ライフサイエンスコーパス: nomogram

1 .72 for Duke Treadmill Score; 0.75 for Lauer nomogram).

2 ase) for inclusion in the logistic model and nomogram.

3 f overall survival was used to construct the nomogram.

4 ge, were selected for the distant metastases nomogram.

5 ltivariable model for the distant metastases nomogram.

6 nalyses assessed the clinical utility of the nomogram.

7 w and prospective validation of a predictive nomogram.

8 d logistic regression and was presented on a nomogram.

9 f MRI to predict upgrading in biopsy GS in a nomogram.

10 mor number, which were incorporated into the nomogram.

11 d onto 127 trials were analyzed to build the nomogram.

12 to select variables for construction of the nomogram.

13 gnostic factors, and performance of proposed nomogram.

14 ctors except dose were included in the final nomogram.

15 Sloan Kettering Cancer Center (MSKCC) online nomogram.

16 sification system, and the 5-gene score in a nomogram.

17 ctioning parathyroid glands based on the WIN nomogram.

18 to mastectomy and were incorporated into the nomogram.

19 ate analysis with a validated gastric cancer nomogram.

20 ated for the seven variables in the original nomogram.

21 to traditional measures, and a postoperative nomogram.

22 f PSA-defined recurrence, based on a popular nomogram.

23 tional institutions was used to validate the nomogram.

24 of the Malawi Adult Meningitis Score (MAMS) nomogram.

25 alized Metabolic Surgery (IMS) score using a nomogram.

26 dated Memorial Sloan Kettering Cancer Center nomogram.

27 ots were used to evaluate the performance of nomogram.

28 ciated carcinoma in the form of a predictive nomogram.

29 evaluate the clinical usefulness of the two nomograms.

30 d procedure for variables selection for both nomograms.

31 is multivariable model was used to develop a nomogram-a weighted tool to calculate 2- and 4-year prob

32 We depicted the results in a series of nomograms accounting for age, comorbidities, and cyst si

33 The nomogram accurately predicted mortality, including very

34 The nomogram accurately predicted readmission (C statistic =

35 The nomogram accurately predicts RFS after resection of loca

36 These nomograms accurately predict OS and DFS.

37 ction of biochemical failure with the Kattan nomogram after external-beam radiation therapy for prost

38 The nomogram also had a discriminative power (AUC, 0.90; sen

39 nts), to develop 2 prediction instruments, a nomogram and a transfusion score, which can be easily im

40 d to predict PFS, which was represented as a nomogram and an online calculator.

41 utperforms the two widely used tools, Kattan nomogram and CAPRA-S score in a head-to-head comparison

42 ots, survival distributions predicted by the nomogram and observed by the Kaplan-Meier method were si

43 The areas under the ROC curve for the Kattan nomogram and the model incorporating MR imaging findings

44 Models were converted to nomograms and a web-based tool to determine individual r

45 velopment of prognostic indicators including nomograms and can be analyzed by Bayesian Belief Network

46 er refractive outcomes, including the use of nomograms and mathematical models.

47 Many of the current nomograms and scoring algorithms have been externally va

48 .70 for Duke Treadmill Score; 0.74 for Lauer nomogram) and men (0.72 for Duke Treadmill Score; 0.75 f

49 tient selection, development of a predictive nomogram, and advances in mutational analysis represent

50 Memorial Sloan Kettering Cancer Center GIST nomogram, and American Joint Committee on Cancer gastric

51 be guided using novel Markov-based clinical nomograms, and depends on age, cyst size, comorbidities,

52 The nomogram appears useful for risk stratification in clini

53 t and validation of transcutaneous bilirubin nomograms are needed.

54 Our nomograms are reliable prognostic methods that can be us

55 Nomograms are widely used as prognostic devices in oncol

56 We propose the nomogram as a decision aid in all patients with T1 melan

57 Instead of constructing nomograms, authors should develop software, such as pred

58 A preoperative nomogram based on clinical variables available before su

59 Conclusion This simple nomogram based on the ALBI grade offers personalized lon

60 The two nomograms both performed well in terms of discrimination

61 A nomogram built from a parametric survival model from the

62 We assessed performance of the nomogram by calculating concordance statistics and asses

63 We developed a nomogram by incorporating the signature with the clinico

64 On the external cohort of 328 patients, the nomogram c-index was 0.84 (95% confidence interval 0.79-

65 ry angiography are associated with PH, and a nomogram can be created that may facilitate identificati

