Screening for Type 2 Diabetes: Report of a World Health Organization and International Diabetes Federation meeting. [http://www.who.int/diabetes/publications/en/screening_mnc03.pdf]
Mulnier HE, Seaman HE, Raleigh VS, Soedamah-Muthu SS, Colhoun HM, Lawrenson RA: Mortality in people with type 2 diabetes in the UK. Diabet Med. 2006, 23: 516-521. 10.1111/j.1464-5491.2006.01838.x.
Article
CAS
PubMed
Google Scholar
Altman DG: Prognostic models: a methodological framework and review of models for breast cancer. Cancer Invest. 2009, 27: 235-243. 10.1080/07357900802572110.
Article
PubMed
Google Scholar
Counsell C, Dennis M: Systematic review of prognostic models in patients with stroke. Cerebrovasc Dis. 2001, 12: 159-170. 10.1159/000047699.
Article
CAS
PubMed
Google Scholar
Jacob M, Lewsey JD, Sharpin C, Gimson A, Rela M, van der Meulen JHP: Systematic review and validation of prognostic models in liver transplantation. Liver Transpl. 2005, 11: 814-825. 10.1002/lt.20456.
Article
PubMed
Google Scholar
Bagley SC, White H, Golomb BA: Logistic regression in the medical literature: standards for use and reporting, with particular attention to one medical domain. J Clin Epidemiol. 2001, 54: 979-985. 10.1016/S0895-4356(01)00372-9.
Article
CAS
PubMed
Google Scholar
Kalil AC, Mattei J, Florescu DF, Sun J, Kalil RS: Recommendations for the assessment and reporting of multivariable logistic regression in transplantation literature. Am J Transplant. 2010, 10: 1686-1694. 10.1111/j.1600-6143.2010.03141.x.
Article
CAS
PubMed
PubMed Central
Google Scholar
Khan KS, Chien PF, Dwarakanath LS: Multivariable analysis: a primer for readers of medical research. Obstet Gynecol. 1999, 93: 1014-1020. 10.1016/S0029-7844(98)00537-7.
CAS
PubMed
Google Scholar
Mikolajczyk RT, DiSilvestro A, Zhang J: Evaluation of logistic regression reporting in current obstetrics and gynecology literature. Obstet Gynecol. 2008, 111: 413-419. 10.1097/AOG.0b013e318160f38e.
Article
PubMed
Google Scholar
Ottenbacher KJ, Ottenbacher HR, Tooth L, Ostir GV: A review of two journals found that articles using multivariable logistic regression frequently did not report commonly recommended assumptions. J Clin Epidemiol. 2004, 57: 1147-1152. 10.1016/j.jclinepi.2003.05.003.
Article
PubMed
Google Scholar
Concato J, Feinsten AR, Holford TR: The risk of determining risk with multivariable models. Ann Intern Med. 1993, 118: 201-210.
Article
CAS
PubMed
Google Scholar
Wasson JH, Sox HC, Neff RK, Goldman L: Clinical prediction rules: applications and methodological standards. N Engl J Med. 1985, 313: 793-799. 10.1056/NEJM198509263131306.
Article
CAS
PubMed
Google Scholar
Schulz KF, Altman DG, Moher D, CONSORT Group: CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMJ. 2010, 340: c332-10.1136/bmj.c332.
Article
PubMed
PubMed Central
Google Scholar
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbrouke JP, STROBE Initiative: Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007, 335: 806-808. 10.1136/bmj.39335.541782.AD.
Article
PubMed
PubMed Central
Google Scholar
Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM, Lijmer JG, Moher D, Rennie D, de Vet HC, Standards for Reporting of Diagnostic Accuracy: Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. BMJ. 2003, 326: 41-44. 10.1136/bmj.326.7379.41.
Article
PubMed
PubMed Central
Google Scholar
Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009, 339: b2535-10.1136/bmj.b2535.
