ライフサイエンスコーパス: predictive value

1 benefit rather than sensitivity or positive predictive value.

2 d demonstrated high specificity and positive predictive value.

3 n or if presence of stenosis has independent predictive value.

4 dentified with high specificity and positive-predictive value.

5 had high probability of having high positive predictive value.

6 ysis, sensitivity, specificity, and positive predictive value.

7 ng the Immunoscore, and their prognostic and predictive value.

8 Both exhibit poor positive predictive value.

9 ciated with low specificity and low positive predictive value.

10 atter has been demonstrated to have a higher predictive value.

11 s persistently high sensitivity and negative predictive values.

12 th better sensitivity, and negative/positive predictive values.

13 rve (average precision [AP; average positive predictive value]).

14 1, 0.67), specificity (0.78, 0.88), positive predictive value (0.74, 0.75), and negative predictive v

15 predictive value (0.74, 0.75), and negative predictive value (0.76, 0.82).

16 l): 1.573 (0.973-2.541), P = 0.032; positive predictive value = 0.257, negative predictive value = 0.

17 itivity = 0.67, specificity = 0.80, positive predictive value = 0.73 and negative predictive value =

18 ositive predictive value = 0.73 and negative predictive value = 0.74, and disease activity by NAS wit

19 astasis with sensitivity = 0.94 and negative predictive value = 0.89.

20 positive predictive value = 0.257, negative predictive value = 0.929].

21 s 92.4%), and both scores have poor positive predictive value (10.9%).

22 edictive value (one of 11), and 97% negative predictive value (132 of 136) for TOC.

23 ensitivity 100%, specificity 93.3%, positive predictive value 88.0%), and starting phototherapy after

24 .7%) and had a significantly higher positive predictive value (90.0%, PPV) than QFT (96.5% specificit

25 The negative predictive value 94.5%, and the accuracy was 71.0% for e

26 , 97% [95% CI: 90%, 99%], 68 of 70; negative predictive value, 94% [95% CI: 79%, 98%], 30 of 32).

27 itive predictive value (98.6%), and negative predictive value (95.6%) as compared with >=20 and >=60

28 , 94% [95% CI: 79%, 99%], 30 of 32; positive predictive value, 97% [95% CI: 90%, 99%], 68 of 70; nega

29 YEARS provides better negative predictive value (98% vs 92.4%), and both scores have po

30 ivity (99.3%), specificity (91.0%), positive predictive value (98.6%), and negative predictive value

31 cute on chronic" renal dysfunction (negative predictive value, 98.0%; sensitivity, 92.9%; specificity

32 patients with acute kidney injury (negative predictive value, 98.8%; sensitivity, 95.8%; specificity

33 ce interval [CI]: 81.5%, 93.6%) and negative predictive value (99.1% [1528 of 1542]; 95% CI: 98.5%, 9

34 Tumour mutational burden might have some predictive value, although blood-based measures of tumou

35 ECG, CineECG at baseline had a 100% positive predictive value and 81% negative predictive value in pr

36 31/200) and 96.6% (170/176), with a positive predictive value and negative predictive value of 83.8%

37 The negative predictive value and positive predictive value of DUS we

38 icted more lymph nodes and improved positive predictive value and specificity when added to multipara

39 to detect cell-type markers, impacting their predictive value and suitability for integration into re

40 sitivity, specificity, positive and negative predictive values and accuracy and discriminant property

41 nd 0.37 and 0.94, respectively, and positive predictive values and negative predictive values ranged

42 Predictive values and optimal thresholds were calculated

43 ody tests (quality, accuracy level, positive predictive value) and what those tests might indicate im

44 e in patients with a sensitivity, a negative predictive value, and a specificity of 71.4%, 87.5%, and

45 ificity, positive predictive value, negative predictive value, and accuracy and to evaluate the estim

46 ificity, positive predictive value, negative predictive value, and accuracy for diagnosis of COVID-19

47 sitivity, specificity, positive and negative predictive value, and accuracy for LNM detection on (68)

48 ificity, positive predictive value, negative predictive value, and accuracy were calculated based on

49 itivity, positive predictive value, negative predictive value, and accuracy were determined for all m

50 ificity, positive predictive value, negative predictive value, and accuracy) were calculated based on

51 itivity, positive predictive value, negative predictive value, and accuracy, were higher in off MAR c

52 ificity, negative predictive value, positive predictive value, and accuracy.

