Version 2.3.0

New Features

• Added StoppingDoseStabilized, a stopping rule that stops when the current next best dose has been administered to a prespecified number of consecutive cohorts.

• Additional plotting options for one-dimensional nextBest methods are available, including log and equally spaced factor dose scales, lollipop layers instead of bars, and dose-grid or regularly spaced axis ticks.

Enhancements

• HierarchicalModel now compiles exchangeable normal priors in non-centered form for JAGS, including analytic Cholesky transformations for correlated parameter pairs. Non-centered hypermean nodes use a reserved z_mu_ prefix so pool names such as "x" and "x_z" cannot generate conflicting JAGS nodes. In the comparison_decider example, this increased the minimum effective sample size across monitored parameters from approximately 450 to 47,000 for 100,000 retained draws, without increasing runtime.

• HierarchicalModel and HierarchicalDesign now support exchangeable "eta" pools for TwoDrugsCombo arms. Each combination arm retains its own interaction parameter while sharing hyperparameters, and singleton interaction pools are supported so that the same hierarchical marginal prior can be used with one combination arm.

Miscellaneous

• Next-dose probability plots now identify the increment, safety, and overdose rules and the recommended dose in legends. It is also possible to use a triangle to mark the highest safe dose. Multi-panel plots put overdose information first and align their plotting areas.

• Extended GeneralSimulationsSummary with a true_mtd slot and enhanced summary plotting accordingly.

• Extended Simulations and SimulationsSummary classes with overdose probability at the final selected dose.

• Simulation trajectory plots now use stepped blue ribbons to show the minimum and maximum and interquartile ranges alongside the median, with a legend and patient-axis ticks inferred from cohort boundaries. Patient tick positions can also be supplied with the new patient_scale argument.

• Minor grid lines are suppressed when dose-grid or factor axes are used, making next-dose and simulation plots easier to read.

• The dependency ggplot2 package now needs to have minimum version 3.2.0 instead of previously 3.0.0. This should not be a practical restriction because version 3.2.0 was already released in 2019.

Bug Fixes

• examine() for DADesign now identifies the current cohort in cohort and lists one cohort index per additional hypothetical DLT in DLT_cohorts. The numeric DLTsearly_1 column has been replaced by DLT_scenario, with values "no additional DLTs", "late DLTs", and "early DLTs". DLT_time includes the onset time of each hypothetical DLT relative to its cohort start and is aligned with DLT_cohorts. Documentation now explains the scenario allocations and that DLTs can include patients from earlier cohorts. The method also correctly counts eligible patients, evaluates both timing scenarios without duplicate allocations, and advances using only the current cohort’s zero-DLT recommendation. These fixes remove replacement-length warnings and correct the no-increment stopping logic.

Version 2.2.1

Miscellaneous

• Fixed tests to be compatible with the new R development version.

Version 2.2.0

New Features

• Combination designs are supported via DesignCombo and HierarchicalDesign. Please see the new vignette combo_designs for details.
• MinimalInformative and Quantiles2LogisticNormal now also support producing LogisticLogNormalSub models, i.e. using the subtraction of a reference dose on the natural dose scale in the regression model.
• Added TITELogisticLogNormalSub model which inherits from LogisticLogNormalSub and can be used for TITE designs, via DADesign.

Bugfixes

• The knit_print method for LogisticNormalMixture did not render correctly previously; this is fixed now.
• The intervals in NextBestNCRMLoss could be non-contiguous without the user being notified; this is fixed now, the construction will fail and ensure contiguous intervals.

Version 2.1.0

• This release marks yet another major update of the package: Backfill cohort simulations are now supported in the Design class, powered by the new Backfill class. This also leads to breaking changes in the Data and GeneralSimulationsSummary classes, which gains new slots, too. Please regenerate any existing Dataor Designas well as resulting SimulationsSummary objects; serialized objects from previous versions will not be compatible.