Article
PubMed
PubMed Central
Google Scholar
McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM, Statistics Subcommittee of the NCI-EORTC Working Group on Cancer Diagnostics: REporting recommendations for tumour MARKer prognostic studies (REMARK). Br J Cancer. 2005, 93: 387-391. 10.1038/sj.bjc.6602678.
Article
CAS
PubMed
PubMed Central
Google Scholar
Harrell FE, Lee KL, Mark DB: Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996, 15: 361-387. 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4.
Article
PubMed
Google Scholar
Metze K: Methodological aspects of prognostic factor studies: some caveats. Sao Paulo Med J. 1998, 116: 1787-1788. 10.1590/S1516-31801998000400011.
Article
CAS
PubMed
Google Scholar
Müller-Riemenschneider F, Holmberg C, Rieckmann N, Kliems H, Rufer V, Müller-Nordhorn J, Willich SN: Barriers to routine risk-score use for healthy primary care patients. Arch Intern Med. 2010, 170: 719-724. 10.1001/archinternmed.2010.66.
Article
PubMed
Google Scholar
Mallett S, Royston P, Dutton S, Waters R, Altman DG: Reporting methods in studies developing prognostic models in cancer: a review. BMC Med. 2010, 8: 20-10.1186/1741-7015-8-20.
Article
PubMed
PubMed Central
Google Scholar
Mallett S, Royston P, Waters R, Dutton S, Altman DG: Reporting performance of prognostic models in cancer: a review. BMC Med. 2010, 8: 21-10.1186/1741-7015-8-21.
Article
PubMed
PubMed Central
Google Scholar
Balkau B, Lange C, Fezeu L, Tichet J, de Lauzon-Guillain B, Czernichow S, Fumeron F, Froguel P, Vaxillaire M, Cauchi S, Ducimetière P, Eschwège E: Predicting diabetes: clinical, biological, and genetic approaches: data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR). Diabetes Care. 2008, 31: 2056-2061. 10.2337/dc08-0368.
Article
CAS
PubMed
PubMed Central
Google Scholar
Cabrera de León A, Coello SD, del Cristo RodríguezPérez M, Medina MB, Almeida González D, Diaz BB, de Fuentes MM, Aguirre-Jaime A: A simple clinical score for type 2 diabetes mellitus screening in the Canary Islands. Diabetes Res Clin Pract. 2008, 80: 128-133. 10.1016/j.diabres.2007.10.022.
Article
PubMed
Google Scholar
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: b880-10.1136/bmj.b880.
Article
PubMed
PubMed Central
Google Scholar
Xie J, Hu D, Yu D, Chen CS, He J, Gu D: A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population. J Epidemiol Community Health. 2010, 64: 236-242. 10.1136/jech.2009.087544.
Article
PubMed
Google Scholar
Aekplakorn W, Bunnag P, Woodward M, Sritara P, Cheepudomwit S, Yamwong S, Yipintsoi T, Rajatanavin R: A risk score for predicting incident diabetes in the Thai population. Diabetes Care. 2006, 29: 1872-1877. 10.2337/dc05-2141.
Article
PubMed
Google Scholar
Chen L, Magliano DJ, Balkau B, Colagiuri S, Zimmet PZ, Tonkin AM, Mitchell P, Phillips PJ, Shaw JE: AUSDRISK: an Australian Type 2 Diabetes Risk Assessment Tool based on demographic, lifestyle and simple anthropometric measures. Med J Aust. 2010, 192: 197-202.
PubMed
Google Scholar
Chien K, Cai T, Hsu H, Su T, Chang W, Chen M, Lee Y, Hu FB: A prediction model for type 2 diabetes risk among Chinese people. Diabetologia. 2009, 52: 443-450. 10.1007/s00125-008-1232-4.
Article
CAS
PubMed
Google Scholar
Gao WG, Qiao Q, Pitkäniemi J, Wild S, Magliano D, Shaw J, Söderberg S, Zimmet P, Chitson P, Knowlessur S, Alberti G, Tuomilehto J: Risk prediction models for the development of diabetes in Mauritian Indians. Diabet Med. 2009, 16: 996-1002.
