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Items: 1 to 50 of 488

1.

Evidence synthesis in prognosis research.

Debray TPA, de Jong VMT, Moons KGM, Riley RD.

Diagn Progn Res. 2019 Jul 11;3:13. doi: 10.1186/s41512-019-0059-4. eCollection 2019.

2.

Decision analytic modeling was useful to assess the impact of a prediction model on health outcomes before a randomized trial.

Jenniskens K, Lagerweij GR, Naaktgeboren CA, Hooft L, Moons KGM, Poldervaart JM, Koffijberg H, Reitsma JB.

J Clin Epidemiol. 2019 Jul 19;115:106-115. doi: 10.1016/j.jclinepi.2019.07.010. [Epub ahead of print]

PMID:
31330250
3.

Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis.

Damen JA, Pajouheshnia R, Heus P, Moons KGM, Reitsma JB, Scholten RJPM, Hooft L, Debray TPA.

BMC Med. 2019 Jun 13;17(1):109. doi: 10.1186/s12916-019-1340-7.

4.

When and how to use data from randomised trials to develop or validate prognostic models.

Pajouheshnia R, Groenwold RHH, Peelen LM, Reitsma JB, Moons KGM.

BMJ. 2019 May 29;365:l2154. doi: 10.1136/bmj.l2154. No abstract available.

PMID:
31142454
5.

Evaluating the impact of prediction models: lessons learned, challenges, and recommendations.

Kappen TH, van Klei WA, van Wolfswinkel L, Kalkman CJ, Vergouwe Y, Moons KGM.

Diagn Progn Res. 2018 Jun 12;2:11. doi: 10.1186/s41512-018-0033-6. eCollection 2018.

6.

Ruling out pulmonary embolism across different subgroups of patients and healthcare settings: protocol for a systematic review and individual patient data meta-analysis (IPDMA).

Geersing GJ, Kraaijpoel N, Büller HR, van Doorn S, van Es N, Le Gal G, Huisman MV, Kearon C, Kline JA, Moons KGM, Miniati M, Righini M, Roy PM, van der Wall SJ, Wells PS, Klok FA.

Diagn Progn Res. 2018 Jul 2;2:10. doi: 10.1186/s41512-018-0032-7. eCollection 2018.

7.

Uniformity in measuring adherence to reporting guidelines: the example of TRIPOD for assessing completeness of reporting of prediction model studies.

Heus P, Damen JAAG, Pajouheshnia R, Scholten RJPM, Reitsma JB, Collins GS, Altman DG, Moons KGM, Hooft L.

BMJ Open. 2019 Apr 24;9(4):e025611. doi: 10.1136/bmjopen-2018-025611.

8.

Reporting of artificial intelligence prediction models.

Collins GS, Moons KGM.

Lancet. 2019 Apr 20;393(10181):1577-1579. doi: 10.1016/S0140-6736(19)30037-6. No abstract available.

PMID:
31007185
9.

Empirical evidence of the impact of study characteristics on the performance of prediction models: a meta-epidemiological study.

Damen JAAG, Debray TPA, Pajouheshnia R, Reitsma JB, Scholten RJPM, Moons KGM, Hooft L.

BMJ Open. 2019 Apr 1;9(4):e026160. doi: 10.1136/bmjopen-2018-026160.

10.

Forcing dichotomous disease classification from reference standards leads to bias in diagnostic accuracy estimates: A simulation study.

Jenniskens K, Naaktgeboren CA, Reitsma JB, Hooft L, Moons KGM, van Smeden M.

J Clin Epidemiol. 2019 Jul;111:1-10. doi: 10.1016/j.jclinepi.2019.03.002. Epub 2019 Mar 20.

PMID:
30904568
11.

External validation of prognostic models for preeclampsia in a Dutch multicenter prospective cohort.