53 tudy were sensitivity, specificity, positive predictive value, and negative predictive value based on

54 lated the sensitivity, specificity, positive predictive value, and negative predictive value for the

55 ssess its sensitivity, specificity, positive predictive value, and negative predictive value in ident

56 Sensitivity, specificity, positive predictive value, and negative predictive value of (18)F

57 a, showed sensitivity, specificity, positive predictive value, and negative predictive value of 86% (

58 Sensitivity, specificity, positive predictive value, and negative predictive value were rep

59 Sensitivity, specificity, positive predictive value, and negative predictive values were 73

60 sitivity, specificity, negative and positive predictive values, and negative and positive likelihood

61 rtex multimodal classifier had a significant predictive value (area under the curve, 0.96; 95% CI, 0.

62 dinal changes of retinal thickness and their predictive value as biomarkers of disease progression in

63 ity, positive predictive value, and negative predictive value based on infants testing positive in bo

64 Quantitative CT measures added incremental predictive value beyond a model with only clinical param

65 was to evaluate if obstructive CAD provides predictive value beyond its association with total calci

66 FDG PET/CT had good specificity and positive predictive value but low to moderate sensitivity and neg

67 o show that immune profiling has substantial predictive value, but few studies focus on childhood tum

68 for associations between microbes had higher predictive value compared to models including moose sex,

69 igands with 1.5-fold improvement in positive predictive value compared with existing tools and correc

70 long corresponding percentiles, the positive predictive value curves for qPET and DeltaSUV(max) were

71 The negative predictive value curves were also superimposable but rem

72 y are limited to few parameters with minimal predictive value, despite some contributions to disease

73 AOX1 associated metabolites have a high predictive value for advanced BLCA and our findings demo

74 range, 25-94 years), resulting in a positive predictive value for biopsy of 43% (181 true-positive fi

75 the first months post-onset, with a positive predictive value for clinically relapsing disease of onl

76 levels of Deltatau314 proteins show a modest predictive value for dementia.

77 are CysC-eGFR and sCr-eGFR, (2) assess their predictive value for early postoperative outcomes, and (

78 eristic curve 0.83 [0.73-0.93]) had the best predictive value for ICU mortality with cutoff values le

79 SPOT.TB, and TST modestly increases positive predictive value for incident TB, but markedly reduces s

80 ce per se, being heritable and having unique predictive value for long-term memory function, hippocam

81 ed in homologous recombination may also have predictive value for PARP inhibitors.

82 01), resulting in a decrease in the positive predictive value for recall for suspicious microcalcific

83 less rapidly, resulting in a lower positive predictive value for recall.

84 To assess its predictive value for response evaluation during programm

85 rtheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as

86 The positive predictive value for SIRE was 25% and the negative predi

87 ed a unique low-dose BPA-gene signature with predictive value for survival outcomes in patients with

88 but low to moderate sensitivity and negative predictive value for the detection of PTLD in a 28-pedia

89 ity, positive predictive value, and negative predictive value for the proposed optimal cutoffs.

90 High sensitivity and negative predictive value for the RAPID Index was associated with

91 evelopment of diagnostic tools with improved predictive value for tuberculosis (TB) is a global resea

92 At an RAI cutoff of >=37, the positive predictive values for 30- and 90-day readmission were 14

93 with 100% negative (NPV) and positive (PPV) predictive values for a positive gold standard functiona

94 ) assays have been recently shown to provide predictive values for both cardiac and peripheral microa

95 n EPIONCHO-IBM but not ONCHOSIM) on positive predictive values for different serological thresholds.

96 AMD eyes with large drusen to determine the predictive values for NE-MNV.

97 Positive predictive and negative predictive values for SS-OCT were 75% (95% CI 59.81-85.8

98 .92, specificity from 0.83 to 0.97, positive predictive value from 0.70 to 0.93, and negative predict

99 ictive value from 0.70 to 0.93, and negative predictive value from 0.94 to 0.96.

