Package: escalation 0.1.10

escalation: A Modular Approach to Dose-Finding Clinical Trials

Methods for working with dose-finding clinical trials. We provide implementations of many dose-finding clinical trial designs, including the continual reassessment method (CRM) by O'Quigley et al. (1990) <doi:10.2307/2531628>, the toxicity probability interval (TPI) design by Ji et al. (2007) <doi:10.1177/1740774507079442>, the modified TPI (mTPI) design by Ji et al. (2010) <doi:10.1177/1740774510382799>, the Bayesian optimal interval design (BOIN) by Liu & Yuan (2015) <doi:10.1111/rssc.12089>, EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the design of Wages & Tait (2015) <doi:10.1080/10543406.2014.920873>, and the 3+3 described by Korn et al. (1994) <doi:10.1002/sim.4780131802>. All designs are implemented with a common interface. We also offer optional additional classes to tailor the behaviour of all designs, including avoiding skipping doses, stopping after n patients have been treated at the recommended dose, stopping when a toxicity condition is met, or demanding that n patients are treated before stopping is allowed. By daisy-chaining together these classes using the pipe operator from 'magrittr', it is simple to tailor the behaviour of a dose-finding design so it behaves how the trialist wants. Having provided a flexible interface for specifying designs, we then provide functions to run simulations and calculate dose-paths for future cohorts of patients.

Authors:Kristian Brock [aut, cre], Daniel Slade [aut], Michael Sweeting [aut]

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escalation.pdf |escalation.html
escalation/json (API)
NEWS

# Install 'escalation' in R:
install.packages('escalation', repos = c('https://brockk.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/brockk/escalation/issues

On CRAN:

7.85 score 13 stars 61 scripts 299 downloads 1 mentions 100 exports 118 dependencies

Last updated 5 months agofrom:ef73adf4a1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-winOKOct 25 2024
R-4.5-linuxOKOct 25 2024
R-4.4-winOKOct 25 2024
R-4.4-macOKOct 25 2024
R-4.3-winOKOct 25 2024
R-4.3-macOKOct 25 2024

Exports:calculate_probabilitiescheck_dose_selector_consistencycohortcohorts_of_ncontinueconvergence_plotCorrelatedPatientSamplecrystallised_dose_pathsdemand_n_at_dosedont_skip_dosesdose_admissibledose_indicesdose_pathsdose_paths_functiondoses_giveneffeff_at_doseeff_limitempiric_eff_rateempiric_tox_rateenforce_three_plus_threefitfollow_pathget_boinget_boin12get_dfcrmget_dfcrm_titeget_dose_pathsget_empiric_crm_skeleton_weightsget_mtpiget_mtpi2get_potential_outcomesget_random_selectorget_three_plus_threeget_tpiget_trialr_crmget_trialr_crm_titeget_trialr_efftoxget_trialr_nbgget_trialr_nbg_titeget_wages_and_taitgraph_pathsis_randomisinglinear_follow_up_weightmean_prob_effmean_prob_toxmedian_prob_effmedian_prob_toxmodel_framen_at_dosen_at_recommended_dosenum_cohort_outcomesnum_dose_path_nodesnum_dosesnum_effnum_patientsnum_toxparse_phase1_2_outcomesparse_phase1_outcomesPatientSamplephase1_2_outcomes_to_cohortsphase1_outcomes_to_cohortsprob_administerprob_eff_exceedsprob_eff_quantileprob_eff_samplesprob_recommendprob_tox_exceedsprob_tox_quantileprob_tox_samplesrecommended_doseselect_boin_mtdselect_boin12_obdselect_dose_by_cibpselect_mtpi_mtdselect_mtpi2_mtdselect_tpi_mtdselectorselector_factorysimulate_comparesimulate_trialssimulation_functionsimulationssimulations_collectionspread_pathsstack_sims_vertstop_at_nstop_when_n_at_dosestop_when_too_toxicstop_when_tox_ci_coveredsupports_samplingthree_plus_threetoxtox_at_dosetox_limittox_targettrial_durationtry_rescue_doseutilityweight