Lamain-de Ruiter M, Kwee A, Naaktgeboren CA, Louhanepessy RD, De Groot I, Evers IM, Groenendaal F, Hering YR, Huisjes AJM, Kirpestein C, Monincx WM, Schielen PCJI, Van 't Zelfde A, Van Oirschot CM, Vankan-Buitelaar SA, Vonk MAAW, Wiegers TA, Zwart JJ, Moons KGM, Franx A, Koster MPH.

Hypertens Pregnancy. 2019 May;38(2):78-88. doi: 10.1080/10641955.2019.1584210. Epub 2019 Mar 20.

PMID:
30892981
12.

Association of menopausal characteristics and risk of coronary heart disease: a pan-European case-cohort analysis.

Dam V, van der Schouw YT, Onland-Moret NC, Groenwold RHH, Peters SAE, Burgess S, Wood AM, Chirlaque MD, Moons KGM, Oliver-Williams C, Schuit E, Tikk K, Weiderpass E, Holm M, Tjønneland A, Kühn T, Fortner RT, Trichopoulou A, Karakatsani A, La Vecchia C, Ferrari P, Gunter M, Masala G, Sieri S, Tumino R, Panico S, Boer JMA, Verschuren WMM, Salamanca-Fernández E, Arriola L, Moreno-Iribas C, Engström G, Melander O, Nordendahl M, Wennberg P, Key TJ, Colorado-Yohar S, Matullo G, Overvad K, Clavel-Chapelon F, Boeing H, Quiros JR, di Angelantonio E, Langenberg C, Sweeting MJ, Riboli E, Wareham NJ, Danesh J, Butterworth A.

Int J Epidemiol. 2019 Feb 22. pii: dyz016. doi: 10.1093/ije/dyz016. [Epub ahead of print]

13.

A guide to systematic review and meta-analysis of prognostic factor studies.

Riley RD, Moons KGM, Snell KIE, Ensor J, Hooft L, Altman DG, Hayden J, Collins GS, Debray TPA.

BMJ. 2019 Jan 30;364:k4597. doi: 10.1136/bmj.k4597. No abstract available.

PMID:
30700442
14.

Interpretation of CVD risk predictions in clinical practice: Mission impossible?

Lagerweij GR, Moons KGM, de Wit GA, Koffijberg H.

PLoS One. 2019 Jan 9;14(1):e0209314. doi: 10.1371/journal.pone.0209314. eCollection 2019.

15.

Cardiovascular risk prediction models for women in the general population: A systematic review.

Baart SJ, Dam V, Scheres LJJ, Damen JAAG, Spijker R, Schuit E, Debray TPA, Fauser BCJM, Boersma E, Moons KGM, van der Schouw YT; CREW consortium.

PLoS One. 2019 Jan 8;14(1):e0210329. doi: 10.1371/journal.pone.0210329. eCollection 2019.

16.

Sample size considerations and predictive performance of multinomial logistic prediction models.

de Jong VMT, Eijkemans MJC, van Calster B, Timmerman D, Moons KGM, Steyerberg EW, van Smeden M.

Stat Med. 2019 Apr 30;38(9):1601-1619. doi: 10.1002/sim.8063. Epub 2019 Jan 6.

17.

PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration.

Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, Reitsma JB, Kleijnen J, Mallett S.

Ann Intern Med. 2019 Jan 1;170(1):W1-W33. doi: 10.7326/M18-1377.

PMID:
30596876
18.

PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies.

Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, Reitsma JB, Kleijnen J, Mallett S; PROBAST Group†.

Ann Intern Med. 2019 Jan 1;170(1):51-58. doi: 10.7326/M18-1376.

PMID:
30596875
19.

Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.