100 st characteristics remained stable: negative predictive value (> 99%), sensitivity (91.2% vs 93.4%),

101 However, low sensitivity and low positive predictive value have led critics to argue that these to

102 The clot contraction assay has a predictive value in assessing the threat of postoperativ

103 lse positive rate and improving the positive predictive value in breast imaging interpretation.

104 vity, specificity, and positive and negative predictive value in comparison with CECT findings.

105 fter NAC prior to surgery has prognostic and predictive value in early TNBC patients.

106 ity, positive predictive value, and negative predictive value in identifying PLWDH.

107 isk of active tuberculosis and evaluated its predictive value in independent cohorts.

108 res of tumour mutational burden did not have predictive value in patients receiving atezolizumab plus

109 % positive predictive value and 81% negative predictive value in predicting ajmaline test results.

110 he harmonic mean of sensitivity and positive predictive value) in the training set was applied to the

111 sensitivity, specificity, positive/negative predictive values, likelihood ratios, and accuracy.

112 Projected predictive values mainly reflect the low frequency of tr

113 tool; however, the sensitivity and positive predictive value may be lower than previously reported w

114 excellent sensitivity, specificity, positive predictive value, negative predictive value, and accurac

115 z value), specificity, sensitivity, positive predictive value, negative predictive value, and accurac

116 metrics (sensitivity, specificity, positive predictive value, negative predictive value, and accurac

117 Sensitivity, specificity, positive predictive value, negative predictive value, and accurac

118 ifier for sensitivity, specificity, positive predictive value, negative predictive value, and accurac

119 The values of sensitivity, positive predictive value, negative predictive value, and accurac

120 ures were sensitivity, specificity, positive predictive value, negative predictive value, positive an

121 92.2% to 97.9%), respectively, with negative predictive value (NPV) (100%), positive predictive value

122 formance criteria were at least 90% negative predictive value (NPV) and at least 90% sensitivity for

123 rimary endpoint was to estimate the negative predictive value (NPV) and positive predictive value (PP

124 Visually, the best negative predictive value (NPV) and positive predictive value (PP

125 109/L at presentation, which had a negative predictive value (NPV) for likely bacterial pneumonia of

126 s shown a sensitivity of 100% and a negative predictive value (NPV) of 100% in our study.

127 e predictive value (PPV) of 57% and negative predictive value (NPV) of 86%.

128 e predictive value (PPV) of 86% and negative predictive value (NPV) of 99% was achieved for the diagn

129 les after 12 hours incubation has a negative predictive value (NPV) of 99.5%.

130 ositive predictive value (PPV), and negative predictive value (NPV) of CryptoPS were assessed against

131 ositive predictive value (PPV), and negative predictive value (NPV) of STs for metronidazole/ornidazo

132 ositive predictive value (PPV), and negative predictive value (NPV) were calculated for each examiner

133 ositive predictive value (PPV), and negative predictive value (NPV) were calculated for MRI using CT

134 y, positive predictive value (PPV), negative predictive value (NPV), accuracy) were compared.

135 y, positive predictive value (PPV), negative predictive value (NPV), and positive and negative likeli

136 Positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity, and ka

137 entire population, expressed as the negative predictive value (NPV), using ICA as the reference stand

138 ially, with a minimal effect on the negative predictive value (NPV).

139 ositive predictive value (PPV), and negative predictive value (NPV).

140 sitive predictive value (PPV): 50%; Negative predictive value (NPV): 95.5%).

141 pecificity of 93%, and negative and positive predictive values (NPV and PPV) of 82% and 93%, respecti

142 edictive value (PPV) with estimated negative predictive values (NPV) of 81%-99%.

143 ity, positive predictive value, and negative predictive value of (18)F-FDG PET/CT for the detection o

144 ysis with log-rank was used to determine the predictive value of (64)Cu-DOTATATE SUV(max) for OS and

145 hology in extramotor brain regions (positive predictive value of 100%).

146 ity of 100% (95% CI 72%-100%) and a negative predictive value of 100%, as compared to a sensitivity o

147 tive predictive value of 87.5%, and negative predictive value of 100%.