New Features

• A new vignette trial_backfill has been added which describes how to use backfill cohorts in crmPack.
• Added new Backfill class which allows to specify backfill cohorts as a new slot in the Design objects.
• Added new slots backfilled and response in the Data class to capture the information whether each patient has been backfilled, and whether a (binary) efficacy response was observed (in order to support backfilling rules which depend on a minimum number of efficacy responses).
• The plot method for Data objects allows to optionally exclude backfill patients, and mark backfill and response information.
• Added new virtual classes Opening and Recruitment and corresponding instantiable subclasses to allow for flexible specification of backfill cohort opening and recruitment rules.
• Added new CohortSizeRandom class to allow for random cohort sizes.
• Simulations of Design objects now support backfill cohorts.
• GeneralSimulationsSummary got new slots any_backfilled, n_backfilland backfill_doses informing whether any backfilling was planned or took place, the number of backfill patients and the doses of the backfill patients across the simulations. The corresponding show method was updated to display this information to the user.
• GeneralSimulations got a simple show method to avoid printing the whole structure to the user, which is probably not helpful.
• StoppingPatientsNearDose got a new slot include_backfill to allow for optionally excluding backfilled patients from the patient count.

Version 2.0.2

Miscellaneous

• Fixed logging tests which had been broken by recent futile.logger updates.

Version 2.0.1

Bugfixes

• The validation of LogisticNormalFixedMixture objects did not allow for a floating point calculation deviation in the sum of the weights when comparing them to 1, which was caught by the M1mac check on CRAN. This has been fixed now.

Version 2.0.0

• This release signifies a major breaking revamp of the package. Over several years, the package has undergone significant cleanup, tests writing and refactoring efforts. The package has thereby reached a major milestone and currently includes:
  • 15 different dose-toxicity models
  • 15 different dose recommendation rules
  • 19 different stopping rules
  • 9 cohort size rules
  • 9 increment rules
  • Reporting functionality (using knitr)
  • 13 vignettes (documentation)
• Users are advised to carefully review the release notes and documentation for detailed information on the changes and any necessary updates to their existing code using a previous CRAN release of crmPack. In particular, there is a new vignette which describes how to use certain functions and features of crmPack after the major refactoring.

New Features

• Added new NextBestNCRMLoss and NextBestEWOC classes and corresponding nextBest methods.
• Added new DataGrouped and DesignGrouped classes with corresponding model LogisticLogNormalGrouped to support simultaneous dose escalation with monotherapy and combination therapy arms.
• Provided basic support for ordinal CRM models in DesignOrdinal (simulation is not yet supported). See the vignette for more details.
• Included rolling CRM design implemented in DADesign. See the vignette for more details.
• Created new ProbitLogNormalRel model class to support the (standardized) dose.
• Implemented knit_print methods for almost all crmPack classes to improve rendering in Markdown and Quarto documents. See the vignette for more details.
• Implemented broom-like tidy methods for all concrete crmPack classes. See the vignette for more details.
• Added logging via the futile.logger package, the user interface consists of four functions: enable_logging, disable_logging, is_logging_enabled, log_trace.
• Created the CrmPackClass class as the ultimate ancestor of all other crmPack classes to allow identification of crmPack classes and simpler definition of generic methods.
• Added no-parameter constructor functions named .Default<class name> to provide usable instances of all concrete subclasses of Increments, Model, NextBest and Stopping.
• Included additional_stats to add reporting of additional parameters to method simulate to summarize MTD.
• report_label can be added to stopping rules for individual or combined stopping rule reporting.
• Implemented the IncrementsMaxToxProb class.

Enhancements

• approximate now returns a list containing the fitted model and, optionally, a ggplot object of the approximated dose/toxicity curve.
• Modified efficacy-EffFlexi method: allowed for vectorized dose; NA is now returned for doses from outside of the dose grid range (and the warning is thrown).
• doselimit argument in nextBest method is now specified as Inf instead of numeric(0).
• Warning message not printed anymore by nextBest methods when doselimit not specified.
• Allowed for from_prior flag - argument to modelspecs function at GeneralModel class.
• Introduced validation of the updated object for update methods for Data-like classes. Added check flag to possibly omit the validation of the updated object.
• Added new functions dose_grid_range and ngrid, which return the range and the number of doses in the dose grid, respectively.
• Added methods names and size for objects of class Samples.

