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.knitr)crmPack. In particular, there is a new vignette which
describes how to use certain functions and features of
crmPack after the major refactoring.NextBestNCRMLoss and
NextBestEWOC classes and corresponding
nextBest methods.DataGrouped and DesignGrouped
classes with corresponding model LogisticLogNormalGrouped
to support simultaneous dose escalation with monotherapy and combination
therapy arms.DesignOrdinal (simulation is not yet supported). See the
vignette for more details.DADesign.
See the vignette for more details.ProbitLogNormalRel model class to support
the (standardized) dose.knit_print methods for almost all
crmPack classes to improve rendering in Markdown and Quarto
documents. See the vignette for more details.broom-like tidy methods for
all concrete crmPack classes. See the vignette for more
details.futile.logger package, the user
interface consists of four functions: enable_logging,
disable_logging, is_logging_enabled,
log_trace.CrmPackClass class as the ultimate ancestor
of all other crmPack classes to allow identification of
crmPack classes and simpler definition of generic methods..Default<class name> to provide usable instances of
all concrete subclasses of Increments, Model,
NextBest and Stopping.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.IncrementsMaxToxProb class.approximate now returns a list containing
the fitted model and, optionally, a ggplot object of the
approximated dose/toxicity curve.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).nextBest methods
when doselimit not specified.from_prior flag - argument to
modelspecs function at GeneralModel
class.update
methods for Data-like classes. Added check
flag to possibly omit the validation of the updated object.dose_grid_range and
ngrid, which return the range and the number of doses in
the dose grid, respectively.names and size for objects
of class Samples.messgae [sic]
attribute of the return value of stopTrial with signature
stopping = "StoppingTDCIRatio".testthat and added unit and
integration tests.lifecycle package to manage
deprecations and breaking changes.ProbitLogNormal so that it supports the log of
(standardized) dose only.cohort or
ID is provided to the user constructor
Data.sampleSize function so that it returns
0 if burnin > iterations.multiplot function. Please use equivalent
functionality in other packages, such as cowplot or
ggpubr.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
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)
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.
LogisticNormal now works again - prec was
not found before.Replaced BayesLogit dependency by JAGS code, since
BayesLogit was taken off CRAN.
Speed up one example to pass CRAN check.
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.
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.
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
across all simulations will also be displayed when using ‘summary’ for simulations.
The value of the 95% CI of the final estimates will be displayed in results when using ‘stopTrial’
Bugfixes for dual endpoint designs:
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.
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).
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
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.
no NEWS until this version