Pennells L, Kaptoge S, Wood A, Sweeting M, Zhao X, White I, Burgess S, Willeit P, Bolton T, Moons KGM, van der Schouw YT, Selmer R, Khaw KT, Gudnason V, Assmann G, Amouyel P, Salomaa V, Kivimaki M, Nordestgaard BG, Blaha MJ, Kuller LH, Brenner H, Gillum RF, Meisinger C, Ford I, Knuiman MW, Rosengren A, Lawlor DA, Völzke H, Cooper C, Marín Ibañez A, Casiglia E, Kauhanen J, Cooper JA, Rodriguez B, Sundström J, Barrett-Connor E, Dankner R, Nietert PJ, Davidson KW, Wallace RB, Blazer DG, Björkelund C, Donfrancesco C, Krumholz HM, Nissinen A, Davis BR, Coady S, Whincup PH, Jørgensen T, Ducimetiere P, Trevisan M, Engström G, Crespo CJ, Meade TW, Visser M, Kromhout D, Kiechl S, Daimon M, Price JF, Gómez de la Cámara A, Wouter Jukema J, Lamarche B, Onat A, Simons LA, Kavousi M, Ben-Shlomo Y, Gallacher J, Dekker JM, Arima H, Shara N, Tipping RW, Roussel R, Brunner EJ, Koenig W, Sakurai M, Pavlovic J, Gansevoort RT, Nagel D, Goldbourt U, Barr ELM, Palmieri L, Njølstad I, Sato S, Monique Verschuren WM, Varghese CV, Graham I, Onuma O, Greenland P, Woodward M, Ezzati M, Psaty BM, Sattar N, Jackson R, Ridker PM, Cook NR, D'Agostino RB, Thompson SG, Danesh J, Di Angelantonio E; Emerging Risk Factors Collaboration.

Eur Heart J. 2019 Feb 14;40(7):621-631. doi: 10.1093/eurheartj/ehy653.

20.

Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes.

Riley RD, Snell KI, Ensor J, Burke DL, Harrell FE Jr, Moons KG, Collins GS.

Stat Med. 2019 Mar 30;38(7):1276-1296. doi: 10.1002/sim.7992. Epub 2018 Oct 24.

21.

Overinterpretation and misreporting of prognostic factor studies in oncology: a systematic review.

Kempf E, de Beyer JA, Cook J, Holmes J, Mohammed S, Nguyên TL, Simera I, Trivella M, Altman DG, Hopewell S, Moons KGM, Porcher R, Reitsma JB, Sauerbrei W, Collins GS.

Br J Cancer. 2018 Nov;119(10):1288-1296. doi: 10.1038/s41416-018-0305-5. Epub 2018 Oct 24.

PMID:
30353050
22.

Minimum sample size for developing a multivariable prediction model: Part I - Continuous outcomes.

Riley RD, Snell KIE, Ensor J, Burke DL, Harrell FE Jr, Moons KGM, Collins GS.

Stat Med. 2019 Mar 30;38(7):1262-1275. doi: 10.1002/sim.7993. Epub 2018 Oct 22.

PMID:
30347470
23.

Implementing systematic reviews of prognosis studies in Cochrane.

Moons KG, Hooft L, Williams K, Hayden JA, Damen JA, Riley RD.

Cochrane Database Syst Rev. 2018 Oct 11;10:ED000129. doi: 10.1002/14651858.ED000129. No abstract available.

PMID:
30306538
24.

Effectiveness of CHA2DS2-VASc based decision support on stroke prevention in atrial fibrillation: A cluster randomised trial in general practice.

van Doorn S, Rutten FH, O'Flynn CM, Oudega R, Hoes AW, Moons KGM, Geersing GJ.

Int J Cardiol. 2018 Dec 15;273:123-129. doi: 10.1016/j.ijcard.2018.08.096. Epub 2018 Sep 8.

PMID:
30224261
25.

Doug Altman's legacy to Cochrane and evidence synthesis.

Deeks JJ, Hopewell S, Moher D, Higgins JP, Moons KG, Chandler J, Antes G.

Cochrane Database Syst Rev. 2018 Sep 14;8:ED000127. doi: 10.1002/14651858.ED000127. No abstract available.

PMID:
30221350
26.

Cardiovascular risk model performance in women with and without hypertensive disorders of pregnancy.

