-
2
-
-
67650045441
-
Prognosis and prognostic research: Developing a prognostic model
-
Royston P, Moons KGM, Altman DG, Vergouwe Y. Prognosis and prognostic research: Developing a prognostic model. BMJ 2009; 338: b604. doi: 10.1136/bmj.b604
-
(2009)
BMJ
, vol.338
, pp. b604
-
-
Royston, P.1
Kgm, M.2
Altman, D.G.3
Vergouwe, Y.4
-
3
-
-
84874505367
-
Prognosis Research Strategy (PROGRESS) 3: Prognostic model research
-
PROGRESS Group
-
Steyerberg EW, Moons KG, van der Windt DA, et al. PROGRESS Group. Prognosis Research Strategy (PROGRESS) 3: prognostic model research. PLoS Med 2013; 10: e1001381. doi: 10.1371/journal.pmed.1001381
-
(2013)
PLoS Med
, vol.10
, pp. e1001381
-
-
Steyerberg, E.W.1
Moons, K.G.2
Van Der Windt, D.A.3
-
5
-
-
47149088261
-
Predicting cardiovascular risk in England and Wales: Prospective derivation and validation of QRISK2
-
Hippisley-Cox J, Coupland C, Vinogradova Y, et al. Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ 2008; 336: 1475-82. doi: 10.1136/bmj.39609.449676.25
-
(2008)
BMJ
, vol.336
, pp. 1475-1482
-
-
Hippisley-Cox, J.1
Coupland, C.2
Vinogradova, Y.3
-
6
-
-
0020031067
-
A prognostic index in primary breast cancer
-
Haybittle JL, Blamey RW, Elston CW, et al. A prognostic index in primary breast cancer. Br J Cancer 1982; 45: 361-6. doi: 10.1038/bjc.1982.62
-
(1982)
Br J Cancer
, vol.45
, pp. 361-366
-
-
Haybittle, J.L.1
Blamey, R.W.2
Elston, C.W.3
-
8
-
-
0034063321
-
Derivation of a simple clinical model to categorize patients probability of pulmonary embolism: Increasing the models utility with the SimpliRED D-dimer
-
Wells PS, Anderson DR, Rodger M, et al. Derivation of a simple clinical model to categorize patients probability of pulmonary embolism: increasing the models utility with the SimpliRED D-dimer. Thromb Haemost 2000; 83: 416-20
-
(2000)
Thromb Haemost
, vol.83
, pp. 416-420
-
-
Wells, P.S.1
Anderson, D.R.2
Rodger, M.3
-
9
-
-
0031588519
-
Value of assessment of pretest probability of deep-vein thrombosis in clinical management
-
Wells PS, Anderson DR, Bormanis J, et al. Value of assessment of pretest probability of deep-vein thrombosis in clinical management. Lancet 1997; 350: 1795-8. doi: 10.1016/S0140-6736(97)08140-3
-
(1997)
Lancet
, vol.350
, pp. 1795-1798
-
-
Wells, P.S.1
Anderson, D.R.2
Bormanis, J.3
-
10
-
-
67650082402
-
Prognosis and prognostic research: Validating a prognostic model
-
Altman DG, Vergouwe Y, Royston P, Moons KG. Prognosis and prognostic research: validating a prognostic model. BMJ 2009; 338: b605. doi: 10.1136/bmj.b605
-
(2009)
BMJ
, vol.338
, pp. b605
-
-
Altman, D.G.1
Vergouwe, Y.2
Royston, P.3
Moons, K.G.4
-
11
-
-
67650089602
-
Prognosis and prognostic research: Application and impact of prognostic models in clinical practice
-
Moons KG, Altman DG, Vergouwe Y, Royston P. Prognosis and prognostic research: application and impact of prognostic models in clinical practice. BMJ 2009; 338: b606. doi: 10.1136/bmj.b606
-
(2009)
BMJ
, vol.338
, pp. b606
-
-
Moons, K.G.1
Altman, D.G.2
Vergouwe, Y.3
Royston, P.4
-
12
-
-
67650022801
-
Prognosis and prognostic research: What why, and how?