66 ts occurrence can be predicted if a clinical nomogram can be developed, thus allowing for selection o

67 This nomogram can be used to accurately predict a patient's r

68 The constructed nomogram can guide prognostication in clinical practice

69 These nomograms can be offered to clinicians to improve their

70 These nomograms can be used to better estimate individual and

71 Contemporary nomograms can estimate individual patient outcomes after

72 Nomograms can help estimate the likelihood of severe rea

73 ntenatal booking visit, deployed as a simple nomogram, can help to optimise care in women with epilep

74 ses revealed the superior net benefit of the nomogram compared with each individual variable included

75 The nomogram concordance indices were 0.68 (FFBF) and 0.74 (

76 A WIN nomogram, consisting of the combination of WIN and parat

77 However, the statistical foundations of nomogram construction, their precise interpretation, and

78 lncRNAs and the user-friendly nomogram could facilitate the early identification of PT

79 Risk stratification with this nomogram could improve delivery of appropriate periopera

80 If validated in prospective cohorts, these nomograms could be used to predict seizure outcomes in p

81 The nomogram created in this model allows for the evaluation

82 One model included only the Kattan nomogram data; the other also incorporated imaging findi

83 The resulting nomogram demonstrated good accuracy in predicting MFS, w

84 study aims to propose a treatment-integrated nomogram derived from BCLC for patients with hepatocellu

85 and S100A4 expression predicted survival and nomograms derived using postoperative clinicopathologica

86 cal approach to evaluating and comprehending nomogram-derived prognoses, with particular emphasis on

87 staging, allow for seamless incorporation of nomogram-derived prognosis to aid clinical decision maki

88 on of tyrosine kinase mutation status in the nomogram did not improve its discriminatory ability.

89 Risk stratification with a derived SPECT nomogram did not result in statistically significant net

90 riate analysis, applying factors used in the nomogram, DSS of Korean GC patients remained significant

91 c, and treatment variables were built into a nomogram estimating probability of IBTR at 5 and 10 year

92 ated at 2 institutions was used to develop a nomogram estimating the rate of freedom from recurrence

93 Various nomograms exist today for identifying individuals at hig

94 A variety of predictive nomograms exists to predict lymph node involvement.

95 The nomograms facilitate prediction of outcomes following dr

96 A nomogram for 6-month mortality was developed and validat

97 A nomogram for extremity STS that includes age, size, marg

98 research is required to develop a new valid nomogram for laser-assisted lens surgery.

99 A nomogram for mortality was created and tested on the rem

100 We developed the nomogram for overall survival using a Cox multivariable

101 urpose of this study was to build a specific nomogram for predicting postoperative overall survival (

102 igate new prognostic factors and construct a nomogram for predicting survival in individual patients.

103 On the basis of the multivariate analysis, a nomogram for predicting the 3- and 5-year risk of LR was

104 clinical parameters were used to construct a nomogram for predicting the risk of pN1.

105 The nomogram for prediction of 5- and 10-year IBTR probabili

106 The DCIS nomogram for prediction of 5- and 10-year IBTR probabili

107 f the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 pa

108 A nomogram for rituximab dose needed to obtain optimal AUC

109 ims to develop a mammography-based radiomics nomogram for the preoperative prediction of ALN metastas

110 Prognostic factors were used to develop nomograms for 2-year PFS, 5-year OS, and pelvic recurren

111 Nomograms for 2-year PFS, five-year OS, and pelvic recur

112 Separate nomograms for DALK and PKP patients may be warranted.

113 nd long-term seizure outcomes and to produce nomograms for estimation of individualised outcomes.

114 Methods To develop and validate nomograms for OS and PFS, we used a derivation cohort of

115 velop and externally validate two prediction nomograms for overall survival and distant metastases in

116 Age-based correction nomograms for presbyopia should therefore consider these

117 A calculator (nomogram) for 90-day mortality was developed and validat

118 aim of our study was to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center to

119 The C-Index of the nomogram from the primary cohort was 0.779 (95% CI, 0.75

120 ional hazards model was used to generate the nomogram from tumor burden, cirrhosis, performance statu

121 The nomogram had a concordance probability of 0.78 (SE 0.02)

122 PFS, OS, and pelvic recurrence nomograms had bootstrap-corrected concordance indices of

123 Conclusion A validated clinical nomogram has been developed to quantify the risk of earl

124 alvage radiotherapy, the first comprehensive nomogram has been developed.