Article
Google Scholar
Kahn HS, Cheng YJ, Thompson TJ, Imperatore G, Gregg EW: Two risk-scoring systems for predicting incident diabetes mellitus in U.S. adults age 45 to 64 years. Ann Intern Med. 2009, 150: 741-751.
Article
PubMed
Google Scholar
Kolberg JA, Jørgensen T, Gerwien RW, Hamren S, McKenna MP, Moler E, Rowe MW, Urdea MS, Xu XM, Hansen T, Pedersen O, Borch-Johnsen K: Development of a type 2 diabetes risk model from a panel of serum biomarkers from the Inter99 cohort. Diabetes Care. 2009, 32: 1207-1212. 10.2337/dc08-1935.
Article
PubMed
PubMed Central
Google Scholar
Lindström J, Tuomilehto J: The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care. 2003, 26: 725-731. 10.2337/diacare.26.3.725.
Article
PubMed
Google Scholar
Schmidt MI, Duncan BB, Bang H, Pankow JS, Ballantyne CM, Golden SH, Folsom AR, Chambless LE, Atherosclerosis Risk in Communities Investigators: Identifying individuals at high risk for diabetes: The Atherosclerosis Risk in Communities study. Diabetes Care. 2005, 28: 2013-2018. 10.2337/diacare.28.8.2013.
Article
PubMed
Google Scholar
Schulze MB, Hoffmann K, Boeing H, Linseisen J, Rohrmann S, Möhlig M, Pfeiffer AF, Spranger J, Thamer C, Häring HU, Fritsche A, Joost HG: An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes. Diabetes Care. 2007, 30: 510-515. 10.2337/dc06-2089.
Article
PubMed
Google Scholar
Stern MP, Williams K, Haffner SM: Identification of persons at high risk for type 2 diabetes mellitus: Do we need the oral glucose tolerance test?. Ann Intern Med. 2002, 136: 575-581.
Article
PubMed
Google Scholar
Sun F, Tao Q, Zhan S: An accurate risk score for estimation 5-year risk of type 2 diabetes based on a health screening population in Taiwan. Diabetes Res Clin Pract. 2009, 85: 228-234. 10.1016/j.diabres.2009.05.005.
Article
PubMed
Google Scholar
Tuomilehto J, Lindström J, Hellmich M, Lehmacher W, Westermeier T, Evers T, Brückner A, Peltonen M, Qiao Q, Chiasson JL: Development and validation of a risk-score model for subjects with impaired glucose tolerance for the assessment of the risk of type 2 diabetes mellitus: the STOP-NIDDM risk-score. Diabetes Res Clin Pract. 2010, 87: 267-274. 10.1016/j.diabres.2009.11.011.
Article
CAS
PubMed
Google Scholar
Wilson PWF, Meigs JB, Sullivan L, Fox CS, Nathan DM, D'Agostino RB: Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Arch Intern Med. 2007, 167: 1068-1074. 10.1001/archinte.167.10.1068.
Article
PubMed
Google Scholar
Gupta AK, Dahlof B, Dobson J, Sever PS, Wedel H, Poulter NR, Anglo-Scandinavian Cardiac Outcomes Trial Investigators: Determinants of new-onset diabetes among 19,257 hypertensive patients randomized in the Anglo-Scandinavian Cardiac Outcomes Trial-Blood Pressure Lowering Arm and the relative influence of antihypertensive medication. Diabetes Care. 2008, 31: 982-988. 10.2337/dc07-1768.
Article
CAS
PubMed
Google Scholar
Al-Lawati JA, Tuomilehto J: Diabetes risk score in Oman: a tool to identify prevalent type 2 diabetes among Arabs of the Middle East. Diabetes Res Clin Pract. 2007, 77: 438-444. 10.1016/j.diabres.2007.01.013.
Article
CAS
PubMed
Google Scholar
Baan CA, Ruige JB, Stolk RP, Witteman JCM, Dekker JM, Heine RJ, Feskens EJM: Performance of a predictive model to identify undiagnosed diabetes in a health care setting. Diabetes Care. 1999, 22: 213-219. 10.2337/diacare.22.2.213.