Bugfixes

• Corrected the spelling of the name of the messgae [sic] attribute of the return value of stopTrial with signature stopping = "StoppingTDCIRatio".

Refactoring

• Set up the package to use testthat and added unit and integration tests.
• Started using the lifecycle package to manage deprecations and breaking changes.
• Changed ProbitLogNormal so that it supports the log of (standardized) dose only.
• Replaced warning with message when no cohort or ID is provided to the user constructor Data.
• Re-factored sampleSize function so that it returns 0 if burnin > iterations.

Miscellaneous

• Removed multiplot function. Please use equivalent functionality in other packages, such as cowplot or ggpubr.

Version 1.0.0

• Reference JSS publication.

Version 0.2.9

• By default only use 5 cores and not all available cores on a machine. Note that this value can also be changed by the user.
• Change of maintainer

Version 0.2.8

Bugfixes:

• PLcohortSize now defaults to 0 placebo patients upon Design class initialization (instead of 1 before - but note that this did not have effect on erroneous simulations, due to option being set in Data class)
• The “examine” function also stops when the stopping rules are fulfilled already in case of no DLTs occurring. This was not the case beforehand and could lead to infinite looping (thanks to John Kirkpatrick for reporting the bug)
• Removed RW2 warnings in “DualEndpointRW” - it seems to work nicely now (thanks to Charles Warne for reporting!)
• Removed WinBUGS since it was not used anyway (and paper does not describe it)

New features:

• The “examine” function now counts the number of times the same dose is recommended contiguously and break after e.g. the default 100 times (can be specified in a new option of “examine”) to further avoid infinite loops and issues a corresponding warning if this condition is met
• New “Increments” class “IncrementsNumDoseLevels” that works directly on the number of dose levels in the dose grid that can be incremented to from the current to the next cohort (thanks to John Kirkpatrick for the suggestion). This can for example be used in order to force the design not to skip any dose level when escalating.
• Included the JSS manuscript as a new vignette.
• It is now possible to specify how many cores should be used when parallel computations are used.

Version 0.2.7

Bugfixes:

• LogisticNormal now works again - prec was not found before.

Version 0.2.6

Bugfixes:

• Replaced BayesLogit dependency by JAGS code, since BayesLogit was taken off CRAN.
• Speed up one example to pass CRAN check.

Version 0.2.5

New features:

• matching of doses with the dose grid now includes a tolerance of 1e-10, in order to make it more user-friendly (thanks to YJ Choi and Giuseppe for investigating)

Bugfixes:

• documentation:

  • minor fix for alpha1 description in LogisticLogNormal-class

• minor fix on scale_colour_manual import from ggplot2 reported by R-Core

Version 0.2.4

New features:

• In case of multiple nextBest plots these are now also returned as original plots in the list singlePlots, to allow for further customization, before jointly plotting them.
• ProbitLogNormal: Now also this model allows for a reference dose and a log transformation of the (standardized) dose. This can be specified with options refDose and useLogDose.
• DualEndpoint: Same additional options as for ProbitLogNormal are now available for the DualEndpoint models. As a consequence, the parameter “refDose” for class DualEndpointBeta needed to be renamed to “refDoseBeta”, and the parameter “refDose” for class DualEndpointEmax renamed to “refDoseEmax”.