125 The obsolete calculators known as nomograms have become epidemic in recent medical literat

126 Although weight-based nomograms have improved the efficacy and safety of dosin

127 Nomograms have the potential to improve selection for su

128 d datasets to create and validate a modified nomogram, IBTR! version 2.0.

129 The Recurrence of Kidney Stone nomogram identifies kidney stone formers at greatest ris

130 tate Risk Assessment Post-Surgical (CAPRA-S) nomogram in a merged RP cohort (n = 734).

131 standard weight-based unfractionated heparin nomogram in ST-segment elevation myocardial infarction,

132 We then tested the nomograms in an external validation cohort operated on o

133 regimen (an age-adjusted and weight-adjusted nomogram) in children younger than 18 years with acute v

134 A postoperative nomogram including only size, site, and age predicts loc

135 The optimal model (i.e., nomogram) incorporated these three lncRNAs and six EHRs

136 A preoperative nomogram incorporating S100A2 and S100A4 expression pred

137 The goal of this study was to construct a nomogram incorporating SLN metastasis size to accurately

138 The radiomics nomogram, incorporating the RS, type of immune checkpoin

139 We also introduce a novel Bayesian nomogram indicating the amount of evidence that each fea

140 The DCIS nomogram integrates 10 clinicopathologic variables to pr

141 This nomogram integrates commonly available factors into a us

142 We validated the nomogram internally using a bootstrap procedure and subs

143 A nomogram introduced this new variable to the model.

144 pular in medicine from about 1925 to 1975, a nomogram is a crude graphical means for solving an equat

145 Our nomogram is a reliable and non-invasive tool for preoper

146 A nomogram is provided for survival probabilities 1 to 4 y

147 In addition, our easy-to-use nomogram may be able to identify potential LTS among pat

148 This nomogram may be useful when stratifying patients with ne

149 iverse prognostic and determinant variables, nomograms meet our desire for biologically and clinicall

150 ion curve analysis showed that the radiomics nomogram model had the highest overall net benefit.

151 We assessed nomogram model performance by examining overall accuracy

152 gression analysis was then used to develop a nomogram model to predict irSAEs, which was assessed by

153 iginal BCLC system, the treatment-integrated nomogram of BCLC system had larger linear trend and like

154 Compared to the nomogram of original BCLC system, the treatment-integrat

155 a previously published, multi-institutional nomogram of outcomes for salvage radiotherapy (SRT) foll

156 The nomogram of the Barcelona Clinic Liver Cancer (BCLC) has

157 Published nomograms of pediatric echocardiographic measurements ar

158 l timing of S2P was determined by generating nomograms of risk-adjusted, 3-year, post-Norwood, TFS ve

159 This has led to the appearance of many nomograms on the internet and in medical journals, and a

160 Two weighted prognostic models or nomograms, one including and one excluding treatment reg

161 ictions, easy to calculate in the frame of a nomogram or of a transfusion score, can be used to ident

162 antly reduced compared with use of the MSKCC nomogram or the NCCN or ASCO/SSO guidelines, without los

163 egimens through either evidence-based dosing nomograms or preferably through the use of dosing softwa

164 the same time period matched by a prognostic nomogram, patients with colloid carcinoma had a signific

165 ng a postresection pancreatic adenocarcinoma nomogram, patients with either tubular or colloid carcin

166 Based on our nomogram, patients with the most favorable characteristi

167 The nomogram performance was estimated by its calibration ab

168 The colon cancer recurrence nomogram predicted relapse with a concordance index of 0

169 The STS nomogram predicted the local recurrence rate with a C-in

170 Two internally validated nomograms predicted 10- and 15-y PCa-specific survival p

171 ire cohort and for four groups predefined by nomogram-predicted risks: group 1: less than 3%; group 2

172 A nomogram predicting the 15-year risk of PCSM was develop

173 We developed and validated a nomogram predicting the likelihood of occult lymph node

174 We created a nomogram predicting the likelihood of pathologic lymph n

175 ith LTS was developed and used to generate a nomogram predicting the likelihood of surviving at least

176 tent surgery for ACC were selected to create nomograms predicting RFS and OS.