148 score of <=2 had a sensitivity and negative predictive value of 100%.

149 of 5.9% (95% CI, 2.6%-12.2%), and a negative predictive value of 100.0% (95% CI, 100.0%-100.0%).

150 tivity of 24% (95% CI 8%-50%) and a negative predictive value of 19% (95% CI 5%-46%) for the index te

151 ity of 90%, a specificity of 71%, a positive predictive value of 32%, and a negative predictive value

152 e machine learning model has a mean positive predictive value of 34.6% [SD: 0.15] for flagging the to

153 y of 99.9% (95% CI, 99.9%-99.9%), a positive predictive value of 5.9% (95% CI, 2.6%-12.2%), and a neg

154 l provides a specificity of 78% and negative predictive value of 73%.

155 of 93.3%, a specificity of 76.5%, a positive predictive value of 77.8%, and a negative predictive val

156 99.0 and 23.2% with a positive and negative predictive value of 8.0 and 99.7%.

157 sitive predictive value of 86%, and negative predictive value of 83%.

158 ith a positive predictive value and negative predictive value of 83.8% (31/37) and 50.1% (170/339), r

159 ity, positive predictive value, and negative predictive value of 86% (119 of 139), 96% (55 of 57), 98

160 itivity of 82%, specificity of 93%, positive predictive value of 86%, and negative predictive value o

161 ity of 100%, specificity of 92.31%, positive predictive value of 87.5%, and negative predictive value

162 of 94.5%, a specificity of 94.4%, a positive predictive value of 88.0%, and a negative predictive val

163 nsity thresholds, a specificity and negative predictive value of 89% and 95% were achieved, respectiv

164 EVM and CMR together conferred a positive predictive value of 89% on EMB.

165 e" (n = 123) pattern demonstrated a positive predictive value of 89.6% and 86.2% for non-COVID-19, re

166 f 55% for severe impairment, with a negative predictive value of 91%.

167 ve predictive value of 77.8%, and a negative predictive value of 92.9%.

168 allowing to predict treatment outcome with a predictive value of 93.8% when combined with clinical fe

169 ve predictive value of 88.0%, and a negative predictive value of 97.6%.

170 tive predictive value of 32%, and a negative predictive value of 98%.

171 dence interval [CI], 15.7-84.3) and negative predictive value of 99.3% (95% CI, 97.5-99.9).

172 h a secondary finding and the lower positive predictive value of a screening result compared to an in

173 eport the patient-level CDR and the positive predictive value of AB-MR examinations after negative/be

174 olling for age and biomarker elevations; the predictive value of adverse RV remodeling was similar ir

175 The predictive value of age, race, marital status, and tumor

176 than TST (54.2%) and TSPOT (51.9%); negative predictive value of all tests was high (TST 97.7%, QFT 9

177 Negative predictive value, positive predictive value of an abnormal examination, and positiv

178 g complete PVD was 53%, whereas the negative predictive value of an OCT scan showing attached vitreou

179 In the study population, the positive predictive value of an OCT scan showing complete PVD was

180 The positive predictive value of AO for AO(post-BD) was 59.1% (52.0-6

181 genetic information added little to the high predictive value of baseline severity of AMD for disease

182 Cancer yield and positive predictive value of biopsies performed (PPV3) were deter

183 value of recall (PPV1) percentage, positive predictive value of biopsies performed percentage, sensi

184 lue of an abnormal examination, and positive predictive value of biopsy were 114 of 114 (100%; 95% CI

185 The predictive value of CAC categories for CHD and stroke se

186 The predictive value of changes of (18)F-FET PET and MRI par

187 istic regression was performed to assess the predictive value of clinical and CT parameters for the p

188 increased to 97.4% in 2015, and the positive predictive value of CT and combined CT and ultrasonograp

189 Furthermore, the predictive value of CT FFR for coronary revascularizatio

190 The predictive value of CTOI was assessed through logistic r

191 In the same cohort, sensitivity and negative predictive value of depth of invasion, currently the bes

192 The negative predictive value and positive predictive value of DUS were 92% (95% CI, 90-95) and 39%

193 dge Base (LTKB) have been used to derive the predictive value of each end point, along with combinati

