Добавил:

Sekretar kiopkiopkiop18@yandex.ru t.me/Prokururor I Вовсе не секретарь, но почту проверяю Опубликованный материал нарушает ваши авторские права? Сообщите нам.

Вуз:

Ростовский Государственный Медицинский Университет

Предмет:

Медицина общая

Файл:

Книга_2767_Библиотеки_им_академика_М_И_Перельмана

.pdf

Скачиваний:

Добавлен:

31.08.2026

Размер:

25 Мб

Скачать

☆

<<< < Предыдущая 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 4142 / 4242

Index

https://t.me/medicina_free

bivariate model (cont’d)

presenting findings 333, 334 sensitivity analysis sparse data and atypical data sets summary statistics

239–241, 266, 320–321

297–303

264–265, 289–291,

317–320,320

undertaking meta-analysis

blinding

176, 184

Boolean operators

112–113 Box-Cox transformations broad questions

87–88

250

222

case-control studies

risk of bias and applicability assessment

177–178

study design

categorical data

Chi

statistic 223, 232

39, 39, 42

151

China National Knowledge Infrastructure

103

(CNKI)

CINAHL

103–104, 115 clinical decisions 25 clinical pathway

defining the clinical pathway unclear and multiple clinical pathways

80–83, 81–82

83–84 clinical reference standard 45 clinical study reports (CSR) 133 Clopper–Pearson method 61 CNKI see China National Knowledge

Infrastructure

CoCites

106

comparative studies

drawing conclusions evaluating medical tests

359–362, 368

28 measures of test accuracy 54, 68–71, 69 meta-analysis 206, 211, 216, 230–238,

272–301 presenting findings 330, 333–336, 334–335 risk of bias and applicability assessment 178–

181, 180–181, 188, 189 study design

45–47, 46–47 composite reference standard 44, 302 concealment of allocation 179 conclusions see drawing conclusions conference abstracts 132 confidence intervals

data collection 143–144 drawing conclusions 355–356, 360, 361,

364,365

measures of test accuracy 60–61, 68

meta-analysis 208, 210, 211, 216, 218, 226,

237, 238, 287, 305, 311 plain language summary presenting findings

392

334, 336, 337, 344–345,

346

risk of bias and applicability

conflicts of interest

171

confounders

drawing conclusions meta-analysis presenting findings

consecutive enrolment

362, 368

231

340

176–177

consensus

data collection

159

drawing conclusions 367

consumer involvement

continuous data

data collection

151 measures of test accuracy 54 review questions

91 controlled vocabulary 110–112 counts 54 coupled forest plots 208, 209, 267 covariates

data collection

151

meta-analysis 215, 222–229

cross-classification

measures of test accuracy

54, 56, 57

planning a systematic review of test

accuracy

study design 37 cross-referencing 133–134 cross-sectional studies

review questions

study design 37, 38–39 CSR see clinical study reports c-statistic see area under the curve

data collection 131–167

2x2 contingency tables 134–135, 141–144,

142, 143, 145–146, 149–150, 161 checklist of data items 136, 136–137 concepts and definitions 132 correspondence with investigators 134–135 demographics 138 extracting and converting study

results 141–151 extracting covariates 151 extracting data from reports 157–160 flow and timing 140–141

400

Index

https://t.me/medicina_free

global measures 144 index test individual patient data managing and sharing data and tools

missing data and partial verification bias

multiple index tests from same study

multiple reports and complex reviews

multiple thresholds and extracting data from

other information to collect 151–152 participant characteristics and

sources of data studies versus reports as unit of

study methods 137–138 subgroups of patients target condition and reference

test failures 147 tools for data collection 152–157, 153–154

what data to collect data mining 120 decision analysis 24 deep learning 121 delayed verification deviance information criterion (DIC) 223 diagnostic odds ratios (DOR)

data collection

drawing conclusions

measures of test accuracy 63, 64

meta-analysis 219, 223, 228, 269

presenting findings 330–332, 331

relative diagnostic odds ratio 228

risk of bias and applicability assessment 192 Diagnostic Test Accuracy Editorial Team 5 DIC see deviance information criterion Discussion section 350, 365–366 dissertations databases 104 DOR see diagnostic odds ratios dot plots 147–148, 148 drawing conclusions 349–376

applicability of findings to review

assessing the strength of the evidence

Authors’ conclusions 350, 369–374

139–140, 146, 148, 149–150

133, 150

160–163, 161–163

140, 148

148–150, 149–150

158–159, 160–163, 161–163

ROC curves or graphics

138–139

setting

132–135

133–134

interest

standard

question 369

352–362

140,145

144

147–148, 148

150

135–137

360

Discussion section GRADE approach heterogeneity implications for practice implications for research incomplete body of evidence precision of summary estimates risk of bias and applicability assessment