Dependencies:abindarrayhelpersbackportsbase64encBHbinombitbit64BOINbriobslibcachemcallrcheckmateclicliprcodacolorspacecpp11crayondescdfcrmDiagrammeRdiffobjdigestdistributionaldplyrevaluatefansifarverfastmapfontawesomefsgenericsggdistggplot2gluegridExtragtablegtoolshighrhmshtmltoolshtmlwidgetsigraphinlineIsoisobandjquerylibjsonliteknitrlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellmvtnormnlmenumDerivpillarpkgbuildpkgconfigpkgloadposteriorpraiseprettyunitsprocessxprogresspspurrrquadprogQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelreadrrematch2rlangrmarkdownrprojrootrstanrstantoolsrstudioapisassscalesStanHeadersstringistringrsvUnittensorAtestthattibbletidybayestidyrtidyselecttinytextrialrtzdbutf8vctrsviridisviridisLitevisNetworkvroomwaldowithrxfunyaml

Bayesian Optimal Interval Design

Rendered fromA230-BOIN.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-10-13
Started: 2020-10-11

Comparing dose-escalation designs by simulation

Rendered fromA710-SimulationComparison.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2024-05-15
Started: 2024-01-04

Continual Reassessment Method

Rendered fromA205-CRM.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-10-13
Started: 2020-10-11

Modified Toxicity Probability Interval Design

Rendered fromA220-mTPI.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-10-17
Started: 2020-10-11

Neuenschwander, Branson & Gsponer

Rendered fromA207-NBG.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-10-13
Started: 2020-10-11

Simulating dose-escalation trials

Rendered fromA700-Simulation.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2024-02-23
Started: 2020-10-11

Toxicity Probability Interval Design

Rendered fromA210-TPI.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-10-13
Started: 2020-10-11

Using escalation

Rendered fromA100-DoseSelectors.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-10-11
Started: 2020-10-11

Working with dose-paths

Rendered fromA600-DosePaths.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-10-11
Started: 2020-10-11