Bugfixes:

• documentation: in the DualEndpoint description fixed the problem in the formula

Version 0.2.3

New features:

• New increment class “IncrementMin” has been added which allows to combine multiple increment rules with the MIN operation

Version 0.2.1

New features:

• Option targetThresh for NextBestDualEndpoint allows to tune from which target probability onwards it will be used to derive the next best dose (before this was fixed to 0.05)
• Added ProbitLogNormal model
• In the NextBestDualEndpoint class, the additional option “scale” now allows to also specify absolute biomarker target ranges. In the corresponding method evaluation, the safety samples are now no longer included in the evaluation of the biomarker target probability, such that now the description is consistent with the computations.
• NextBestNCRM and NextBestDualEndpoint now return the matrix of target and overdosing probabilities as additional list element “probs” in the result of “nextBest” applied.
• Note that in the StoppingTargetBiomarker evaluation, the toxicity is no longer a part of the biomarker target probability.

Bugfixes:

• Added back the example vignette, so that it can be opened with crmPackExample()
• Clarified that for the DualEndpointRW model samples from the prior cannot be obtained due to impropriety of the RW prior (added to model class description).
• For DualEndpointRW models, it is now possible to have non-equidistant grid points, and obtain sensible results. (But still needs to be thoroughly tested though.)
• For DualEndpointBeta model, it is now possible to have negative E0 and Emax parameters.
• Cohort size of 0 for placebo is now possible - e.g. to only start with patients and then later move to larger cohorts also including placebo subjects.
• When simulating with firstSeparate=TRUE and placebo, now the first (sentinel) cohort includes one active and one placebo patients, and the next patients use the cohort size for the active and placebo arms, respectively.
• Barplots work now also when there was only one observed value in all simulations
• NextBestDualEndpoint now only takes into account active doses when optimizing the biomarker outcome for the next best dose among admissible doses, thus avoiding early stopping at the placebo dose level.
• If DataMixture objects are used, mcmc now correctly sets fromPrior to FALSE if the shared data object contains any data.

Version 0.2.0

• Added arguments probmin and probmax to MinimalInformative in order to control the probability threshold at the minimum and maximum dose for the minimally informative prior

• Values of 95% CI and the corresponding ratio of the upper to the lower limit of this CI are displayed in results when using ‘nextBest’

• The six- number summary tables including the values of the lowest, 25th percentile, 50th percentile or the median, the mean, the 75th precentile and the highest of the final (at stopping) estimates of the

  1. dose levels corresponds to the target probability of DLE used at the end of a trial, TDEOT
  2. ratios of the upper to the lower 95% credibility intervals (CI) of TDEOT
  3. dose levels corresponds to the target probability of DLE used during a trial
  4. dose levels corresponds to the maximum gain value, Gstar
  5. ratios of the upper to the lower 95% CI of the final estimates of Gstar
  6. optimal doses, either the TDEOT (for DLE response only) or the minimum of TDEOT and Gstar (for DLE and efficacy response)
  7. ratios of the optimal dose

  across all simulations will also be displayed when using ‘summary’ for simulations.

Version 0.1.8

• The value of the 95% CI of the final estimates will be displayed in results when using ‘stopTrial’

• Bugfixes for dual endpoint designs:

  • Improved graphical display in plots for nextBest dose
  • Improved methodology to compute Gstar
  • Warnings are removed when using nextBest in simulations
  • Stopping rules can now also be freely combined using the and/or operators with the dual endpoint design stopping rules not using MCMC samples.

Version 0.1.6

• New model class “LogisticLogNormalMixture” has been added, for use with the new data class “DataMixture”.
• New stopping rule “StoppingHighestDose” has been added.
• The “examine” method no longer stops when two consecutive cohorts start with the same dose. This is important e.g. for the two-parts study designs, where part 1 can end with the same dose as part 2 starts.
• The contents of the “datanames” slot of new models are no longer restricted to a specific set, which was previously enforced by the validation function of the GeneralModel and AllModels classes.
• Sampling from the prior can now be enabled/disabled by the user for the mcmc function, which is necessary for models where it might not be from the prior even though nObs == 0.
• Bugfix: The results from the MinimalInformative function were not reproducible beforehand. Now a seed parameter can be supplied, which ensures reproducibility.
• Bugfix: Compatibility of help file links with new ggplot2 package version.