Article
CAS
PubMed
Google Scholar
Bang H, Edwards AM, Bomback AS, Ballantyne CM, Brillon D, Callahan MA, Teutsch SM, Mushlin AI, Kern LM: Development and validation of a patient self-assessment score for diabetes risk. Ann Intern Med. 2009, 151: 775-783.
Article
PubMed
PubMed Central
Google Scholar
Chaturvedi V, Reddy KS, Prabhakaran D, Jeemon P, Ramakrishnan L, Shah P, Shah B: Development of a clinical risk score in predicting undiagnosed diabetes in urban Asian Indian adults: a population-based study. CVD Prev Control. 2008, 3: 141-151. 10.1016/j.cvdpc.2008.07.002.
Article
Google Scholar
Gao WG, Dong YH, Pang ZC, Nan HR, Wang SJ, Ren J, Zhang L, Tuomilehto J, Qiao Q: A simple Chinese risk score for undiagnosed diabetes. Diabet Med. 2010, 27: 274-281. 10.1111/j.1464-5491.2010.02943.x.
Article
CAS
PubMed
Google Scholar
Glümer C, Carstensen B, Sabdbaek A, Lauritzen T, Jørgensen T, Borch-Johnsen K: A Danish diabetes risk score for targeted screening. Diabetes Care. 2004, 27: 727-733. 10.2337/diacare.27.3.727.
Article
PubMed
Google Scholar
Keesukphan P, Chanprasertyothin S, Ongphiphadhanakul B, Puavilai G: The development and validation of a diabetes risk score for high-risk Thai adults. J Med Assoc Thai. 2007, 90: 149-154.
PubMed
Google Scholar
Ko G, So W, Tong P, Ma R, Kong A, Ozakit R, Chow C, Cockram C, Chan J: A simple risk score to identify Southern Chinese at high risk for diabetes. Diabet Med. 2010, 27: 644-649. 10.1111/j.1464-5491.2010.02993.x.
Article
CAS
PubMed
Google Scholar
Mohan V, Deepa R, Deepa M, Somannavar S, Datta M: A simplified Indian Diabetes Risk Score for screening for undiagnosed diabetic subjects. J Assoc Physicians India. 2005, 53: 759-763.
CAS
PubMed
Google Scholar
Pires de Sousa AG, Pereira AC, Marquezine GF, Marques do Nascimento-Neto R, Freitas SN, Nicolato RLdC, Machado-Coelho GL, Rodrigues SL, Mill JG, Krieger JE: Derivation and external validation of a simple prediction model for the diagnosis of type 2 diabetes mellitus in the Brazilian urban population. Eur J Epidemiol. 2009, 24: 101-109. 10.1007/s10654-009-9314-2.
Article
PubMed
Google Scholar
Ramachandran A, Snehalatha C, Vijay C, Wareham NJ, Colagiuri S: Derivation and validation of diabetes risk score for urban Asian Indians. Diabetes Res Clin Pract. 2005, 70: 63-70. 10.1016/j.diabres.2005.02.016.
Article
CAS
PubMed
Google Scholar
Ruige JB, de Neeling JND, Kostense PJ, Bouter LM, Heine RJ: Performance of an NIDDM screening questionnaire based on symptoms and risk factors. Diabetes Care. 1997, 20: 491-496. 10.2337/diacare.20.4.491.
Article
CAS
PubMed
Google Scholar
Tabaei BP, Herman WH: A multivariate logistic regression equation to screen for diabetes: development and validation. Diabetes Care. 2002, 25: 1999-2003. 10.2337/diacare.25.11.1999.
Article
PubMed
Google Scholar
Bindraban NR, van Valkengoed IGM, Mairuhu G, Holleman F, Hoekstra JBL, Michels BPJ, Koopmans RP, Stronks K: Prevalence of diabetes mellitus and the performance of a risk score among Hindustani Surinamese, African Surinamese and ethnic Dutch: a cross-sectional population-based study. BMC Public Health. 2008, 8: 271-10.1186/1471-2458-8-271.