-
Moons KG, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: what, why, and how?BMJ 2009; 338: b375. doi: 10.1136/bmj.b375
-
(2009)
BMJ
, vol.338
, pp. b375
-
-
Moons, K.G.1
Royston, P.2
Vergouwe, Y.3
De, G.4
Altman, D.G.5
-
13
-
-
84874484807
-
Prognosis research strategy (PROGRESS) 1: A framework for researching clinical outcomes
-
PROGRESS Group
-
Hemingway H, Croft P, Perel P, et al. PROGRESS Group. Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes. BMJ 2013; 346: e5595. doi: 10.1136/bmj.e5595
-
(2013)
BMJ
, vol.346
, pp. e5595
-
-
Hemingway, H.1
Croft, P.2
Perel, P.3
-
14
-
-
84874455583
-
Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research
-
PROGRESS Group
-
Riley RD, Hayden JA, Steyerberg EW, et al. PROGRESS Group. Prognosis Research Strategy (PROGRESS) 2: prognostic factor research. PLoS Med 2013; 10: e1001380. doi: 10.1371/journal. pmed.1001380
-
(2013)
PLoS Med
, vol.10
, pp. e1001380
-
-
Riley, R.D.1
Hayden, J.A.2
Steyerberg, E.W.3
-
15
-
-
84874455291
-
PROGRESS Group. Prognosis research strategy (PROGRESS) 4: Stratified medicine research
-
Hingorani AD, Windt DA, Riley RD, et al. PROGRESS Group. Prognosis research strategy (PROGRESS) 4: stratified medicine research. BMJ 2013; 346: e5793. doi: 10.1136/bmj.e5793
-
(2013)
BMJ
, vol.346
, pp. e5793
-
-
Hingorani, A.D.1
Windt, D.A.2
Riley, R.D.3
-
16
-
-
84942465542
-
How to develop a more accurate risk prediction model when there are few events [correction in BMJ 2016 353: I3235]
-
Pavlou M, Ambler G, Seaman SR, et al. How to develop a more accurate risk prediction model when there are few events [correction in BMJ 2016; 353: i3235]. BMJ 2015; 351: h3868. doi: 10.1136/bmj.h3868
-
(2015)
BMJ
, vol.351
, pp. h3868
-
-
Pavlou, M.1
Ambler, G.2
Seaman, S.R.3
-
17
-
-
84860113852
-
Risk prediction models i Development, internal validation, and assessing the incremental value of a new (bio)marker
-
Moons KG, Kengne AP, Woodward M, et al. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart 2012; 98: 683-90. doi: 10.1136/heartjnl-2011-301246
-
(2012)
Heart
, vol.98
, pp. 683-690
-
-
Moons, K.G.1
Kengne, A.P.2
Woodward, M.3
-
19
-
-
0141514712
-
External validation is necessary in prediction research: A clinical example
-
Bleeker SE, Moll HA, Steyerberg EW, et al. External validation is necessary in prediction research: a clinical example. J Clin Epidemiol 2003; 56: 826-32. doi: 10.1016/S0895-4356(03)00207-5
-
(2003)
J Clin Epidemiol
, vol.56
, pp. 826-832
-
-
Bleeker, S.E.1
Moll, H.A.2
Steyerberg, E.W.3
-
20
-
-
84923527988
-
A new framework to enhance the interpretation of external validation studies of clinical prediction models
-
Debray TP, Vergouwe Y, Koffijberg H, Nieboer D, Steyerberg EW, Moons KG. A new framework to enhance the interpretation of external validation studies of clinical prediction models. J Clin Epidemiol 2015; 68: 279-89. doi: 10.1016/j.jclinepi.2014.06.018
-
(2015)
J Clin Epidemiol
, vol.68
, pp. 279-289
-
-
Debray, T.P.1
Vergouwe, Y.2
Koffijberg, H.3
Nieboer, D.4
Steyerberg, E.W.5
Moons, K.G.6
-
21
-
-
77950389784
-
Reporting performance of prognostic models in cancer: A review
-
Mallett S, Royston P, Waters R, Dutton S, Altman DG. Reporting performance of prognostic models in cancer: a review. BMC Med 2010; 8: 21. doi: 10.1186/1741-7015-8-21
-
(2010)
BMC Med
, vol.8
, pp. 21
-
-
Mallett, S.1
Royston, P.2
Waters, R.3
Dutton, S.4
Altman, D.G.5
-
22
-
-
33644855006
-
Translating clinical research into clinical practice: Impact of using prediction rules to make decisions
-
Reilly BM, Evans AT. Translating clinical research into clinical practice: impact of using prediction rules to make decisions. Ann Intern Med 2006; 144: 201-9. doi: 10.7326/0003-4819-144-3-200602070-00009
-
(2006)
Ann Intern Med
, vol.144
, pp. 201-209
-
-
Reilly, B.M.1
Evans, A.T.2
-
23
-
-
84861556816
-
Reporting and methods in clinical prediction research: A systematic review
-
Bouwmeester W, Zuithoff NP, Mallett S, et al. Reporting and methods in clinical prediction research: a systematic review. PLoS Med 2012; 9: e1001221. doi: 10.1371/journal.pmed.1001221
-
(2012)
PLoS Med
, vol.9
, pp. e1001221
-
-
Bouwmeester, W.1
Zuithoff, N.P.2
Mallett, S.3
-
25
-
-
84872190358
-
Fracture risk assessment: State of the art methodologically unsound or poorly reported?