Readme and manuals

Help Manual

Help pageTopics
The 'escalation' package.escalation-package escalation
Cast 'dose_paths' object to 'tibble'.as_tibble.dose_paths
Cast 'dose_selector' object to 'tibble'.as_tibble.selector
Convert a simulations_collection to a tibbleas_tibble.simulations_collection
Calculate dose-path probabilitiescalculate_probabilities
Check the consistency of a dose_selector instancecheck_dose_selector_consistency
Cohort numbers of evaluated patients.cohort
Sample times between patient arrivals using the exponential distribution.cohorts_of_n
Should this dose-finding experiment continue?continue
Plot the convergence processes from a collection of simulations.convergence_plot
A sample of patients that experience correlated events in simulations.CorrelatedPatientSample
Dose-paths with probabilities attached.crystallised_dose_paths
Demand there are n patients at a dose before condisdering stopping.demand_n_at_dose
Prevent skipping of doses.dont_skip_doses
Is each dose admissible?dose_admissible
Dose indicesdose_indices
Dose pathwaysdose_paths
Get function for calculating dose pathways.dose_paths_function
Doses given to patients.doses_given
Binary efficacy outcomes.eff
Number of toxicities seen at each dose.eff_at_dose
Efficacy rate limiteff_limit
Observed efficacy rate at each dose.empiric_eff_rate
Observed toxicity rate at each dose.empiric_tox_rate
Enforce that a trial path has followed the 3+3 method.enforce_three_plus_three
Fit a dose-finding model.fit
Follow a pre-determined dose administration path.follow_path
Get an object to fit the BOIN model using the BOIN package.get_boin
Get an object to fit the BOIN12 model for phase I/II dose-finding.get_boin12
Get an object to fit the CRM model using the dfcrm package.get_dfcrm
Get an object to fit the TITE-CRM model using the dfcrm package.get_dfcrm_tite
Calculate future dose paths.get_dose_paths
Get posterior model weights for several empiric CRM skeletons.get_empiric_crm_skeleton_weights
Get an object to fit the mTPI dose-finding model.get_mtpi
Get an object to fit the mTPI-2 dose-finding model.get_mtpi2
Get potential outcomes from a list of PatientSamplesget_potential_outcomes
Get an object to fit a dose-selector that randomly selects doses.get_random_selector
Get an object to fit the 3+3 model.get_three_plus_three
Get an object to fit the TPI dose-finding model.get_tpi
Get an object to fit the CRM model using the trialr package.get_trialr_crm
Get an object to fit the TITE-CRM model using the trialr package.get_trialr_crm_tite
Get an object to fit the EffTox model using the trialr package.get_trialr_efftox
Get an object to fit the NBG dose-finding model using the trialr package.get_trialr_nbg
Get an object to fit a TITE version of the NBG dose-finding model using trialrget_trialr_nbg_tite
Get an object to fit Wages & Tait's model for phase I/II dose-finding.get_wages_and_tait
Visualise dose-paths as a graphgraph_paths
Is this selector currently randomly allocating doses?is_randomising
Weights for tolerance and toxicity events using linear function of timelinear_follow_up_weight
Mean efficacy rate at each dose.mean_prob_eff
Mean toxicity rate at each dose.mean_prob_tox
Median efficacy rate at each dose.median_prob_eff
Median toxicity rate at each dose.median_prob_tox
Model data-frame.model_frame
Number of patients treated at each dose.n_at_dose
Number of patients treated at the recommended dose.n_at_recommended_dose
Number of different possible outcomes for a cohort of patientsnum_cohort_outcomes
Number of nodes in dose-paths analysisnum_dose_path_nodes
Number of doses.num_doses
Total number of efficacies seen.num_eff
Number of patients evaluated.num_patients
Total number of toxicities seen.num_tox
Parse a string of phase I/II dose-finding outcomes to vector notation.parse_phase1_2_outcomes
Parse a string of phase I dose-finding outcomes to vector notation.parse_phase1_outcomes
A sample of patients to use in simulations.PatientSample
Break a phase I/II outcome string into a list of cohort parts.phase1_2_outcomes_to_cohorts
Break a phase I outcome string into a list of cohort parts.phase1_outcomes_to_cohorts
Percentage of patients treated at each dose.prob_administer
Quantile of the efficacy rate at each dose.prob_eff_quantile
Probability of recommendationprob_recommend
Probability that the toxicity rate exceeds some threshold.prob_eff_exceeds prob_tox_exceeds
Quantile of the toxicity rate at each dose.prob_tox_quantile
Get samples of the probability of toxicity.prob_eff_samples prob_tox_samples
Recommended dose for next patient or cohort.recommended_dose
Select dose by BOIN's MTD-choosing algorithm.select_boin_mtd
Select dose by BOIN12's OBD-choosing algorithm.select_boin12_obd
Select dose by the CIBP selection criterion.select_dose_by_cibp
Select dose by mTPI's MTD-choosing algorithm.select_mtpi_mtd
Select dose by mTPI2's MTD-choosing algorithm.select_mtpi2_mtd
Select dose by TPI's MTD-choosing algorithm.select_tpi_mtd
Dose selector.selector
Dose selector factory.selector_factory
Simulate clinical trials for several designs using common patients.simulate_compare
Simulate clinical trials.simulate_trials
Get function for simulating trials.simulation_function
Simulated trials.simulations
Make an instance of type 'simulations_collection'simulations_collection
Spread the information in dose_finding_paths object to a wide data.frame format.spread_paths
Stack 'simulations_collection' results verticallystack_sims_vert
Stop when there are n patients in total.stop_at_n
Stop when there are n patients at a dose.stop_when_n_at_dose
Stop trial and recommend no dose when a dose is too toxic.stop_when_too_toxic
Stop when uncertainty interval of prob tox is covered.stop_when_tox_ci_covered
Does this selector support sampling of outcomes?supports_sampling
Fit the 3+3 model to some outcomes.three_plus_three
Binary toxicity outcomes.tox
Number of toxicities seen at each dose.tox_at_dose
Toxicity rate limittox_limit
Target toxicity ratetox_target
Duration of trials.trial_duration
Demand that a rescue dose is tried before stopping is permitted.try_rescue_dose
Utility score of each dose.utility
Outcome weights.weight