 2020 Jul 1;27(7):1019-1027. doi: 10.1093/jamia/ocaa060.