-
Collins GS, Michaëlsson K. Fracture risk assessment: state of the art, methodologically unsound, or poorly reported?Curr Osteoporos Rep 2012; 10: 199-207. doi: 10.1007/s11914-012-0108-1
-
(2012)
Curr Osteoporos Rep
, vol.10
, pp. 199-207
-
-
Collins, G.S.1
Michaëlsson, K.2
-
26
-
-
0034906866
-
Internal validation of predictive models: Efficiency of some procedures for logistic regression analysis
-
Steyerberg EW, Harrell FEJ Jr, , Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 2001; 54: 774-81. doi: 10.1016/S0895-4356(01)00341-9
-
(2001)
J Clin Epidemiol
, vol.54
, pp. 774-781
-
-
Steyerberg, E.W.1
Harrell, F.E.J.2
Borsboom, G.J.3
Eijkemans, M.J.4
Vergouwe, Y.5
Habbema, J.D.6
-
27
-
-
77749306261
-
Meta-Analysis of individual participant data: Rationale, conduct, and reporting
-
Riley RD, Lambert PC, Abo-Zaid G. Meta-Analysis of individual participant data: rationale, conduct, and reporting. BMJ 2010; 340: c221. doi: 10.1136/bmj.c221
-
(2010)
BMJ
, vol.340
, pp. c221
-
-
Riley, R.D.1
Lambert, P.C.2
Abo-Zaid, G.3
-
28
-
-
84892152641
-
Developing and validating risk prediction models in an individual participant data meta-Analysis
-
Ahmed I, Debray TP, Moons KG, Riley RD. Developing and validating risk prediction models in an individual participant data meta-Analysis. BMC Med Res Methodol 2014; 14: 3. doi: 10.1186/1471-2288-14-3
-
(2014)
BMC Med Res Methodol
, vol.14
, pp. 3
-
-
Ahmed, I.1
Debray, T.P.2
Moons, K.G.3
Riley, R.D.4
-
29
-
-
84946072388
-
Cochrane IPD Meta-Analysis Methods group. Individual participant data (IPD) meta-Analyses of diagnostic and prognostic modeling studies: Guidance on their use
-
Debray TPA, Riley RD, Rovers MM, Reitsma JB, Moons KG. Cochrane IPD Meta-Analysis Methods group. Individual participant data (IPD) meta-Analyses of diagnostic and prognostic modeling studies: guidance on their use. PLoS Med 2015; 12: e1001886. doi: 10.1371/journal.pmed.1001886
-
(2015)
PLoS Med
, vol.12
, pp. e1001886
-
-
Debray, T.P.A.1
Riley, R.D.2
Rovers, M.M.3
Reitsma, J.B.4
Moons, K.G.5
-
30
-
-
84896692640
-
Emerging Risk Factors Collaboration. Assessing risk prediction models using individual participant data from multiple studies
-
Pennells L, Kaptoge S, White IR, Thompson SG, Wood AM. Emerging Risk Factors Collaboration. Assessing risk prediction models using individual participant data from multiple studies. Am J Epidemiol 2014; 179: 621-32. doi: 10.1093/aje/kwt298
-
(2014)
Am J Epidemiol
, vol.179
, pp. 621-632
-
-
Pennells, L.1
Kaptoge, S.2
White, I.R.3
Thompson, S.G.4
Wood, A.M.5
-
31
-
-
84923013798
-
The rise of big clinical databases
-
Cook JA, Collins GS. The rise of big clinical databases. Br J Surg 2015; 102: e93-101. doi: 10.1002/bjs.9723
-
(2015)
Br J Surg
, vol.102
, pp. e93-e101
-
-
Cook, J.A.1
Collins, G.S.2
-
32
-
-
77953707407
-
An independent and external validation of QRISK2 cardiovascular disease risk score: A prospective open cohort study
-
Collins GS, Altman DG. An independent and external validation of QRISK2 cardiovascular disease risk score: a prospective open cohort study. BMJ 2010; 340: c2442. doi: 10.1136/bmj.c2442
-
(2010)
BMJ
, vol.340
, pp. c2442
-
-
Collins, G.S.1
Altman, D.G.2
-
33
-
-
50949101668
-
Predicting outcome after traumatic brain injury: Development and international validation of prognostic scores based on admission characteristics
-
Steyerberg EW, Mushkudiani N, Perel P, et al. Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med 2008; 5: e165. doi: 10.1371/journal.pmed.0050165
-
(2008)
PLoS Med
, vol.5
, pp. e165
-
-
Steyerberg, E.W.1
Mushkudiani, N.2
Perel, P.3
-
34
-
-
84923923813
-
Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD statement
-
Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med 2015; 162: 55-63. doi: 10.7326/M14-0697
-
(2015)
Ann Intern Med
, vol.162
, pp. 55-63
-
-
Collins, G.S.1
Reitsma, J.B.2
Altman, D.G.3
Moons, K.G.4
-
35
-
-
84920623458
-
Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): Explanation and elaboration
-
Moons KG, Altman DG, Reitsma JB, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med 2015; 162: W1-73. doi: 10.7326/M14-0698
-
(2015)
Ann Intern Med
, vol.162
, pp. W1-W73
-
-
Moons, K.G.1
Altman, D.G.2
Reitsma, J.B.3
-
36
-
-
1442351098
-
A new measure of prognostic separation in survival data
-
Royston P, Sauerbrei W. A new measure of prognostic separation in survival data. Stat Med 2004; 23: 723-48. doi: 10.1002/sim.1621
-
(2004)
Stat Med
, vol.23
, pp. 723-748
-
-
Royston, P.1
Sauerbrei, W.2
-
37
-
-
84957076656
-
A calibration hierarchy for risk models was defined: From utopia to empirical data
-
Van Calster B, Nieboer D, Vergouwe Y, De Cock B, Pencina MJ, Steyerberg EW. A calibration hierarchy for risk models was defined: from utopia to empirical data. J Clin Epidemiol 2016; S0895-4356(15)00581-8. doi: 10.1016/j.jclinepi.2015.12.005 PubMed
-
(2016)
J Clin Epidemiol
, vol.15
, pp. S0895-S4356
-
-
Van Calster, B.1
Nieboer, D.2
Vergouwe, Y.3
De Cock, B.4
Pencina, M.J.5
Steyerberg, E.W.6
-
38
-
-
84874529489
-
External validation of a Cox prognostic model: Principles and methods
-
Royston P, Altman DG. External validation of a Cox prognostic model: principles and methods. BMC Med Res Methodol 2013; 13: 33. doi: 10.1186/1471-2288-13-33
-
(2013)
BMC Med Res Methodol
, vol.13
, pp. 33
-
-
Royston, P.1
Altman, D.G.2
-
39
-
-
84899459258
-
External validation of multivariable prediction models: A systematic review of methodological conduct and reporting
-
Collins GS, de Groot JA, Dutton S, et al. External validation of multivariable prediction models: a systematic review of methodological conduct and reporting. BMC Med Res Methodol 2014; 14: 40. doi: 10.1186/1471-2288-14-40
-
(2014)
BMC Med Res Methodol
, vol.14
, pp. 40
-
-
Collins, G.S.1
De Groot, J.A.2
Dutton, S.3
-
40
-
-
17444420853
-
Substantial effective sample sizes were required for external validation studies of predictive logistic regression models
-
Vergouwe Y, Steyerberg EW, Eijkemans MJ, Habbema JD. Substantial effective sample sizes were required for external validation studies of predictive logistic regression models. J Clin Epidemiol 2005; 58: 475-83. doi: 10.1016/j.jclinepi.2004.06.017
-
(2005)
J Clin Epidemiol
, vol.58
, pp. 475-483
-
-
Vergouwe, Y.1
Steyerberg, E.W.2
Eijkemans, M.J.3
Habbema, J.D.4
-
41
-
-
84954405416
-
Sample size considerations for the external validation of a multivariable prognostic model: A resampling study
-
Collins GS, Ogundimu EO, Altman DG. Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Stat Med 2016; 35: 214-26. doi: 10.1002/sim.6787
-
(2016)
Stat Med
, vol.35
, pp. 214-226
-
-
Collins, G.S.1
Ogundimu, E.O.2
Altman, D.G.3
-
42
-
-
1542506052
-
Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer
-
Royston P, Parmar MKB, Sylvester R. Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer. Stat Med 2004; 23: 907-26. doi: 10.1002/sim.1691
-
(2004)
Stat Med
, vol.23
, pp. 907-926
-
-
Royston, P.1
Mkb, P.2
Sylvester, R.3
-
43
-
-
77958090625
-
External validity of risk models: Use of benchmark values to disentangle a case-mix effect from incorrect coefficients
-
Vergouwe Y, Moons KG, Steyerberg EW. External validity of risk models: Use of benchmark values to disentangle a case-mix effect from incorrect coefficients. Am J Epidemiol 2010; 172: 971-80. doi: 10.1093/aje/kwq223
-
(2010)
Am J Epidemiol
, vol.172
, pp. 971-980