359, 363–364, 367

strengths and weaknesses of included

studies strengths and weaknesses of review Summary of findings tables

353–358

ecological bias eligibility/inclusion criteria

data collection drawing conclusions 369 literature searches 120–121 meta-analysis plain language summary 384 presenting findings 328 review questions 77, 76, 88–93 risk of bias and applicability assessment

193, 195 study design

Embase 102–103, 105, 110–111, 115 errata

data collection literature searches 114

explanatory studies 48–49

false negatives/false positives

data collection 141–148 drawing conclusions 351 evaluating medical tests 23, 25 measures of test accuracy 57, 68, 70 meta-analysis 219, 297, 312, 315 plain language summary 381 presenting findings 330–332, 341 risk of bias and applicability assessment

187, 192 study design

field tags 111 fixed-effect meta-analysis 214, 302–303 flow and timing

data collection presenting findings 340 risk of bias and applicability assessment

191–195, 194–195

350, 365–366

362–365

359–360, 364

370–373

373–374

361–362

360–361

351,

366–367

367–368

350–352,

340

133–134, 138

205, 239

178,

36, 39–40

132

140–141

401

Index

https://t.me/medicina_free

flow diagrams 174–175, 175 forest plots

coupled forest plots data collection heterogeneity meta-analysis

208, 209, 267

151 338 208, 209, 210, 267, 297–298,

302,338

reviews without meta-analysis fraudulent studies full-text reports fully paired design funding

114, 159–160

120–121

179

345

funnel plots 242

Gelman-Rubin statistic global measures

264

144 gold standard 45, 187 Google Scholar 106–107 GRADE approach 352, 362–365 graphics/figures

data collection

147–148, 148

plain language summary 388–390, 389,

390,396

risk of bias and applicability assessment

196, 196

see also presenting findings

grey literature

100, 107

guidelines 105

heterogeneity

drawing conclusions 359–360, 364 meta-analysis

205, 214–215, 222–230, 225,

226–227, 229, 230, 299–302

plain language summary

391 presenting findings 333, 336–340, 338, 339, 344 review questions 77

hierarchical summary receiver operating

characteristic (HSROC) model 215–216, 219–220, 220, 221

analysis with small numbers of

studies 238–239

Bayesian estimation of the model 268–272,

270, 272, 294–296, 295, 311–315, 315 comparing index tests 234–235, 235 comparison of summary curves 291–296 estimation of a summary curve 266–272 fitting model using R 306–311, 310–311 fitting model using SAS 267, 268, 292 imperfect reference standard 317–320 investigating heterogeneity 222–230,

228–230, 227, 229, 230

monitoring convergence multiple thresholds per study

270–271

221–222,

305–315, 310–311, 315 sensitivity analysis sparse data and atypical data sets specification of HSROC in rjags summary statistics undertaking meta-analysis

239–241, 272

299, 302

268–272

271, 295, 317–320, 320

249–250

HSROC see hierarchical summary receiver

operating characteristic model

statistic 214 incomplete reporting 108 inconclusive results 145–147 inconsistency see heterogeneity indexing systems

99–100, 102, 108, 110–111

index test

data collection drawing conclusions

139–140, 146, 148, 149–150

351–352, 362, 372–373 inconclusive index test results 55–56 literature searches 100–101 measures of test accuracy 53–56, 57 meta-analysis 230–238, 233, 233, 234,

237,238

plain language summary

380–383, 386–387,

391–392 presenting findings review questions

330, 345

77, 82, 85, 90–91

risk of bias and applicability assessment

182–186, 185–186, 191 study design

individual participation data (IPD)

37–38, 48

133, 150 information specialists 100–101, 108 intermediate results 55 interpretation bias 184, 188 IPD see individual participation data

joint classification

68, 69

Jones multiple thresholds model 222, 305–315,

310–311

journal articles 132

keyword searching 112–113, 119

language bias 113, 361 latent class analysis (LCA)

meta-analysis 241, 316–321, 318, 320 study design 45

Latin American Caribbean Health Sciences

Literature (LILACS) database 103, 115

LCA see latent class analysis

402

Index

https://t.me/medicina_free

letters 132 likelihood ratios

data collection drawing conclusions measures of test accuracy meta-analysis presenting findings