Dam V, Onland-Moret NC, Verschuren WMM, Boer JMA, Benschop L, Franx A, Moons KGM, Boersma E, van der Schouw YT; CREW-consortium.

Heart. 2018 Sep 12. pii: heartjnl-2018-313439. doi: 10.1136/heartjnl-2018-313439. [Epub ahead of print]

PMID:
30209122
27.

Risk of cardiac and non-cardiac adverse events in community-dwelling older patients with atrial fibrillation: a prospective cohort study in the Netherlands.

van Doorn S, Tavenier A, Rutten FH, Hoes AW, Moons KGM, Geersing GJ.

BMJ Open. 2018 Aug 23;8(8):e021681. doi: 10.1136/bmjopen-2018-021681.

28.

Investigating Risk Adjustment Methods for Health Care Provider Profiling When Observations are Scarce or Events Rare.

Brakenhoff TB, Moons KG, Kluin J, Groenwold RH.

Health Serv Insights. 2018 Jul 5;11:1178632918785133. doi: 10.1177/1178632918785133. eCollection 2018.

29.

A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes.

Debray TP, Damen JA, Riley RD, Snell K, Reitsma JB, Hooft L, Collins GS, Moons KG.

Stat Methods Med Res. 2018 Jul 23:962280218785504. doi: 10.1177/0962280218785504. [Epub ahead of print]

PMID:
30032705
30.

Poor reporting of multivariable prediction model studies: towards a targeted implementation strategy of the TRIPOD statement.

Heus P, Damen JAAG, Pajouheshnia R, Scholten RJPM, Reitsma JB, Collins GS, Altman DG, Moons KGM, Hooft L.

BMC Med. 2018 Jul 19;16(1):120. doi: 10.1186/s12916-018-1099-2.

31.

Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins.

Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Consortium for Early Detection of Lung Cancer, Guida F, Sun N, Bantis LE, Muller DC, Li P, Taguchi A, Dhillon D, Kundnani DL, Patel NJ, Yan Q, Byrnes G, Moons KGM, Tjønneland A, Panico S, Agnoli C, Vineis P, Palli D, Bueno-de-Mesquita B, Peeters PH, Agudo A, Huerta JM, Dorronsoro M, Barranco MR, Ardanaz E, Travis RC, Byrne KS, Boeing H, Steffen A, Kaaks R, Hüsing A, Trichopoulou A, Lagiou P, La Vecchia C, Severi G, Boutron-Ruault MC, Sandanger TM, Weiderpass E, Nøst TH, Tsilidis K, Riboli E, Grankvist K, Johansson M, Goodman GE, Feng Z, Brennan P, Johansson M, Hanash SM.

JAMA Oncol. 2018 Oct 1;4(10):e182078. doi: 10.1001/jamaoncol.2018.2078. Epub 2018 Oct 11.

32.

Sample size for binary logistic prediction models: Beyond events per variable criteria.

van Smeden M, Moons KG, de Groot JA, Collins GS, Altman DG, Eijkemans MJ, Reitsma JB.

Stat Methods Med Res. 2019 Aug;28(8):2455-2474. doi: 10.1177/0962280218784726. Epub 2018 Jul 3.

PMID:
29966490
33.

Outlier classification performance of risk adjustment methods when profiling multiple providers.

Brakenhoff TB, Roes KCB, Moons KGM, Groenwold RHH.

BMC Med Res Methodol. 2018 Jun 15;18(1):54. doi: 10.1186/s12874-018-0510-1.

34.

Contemporary cardiovascular risk prediction.

Damen JAAG, Hooft L, Moons KGM.

Lancet. 2018 May 12;391(10133):1867-1868. doi: 10.1016/S0140-6736(18)30842-0. Epub 2018 May 4. No abstract available.

PMID:
29735390
35.

Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals: a systematic literature review and external validation in the EPIC and UK Biobank prospective cohort studies.