-
-
Vergouwe, Y.1
Moons, K.G.2
Steyerberg, E.W.3
-
44
-
-
84864387127
-
Predicting the 10 year risk of cardiovascular disease in the United Kingdom: Independent and external validation of an updated version of QRISK2
-
Collins GS, Altman DG. Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ 2012; 344: e4181. doi: 10.1136/bmj.e4181
-
(2012)
BMJ
, vol.344
, pp. e4181
-
-
Collins, G.S.1
Altman, D.G.2
-
45
-
-
84880044696
-
A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-Analysis
-
Debray TP, Moons KG, Ahmed I, Koffijberg H, Riley RD. A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-Analysis. Stat Med 2013; 32: 3158-80. doi: 10.1002/sim.5732
-
(2013)
Stat Med
, vol.32
, pp. 3158-3180
-
-
Debray, T.P.1
Moons, K.G.2
Ahmed, I.3
Koffijberg, H.4
Riley, R.D.5
-
46
-
-
0036787049
-
Spectrum bias or spectrum effect? Subgroup variation in diagnostic test evaluation
-
Mulherin SA, Miller WC. Spectrum bias or spectrum effect?. Subgroup variation in diagnostic test evaluation. Ann Intern Med 2002; 137: 598-602. doi: 10.7326/0003-4819-137-7-200210010-00011
-
(2002)
Ann Intern Med
, vol.137
, pp. 598-602
-
-
Mulherin, S.A.1
Miller, W.C.2
-
47
-
-
0018178436
-
Problems of spectrum and bias in evaluating the efficacy of diagnostic tests
-
Ransohoff DF, Feinstein AR. Problems of spectrum and bias in evaluating the efficacy of diagnostic tests. N Engl J Med 1978; 299: 926-30. doi: 10.1056/NEJM197810262991705
-
(1978)
N Engl J Med
, vol.299
, pp. 926-930
-
-
Ransohoff, D.F.1
Feinstein, A.R.2
-
48
-
-
0036959539
-
Between iatrotropic stimulus and interiatric referral: The domain of primary care research
-
Knottnerus JA. Between iatrotropic stimulus and interiatric referral: the domain of primary care research. J Clin Epidemiol 2002; 55: 1201-6. doi: 10.1016/S0895-4356(02)00528-0
-
(2002)
J Clin Epidemiol
, vol.55
, pp. 1201-1206
-
-
Knottnerus, J.A.1
-
49
-
-
22144482023
-
The Wells rule does not adequately rule out deep venous thrombosis in primary care patients
-
Oudega R, Hoes AW, Moons KG. The Wells rule does not adequately rule out deep venous thrombosis in primary care patients. Ann Intern Med 2005; 143: 100-7. doi: 10.7326/0003-4819-143-2-200507190-00008
-
(2005)
Ann Intern Med
, vol.143
, pp. 100-107
-
-
Oudega, R.1
Hoes, A.W.2
Moons, K.G.3
-
50
-
-
16644400192
-
Prognostic factors-confusion caused by bad quality of design, analysis and reporting of many studies
-
Bier H, ed. Karger
-
Sauerbrei W. Prognostic factors-confusion caused by bad quality of design, analysis and reporting of many studies. In: Bier H, ed. Current research in head and neck cancer advances in oto-rhinolaryngology. Karger, 2005: 184-200
-
(2005)
Current Research in Head and Neck Cancer Advances in Oto-rhinolaryngology
, pp. 184-200
-
-
Sauerbrei, W.1
-
51
-
-
36849089158
-
Updating methods improved the performance of a clinical prediction model in new patients
-
Janssen KJ, Moons KG, Kalkman CJ, Grobbee DE, Vergouwe Y. Updating methods improved the performance of a clinical prediction model in new patients. J Clin Epidemiol 2008; 61: 76-86. doi: 10.1016/j. jclinepi.2007.04.018
-
(2008)
J Clin Epidemiol
, vol.61
, pp. 76-86
-
-
Janssen, K.J.1
Moons, K.G.2
Kalkman, C.J.3
De, G.4
Vergouwe, Y.5
-
52
-
-
79955544813
-
Interpretation of random effects meta-Analyses
-
Riley RD, Higgins JP, Deeks JJ. Interpretation of random effects meta-Analyses. BMJ 2011; 342: d549. doi: 10.1136/bmj.d549
-
(2011)
BMJ
, vol.342
, pp. d549
-
-
Riley, R.D.1
Higgins, J.P.2
Deeks, J.J.3
-
53
-
-
84952630758
-
Multivariate meta-Analysis of individual participant data helped externally validate the performance and implementation of a prediction model
-