177 e who have not) and calibration (accuracy of nomogram prediction) when applied to the validation coho

178 Nomogram predictions of RFS seemed better calibrated tha

179 Nomogram predictions were well calibrated.

180 The WIN nomogram predicts the likelihood of additional hyperfunc

181 Our externally validated nomogram predicts the probability of recurrence-free sur

182 The nomogram proved well calibrated and had good discriminat

183 ically significant variables in a predictive nomogram provided a reliable point system for estimating

184 Conclusion The validated nomograms provided useful prediction of OS and PFS for p

185 etter multivariate risk assessment tools and nomograms providing continuous scales and incorporating

186 In conclusions, our developed nomogram resulted in more accurate individualized predic

187 iscriminative ability and calibration of the nomograms revealed good predictive ability as indicated

188 Of those patients with a poor preoperative nomogram score, approximately 50% of patients died withi

189 56% between the first and fifth quintiles of nomogram score.

190 independent of prostate-specific antigen or nomogram score.

191 e significantly different across tertiles of nomogram scores (log-rank P = .003;< .001).

192 ootstrap procedure and subsequently used the nomogram scores to further interpret the effects of adju

193 The nomogram showed an area under the receiver operating cha

194 The nomogram showed an AUC of 0.89, a sensitivity of 0.86, a

195 ]), which improved the C-index of predictive nomogram significantly (0.90 vs. 0.64, p < 0.05).

196 cripts in PCa with Gleason's grading or with nomogram significantly improves the prediction rate of P

197 This allowed a nomogram, starting at a known fixed point during the cyc

198 The nomogram still overestimates risk in a minority of patie

199 , we incorporated SLN metastasis size into a nomogram that accurately predicts the likelihood of havi

200 riables from an internationally validated GC nomogram that estimates the probability of 5- and 9-year

201 a minimum pathology dataset and a prognostic nomogram that may have utility in stratifying patients f

202 This novel nomogram that predicts postoperative mortality may facil

203 nce guide for physicians to locate published nomograms that apply to the clinical decision in questio

204 Nomograms that incorporate these independent predictors

205 For the overall survival nomogram, the variables selected applying a backward pro

206 tive technology in their practice, such as a nomogram, there is always a question of whether the new

207 Surgeons can use this prognostic nomogram to accurately provide patients with their 2-yea

208 r incorporation into an externally validated nomogram to better select patients with T1 disease for S

209 We derived a transmission nomogram to determine the plausibility of direct or indi

210 Here, we constructed a prognostic nomogram to enable individualized predictions of surviva

211 se 5 parameters allowed the compilation of a nomogram to estimate the individual risk of lymph node m

212 The reduced model was used to build a nomogram to estimate the risk of death in individual pat

213 We developed and validated a prognostic nomogram to guide shared decision making for these patie

214 Of 124 patients predicted by the Chun nomogram to have an upgrading event, 47 actually did.

215 ors of survival and were used to construct a nomogram to predict 12-year overall survival.

216 A nomogram to predict brain metastasis was constructed and

217 A nomogram to predict probability of TO was developed and

218 We aimed to develop a nomogram to predict RFS after surgery in the absence of

219 A nomogram to predict RFS based on tumour size (cm), locat

220 Accordingly, we developed a nomogram to predict the likelihood of long-term breast p

221 A nomogram to predict the probability of death within 24 m

222 Our goal was to develop a nomogram to predict the risk of cycle-one SDRT to better

223 We, therefore, constructed a nomogram to predict the risk of pN1 prior to surgical re

224 th localized RCC and develop a comprehensive nomogram to quantitate survival differences.

225 We developed evidence-based nomograms to assist with clinical decision making.

226 ividual biomarkers and were used to generate nomograms to calculate the probability of serious advers

227 We developed nomograms to predict complete freedom from seizures and

228 into multivariate risk assessment tools and nomograms to predict disease behavior and guide manageme

229 Nomograms to predict individual 30-day risk of complicat

230 We have constructed nomograms to predict individual risk of 30-day morbidity

231 Nomograms to predict RFS and OS after surgical resection

232 iscriminative ability and calibration of the nomograms to predict RFS and OS were tested using C stat

233 nal validation was performed by applying the nomograms to the patients of an external cohort.

234 and in medical journals, and an increase in nomogram use by patients and physicians alike.

235 tion of the inherent uncertainties regarding nomogram use.