Smith T, Muller DC, Moons KGM, Cross AJ, Johansson M, Ferrari P, Fagherazzi G, Peeters PHM, Severi G, Hüsing A, Kaaks R, Tjonneland A, Olsen A, Overvad K, Bonet C, Rodriguez-Barranco M, Huerta JM, Barricarte Gurrea A, Bradbury KE, Trichopoulou A, Bamia C, Orfanos P, Palli D, Pala V, Vineis P, Bueno-de-Mesquita B, Ohlsson B, Harlid S, Van Guelpen B, Skeie G, Weiderpass E, Jenab M, Murphy N, Riboli E, Gunter MJ, Aleksandrova KJ, Tzoulaki I.

Gut. 2019 Apr;68(4):672-683. doi: 10.1136/gutjnl-2017-315730. Epub 2018 Apr 3.

36.

Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model.

Westeneng HJ, Debray TPA, Visser AE, van Eijk RPA, Rooney JPK, Calvo A, Martin S, McDermott CJ, Thompson AG, Pinto S, Kobeleva X, Rosenbohm A, Stubendorff B, Sommer H, Middelkoop BM, Dekker AM, van Vugt JJFA, van Rheenen W, Vajda A, Heverin M, Kazoka M, Hollinger H, Gromicho M, Körner S, Ringer TM, Rödiger A, Gunkel A, Shaw CE, Bredenoord AL, van Es MA, Corcia P, Couratier P, Weber M, Grosskreutz J, Ludolph AC, Petri S, de Carvalho M, Van Damme P, Talbot K, Turner MR, Shaw PJ, Al-Chalabi A, Chiò A, Hardiman O, Moons KGM, Veldink JH, van den Berg LH.

Lancet Neurol. 2018 May;17(5):423-433. doi: 10.1016/S1474-4422(18)30089-9. Epub 2018 Mar 26.

37.

Acute Brain Dysfunction: Development and Validation of a Daily Prediction Model.

Marra A, Pandharipande PP, Shotwell MS, Chandrasekhar R, Girard TD, Shintani AK, Peelen LM, Moons KGM, Dittus RS, Ely EW, Vasilevskis EE.

Chest. 2018 Aug;154(2):293-301. doi: 10.1016/j.chest.2018.03.013. Epub 2018 Mar 24.

38.

Opportunistic screening for heart failure with natriuretic peptides in patients with atrial fibrillation: a meta-analysis of individual participant data of four screening studies.

van Doorn S, Geersing GJ, Kievit RF, van Mourik Y, Bertens LC, van Riet EES, Boonman-de Winter LJ, Moons KGM, Hoes AW, Rutten FH.

Heart. 2018 Aug;104(15):1236-1237. doi: 10.1136/heartjnl-2017-312781. Epub 2018 Mar 16.

PMID:
29549089
39.

Measurement error is often neglected in medical literature: a systematic review.

Brakenhoff TB, Mitroiu M, Keogh RH, Moons KGM, Groenwold RHH, van Smeden M.

J Clin Epidemiol. 2018 Jun;98:89-97. doi: 10.1016/j.jclinepi.2018.02.023. Epub 2018 Mar 6. Review.

40.

A new selection method to increase the health benefits of CVD prevention strategies.

Lagerweij GR, de Wit GA, Moons KG, van der Schouw YT, Verschuren WM, Dorresteijn JA, Koffijberg H; CREW consortium.

Eur J Prev Cardiol. 2018 Apr;25(6):642-650. doi: 10.1177/2047487317752948. Epub 2018 Feb 7.

41.

Overdiagnosis across medical disciplines: a scoping review.

Jenniskens K, de Groot JAH, Reitsma JB, Moons KGM, Hooft L, Naaktgeboren CA.

BMJ Open. 2017 Dec 27;7(12):e018448. doi: 10.1136/bmjopen-2017-018448. Review.

42.

Event rate net reclassification index and the integrated discrimination improvement for studying incremental value of risk markers.

van Smeden M, Moons KGM.

Stat Med. 2017 Dec 10;36(28):4495-4497. doi: 10.1002/sim.7286. No abstract available.