Snell KI, Hua H, Debray TP, et al. Multivariate meta-Analysis of individual participant data helped externally validate the performance and implementation of a prediction model. J Clin Epidemiol 2016; 69: 40-50. doi: 10.1016/j.jclinepi.2015.05.009
-
(2016)
J Clin Epidemiol
, vol.69
, pp. 40-50
-
-
Snell, K.I.1
Hua, H.2
Debray, T.P.3
-
56
-
-
84896930969
-
Exclusion of deep vein thrombosis using the Wells rule in clinically important subgroups: Individual patient data meta-Analysis
-
Geersing GJ, Zuithoff NP, Kearon C, et al. Exclusion of deep vein thrombosis using the Wells rule in clinically important subgroups: individual patient data meta-Analysis. BMJ 2014; 348: g1340. doi: 10.1136/bmj.g1340
-
(2014)
BMJ
, vol.348
, pp. g1340
-
-
Geersing, G.J.1
Zuithoff, N.P.2
Kearon, C.3
-
57
-
-
43949083703
-
Comparison of non-parametric confidence intervals for the area under the ROC curve of a continuous-scale diagnostic test
-
Gengsheng Qin , Hotilovac L. Comparison of non-parametric confidence intervals for the area under the ROC curve of a continuous-scale diagnostic test. Stat Methods Med Res 2008; 17: 207-21. doi: 10.1177/0962280207087173
-
(2008)
Stat Methods Med Res
, vol.17
, pp. 207-221
-
-
Qin, G.1
Hotilovac, L.2
-
58
-
-
84896732451
-
QRISK2 validation by ethnic group
-
Tillin T, Hughes AD, Whincup P, et al. QRISK2 validation by ethnic group. Heart 2014; 100: 437. doi: 10.1136/heartjnl-2013-305333
-
(2014)
Heart
, vol.100
, pp. 437
-
-
Tillin, T.1
Hughes, A.D.2
Whincup, P.3
-
59
-
-
84900855393
-
Ethnic group differences in cardiovascular risk assessment scores: National cross-sectional study
-
Dalton AR, Bottle A, Soljak M, Majeed A, Millett C. Ethnic group differences in cardiovascular risk assessment scores: national cross-sectional study. Ethn Health 2014; 19: 367-84. doi: 10.1080/13557858.2013.797568
-
(2014)
Ethn Health
, vol.19
, pp. 367-384
-
-
Dalton, A.R.1
Bottle, A.2
Soljak, M.3
Majeed, A.4
Millett, C.5
-
61
-
-
84928762608
-
Summarising and validating test accuracy results across multiple studies for use in clinical practice
-
Riley RD, Ahmed I, Debray TP, et al. Summarising and validating test accuracy results across multiple studies for use in clinical practice. Stat Med 2015; 34: 2081-103. doi: 10.1002/sim.6471
-
(2015)
Stat Med
, vol.34
, pp. 2081-2103
-
-
Riley, R.D.1
Ahmed, I.2
Debray, T.P.3
-
62
-
-
84897537279
-
Estimating a test's accuracy using tailored meta-Analysis-How setting-specific data may aid study selection
-
Willis BH, Hyde CJ. Estimating a test's accuracy using tailored meta-Analysis-How setting-specific data may aid study selection. J Clin Epidemiol 2014; 67: 538-46. doi: 10.1016/j.jclinepi.2013.10.016
-
(2014)
J Clin Epidemiol
, vol.67
, pp. 538-546
-
-
Willis, B.H.1
Hyde, C.J.2
-
63
-
-
84881493693
-
Variation of a test's sensitivity and specificity with disease prevalence
-
Leeflang MM, Rutjes AW, Reitsma JB, Hooft L, Bossuyt PM. Variation of a test's sensitivity and specificity with disease prevalence. CMAJ 2013; 185: E537-44. doi: 10.1503/cmaj.121286
-
(2013)
CMAJ
, vol.185
, pp. E537-E544
-
-
Leeflang, M.M.1
Rutjes, A.W.2
Reitsma, J.B.3
Hooft, L.4
Bossuyt, P.M.5
-
64
-
-
56349139109
-
Predicting mortality with pneumonia severity scores: Importance of model recalibration to local settings
-
Schuetz P, Koller M, Christ-Crain M, et al. Predicting mortality with pneumonia severity scores: importance of model recalibration to local settings. Epidemiol Infect 2008; 136: 1628-37. doi: 10.1017/S0950268808000435
-
(2008)
Epidemiol Infect
, vol.136
, pp. 1628-1637
-
-
Schuetz, P.1
Koller, M.2
Christ-Crain, M.3
-
65
-
-
84859928513
-
Individual participant data meta-Analysis of prognostic factor studies: State of the art?