LILACS see Latin American Caribbean Health

Sciences Literature linear mixed-effects modelling linked summary receiver operating characteristic

plots linking reports 134 literature searches 97–129

co-citation searching 105–106, 115 controlled vocabulary and text

words

designing search strategies 108–115 documenting and reporting the search

process

drawing conclusions forward citation searching 105–106 fraudulent studies, retracted publications,

errata and comments

future developments 121 handsearching information specialists 100–101, 108 keyword searching 112–113, 119 language, date and type of document

restrictions

minimizing risk-of-bias through search

methods

performance measures for search

strategies

review author roles 100–101 search filters 113 searching for studies 98–101 selecting relevant studies 119–121 sources to search 101–108 structuring the search strategy 109–110,

110,111

text word or keyword searching 112–113 working in partnership 100

logistic regression models 71

machine learning 120, 157 management studies 43 Markov chain Monte Carlo (MCMC)

simulation 223, 250, 263, 263, 270, 270,

295, 315, 317, 318 measures of test accuracy 53–72

143

352

61–63

216, 223, 229, 282

332, 332, 344

222

210

110–112

115–119, 118

367

114

105, 115

113

114–115

analysis of primary test accuracy study comparative studies concepts and definitions confidence intervals inconclusive index test results interpretation other measures positivity thresholds predictive values pre-test and post-test probabilities proportion with the target condition receiver operating characteristic curves

66–68, 67 sensitivity and specificity target condition 56 types of test data 54–55

medical test evaluation 21–33

biomarker discovery/development clinical evaluations of test accuracy 28 early evaluations of test accuracy 27 how diagnostic tests affect patient

outcomes purposes of medical testing 28–31, 28 test accuracy 23–24 test development 26–28 types of medical tests

MEDLINE 102–103, 105, 108, 112, 114, 121 meta-analysis 203–247, 249–325

aims for reviews of test accuracy 204 analysis with small numbers of

studies Bayesian statistics 61, 221, 241, 250, 261–266,

270, 268–272, 270, 272, 287–291, 290–291,

294–296, 295, 311–320, 315, 318, 343 comparing index tests

237, 238 comparison of summary curves comparison of summary points 272–291 data collection 150 drawing conclusions 352, 366, 368, 369 estimation of a summary curve 266–272 estimation of a summary point 251–266 facilitating convergence 297–301, 298 fitting hierarchical models 215–241 fixed-effect meta-analysis 214, 302–303 graphical and tabular presentation 208–211,

209–210

heterogeneity

226–227, 229, 230 imperfect reference standard 241, 316–321,

318,320

68–71, 69

53–54

60–61

55–56

59–60

61–64, 62, 64

64–65, 65

57–58, 64–65,67

24–26

22–23, 22

238–239

230–238, 233, 233,235,

205, 214–215, 222–230, 225,

56–64

58–59

26–27

291–296

403

Index

https://t.me/medicina_free

meta-analysis (cont’d)

literature searches 105 methodological developments monitoring convergence

270–271, 295, 317, 318

multiple thresholds per study

305–315, 310–311, 315 plain language summary planning a systematic review of test

accuracy planning the analysis presenting findings

340–346,342 publication bias regression analysis 223–224, 227–228 reviews of test accuracy versus reviews of

interventions sensitivity analysis

320–321 simplifying hierarchical models

303, 305 sparse data and atypical data sets

297–298, 302, 303, 305 special topics summary statistics 264–265, 271, 289–291,

295, 317–320, 320 verification bias when not to use in a review 204–205 see also bivariate model; hierarchical

summary receiver operating

characteristic model

meta-epidemiology 172 misclassification 187, 192 missing data

data collection drawing conclusions 361–362 risk of bias and applicability assessment 194

multiple-group studies 39–42, 40 multiple index tests

data collection 148–150, 149–150 risk of bias and applicability assessment 184

multiple thresholds model

data collection 147–148, 148 hierarchical summary receiver operating

characteristic model 221–222, 305–315,

310–311, 315 Jones method 222, 305–315, 310–311 Steinhauser method 222, 305–315, 310–311

narrative summary

drawing conclusions 366

207–208

329–336, 334–335,

242–243

205–206

239–241, 266, 272,

241–243

241–242

134–135, 140, 144, 148

241

263–264, 270,

221–222,

387

301–305, 302,

296–305,

presenting findings 346, 347 risk of bias and applicability assessment

writing a plain language summary narrow questions national databases network meta-analysis non-randomized comparative accuracy