236 is curve was constructed assessing impact of nomogram using different thresholds for probabilities of

237 We derived a nomogram using mortality predictors derived from a logis

238 We constructed nomograms utilizing clinically and statistically signifi

239 When applied to an external cohort, the nomogram was accurate and discriminating with an AUC = 0

240 The nomogram was assessed by calculating concordance probabi

241 Using this score, a nomogram was built enabling individualized prediction of

242 A Web browser-based nomogram was built from this model to make individualize

243 model was used to predict HCC, after which a nomogram was computed to assess individualized risk.

244 Using these variables, a nomogram was constructed and subsequently validated usin

245 A nomogram was constructed for presentation of the final m

246 The nomogram was constructed using a cohort of 632 patients.

247 A nomogram was created for pN1 using these clinical parame

248 A nomogram was created to easily predict the risk of anast

249 On the basis of these factors, a nomogram was created to predict survival of ICC after re

250 A nomogram was created using these variables (AUC = 0.80;

251 A recently developed nomogram was demonstrated to predict disease recurrence

252 A nomogram was developed as a graphical representation of

253 A new nomogram was developed by replacing body site and Clark

254 A nomogram was developed for predicting the probability of

255 A nomogram was developed from a multivariable model based

256 The nomogram was developed from August 1, 2006, through Dece

257 A nomogram was developed on the basis of these five variab

258 A robust nomogram was developed that more accurately estimates th

259 A nomogram was developed to predict 5- and 10-year MFS, gi

260 asis of an Eastern and Western experience, a nomogram was developed to predict overall survival after

261 A predictive nomogram was developed with the linear predictor method

262 te chance of cure for individual patients, a nomogram was developed, which allowed for weighting of t

263 multiple binary logistic model from which a nomogram was elaborated.

264 The nomogram was externally validated in an independent seri

265 The predictive performance of the new nomogram was externally validated using data from The Un

266 f the Memorial Sloan Kettering Cancer Center nomogram was higher in the ePLND+SNB than in the ePLND g

267 The nomogram was internally validated using bootstrap resamp

268 Internal and external validation of the nomogram was performed to assess clinical utility.

269 A modified Fagan nomogram was provided to assist calculation of posttest

270 The nomogram was tested in patients from the Spanish Group f

271 A modified nomogram was then tested against 664 patients from Massa

272 However, the nomogram was underestimating the probability of BCR-free

273 The nomogram was well calibrated and had good discriminative

274 The nomogram was well calibrated, with no significant differ

275 A final model, or nomogram, was chosen based on both clinical and statisti

276 Factors included in the nomogram were age (</= 50 vs. >50), size (</= 5 vs. >5 c

277 Clinical data required by the Chun nomogram were available from 201 patients from the Coope

278 Concordance probabilities of the nomogram were better than those of the two NIH staging s

279 multivariate model for 30-day mortality and nomogram were created.

280 Variables included in the nomogram were the number of positive nodes, tumor diamet

281 e original and new treatment-integrated BCLC nomogram were used to evaluate the prognostic performanc

282 The nomograms were able to stratify patients into prognostic

283 Nomograms were constructed to predict each patient's ris

284 Nomograms were created from Cox models and internally va

285 Nomograms were developed to facilitate point-of-care ris

286 Nomograms were developed to predict DSD, LR, and DR.

287 Nomograms were externally validated in a cohort of 153 p

288 es (DM) rates were estimated, and predictive nomograms were generated.

289 Variables included in the nomograms were sex, seizure frequency, secondary seizure

290 , and necrosis) were combined to construct a nomogram, which had a predictive accuracy significantly

291 e optimal model was presented as a Web-based nomogram, which was evaluated in the validation cohort.

292 sess risk factors and to create a recurrence nomogram, which was validated using an international, mu

293 a patients can be estimated by this clinical nomogram, which will allow the identification of patient

294 logy/American Heart Association weight-based nomogram with centrally monitored activated partial thro

295 Age, site, and size were used to construct a nomogram with concordance index of 0.703 in internal val

296 Purpose To construct a nomogram with the albumin-bilirubin (ALBI) grade to asse

297 A nomogram with these variables had good predictive accura

298 INTERPRETATION: We present evidence-based nomograms with robust performance across populations of

299 We built nomograms with the changes of the parameters evaluated i

300 A prognostic nomogram yielded success probability of catheter drainag