-
Abo-Zaid G, Sauerbrei W, Riley RD. Individual participant data meta-Analysis of prognostic factor studies: state of the art?BMC Med Res Methodol 2012; 12: 56. doi: 10.1186/1471-2288-12-56
-
(2012)
BMC Med Res Methodol
, vol.12
, pp. 56
-
-
Abo-Zaid, G.1
Sauerbrei, W.2
Riley, R.D.3
-
66
-
-
84926444242
-
Imputation of systematically missing predictors in an individual participant data meta-Analysis: A generalized approach using MICE
-
Jolani S, Debray TP, Koffijberg H, van Buuren S, Moons KG. Imputation of systematically missing predictors in an individual participant data meta-Analysis: a generalized approach using MICE. Stat Med 2015; 34: 1841-63. doi: 10.1002/sim.6451
-
(2015)
Stat Med
, vol.34
, pp. 1841-1863
-
-
Jolani, S.1
Debray, T.P.2
Koffijberg, H.3
Van Buuren, S.4
Moons, K.G.5
-
67
-
-
84887138473
-
Multiple imputation for handling systematically missing confounders in meta-Analysis of individual participant data
-
PROG-IMT Study Group
-
Resche-Rigon M, White IR, Bartlett JW, Peters SA, Thompson SG. PROG-IMT Study Group. Multiple imputation for handling systematically missing confounders in meta-Analysis of individual participant data. Stat Med 2013; 32: 4890-905. doi: 10.1002/sim.5894
-
(2013)
Stat Med
, vol.32
, pp. 4890-4905
-
-
Resche-Rigon, M.1
White, I.R.2
Bartlett, J.W.3
Peters, S.A.4
Thompson, S.G.5
-
68
-
-
84939607655
-
Data Resource Profile: Clinical Practice Research Datalink (CPRD
-
Herrett E, Gallagher AM, Bhaskaran K, et al. Data Resource Profile: Clinical Practice Research Datalink (CPRD). Int J Epidemiol 2015; 44: 827-36. doi: 10.1093/ije/dyv098
-
(2015)
Int J Epidemiol
, vol.44
, pp. 827-836
-
-
Herrett, E.1
Gallagher, A.M.2
Bhaskaran, K.3
-
69
-
-
84938702916
-
Individual Participant Data (IPD) Meta-Analyses of Randomised Controlled Trials: Guidance on Their Use
-
Tierney JF, Vale C, Riley R, et al. Individual Participant Data (IPD) Meta-Analyses of Randomised Controlled Trials: Guidance on Their Use. PLoS Med 2015; 12: e1001855. doi: 10.1371/journal. pmed.1001855
-
(2015)
PLoS Med
, vol.12
, pp. e1001855
-
-
Tierney, J.F.1
Vale, C.2
Riley, R.3
-
70
-
-
33747170479
-
Systematic review of multiple studies of prognosis: The feasibility of obtaining individual patient data
-
Auget J-L, Balakrishnan N, Mesbah M, et al, eds Birkhäuser
-
Altman DG, Trivella M, Pezzella F, et al. Systematic review of multiple studies of prognosis: the feasibility of obtaining individual patient data. In: Auget J-L, Balakrishnan N, Mesbah M, et al, eds. Advances in statistical methods for the health sciences. Birkhäuser, 2006: 3-18
-
(2006)
Advances in Statistical Methods for the Health Sciences
, pp. 3-18
-
-
Altman, D.G.1
Trivella, M.2
Pezzella, F.3
-
71
-
-
84857135675
-
Assessment of publication bias, selection bias, and unavailable data in meta-Analyses using individual participant data: A database survey
-
Ahmed I, Sutton AJ, Riley RD. Assessment of publication bias, selection bias, and unavailable data in meta-Analyses using individual participant data: a database survey. BMJ 2012; 344: d7762. doi: 10.1136/bmj.d7762
-
(2012)
BMJ
, vol.344
, pp. d7762
-
-
Ahmed, I.1
Sutton, A.J.2
Riley, R.D.3
-
72
-
-
0030474271
-
A simulation study of the number of events per variable in logistic regression analysis
-
Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996; 49: 1373-9. doi: 10.1016/S0895-4356(96)00236-3
-
(1996)
J Clin Epidemiol
, vol.49
, pp. 1373-1379
-
-
Peduzzi, P.1
Concato, J.2
Kemper, E.3
Holford, T.R.4
Feinstein, A.R.5
-
73
-
-
84944065233
-
Discrimination-based sample size calculations for multivariable prognostic models for time-to-event data
-
Jinks RC, Royston P, Parmar MK. Discrimination-based sample size calculations for multivariable prognostic models for time-to-event data. BMC Med Res Methodol 2015; 15: 82. doi: 10.1186/s12874-015-0078-y.