Version 0.1.5

• Bugfix: In newer versions of grid the plotting of simulation objects did no longer work. This was fixed.

Version 0.1.2

• Bugfix: The MinimalInformative function previously produced too uninformative prior quantiles, which were not fulfilling the requirements in the function’s documentation. With this bugfix, the correct (as per the Neuenschwander et al (2008) publication) prior quantiles are specified and then approximated with logistic (log) normal priors.

Version 0.1.1

• Bugfix: Previously, it could happen with NextBestNCRM rule, that higher doses lead to decreasing probability of overdosing, only because for some doses there was numerically probability 1 of having a DLT. With this bugfix, it was clarified in the rules documentation and fixed in the rule method, that the right limit of the overdose interval vector will be inclusive.

Version 0.1.0

• Added examine function to generate a table of hypothetical trial courses for model-based and rule-based DLT-endpoint designs
• Made results from mcmc() (works with the usual set.seed in earlier user code) and simulate() (as previously already promised) reproducible. See help file for mcmc for more details. Additional improvements to reduce confusing warning messages / notes from mcmc() and higher-level functions.
• Made simulate with parallel=TRUE work on r.roche.com (Linux server), using the same parallelization method as for laptops (Windows)
• Passing an empty (zero length) vector as the doselimit parameter of the nextBest function is now considered as requesting a dose recommendation without a strict dose limit, and a corresponding warning is printed.
• Introduced GeneralModel class, from which then the class Model for single agent dose escalation derives. Another branch will be the ComboLogistic model for multiple agent combinations (in a future version). Similarly introduced GeneralData class, from which the class Data for single agent derives, separately from that will be the subclass DataCombo (in a future version).

Version 0.0.23

• Fixed bug in mcmc function which led to error “all data elements must have as many rows as the sample size was” and slightly changed JAGS way of handling burnin / thinning (which should not have a user impact).
• Reduced number of MCMC samples for dual-endpoint example in vignette to be able to plot the vignette

Version 0.0.22

• simulate function has been fixed (specification of arguments)
• Dual-endpoint model-based design has been added.
• 3+3 design simulation is now possible, see ?ThreePlusThreeDesign
• Welcome message on attaching crmPack, i.e. when library(“crmPack”) is run
• crmPackUpgrade() function for easy upgrade of crmPack to the latest version
• Rule-based designs now can be specified with the class RuleDesign, while the model-based designs stay with the class Design. An even more special class is the DualDesign class, for dual-endpoint model-based designs. Corresponding classes GeneralSimulations, Simulations and DualSimulations capture the output of the trial simulations for rule-based, model-based and dual-endpoint designs.
• The class Simulations-summary has been renamed to SimulationsSummary, similarly for the classes GeneralSimulationsSummary and DualSimulationsSummary.
• All Stopping and CohortSize rules that are based on intervals (IncrementsRelative, IncrementsRelativeDLT, CohortSizeRange, CohortSizeDLT) now use a different intervals definition. Now the “intervals” slots only contain the left bounds of the intervals. Before, the last element needed to be infinity. See the vignette for examples.
• StoppingMaxPatients class has been removed, as it was redundant with the class StoppingMinPatients. Please just use the StoppingMinPatients class instead.
• Initialization methods have been replaced by dedicated initialization functions. Please now use these Class(…) functions instead of new(“Class”, …) calls to obtain the correct objects. This change is also reflected in the vignette.
• The extract function for extracting parameter samples from Samples objects has been removed (due to a name conflict with ggmcmc dependency packages). Please now use instead the “get” method for Samples objects (see the vignette for an example) to obtain data in the ggmcmc format.
• crmPack now needs the package httr (it’s now in the “Imports” field). Packages Rcpp and RcppArmadillo have been moved from “Depends” to “Suggests” packages. Currently we are not using them at all.
• showLegend argument for model fit plotting functions, in order to show the legend or not.

Version 0.0.21

no NEWS until this version

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