194 erventions on cancer outcomes as well as the predictive value of geriatric assessment in the context

195 his study was to evaluate the prognostic and predictive value of HLA-G and HLA-F protein isoform expr

196 re are subtle sex-related differences in the predictive value of individual biomarkers, but the overa

197 ncident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with

198 s, response to subsequent therapies, and the predictive value of molecular and genetic characteristic

199 etrospectively addressed the question of the predictive value of molecular events on the benefit of t

200 This allowed us to explore the predictive value of neuroimaging biomarkers and determin

201 The positive predictive value of new or progressive multiple organ dy

202 the ME panel test utilization rate, negative predictive value of nonpleocytic CSF samples, test yield

203 The predictive value of NT1 versus tau measured using assays

204 Modeling the predictive value of pattern of injury and other relevant

205 -based testing as the standard, the negative predictive value of PCR was found to be 100%, while the

206 otype of FGR in women with AMSB and test the predictive value of placental sonographic screening to p

207 limiting membrane at 3 months is a positive predictive value of postoperative BCVA 6 months after in

208 Positive predictive value of Pretest Probability Score in identif

209 The aim of this study was to evaluate the predictive value of PSMA PET for a 3-y freedom from prog

210 ative rate per 1000 women screened, positive predictive value of recall (PPV1) percentage, positive p

211 ngs, biopsy, cancer detection rate, positive predictive value of recalls and biopsies, and histopatho

212 ections identified, and improve the positive predictive value of results.

213 incidence, and treatments, plus the positive predictive value of screening mammography by age group.

214 origin of the aneuploidy and the diagnostic predictive value of segmental aneuploidy detection in TE

215 We investigated the predictive value of sporadic cases on outbreaks using a

216 y of MPS cellular phenotypes and the limited predictive value of surface markers to define lineages,

217 The negative predictive value of the first-day result among repeat-te

218 ps when receiving standard chemotherapy, the predictive value of the genetic background and co-occurr

219 The negative predictive value of the negligible risk category was 98.

220 The positive predictive value of the Pretest Probability Score in ide

221 It is critical to understand how the predictive value of the test varies with time from expos

222 This study is the first to report the predictive value of the WHO-defined diagnostic classific

223 and demonstrate the scientific validity and predictive value of this approach using an assortment of

224 To evaluate the predictive value of this imaging modality, treatment res

225 ed probability of hearing loss, the positive predictive value of this model was 83% and negative pred

226 We explored the clinical significance and predictive value of trans-ethnic variants in multiple po

227 The positive predictive value of ultrasonography increased to 97.4% i

228 f -1.455 (NFS) and 1.3 (FIB-4) have negative predictive values of 0.80 and 0.82, respectively.

229 vity, specificity, and positive and negative predictive values of 18F-FDG-PET/CT focal uptake were 93

230 The negative predictive values of a normal CSF white blood cell (WBC)

231 The present study examined the predictive values of amyloid PET, (18)F-FDG PET, and non

232 is low, a large gap exists between positive predictive values of chest CT versus those of reverse tr

233 ther epilepsy centers was used to assess the predictive values of each model and regional anatomical

234 how activating ESR1 mutations may alter the predictive values of molecular imaging agents for endocr

235 vity, specificity, and positive and negative predictive values of the panel compared to myco/f lytic

236 cond ECG yielded a sensitivity (and negative predictive value) of 1.5% (66%) for AF detection, increa

237 ), 93% specificity (132 of 142), 9% positive predictive value (one of 11), and 97% negative predictiv

238 relative performance (sensitivity, positive predictive value or PPV, and computational efficiency) o

239 P = .52 and P = .98, respectively), positive predictive value (P = .78), or sensitivity (P = .33) for

240 ificity, positive predictive value, negative predictive value, positive and negative likelihood ratio

241 Negative predictive value, positive predictive value of an abnorm

242 included sensitivity, specificity, negative predictive value, positive predictive value, and accurac

243 tive predictive value (NPV) (100%), positive predictive value (PPV) (63.5%), and area under the curve

244 sis-based detection sensitivity and positive predictive value (PPV) at a 50% confidence threshold.