-
(2015)
BMC Med Res Methodol
, vol.15
, pp. 82
-
-
Jinks, R.C.1
Royston, P.2
Parmar, M.K.3
-
74
-
-
84962074698
-
Adequate sample size for developing prediction models is not simply related to events per variable
-
30011-30017
-
Ogundimu EO, Altman DG, Collins GS. Adequate sample size for developing prediction models is not simply related to events per variable. J Clin Epidemiol 2016; S0895-4356(16)30011-7
-
(2016)
J Clin Epidemiol
, vol.16
, pp. S0895-S4356
-
-
Ogundimu, E.O.1
Altman, D.G.2
Collins, G.S.3
-
75
-
-
84885970943
-
Screening for data clustering in multicenter studies: The residual intraclass correlation
-
Wynants L, Timmerman D, Bourne T, Van Huffel S, Van Calster B. Screening for data clustering in multicenter studies: the residual intraclass correlation. BMC Med Res Methodol 2013; 13: 128. doi: 10.1186/1471-2288-13-128
-
(2013)
BMC Med Res Methodol
, vol.13
, pp. 128
-
-
Wynants, L.1
Timmerman, D.2
Bourne, T.3
Van Huffel, S.4
Van Calster, B.5
-
76
-
-
84928753669
-
Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: The PRISMA-IPD Statement
-
PRISMA-IPD Development Group
-
Stewart LA, Clarke M, Rovers M, et al. PRISMA-IPD Development Group. Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD Statement. JAMA 2015; 313: 1657-65. doi: 10.1001/jama.2015.3656
-
(2015)
JAMA
, vol.313
, pp. 1657-1665
-
-
Stewart, L.A.1
Clarke, M.2
Rovers, M.3
-
77
-
-
66849095444
-
Predicting risk of type 2 diabetes in England and Wales: Prospective derivation and validation of QDScore
-
b880
-
Hippisley-Cox J, Coupland C, Robson J, Sheikh A, Brindle P. Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore. BMJ 2009; 338: b880. doi: 10.1136/bmj. b880
-
(2009)
BMJ
, vol.338
-
-
Hippisley-Cox, J.1
Coupland, C.2
Robson, J.3
Sheikh, A.4
Brindle, P.5
-
78
-
-
84866440887
-
Aggregating published prediction models with individual participant data: A comparison of different approaches
-
Debray TP, Koffijberg H, Vergouwe Y, Moons KG, Steyerberg EW. Aggregating published prediction models with individual participant data: a comparison of different approaches. Stat Med 2012; 31: 2697-712. doi: 10.1002/sim.5412
-
(2012)
Stat Med
, vol.31
, pp. 2697-2712
-
-
Debray, T.P.1
Koffijberg, H.2
Vergouwe, Y.3
Moons, K.G.4
Steyerberg, E.W.5
-
79
-
-
84861872921
-
Comparing risk prediction models
-
Collins GS, Moons KG. Comparing risk prediction models. BMJ 2012; 344: e3186. doi: 10.1136/bmj.e3186
-
(2012)
BMJ
, vol.344
, pp. e3186
-
-
Collins, G.S.1
Moons, K.G.2
-
80
-
-
33750905259
-
Decision curve analysis: A novel method for evaluating prediction models
-
Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 2006; 26: 565-74. doi: 10.1177/0272989X06295361
-
(2006)
Med Decis Making
, vol.26
, pp. 565-574
-
-
Vickers, A.J.1
Elkin, E.B.2
-
81
-
-
84928713036
-
Why data sharing should be the expected norm
-
Krumholz HM. Why data sharing should be the expected norm. BMJ 2015; 350: h599. doi: 10.1136/bmj.h599
-
(2015)
BMJ
, vol.350
, pp. h599
-
-
Krumholz, H.M.1
-
82
-
-
84925764176
-
Uptake of systematic reviews and meta-Analyses based on individual participant data in clinical practice guidelines: Descriptive study
-
Cochrane IPD Meta-Analysis Methods Group
-
Vale CL, Rydzewska LH, Rovers MM, Emberson JR, Gueyffier F, Stewart LA. Cochrane IPD Meta-Analysis Methods Group. Uptake of systematic reviews and meta-Analyses based on individual participant data in clinical practice guidelines: descriptive study. BMJ 2015; 350: h1088. doi: 10.1136/bmj.h1088
-
(2015)
BMJ
, vol.350
, pp. h1088
-
-
Vale, C.L.1
Rydzewska, L.H.2
Rovers, M.M.3
Emberson, J.R.4
Gueyffier, F.5
Stewart, L.A.6
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