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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_2946_Библиотеки_им_академика_М_И_Перельмана
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Index 345
quality‐lifetime adjusted utility, 201
quality‐lifetime parametric utility model,
200–2
quality‐lifetime tradeoff models, 193–203
quality‐survival tradeoff models, 203–9
certainty equivalent, 147–8 see also risk
attitudes
clinical applications
communication with patients, 181–3
parametric model, 160–72, 183
risk attitudes, 172–81
determining
lifetime‐tradeoff assessment, 152–3
survival‐tradeoff assessment, 154–6
direct approach, to utility assessment,
209–11
risk attitudes, 135–6
certainty equivalent, 148–51
in medical condition, 136–47
outcome values, 94
P
parametric two‐part survival models, 238,
240–3, 245
parametric utility model
defined, 160, 161
exponential utility model, 161–2, 184
alternate assessment approach, 166–70
assumption, 163–5
first approach, 165–6
nomogram, 186–7
and risk attitude, 171–2
risk parameter, 171
scaling, 162–3
pattern recognition, 6
percutaneous coronary intervention (PCI), 104,
124
pessimistic survival model, 224
positive predictive value, 66
positron emission tomography (PET), 313
posterior probability, 4
post‐test odds, 48
post‐test probability, 4, 66–7, 291 see also posterior
probability
negative test result, 45
positive test result, 45
predictive validity, 318
predictive value
negative, 66
pitfalls, 69–70
positive, 66
vs. post‐test probability, 66–7
predictor variables, 32
pre‐test probability, 4, 4, 44, 51
prior probability, 4, 39
probabilistic dependence, 20
probabilistic independence, 20
probabilistic sensitivity analysis, 317
probability, 19, 20
direct probability assessment, 23
disease prevalence, in patients
with clinical syndrome, 31
with symptoms/test result, 30–1
indirect probability assessment, 22–3
odds, 20–1
as present state vs. future event, 20
quantification, 21–2
sources of error, 23–30
using clinical prediction model, 32–5
probability‐based standard gamble
assessment, 140
probability mass function, 220
productivity costs, 336
prospect theory, 164
pulmonary embolism (PE), 211, 212, 278
treatment decision, 216
Q
quality‐adjusted life years (QALY), 202–3,
310, 325
quality‐lifetime parametric utility model, 197,
200–2
quality‐lifetime tradeoff models, 189, 190, 192,
194, 203, 216
and healthcare policy analysis, 202–3
mathematical expression, 195
parameterizing, 196–200
and risk aversion, 202
quality‐lifetime tradeoff parameter, 197, 216
quality‐survival adjusted utility, with
exponential survival, 209
quality‐survival parametric model, 208, 217
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346 Index
quality‐survival tradeoff model, 189, 203,
204, 217
parameterized quality‐survival tradeoff model,
206–8
quality‐lifetime tradeoff function, 195
quality preferences, 204–6
R
radiotherapy, 183
random variable, 94
receiver operating characteristic (ROC) curve,
83–5, 84, 87, 89–91
recursive partitioning, 34
reference case analysis, 332
regression analysis, 32–4, 34
regression to the mean, 26–7, 27
representativeness heuristic, 12, 24
errors
ignoring prior probability, of disease,
24–5
inaccurate clinical cues, to predict disease,
25–6
redundant predictors, 26
regression to the mean, 26–7
small unrepresentative experience, with
disease, 27–8
rescaled utilities, 216
risk‐adjusted clinical policies, 172–3,
179–81
risk adjustments see survival models
risk attitudes, 134–6, 156
certainty equivalent, 148–51
clinical applications
age and gender‐specific clinical policy,
179–80
assessment question, 177–9, 181
clinical policy design, 173–4
risk‐adjusted clinical policies, 172–3,
180–1
risk parameter threshold, 174–7
constant risk attitudes, 184
in medical condition
branch probabilities, for lung cancer
treatment decision, 137–8
expected utility calculations, 144–6, 145
lung cancer treatment, as decision tree, 137
outcome utilities, for lung cancer decision
problem, 141–4
for selecting treatment, 146–7
using standard gamble assessment, 139–41
von Neumann Morgenstern utility, 138
risk‐averse preferences, 149
risk aversion, 134, 158
risk‐indifferent preferences, 151, 157
risk‐neutral preferences, 151
risk parameter, 164
guaranteed outcome assessment, 167
uncertain outcome assessment, 167
risk preferring, 136
risk seeking, 136
risk tolerance, 136
risk‐tolerant preferences, 150
