def print_comparative_outcomes(calibrated_model_no_drug,
calibrated_model_with_drug):
""" prints expected and percentage increase in average survival time when drug is available
:param calibrated_model_no_drug: calibrated model simulated when drug is not available
:param calibrated_model_with_drug: calibrated model simulated when drug is available
"""
# increase in survival time
increase_stat = Stat.DifferenceStatPaired(
name='Increase in mean survival time',
x=calibrated_model_with_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes,
y_ref=calibrated_model_no_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes)
# mean and prediction interval
mean = increase_stat.get_mean()
pred_int = increase_stat.get_PI(alpha=D.ALPHA)
print(
"Expected increase in mean survival time (years) and {:.{prec}%} prediction interval:"
.format(1 - D.ALPHA, prec=0), mean, pred_int)
# % increase in mean survival time
relative_diff_stat = Stat.RelativeDifferencePaired(
name='% increase in mean survival time',
x=calibrated_model_with_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes,
y_ref=calibrated_model_no_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes)
# estimate and prediction interval
mean = relative_diff_stat.get_mean()
pred_int = relative_diff_stat.get_PI(alpha=D.ALPHA)
print(
"Expected percentage increase in mean survival time and {:.{prec}%} confidence interval:"
.format(1 - D.ALPHA, prec=0), mean, pred_int)
def get_diff_mean_interval(self,
scenario_name_base,
scenario_names,
outcome_name,
deci=0,
form=None,
multiplier=1,
interval_type='p'):
if type(scenario_names) is not list:
scenario_names = [scenario_names]
list_mean_PI = {}
for name in scenario_names:
stat = Stat.DifferenceStatPaired(
name='',
x=self.scenarios[name].outcomes[outcome_name],
y_ref=self.scenarios[scenario_name_base].outcomes[outcome_name]
)
list_mean_PI[name] = Support.get_mean_interval(
stat=stat,
interval_type=interval_type,
deci=deci,
form=form,
multiplier=multiplier)
if len(scenario_names) == 1:
return list_mean_PI[scenario_names[0]]
else:
return list_mean_PI
def print_comparative_outcomes(multi_cohort_outcomes_mono,
multi_cohort_outcomes_combo):
""" prints average increase in survival time, discounted cost, and discounted utility
under combination therapy compared to mono therapy
:param multi_cohort_outcomes_mono: outcomes of a multi-cohort simulated under mono therapy
:param multi_cohort_outcomes_combo: outcomes of a multi-cohort simulated under combination therapy
"""
# increase in mean survival time under combination therapy with respect to mono therapy
increase_mean_survival_time = Stat.DifferenceStatPaired(
name='Increase in mean survival time',
x=multi_cohort_outcomes_combo.meanSurvivalTimes,
y_ref=multi_cohort_outcomes_mono.meanSurvivalTimes)
# estimate and PI
estimate_PI = increase_mean_survival_time.get_formatted_mean_and_interval(
interval_type='p', alpha=D.ALPHA, deci=2)
print(
"Increase in mean survival time and {:.{prec}%} uncertainty interval:".
format(1 - D.ALPHA, prec=0), estimate_PI)
# increase in mean discounted cost under combination therapy with respect to mono therapy
increase_mean_discounted_cost = Stat.DifferenceStatPaired(
name='Increase in mean discounted cost',
x=multi_cohort_outcomes_combo.meanCosts,
y_ref=multi_cohort_outcomes_mono.meanCosts)
# estimate and PI
estimate_PI = increase_mean_discounted_cost.get_formatted_mean_and_interval(
interval_type='p', alpha=D.ALPHA, deci=2, form=',')
print(
"Increase in mean discounted cost and {:.{prec}%} uncertainty interval:"
.format(1 - D.ALPHA, prec=0), estimate_PI)
# increase in mean discounted QALY under combination therapy with respect to mono therapy
increase_mean_discounted_qaly = Stat.DifferenceStatPaired(
name='Increase in mean discounted QALY',
x=multi_cohort_outcomes_combo.meanQALYs,
y_ref=multi_cohort_outcomes_mono.meanQALYs)
# estimate and PI
estimate_PI = increase_mean_discounted_qaly.get_formatted_mean_and_interval(
interval_type='p', alpha=D.ALPHA, deci=2)
print(
"Increase in mean discounted utility and {:.{prec}%} uncertainty interval:"
.format(1 - D.ALPHA, prec=0), estimate_PI)
def mytest_diff_stat_paired(x, y):
# define
stat = Stat.DifferenceStatPaired(x, y, name='Test DifferenceStatPaired')
print('Testing DifferenceStatPaired:')
print_results(stat)