studies

objectives odds ratios see diagnostic odds ratios online publications ordinal data 54 overall accuracy

paired comparative accuracy studies panel-based reference partial verification bias 148, 192 participant selection see recruitment patient outcomes

altering clinical decisions and actions

changes to time frames and

populations direct test effects 25 disease progression/recurrence 31 drawing conclusions evaluating medical tests 24–26 influencing patient and clinician

perceptions study design

peer review

data collection literature searches 107, 117

PICO format pilot testing 156–157 PIT format 84–86 plain language summary 377–397

aims of review 382, 395 audience and writing style 378–379 case example concepts and definitions 377–378 contents and structure 379–392 description of index test 382, 394 description of study benefits 381, 394–395 how up to date the evidence is 392, 397 included studies 383–384 key messages 380–381, 394 limitations of the evidence 391–392, 397 multiple index tests 386–387, 392 presenting findings 384–390, 389, 390,

395–397,396

87–88

103

236

86, 87

132

44–45, 46

25–26

372–373

132, 157

394–397, 396

377–397

46, 46

197

404

Index

https://t.me/medicina_free

review methods 382, 395–397 title

380

planning a systematic review of test

accuracy author team Cochrane protocols conduct and reporting expectations data management and quality assurance Diagnostic Test Accuracy Editorial Team funding and conflicts of interest keeping review up to date proposing a new review rationale 7 resources and support 13–15 software tools 15 specific features of Cochrane Reviews 5–6 title formats training 14–15

point estimates

drawing conclusions measures of test accuracy meta-analysis 211, 225, 265, 284 presenting findings 332, 333, 344, 346 review questions 77

point-of-care tests 79 populations

data collection evaluating medical tests 25–26 plain language summary 380 review questions study design 39–42, 40

positivity thresholds

data collection measures of test accuracy meta-analysis 212, 219, 222, 305–315, 310,

311,315 risk of bias and applicability assessment

post-test odds/probabilities 59, 345 pragmatic studies 48–49 precision

drawing conclusions 360–361, 365 literature searches 99, 108 meta-analysis 270 plain language summary 392 risk of bias and applicability assessment 171

predictive tests 31 predictive value

data collection 141–143, 142, 143 drawing conclusions 352, 366 measures of test accuracy 58 meta-analysis 217

3–18

11–13

7–11

5–6

6–7, 8

7, 8

359–360, 364

138

77, 80–81, 84–85, 89

147–148

64, 65

183

positive/negative predictive value

141–143, 142, 143

presenting findings predisposition tests preprints presenting findings

pre-test odds/probabilities prevalence prior distribution function 261, 269–270,

PRISMA-S/PRISMA-DTA 5, 116–119, 118 probability 59, 70–71, 345 prognostic tests 30 proof-of-concept studies

prospective studies 48 PsycINFO 103–104 publication bias

PubMed 102–103, 106, 111

132

comparisons of test accuracy

334–335

confidence intervals for differences in test

accuracy description of included studies individual and summary estimates of

testaccuracy investigations of sources of heterogeneity

336–340, 338, 339 meta-analysis

311, 310–311, 317–320, 320, 338 methodological quality of included

studies narrative summary 197 plain language summary 377–397 re-expressing summary estimates

numerically results of the search 328 Summary of findings tables 211, 345,

350–352, 353–358 summary points uncertainty and heterogeneity in summary

statistics when meta-analysis cannot be

performed see also forest plots; summary receiver

operating characteristic plots

341–344, 342

287, 294

evaluating medical tests study design 41

drawing conclusions 361–362, 365 funnel plots 242 literature searches 98, 107 meta-analysis 242

334, 341–344, 342

327–348

336–337

329–333, 331, 331–332

208–211, 209–210, 265,308–

329

340–344, 342

211–214, 333–334, 334

332

344–346

59, 345

58,

333–336,

328–329

405

Index

https://t.me/medicina_free

QUADAS-2/QUADAS-C see risk of bias and

applicability assessment

quality assurance

random-effects meta-analysis randomization

comparative accuracy studies enrolment review questions sampling

study design RDOR see relative diagnostic odds ratio receiver operating characteristic (ROC) plots

data collection

measures of test accuracy 54, 66–68, 67

risk of bias and applicability assessment