Article
PubMed
PubMed Central
Google Scholar
Griffin SJ, Little PS, Hales CN, Kinmonth AL, Wareham NJ: Diabetes risk score: towards earlier detection of type 2 diabetes in general practice. Diabetes Metab Res Rev. 2000, 16: 164-171. 10.1002/1520-7560(200005/06)16:3<164::AID-DMRR103>3.0.CO;2-R.
Article
CAS
PubMed
Google Scholar
Heikes KE, Eddy DM, Arondekar B, Schlessinger L: Diabetes Risk Calculator: a simple tool for detecting undiagnosed diabetes and pre-diabetes. Diabetes Care. 2008, 31: 1040-1045. 10.2337/dc07-1150.
Article
PubMed
Google Scholar
Kanaya AM, Wassel Fyr CL, de Rekeneire N, Schwartz AV, Goodpaster BH, Newman AB, Harris T, Barrett-Connor E: Predicting the development of diabetes in older adults: the derivation and validation of a prediction rule. Diabetes Care. 2005, 28: 404-408. 10.2337/diacare.28.2.404.
Article
PubMed
Google Scholar
Gray LJ, Taub NA, Khunti K, Gardiner E, Hiles S, Webb DR, Srinivasan BT, Davies MJ: The Leicester Risk Assessment score for detecting undiagnosed type 2 diabetes and impaired glucose regulation for use in a multiethnic UK setting. Diabet Med. 2010, 27: 887-895. 10.1111/j.1464-5491.2010.03037.x.
Article
CAS
PubMed
Google Scholar
Borrell LN, Kunzel C, Lamster I, Lalla E: Diabetes in the dental office: using NHANES III to estimate the probability of undiagnosed disease. J Periodontal Res. 2007, 42: 559-565. 10.1111/j.1600-0765.2007.00983.x.
Article
CAS
PubMed
Google Scholar
Al Khalaf MM, Eid MM, Najjar HA, Alhajry KM, Doi SA, Thalib L: Screening for diabetes in Kuwait and evaluation of risk scores. East Mediterr Health J. 2010, 16: 725-731.
CAS
PubMed
Google Scholar
Liu M, Pan C, Jin M: A Chinese diabetes risk score for screening of undiagnosed diabetes and abnormal glucose tolerance. Diabetes Technol Ther. 2011, 13: 501-507. 10.1089/dia.2010.0106.
Article
PubMed
Google Scholar
Sullivan LM, Massaro JM, D'Agostino RB: Presentation of multivariate data for clinical use: the Framingham study risk score functions. Stat Med. 2004, 23: 1631-1660. 10.1002/sim.1742.
Article
PubMed
Google Scholar
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: 1373-1379. 10.1016/S0895-4356(96)00236-3.
Article
CAS
PubMed
Google Scholar
Feinstein AR: Multivariable Analysis: An Introduction. 1996, New Haven: Yale University Press
Google Scholar
Babyak MA: What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models. Psychosom Med. 2004, 66: 411-421. 10.1097/01.psy.0000127692.23278.a9.
PubMed
Google Scholar
Concato J, Peduzzi P, Holford TR, Feinstein AR: Importance of events per independent variable in proportional hazards analysis. I. Background, goals, and general strategy. J Clin Epidemiol. 1995, 48: 1495-1501. 10.1016/0895-4356(95)00510-2.
Article
CAS
PubMed
Google Scholar
Royston P, Altman DG, Sauerbrei W: Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med. 2006, 25: 127-141. 10.1002/sim.2331.
Article
PubMed
Google Scholar
Hukkelhoven CWPM, Rampen AJJ, Maas AIR, Farace E, Habbema JDF, Marmarou A, Marshall LF, Murray GD, Steyerberg EW: Some prognostic models for traumatic brain injury were not valid. J Clin Epidemiol. 2006, 59: 132-143. 10.1016/j.jclinepi.2005.06.009.