risky treatment alternatives, 4
Rule of Parsimony, 12–13
S
scarce resources allocation, principles,
324–5
sensitivity, 64
inaccurate measurement, 79–81
test, 42, 51–2
sensitivity analysis, 114, 127
clinical policies, 132
life expectancy, 130
one‐way, 127–9, 131
for problems, with two decisions, 131–2
two‐way, 129–31, 130
slow distant recurrence health state, 253
Social Security Administration, 104, 272
source population, 63, 68–69, 70
specificity, 64
accurate measurement, 79
of diagnostic test, 64–5
spectrum bias, 74
adjustments, disease severity bias, 78–9
exact adjustment, 78–9
first phase of test evaluation
sickest of the sick, 74–75
wellest of the well, 74–75
second phase, test evaluation, 75
sensitivity and specificity adjustments, 78
spleen scan, 76
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Index 347
test sensitivity, 75–8
test specificity, 77
splenomegaly, 67, 68
standard deviations, 59
of normal distribution, 59
standard gamble assessment, 139–41
decision tree, 210
outcome based, 156
probability based, 156
Standards for Reporting of Diagnostic Accuracy
(STARD) statement, 74
state‐transition models, 304
stationarity, 254–7
streptococcal pharyngitis, 280
successful treatment health state, 259, 268, 271
surgery‐based therapies, 103
survival models, 218, 247
actuarial survival models, 232, 239
age‐and gender‐specific, 233–4, 234
derivation from life tables, 234
as representation of general population, 232
risk adjustments of, 235
basic elements, 219–26
estimation, 223–4
exponential survival model
annual mortality rate, 232
fitting an, 230–2
lifetime probabilities, 229–30
hazard rates, 222–3
Kaplan‐Meier survival model
assumption, 224, 225
estimation, 224, 225
lifetime probabilities, 220
observation based survival models, 228
survival after breast cancer recurrence,
226–8
survival probabilities, 220, 246, 250
time representation, 220–1
two‐part survival models
age adjustment, 239–40, 240
limitations, 243–5
observed survival, with exponential survival
model, 236–8
expected utility calculation with parametric
utility model, 240–3
parametric two‐part survival models, 238
unexpected deaths, 243
values, 223
survival probability, 246, 250 see also survival
models
survival transitions, 250
suspected pulmonary embolism (PE)
clinical prediction model
D‐dimer test and CTPA, 294
pre‐test probability, of PE (Wells’ Criteria),
294
decision tree, 212
test selection, 293
syndrome, defined, 31
systematic review, 87–88
T
target condition, 20, 41, 59
defined, 313
prevalence, published reports, 35–6
severity bias, 75, 77
test cut point value, 61, 86–87
test negative, 41, 51
test of time, 26
test performance, 62
test positive, 41, 51
test‐referral bias, 75–77
test results
continuous variable as, 61–2
dichotomous variable as, 60
normal vs. abnormal, 61
positive and negative, 61
upper limit of normal, 60–1
test‐review bias, 73
test sets, 34
test‐treat threshold, 291
therapeutic trial, 26
threshold probabilities, 50, 211, 286
of intracranial hemorrhage, 299
for testing
criteria, 288
equations, 291–2
no treat option, 290
performing diagnostic test, 288–91
test option, 289
treat option, 290
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348 Index
for treatment
derivation, 282–5
harm and benefit, 283
heuristics, 285–6
pulmonary embolism, 286–8, 287
rationale, 281–2
time representation in survival models see
survival models
training set, 34
trapping state, 250
treatment‐free life expectancy, 129
treatment threshold probability, 4, 282
true negative result, 64
true positive result, 64
two‐part survival models see also survival
models
age adjustment, 239–40, 240
limitations, 243–5
observed survival, with exponential survival
model, 236–8
outcome utilities, calculation, 240–3
parametric, 238
two‐way sensitivity analysis, 129–31, 130
U
unbiased probability, 30
uncertainty, 3, 218
clinical information, 18–19
defined, 19–20
utility, 4, 135 see also expected utility analysis;
exponential utility model; parametric
utility model
assessment
direct approach, 209–11
lifetime‐tradeoff assessment, 152–3, 157,
170, 189
outcome separation approach, 211
survival‐tradeoff assessment, 154–6, 170
scaling, 163
utility curve shape, 156, 157
V
verified sample, 63, 69, 70
von Neumann, John, 138
von Neumann Morgenstern utility, 135, 138, 156
W
Wells Criteria score, 294–6
threshold probabilities (cont’d)
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