PMID:
29156501
43.

The effects of misclassification in routine healthcare databases on the accuracy of prognostic prediction models: a case study of the CHA2DS2-VASc score in atrial fibrillation.

van Doorn S, Brakenhoff TB, Moons KGM, Rutten FH, Hoes AW, Groenwold RHH, Geersing GJ.

Diagn Progn Res. 2017 Nov 16;1:18. doi: 10.1186/s41512-017-0018-x. eCollection 2017.

44.

Separate and combined associations of obesity and metabolic health with coronary heart disease: a pan-European case-cohort analysis.

Lassale C, Tzoulaki I, Moons KGM, Sweeting M, Boer J, Johnson L, Huerta JM, Agnoli C, Freisling H, Weiderpass E, Wennberg P, van der A DL, Arriola L, Benetou V, Boeing H, Bonnet F, Colorado-Yohar SM, Engström G, Eriksen AK, Ferrari P, Grioni S, Johansson M, Kaaks R, Katsoulis M, Katzke V, Key TJ, Matullo G, Melander O, Molina-Portillo E, Moreno-Iribas C, Norberg M, Overvad K, Panico S, Quirós JR, Saieva C, Skeie G, Steffen A, Stepien M, Tjønneland A, Trichopoulou A, Tumino R, van der Schouw YT, Verschuren WMM, Langenberg C, Di Angelantonio E, Riboli E, Wareham NJ, Danesh J, Butterworth AS.

Eur Heart J. 2018 Feb 1;39(5):397-406. doi: 10.1093/eurheartj/ehx448.

45.

An alternative approach identified optimal risk thresholds for treatment indication: an illustration in coronary heart disease.

van Giessen A, de Wit GA, Moons KGM, Dorresteijn JAN, Koffijberg H.

J Clin Epidemiol. 2018 Feb;94:122-131. doi: 10.1016/j.jclinepi.2017.09.020. Epub 2017 Oct 3.

PMID:
28986242
46.

Detecting small-study effects and funnel plot asymmetry in meta-analysis of survival data: A comparison of new and existing tests.

Debray TPA, Moons KGM, Riley RD.

Res Synth Methods. 2018 Mar;9(1):41-50. doi: 10.1002/jrsm.1266. Epub 2017 Nov 28.

47.

External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol.

Allotey J, Snell KIE, Chan C, Hooper R, Dodds J, Rogozinska E, Khan KS, Poston L, Kenny L, Myers J, Thilaganathan B, Chappell L, Mol BW, Von Dadelszen P, Ahmed A, Green M, Poon L, Khalil A, Moons KGM, Riley RD, Thangaratinam S; IPPIC Collaborative Network.

Diagn Progn Res. 2017 Oct 3;1:16. doi: 10.1186/s41512-017-0016-z. eCollection 2017.

48.

Predicted burden could replace predicted risk in preventive strategies for cardiovascular disease.

Lagerweij GR, de Wit GA, Moons KGM, Verschuren WMM, Boer JMA, Koffijberg H.

J Clin Epidemiol. 2018 Jan;93:103-111. doi: 10.1016/j.jclinepi.2017.09.014. Epub 2017 Sep 21.

PMID:
28943378
49.

Treatment use in prognostic model research: a systematic review of cardiovascular prognostic studies.

Pajouheshnia R, Damen JAAG, Groenwold RHH, Moons KGM, Peelen LM.

Diagn Progn Res. 2017 Sep 26;1:15. doi: 10.1186/s41512-017-0015-0. eCollection 2017. Review.

50.

Integrated management of atrial fibrillation including tailoring of anticoagulation in primary care: study design of the ALL-IN cluster randomised trial.

van den Dries CJ, Oudega R, Elvan A, Rutten FH, van de Leur SJCM, Bilo HJG, Hoes AW, Moons KGM, Geersing GJ.

BMJ Open. 2017 Sep 18;7(9):e015510. doi: 10.1136/bmjopen-2016-015510.

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