Article
PubMed
Google Scholar
Leushuis E, van der Steeg JW, Steures P, Bossuyt PMM, Eijkemans MJC, van der Veen F, Mol BWJ, Hompes PGA: Prediction models in reproductive medicine. Hum Reprod Update. 2009, 15: 537-552. 10.1093/humupd/dmp013.
Article
PubMed
Google Scholar
Mallett S, Royston P, Dutton S, Waters R, Altman DG: Reporting methods in studies developing prognostic models in cancer: a review. BMC Med. 2010, 8: 20-10.1186/1741-7015-8-20.
Article
PubMed
PubMed Central
Google Scholar
Mallett S, Royston P, Waters R, Dutton S, Altman DG: Reporting performance of prognostic models in cancer: a review. BMC Med. 2010, 8: 21-10.1186/1741-7015-8-21.
Article
PubMed
PubMed Central
Google Scholar
Mushkudiani NA, Hukkelhoven CWPM, Hernandez AV, Murray GD, Choi SC, Maas AIR, Steyerberg EW: A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes. J Clin Epidemiol. 2008, 61: 331-343. 10.1016/j.jclinepi.2007.06.011.
Article
PubMed
Google Scholar
Perel P, Edwards P, Wentz R, Roberts I: Systematic review of prognostic models in traumatic brain injury. BMC Med Inform Decis Mak. 2006, 6: 38-10.1186/1472-6947-6-38.
Article
PubMed
PubMed Central
Google Scholar
Wasson JH, Sox HC, Neff RK, Goldman L: Clinical prediction rules: applications and methodological standards. N Engl J Med. 1985, 313: 793-799. 10.1056/NEJM198509263131306.
Article
CAS
PubMed
Google Scholar
Lagakos SW: Effects of mismodelling and mismeasuring explanatory variables on tests of their association with a response variable. Stat Med. 1988, 7: 257-274. 10.1002/sim.4780070126.
Article
CAS
PubMed
Google Scholar
Royston P, Sauerbrei W: Multivariable Model-Building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables. 2008, Chichester: John Wiley & Sons
Book
Google Scholar
Little RA: Regression with missing X's: a review. J Am Stat Assoc. 1992, 87: 1227-1237. 10.2307/2290664.
Google Scholar
Burton A, Altman DG: Missing covariate data within cancer prognostic studies: a review of current reporting and proposed guidelines. Br J Cancer. 2004, 91: 4-8. 10.1038/sj.bjc.6601907.
Article
CAS
PubMed
PubMed Central
Google Scholar
Marshall A, Altman DG, Royston P, Holder RL: Comparison of techniques for handling missing covariate data withing prognostic modelling studies: a simulation study. BMC Med Res Meth. 2010, 10: 7-10.1186/1471-2288-10-7.
Article
Google Scholar
Vergouwe Y, Royston P, Moons KGM, Altman DG: Development and validation of a prediction model with missing predictor data: a practical approach. J Clin Epidemiol. 2010, 63: 205-214. 10.1016/j.jclinepi.2009.03.017.
Article
PubMed
Google Scholar
Sun GW, Shook TL, Kay GL: Inappropriate use of bivariable analysis to screen risk factors for use in multivariable analysis. J Clin Epidemiol. 1996, 49: 907-916. 10.1016/0895-4356(96)00025-X.
Article
CAS
PubMed
Google Scholar
Austin PC, Tu JV: Automated variable selection methods for logistic regression produced unstable models for predicting acute myocardial infarction mortality. J Clin Epidemiol. 2004, 57: 1138-1146. 10.1016/j.jclinepi.2004.04.003.
Article
PubMed
Google Scholar
Steyerberg EW, Eijkemans MJ, Habbema JD: Stepwise selection in small data sets: a simulation study of bias in logistic regression analysis. J Clin Epidemiol. 1999, 52: 935-942. 10.1016/S0895-4356(99)00103-1.