245 ith the individual assays), and the positive predictive value (PPV) improved substantially, with a mi

246 negative predictive value (NPV) and positive predictive value (PPV) occurred when iPET was defined as

247 e the sensitivity, specificity, and positive predictive value (PPV) of (18)F-DCFPyL PET/CT based on h

248 BATF2, GBP5, and SCARF1 achieved a positive predictive value (PPV) of 23% for progression to active

249 itivity of 86%, specificity of 58%, positive predictive value (PPV) of 57% and negative predictive va

250 tified patients at high risk with a positive predictive value (PPV) of 76.8% (95% CI: 68.9% to 83.6%)

251 An accuracy of 98%, positive predictive value (PPV) of 86% and negative predictive va

252 al imaging recommendation rate, and positive predictive value (PPV) of biopsy, using invasive cancer

253 negative predictive value (NPV) and positive predictive value (PPV) of ctHPVDNA surveillance.

254 predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predict

255 We estimated the positive predictive value (PPV) that a new diagnosis of CSC would

256 asion, although the specificity and positive predictive value (PPV) were 100%.

257 ection rate (CDR), recall rate, and positive predictive value (PPV) were calculated for each reader,

258 y (95% CI, 82%-100%) and up to 100% positive predictive value (PPV) with estimated negative predictiv

259 to assess the detection rate (DR), positive predictive value (PPV), and correct detection rate (CDR)

260 Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (N

261 The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (N

262 imated as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (N

263 Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (N

264 Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (N

265 lated the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV),

266 metrics (sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV),

267 Positive predictive value (PPV), negative predictive value (NPV),

268 itivity: 88.9%; specificity: 72.4%; Positive predictive value (PPV): 50%; Negative predictive value (

269 Positive predictive values (PPVs) for any neoplasm 6 mm or greate

270 and positive predictive values and negative predictive values ranged between 0.59 and 0.92 and 0.57

271 2.6 and 1.5, with high-positive and negative predictive values, respectively.

272 erval [CI]: 86.8% to 94.1%) and the positive predictive value, sensitivity, and specificity were 87.9

273 gative rate, cancer detection rate, positive predictive value, sensitivity, and specificity were calc

274 d sensitivity, but has insufficient negative predictive value to exclude TBM.

275 likelihood ratios, and positive and negative predictive values to determine the diagnostic performanc

276 As a consequence, the positive-predictive value toward ICM configuration was significan

277 cancer detection and recall rates, positive predictive values, tumor size, histologic features, and

278 ndard was 85.4% (35 of 41), and the positive predictive value was 100% (35 of 35).

279 ive predictive value was 21.8%, and negative predictive value was 100%.

280 tive value for SIRE was 25% and the negative predictive value was 100%.

281 The positive predictive value was 20.6%.

282 ty was 100%, specificity was 51.1%, positive predictive value was 21.8%, and negative predictive valu

283 ive value of this model was 83% and negative predictive value was 40%.

284 PCR was found to be 100%, while the positive predictive value was 79%.

285 The positive predictive value was 86.3% (95% CI, 80.4 to 90.6), negat

286 On a per-patient basis, positive predictive value was 93.3% (95% confidence interval, 77.

287 Negative predictive value was 98%.

288 e was 86.3% (95% CI, 80.4 to 90.6), negative predictive value was 99.3% (95% CI, 98.0 to 99.8) with a

289 sensitivity was high (67%), but the positive predictive value was low, as only 8% of TWAS association

290 ity, positive predictive value, and negative predictive value were reported for each radiotracer.

291 Sensitivity and positive predictive values were <90% for all biomarkers.

292 The positive and negative predictive values were 40.7% and 98.5%, respectively.

293 ity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, r

294 ecificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% wi

295 14.8% and 26.2%, respectively, and negative predictive values were 91.6% and 86.4%, respectively.

296 Positive and negative predictive values were calculated for progression-free s

297 SN), specificity (SP), positive and negative predictive values were performed for all questions alone

298 Sensitivity, specificity, and predictive values were reported at different risk thresh

299 53 serious adverse events with high positive predictive values where well-characterized target-event

300 -up, there was a modest increase in positive predictive value with the higher thresholds (3.0% for QF