Article
CAS
PubMed
Google Scholar
Steyerberg EW, Eijkemans MJC, Harrell FE, Habbema JDF: Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets. Stat Med. 2000, 19: 1059-1079. 10.1002/(SICI)1097-0258(20000430)19:8<1059::AID-SIM412>3.0.CO;2-0.
Article
CAS
PubMed
Google Scholar
Altman DG, Royston P: What do we mean by validating a prognostic model?. Stat Med. 2000, 19: 453-473. 10.1002/(SICI)1097-0258(20000229)19:4<453::AID-SIM350>3.0.CO;2-5.
Article
CAS
PubMed
Google Scholar
Altman DG, Vergouwe Y, Royston P, Moons KGM: Prognosis and prognostic research: validating a prognostic model. BMJ. 2009, 338: b605-10.1136/bmj.b605.
Article
PubMed
Google Scholar
Laupacis A, Sekar N, Stiell IG: Clinical prediction rules: a review and suggested modifications of methodological standards. JAMA. 1997, 277: 488-494. 10.1001/jama.277.6.488.
Article
CAS
PubMed
Google Scholar
Hier DB, Edelstein G: Deriving clinical prediction rules from stroke outcome research. Stroke. 1991, 22: 1431-1436. 10.1161/01.STR.22.11.1431.
Article
CAS
PubMed
Google Scholar
Ritter AV, Shugars DA, Bader JD: Root caries risk indicators: a systematic review of risk models. Community Dent Oral Epidemiol. 2010, 38: 383-397. 10.1111/j.1600-0528.2010.00551.x.
Article
PubMed
PubMed Central
Google Scholar
Schulz KF, Altman DG, Moher D, CONSORT Group: CONSORT 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med. 2010, 152: 726-732.
Article
PubMed
Google Scholar
Little J, Higgins JP, Ioannidis JP, Moher D, Gagnon F, von Elm E, Khoury MJ, Cohen B, Davey-Smith G, Grimshaw J, Scheet P, Gwinn M, Williamson RE, Zou GY, Hutchings K, Johnson CY, Tait V, Wiens M, Golding J, van Duijn C, McLaughlin J, Paterson A, Wells G, Fortier I, Freedman M, Zecevic M, King R, Infante-Rivard C, Stewart A, Birkett N, STrengthening the REporting of Genetic Association Studies: STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement. PLoS Med. 2009, 6: e22-10.1371/journal.pmed.1000022.
Article
PubMed
Google Scholar
McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM, Statistics Subcommittee of NCI-EORTC Working Group on Cancer Diagnostics: REporting recommendations for tumor MARKer prognostic studies (REMARK). Breast Cancer Res Treat. 2006, 100: 229-235. 10.1007/s10549-006-9242-8.
Article
PubMed
Google Scholar
Hopewell S, Dutton S, Yu LM, Chan AW, Altman DG: The quality of reports of randomised trials in 2000 and 2006: comparative study of articles indexed in PubMed. BMJ. 2010, 340: c723-10.1136/bmj.c723.
Article
PubMed
PubMed Central
Google Scholar
Plint AC, Moher D, Morrison A, Schulz K, Altman DG, Hill C, Gaboury I: Does the CONSORT checklist improve the quality of reports of randomised controlled trials? A systematic review. Med J Aust. 2006, 185: 263-267.
PubMed
Google Scholar
Webster JD, Dennis MM, Dervisis N, Heller J, Bacon NJ, Bergman PJ, Bienzle D, Cassali G, Castagnaro M, Cullen J, Esplin DG, Peña L, Goldschmidt MH, Hahn KA, Henry CJ, Hellmén E, Kamstock D, Kirpensteijn J, Kitchell BE, Amorim RL, Lenz SD, Lipscomb TP, McEntee M, McGill LD, McKnight CA, McManus PM, Moore AS, Moore PF, Moroff SD, Nakayama H, American College of Veterinary Pathologists' Oncology Committee, et al: Recommended guidelines for the conduct and evaluation of prognostic studies in veterinary oncology. Vet Pathol. 2011, 48: 7-18. 10.1177/0300985810377187.
Article
CAS
PubMed
Google Scholar